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Proceedings of the 14th European Conference on Knowledge Management Kaunas University of Technology, Lithuania 5-6 September 2013

Edited by Brigita JaniĹŤnaitÄ— and Monika Petraite Kaunas University of Technology, Kaunas, Lithuania

Volume One A conference managed by ACPI, UK www.academic-conferences.org


7th European Conference on Information  Management & Evaluation  12‐13 September 2013  Sopot, Poland 

9th International Conference on   e‐Learning  26‐27 June 2014  Santiago, Chile 

See the website for latest dates & venues www.academic‐conferences.org

15th European Conference on  Knowledge Management  4-5 September 2014  Santarem, Portugal 

7th European Conference on Game  Based Learning  3‐4 October 2013  Porto, Portugal 

13th European Conference on Information  Warfare & Security  3‐4 July 2014  University of Piraeus, Greece 

European Conference on Social  Media  10‐11 July 2014  Brighton, UK 

10th International Conference on  Intellectual Capital and  Knowledge Management  24‐25 October 2013  Washington, DC, USA  12th European Conference on e‐ Learning  30‐31 October 2013  Sophia Antipolis, France  9th European Conference on  Management, Leadership &  Governance  14‐15 November 2013  Klagenfurt, Austria 

International Conference on  Cloud Security Management  17‐18 October 2013  Seattle, USA 

8th European Conference on  Innovation & Entrepreneurship  19‐20 September 2013  Brussels, Belgium 

13th European Conference on Research  Methods  Date and Venue tbc 

14th European Conference on e‐ Government  12‐13 June 2014  Brasov, Romania 

5th International Conference on  Information Management and  Evaluation  Date and venue tbc 

6th European Conference on Intellectual  Capital  11‐12 April 2014  Trnava, Slovak Republic 

2nd International Conference on  Innovation and Entrepreneurship  6‐7 February 2014  Bangkok, Thailand  2nd International Conference on  Management, Leadership and  Governance  20‐21 March 2014  Wellesley, Massachusetts, USA  9th International Conference on Cyber  Warfare & Security  24‐25 March 2014   (formally ICIW)  West Lafayette, Indiana, USA 


Proceedings of the 14th European Conference on Knowledge Management ECKM 2013 Volume One Kaunas University of Technology Kaunas Lithuania 5-6 September 2013 Edited by Prof. Dr. Brigita JaniĹŤnaitÄ—, Prof.Dr. Asta Pundziene Prof. Dr. Monika Petraite


Copyright The Authors, 2013. All Rights Reserved. No reproduction, copy or transmission may be made without written permission from the individual authors. Papers have been double-blind peer reviewed before final submission to the conference. Initially, paper abstracts were read and selected by the conference panel for submission as possible papers for the conference. Many thanks to the reviewers who helped ensure the quality of the full papers. These Conference Proceedings have been submitted to Thomson ISI for indexing. Please note that the process of indexing can take up to a year to complete. Further copies of this book and previous year’s proceedings can be purchased from http://academic-bookshop.com E-Book ISBN: 978-1-909507-40-1 E-Book ISSN: 2048-8971 Book version ISBN: 978-1-909507-38-8 Book Version ISSN: 2048-8963 CD Version ISBN: 978-1-909507-41-8 CD Version ISSN: 2048-898X The Electronic version of the Proceedings is available to download at ISSUU.com. You will need to sign up to become an ISSUU user (no cost involved) and follow the link to http://issuu.com Published by Academic Conferences and Publishing International Limited Reading UK 44-118-972-4148 www.academic-publishing.org


Contents Paper Title

Author(s)

Page No.

Preface

vii

Committee

viii

Biographies

xi

Using Neuromarketing Studies to Explore Emotional Intelligence – as a key to the Buying Decision Process

Nicolae Al. Pop, Ana Maria Iorga and Corina Pelau

1

Enabling Knowledge Sharing in an Academic Environment: A Case Study

Versavia Ancusa, Razvan Bogdan and Oana Caus

9

Filling the Knowledge gap: How Relevant is University Programmes to Industry Needs?

Nicolene Barkhuizen

17

Embedding Knowledge Management in Public Sector Procurement – Redesigning for the Knowledge Economy

Denise A. D. Bedford

25

Topology of Knowledge and Information in the Transportation Sector

Denise A. D. Bedford1 and Lisa Loyo

35

Collaborative Solutions Quick&Clean: The SFM Method

Marco Bettoni, Willi Bernhard and Nicole Bittel

44

Intra-Organisational Knowledge Sharing: Scenarios and Corresponding Strategies

Madeleine Block and Tatiana Khvatova

52

Organizational Culture vs. Structure: An Academic Case Study

Razvan Bogdan, Versavia Ancusa and Oana Caus

61

Entropy vs. Organizational Learning and Dynamic Capabilities: The Thermodynamic Analogy

Pavel Bogolyubov, Evgeniy Blagov and Boyka Simeonova

69

A new Marketing Audit Tool for Knowledge Intensive Business Services

Ettore Bolisani and Enrico Scarso

74

Emotional Knowledge: The Hidden Part of the Knowledge Iceberg

Constantin Bratianu and Ivona Orzea

82

Managerial Factors of Organizational Learning for Sustainable Development

Valentina Burksiene and Palmira Juceviciene

91

Capturing Safety Knowledge: Using a Safety-Specific Exit Survey

Christopher Burt, Cassandra Cottle, Katharina Näswall and Skye Williams

99

Knowledge Management in Defence

Barry Byrne and Frank Bannister

106

A Framework for Improving an Organizational Memory Information System’s Deployment Architecture

Osvaldo Cairo and Oscar Ojeda Galicia

117

The KAMET II Methodology: A Real Process for Knowledge Generation

Osvaldo Cairó and Silvia Guardati

124

Knowledge management capabilities in family firms

Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez

131

Relationship Between Perceived Organizational Support, Self-Efficacy, Subjective Norms and Knowledge Sharing

Delio Ignacio Castaneda and Manuel Fernández Ríos

140

The Value of Extended Framework of TAM in the Electronic Government Services

Juan-Gabriel Cegarra-Navarro, Stephen Eldridge, Eva Martinez-Caro and Maria Teresa Sanchez Polo

148

i


Paper Title

Author(s)

Page No.

A Context-Aware Architecture for the Management of Laundry Business Processes

Ufuk Celikkan and Kaan Kurtel

159

Modeling Organizational Intelligence Based on Knowledge Management in the Technical and Vocational Training Organization of Tehran

Hossein Chenari, Fattah Nazem, Mahmood Safari

167

An Introduction to STRIKE: STRuctured Interpretation of the Knowledge Environment

Sally Eaves and John Walton

174

Ipe Revisited: Validating a Multidimensional Model of Individual Knowledge Sharing Influences

Sally Eaves

184

Simulation of Space Operation - A Study on Learning in Control Rooms

Anandasivakumar Ekambaram, Brit-Eli Danielsen, Liz Helena Froes Coelho and Trine Marie Stene

194

The Role of Knowledge Management and Innovation in Challenging Times – A View on the Leisure Boat Industry

Anandasivakumar Ekambaram, Carl Christian Røstad and Bjørnar Henriksen

202

Knowledge Sharing Challenges in Developing Earlystage Entrepreneurship

Tiit Elenurm and Anne Reino

211

A Systematic Review and Comparison of Knowledge Management-Frameworks

Nora Fteimi and Franz Lehner

219

Organizational Characteristics That Influence the way Middle Managers and Their Subordinates are Available to Each Other

Zoltán Gaál, Lajos Szabó, and Anikó Csepregi

227

A Knowledge-Based Reference Model to Support Demand Management in Contemporary Supply Chains

Sotiris Gayialis, Stavros Ponis, Ilias Tatsiopoulos, Nikolaos Panayiotou and Dimitrios-Robert Stamatiou

236

Loosely-Coupled Networks of Knowledge Production and Diffusion

Gianna Giudicati and Massimo Riccaboni

245

The Factors of Knowledge Sharing in a SelfOrganisation Based System

Kristina Grumadaite

254

Mapping Research Community and Interests in KM: A Case of JKM

Meliha Handzic and Nermina Durmic

262

Developing a Knowledge Strategy Using Tacit Knowledge Measurement: Implications for the Balanced Scorecard Innovation and Learning Perspective

Harold Harlow

270

Applying the Concept of Communities of Practice: An Empirical Study of Innovative Collaboration Between Academia and Industry

Päivi Iskanius and Ilpo Pohjola

278

A Scientifically Grounded Model to Reduce Knowledge Loss in Organisations

Thomas Jackson, Paul Parboteeah and Nicola Wilkinson

287

Knowledge Management, Call Centres and Customer Satisfaction: A Case Study From the Transport Sector

Mahsa Jahantab and Alexeis Garcia-Perez

295

Social Media in Knowledge Management – Overcoming Fundamental Knowledge Problems

Harri Jalonen

300

Customer Experiential Knowledge Management (CEKM) - Concept Proposition and Research Framework Development

Dhouha Jaziri Bouagina and Abdelfattah Triki

307

ii


Paper Title

Author(s)

Page No.

MNCs Innovation, Reverse Knowledge Transfer and Firm Absorptive Capacity

Daniel Jimenéz-Jimenéz; Micaela Martínez-Costa and Raquel Sanz-Valle

315

Peculiarities of organization’s knowing

Habil. Palmira Juceviciene and Vyda Mozuriuniene

323

The Dimension of Smart Specialisation in the Business System

Robertas Jucevicius and Aukse Galbuogiene

333

The Effectiveness of Storytelling in Transferring Different Types of Knowledge

Marcela Katuščáková and Martin Katuščák

341

Impact of Knowledge Management Practices (KMPs) on Competitive Advantage in Pharmaceutical Firms

Radwan Kharabsheh and Ayman Aqrabawi

349

The Impact of Knowledge Management Practices on Organizational Performance

Aino Kianto, Paavo Ritala, Mika Vanhala and Henri Inkinen

356

Creating Banks’ Competitiveness by Proper Identification and Usage of Intangibles – Survey Results

Monika Klimontowicz

362

Effective Knowledge Sharing Through Social Technologies

Jaroslava Kubátová

372

The Manufacturer, the Screener, the User, and the Scientist: Producing and Circulating Information and Knowledge About Equipment

Monique Lortie, Angel Alberto Toyos Alvares, Steve Vezeau and Maud Gonella

380

387The Importance of Emotional Inte397lligence in Effective Leaders404hip Skills: The Case of Romanian S413oftware Development C421ompanies

Edit Lukacs, Sofia David and Alexandru Capatina

387

Information Technology: An Enabler for Trust-Building, Knowledge Sharing and Knowledge Transfer to Enhance Absorptive Capacity

Athar Mahmood Ahmed Qureshi and Nina Evans

397

Applying a Technology Acceptance Model to Test Business e-Loyalty Towards Online Banking Transactions

Eva Martinez-Caro, Gabriel CepedaCarrión, and Juan-Gabriel Cegarra-Navarro

404

Knowledge Management for Organizational Innovation: A Multinational Corporations Perspective

Micaela Martínez-Costa, Daniel JimenézJimenéz and Raquel Sanz-Valle

413

Expatriates’ Influence on Knowledge Sharing: An Empirical Study With International Portuguese Companies

Dora Martins

421

Intellectual Capital: A Valuable Resource for University Technology Commercialisation?

Kristel Miller Sandra Moffett Rodney McAdam and Michael Brennan

429

Reconceptualising knowledge transfer practices in the South African public sector

Peter L Mkhize

438

Knowledge Worker From the Perspective of Their Managers

Ludmila Mládková

446

Strategies for KM Implementation: UK Case Study Perspectives

Sandra Moffett

453

Motivating key Employees Towards Knowledge Sharing - Research Findings and Suggested Solutions

Mieczysław Morawski

462

iii

,


Volume Two Improved Information Sharing in Supply Chain Environment Using Knowledge Management Technologies

Edrisi Muñoz, Elisabet Capón-García, José M. Laínez, Antonio Espuña and Luis Puigjaner

472

Institutional Wiki: Evolving Public and Private Knowledge in MPMG

Lilian Noronha Nassif and Daniel Silva Carnevalli

482

Validation of the Scale of Knowledge Management Assessment in the Technical and Vocational Training Organization of Tehran

Fattah Nazem, Hossein Chenari and Omalbanin Sadeghi

490

Organisational Knowledge and Human Capital: A Conceptualisation for the Non-Profit Sector

Olimpia Neagu

496

Theorising a new Concept: ‘Micro Intellectual Capital’ (MIC) Using Knowledge From Inside the Classroom

Gary Oliver

506

Analysis of Awareness and Priorities, Focused on Intellectual Capital Among Slovak Companies

Ján Papula, Jana Volná, Anna Pilková, Jaroslav Huľvej

517

Towards Born-Global Innovation: the Role of Knowledge Management and Social Software

Jan M. Pawlowski

527

The Importance of Language Knowledge in International Companies

Corina Pelau, Irina Purcarea and Stelian Stancu

535

Linking External and Internal R&D and experience based Knowledge Flows for Innovation via Organisational Design Elements

Monika Petraite

543

The Role of Rational, Emotional and Spiritual Knowledge in Customer Relationship Management

Carmen Petrisoaia and Nicolae Al. Pop

552

Decision-Making Processes Based on Emotions in Universities as Learning Organizations

Magdalena Platis

560

Inter-Organizational Knowledge Transfer for Supply Chains in Crisis

Stavros Ponis and Epaminondas Koronis

569

Institutional Planning of Knowledge Generation

Evgeny Popov, Maxim Vlasov, Anna Yu.Veretennikova

577

Knowledge Audit: Findings From a Case Study in the Energy Sector

Gillian Ragsdell, Steve Probets, Ghosia Ahmed and Ian Murray

584

Shared Knowledge: Eliminating the “Ba”

Thomas Schalow

594

Correlation Between Individual Knowledge and Organizational Learning Process

Christian-Andreas Schumann and Claudia Tittmann

600

Heuristic for Unscheduled Public Transport Navigation System

José Sendra Salcedo and Osvaldo Cairó Battistuti

607

On Some Knowledge Issues in Sciences and Society

Dan Serbanescu

616

Using the SECI Model to Analyze Knowledge Creation in Students’ Software Teams

Mzwandile Shongwe

626

Do it Like the European Union (EU) Does: The Applicability of EU Knowledge Cost Management to Start ups

Evangelia Siachou and Dimitris Apostolidis

634

Use and Acceptance of Learning Platforms Within Universities

Boyka Simeonova, Pavel Bogolyubov and Evgeny Blagov

642

iv


The Relationship between Knowledge Management and Employees' Empowerment in Justice Administration of Tehran Province

Faezeh Sohrabi, Alireza Chenari, Fattah Nazem, Mohamad Farahzadi and Masoumeh Bahmanabadi

652

Software Agent Societies for Process Management in Knowledge-Based Organization

Anna Sołtysik-Piorunkiewicz and Mariusz Żytniewski

661

Innovation and Sustainability: Two-Sided Knowledge Management by an Ice-Cream Producer

Inga Stankevice and Birute Slaustaite

670

Business Innovative Environment as a Prerequisite for a Long-run Competitive Advantage

Marta Christina Suciu and Cristina Andreea Florea

678

The Creative Society, Urban Revitalisation in the Creative Economy and Society: The Romanian Case

Marta-Christina Suciu and Mina FaneaIvanovici

686

Strategic Innovation – Access Path Towards a New Paradigm of an Academic Career Management

Marta-Christina Suciu, Irina Dumitrescu and Andrei Dumitrescu

692

Success Factors in Knowledge Sharing Behaviour Among Student Bloggers

Nor Intan Saniah Sulaiman, Mazlan Mohd Sappri, Mohd Syazwan Abdullah and Nazean Jomhari

702

Innovation, Knowledge and Incompetence: The Case of the Eurozone Macroeconomic Policies

Eduardo Tomé

712

Competence Management in Industrial Engineering Departments in the Czech Republic

David Tuček and Jaroslav Dlabač

722

Economic Evaluation of the Level of Knowledge Services in Selected OECD Countries

Zuzana Tučková and David Tuček

732

A Three-Dimensional Model of Identifying Barriers to Knowledge Management

Anna Ujwary-Gil

741

From KM Evaluation to Developing Evaluative Capability for Learning

Christine van Winkelen and Jane McKenzie

750

Profiling the Intellectual Capital of Italian Manufacturing SMEs: An Empirical Analysis

Chiara Verbano and Maria Crema

758

The Obligatory Passage Point: Abstracting the Meaning in Tacit Knowledge

John Walton

769

New Knowledge Creation by Collaborating GoalOriented Experts: Methodology and Models

Igor Zatsman and Pavel Buntman

776

Knowledge-Intensive Business Services (KIBS) and Their Role in the Knowledge-Based Economy

Malgorzata Zieba

785

Late Submission

793

Characteristics of Decision Problems In Innovation Process Planning

Magdalena Jurczyk – Bunkowska

795

Can Knowledge be Reliably Measured?

Rumniak Paweł

805

Insights into Knowledge Sharing in the Dubai Police Force

Dr Ibrahim Seba, Professor Jennifer Rowley and Dr Rachel Delbridge

814

PHD papers

823

Knowledge Management and Creative Thinking Framework Integrated in Training of Future Students

Andra Badea, Gabriela Prostean, Adrian Adam and Olivia Giuca

825

The Importance of Play in Overcoming Fears of Entrepreneurial Failure

Ramona Cantaragiu and Shahrazad Hadad

833

v


The Role of Emotional Intelligence Efficiency in Multinational Financial Institutions

Elizabeth Lorena Croitor (Tcaciuc), Cristian Valentin Hapenciuc, Livia Elena Blanariu (Vranciu) and Daniela Mihaela Sandu (Neamtu)

840

Knowledge Sharing and Channel Choice: Effects of the new way of Working

Arjan de Kok, Bart Bellefroid and Remko Helms

849

Job Evaluation for Knowledge-Based Organizations

Paweł Fiedor

860 ,

Towards a Decision Approach for the Characterization of Potential

Sahar Ghrab, Ines Saad, Faiez Gargouri and Gilles Kassel

868

Knowledge Management Influence on Innovation: Theoretical Analysis of Organizational Factors

Ingrida Girniene

877

Developing Knowledge Management Capabilities in Social Enterprises: UK Experience

Maria Granados, Vlatka Hlupic, Elayne Coakes and Souad Mohamed

886

Research Regarding the Informational System (Information and Knowledge) Required for an Environmental Manager

Ionut Viorel Herghiligiu , Luminita Mihaela Lupu and Bogdan Budeanu

896

The Impact of Emotional Knowledge on key Aspects of the Economy

Andrei-Alexandru Morosan, Gabriela Arionesei, Paul-Panfil Ivan and CristianValentin Hapenciuc

905

Factors for Knowledge Sharing Behaviour to Develop Trust in Professional Organisations Environment

Salah Rana, Malcolm Crowe and Abel Usoro

914

Knowledge Sharing as a Problem of the Individual Nature of Knowledge

Vaclav Reznicek, Zdenek Smutny, Jaroslav Kalina and Alexander Galba

920

DataTalks: A Unified Knowledge Pool in SaaS and Mashup Systems

Sasha Mile Rudan, Dino Karabeg and Alf Martin Johansen

926

Data Mart With Lean Six Sigma Concept for Performance Level Assessment in Knowledge Management Framework

Jevgeni Sahno, Eduard Shevtshenko and Tatjana Karaulova

932

What is Your Organization’s IQ? – A Practical Tool to Gauge Enterprise Intelligence

Evren Satıcı and Özalp Vayvay

942

Intra-Organizational Cooperation and Knowledge Sharing: A Comparison of Slovak LIS University Departments

Peter Steranka

950

The Role of Individual Factor in Knowledge Sharing Behavior Among Profit Oriented Webloggers

Ruzleeta Zakaria, Nor Intan Saniah Sulaiman, Haslinda Ibrahim, Mohd Syazwan Abdullah, and Nerda Zura Zabidi

961

1

Work In Progress Paper

969

A Knowledge Sharing System Based On Structured And Unstructured Knowledge

vi

Leandro Ramos da Silva and Nizam Omar

971


Preface These proceedings represent the work of researchers presenting at the 14th European Conference on Knowledge Management (ECKM 2013). We are delighted to be hosting ECKM at the Kaunas University of Technology.The conference will be opened by David Snowden of Cognitive Edge in the UK, who will talk about “Sense-making and Knowledge Management”. The second day will be opened by Soumodip Sarkar from the Univeristy of Evora, Portugal and will address “Osmosis and Knowledge flows in Entresutra”. ECKM provides an opportunity for academics concerned with current research and for those from the wider community involved in Knowledge Management, to present their findings and ideas to peers from the KM and associated fields. ECKM is also a platform for face to face interaction with colleagues from similar areas of interests. The conference has a wellestablished history of helping attendees advance their understanding of how people, organisations, regions and even countries generate and exploit knowledge to achieve a competitive advantage, and drive their innovations forward. The range of issues and mix of approaches followed will ensure an interesting two days. 221 abstracts were initially received for this conference. However, the academic rigor of ECKM means that, after the double blind peer review process there are 97 academic papers, 17 PhD research papers and 1 Work in Progress paper published in these Conference Proceedings. These papers reflect the continuing interest and diversity in the field of Knowledge Management, and they represent truly global research from some 46 different countries, including Algeria Australia, Austria, Bahrain, Boznia and Herzegovina, Brazil, Canada, Colombia, Costa Rica, Czech Republic, Denmark, Ethiopia, Finland, France, Germany, Hungary, India, Iran, Ireland, Israel, Italy, Japan, Jordan, Lithuania, Malaysia, Mexico, New Zealand, Norway, Poland, Portugal, Romania, Russia, Slovakia, Slovenia, South Africa, Spain, Sweden, Switzerland, Taiwan, Thailand, The Netherlands, Tunisia, United Kingdom, the USA and Vietnam. We hope that you have an enjoyable conference. Prof. Dr. Brigita Janiūnaitė Head, Department of Educational Science, Faculty of Social Sciences Programme Chair Prof.Dr. Asta Pundziene, Vice Rector for Research Prof.Dr. Monika Petraite, Dean, Faculty of Social Sciences Co-Conference Chairs Kaunas University of Technology, Kaunas, Lithuania September 2013

vii


Conference Committee Conference Executive Prof.Dr. Asta Pundziene, Kaunas University of Technology, Kaunas, Lithuania Dr.Monika Petraitė, Kaunas University of Technology, Kaunas, Lithuania Prof. Dr. Brigita Janiūnaitė, Kaunas University of Technology, Kaunas, Lithuania Doc.Dr. Jurgita Sekliuckiene, Kaunas University of Technology, Kaunas, Lithuania Prof.Habil.Dr. Palimra Juceviciene, Kaunas University of Technology, Lithuania Prof. Habil.Dr. Robertas Jucevicius Kaunas University of Technology, , Lithuania Doc.Dr. Gintare Tautkeviciene, Kaunas University of Technology, Lithuania Doc.Dr. Svetlana Sajeva, Kaunas University of Technology, , Lithuania Mini Track Chairs: Dr Alexeis Garcia-Perez, Coventry University, UK Dr Anikó Csepregi, University of Pannonia, Hungary Amani Shajera, University of Bahrain (UOB), Bahrain Dr Sandra Moffett, University of Ulster, Belfast, UK Dr Kristel Miller, Queens University, Belfast, UK Dr Christine van Winkelen, Henley Knowledge Management Forum, UK Professor Jane McKenzie, Henley Knowledge Management Forum, UK Prof.Dr.Constantin Bratianu, Academy of Economic Studies, Bucharest, Romania Gintare Tauteviciene, Kaunas University of Technology, Kaunas, Lithuania Dr Jan M. Pawlowski, University of Jyväskylä, Jyväskylä, Finland. Dr. Stavros T. Ponis, National Technical University of Athens (NTUA), Greece Dr. Epaminondas Koronis, University of Lincoln, UK Prof.dr. Marta-Christina Suciu, Academy of Economic Studies Bucharest, Romania Assistant Prof. dr. Evangelia Siachou, Hellenic American University, Greece Committee Members The conference programme committee consists of key individuals from countries around the world working and researching in the Knowledge Management and IS community. The following have confirmed their participation: Mahmoud Abdelrahman (Manchester Business School, UK); Habib Abubakar (African Development Bank Group, Tunisia); Pichamon Adulavidhaya (Bangkok University, Thailand,); Dr Ali Alawneh (Philadelphia University, Jordan); Dr Abdallah AlShawabkeh (University of Greenwich, UK,); Prof. Dr Eckhard Ammann (Reutlingen University, Germany); Albena Antonova (Sofia University, Bulgaria,); Dr Nekane Aramburu (University Of Deusto, San Sebastian, Spain); Dr Derek Asoh (Ministry of Government Services, Ontario , Canada); Associate Professor George Balan (Romanian-German University, Romania); Dr Joan Ballantine (University of Ulster, UK); Dr Pierre Barbaroux (French Air Force Academy / Research Center of the French Air Force, France); Dr Mary Basaasa Muhenda (Uganda Management Institute, Uganda); Prof. Dr. Aurelie Aurilla Bechina Arnzten (College University of Bruskerud, Norway); Prof Julie Béliveau (University of Sherbrooke, Canada); Dr. David Benmahdi (Université Paris 8, France,); Asst Professor Maumita Bhattacharya (Charles Sturt University, Albery, Australia); Prof. Dr. Markus Bick (ESCP Europe Wirtschaftshochschule Berlin, Germany); Heather Bircham-Connolly (University of Waikato, Hamilton, New Zealand); Dr Claudia Bitencourt (Universidade do Vale do Rio dos Sinos , Brazil); Pavel Bogolyubov (Lancaster University Management School, UK,); Karsten Bohem (University of Applied Sciences, Kufstein, Austria); Dr Ettore Bolisani (University of Padua, Vicenza, Italy); Prof Ionel Bostan (University of Iasi, Faculty of Economics, Romania); Andreas Brandner (KM-Net Austria, Austria); Prof Constantin Bratianu (Academy of Economic Studies, Bucharest, Romania, Romania); Dr Antonio Juan Briones (Universidad Politécnica de Cartagena, Spain); Prof Elisabeth Brito (University of Aveiro, ESTGA, Portugal); Sheryl Buckley (Unisa, South Africa); Dr Dagmar Caganova (Slovak University of Technology, Slovakia); Prof. Leonor Cardoso (University of Coimbra, Portugal); Professor Sven Carlsson (School of Economics and Management, Lund University, Sweden); Dr Gabriel Cepeda Carrion (Universidad de Sevilla, Spain); Dr David Cegarra (Universidad Politécnica de Cartagena, Spain); Dr Juan-Gabriel Cegarra-Navarro (Universidad Politécnica de Cartagena, Spain); Daniele Chauvel (SKEMA Business School , France); Satyadhyan Chickerur (M.S. Ramaiah Institute of Technology, Bangalore, , India); Alfred Chinta (University of Bolton, UK); Ana Maria Correia (Universidade Nova de Lisboa, Portugal); Dr Bruce Cronin (University of Greenwich Business School, UK); Dr Reet Cronk (Harding University, Searcy, Arkansas, USA); Anikó Csepregi (University of Pannonia, Department of Management, Hungary,); Roberta Cuel (University Of Trento – Faculty Of Economics, Italy); Dr Farhad Daneshgar (University of New South Wales, Australia); Dr Ben Daniel (University of Saskatchewan, Saskatoon, Canada); Prof Monica De Carolis (University of Calabria, Italy); Prof Annunziata De Felice (University of Bari, Italy); John Deary (Independent Consultant, UK & Italy); Dr Paulette DeGard (The Boeing Company, Seattle, USA); Dr Izabela Dembinska (University of Szczecin, Poland); Dr Charles Despres (Conservatoire des Arts et Metiers, Paris, France); Zeta Dooly (Waterford Institute of Technology , Ireland); Prof Dr Heinz Dreher (Curtin University, Perth, Australia); Dr Yan Qing Duan (Luton Business School, University of Luton, UK); Nasser Easa (University of Stirling, Scotland, UK); Sally Eaves (Sheffield Hallam University, UK); Professor John Edwards (Asviii


ton Business School, UK); Dr Anandasivakumar Ekambaram (SINTEF, Norway); Jamal El Den (Charles Darwin University, Australia); Dr Steve Eldridge (Manchester Business School, , UK); Isaac Enakimio (University of Greenwich/Kent and Medway Health Informatics, Kent,); Dr Scott Erickson (Ithaca University, USA); Mercy Escalante (Sao Paulo University, Brazil); Nima Fallah (University of Strasbourg, France); Dr Doron Faran (Ort Braude College, Israel); Dr Péter Fehér (Corvinus University of Budapest, Hungary); Dr Silvia Florea (Lucian Blaga University, Romania,); Dr Andras Gabor (Budapest University of Economic Sciences and Public Administration, Hungary); Brendan Galbraith (University of Ulster, UK); Elli Georgiadou (Middlesex University, UK); Dr Lilia Georgieva (Heriot-Watt University, UK); Gerald Guan Gan Goh (Multimedia University, Melaka, Malaysia); Dr Andrew Goh (International Management Journals, Singapore); Dr Miguel González-Loureiro (University of Vigo, Spain); Dr Loganathan Narayansamy Govender (University of Kwazulu-Natal, South Africa); Francesca Grippa (Scuola Superiore ISUFI, University of Salento, Italy); Norbert Gronau (University of Potsdam, Germany); David Gurteen (Gurteen Associates, UK); Dr Leila Halawi (Quinnipiac University, Hamden, USA); Linda Cathrine Hald (NTNU, Norway); Dr Matthew Hall (Aston Business School, UK); Associate Professor Meliha Handzic (International Burch University, Bosnia and Herzegovina); Dr. Harold Harlow (Wingate Univeristy, USA); Deogratias Harorimana (Southampton Solent University, , UK); Dr Mahmoud Hassanin (Pharos University,Alexandria, Eygpt); Prof Igor Hawryszkiewycz (University of Technology, Sydney, Australia); Dr Ciara Heavin (University college cork, Ireland,); Dr Peter Heisig (Leeds University Business School, UK); Remko Helms (Universiteit Utrecht, The Netherlands); Dr Ali Hessami (Vega Systems Ltd., UK); Dr Eli Hustad (University of Agder, Norway); Fahmi Ibrahim (Glasgow Caledonian University, UK); Dr Thomas Jackson (Loughborough University, UK); Dr Harri Jalonen (Turku University of Applied Sciences, Finland); Prof. Brigita Janiunaite (Kaunas University of Technology, Lithuania); Dr Daniel Jimenez (Universidad de Murcia, Spain); Prof. Palimra Juceviciene (Kaunas University of Technology , Lithuania); Prof. Robertas Jucevicius (Kaunas University of Technology , Lithuania); Selvi Kannan (Victoria University, Melbourne, Australia); Dr Silva Karkoulian (Lebanese American University Beirut Campus, Lebanon); Dr Sarinder Kaur Kashmir Singh (University Malaya, Malaysia,); Dr Marcela Katuščáková (University of Žilina, Slovakia); Prof. Dr. Turksel Kaya Bensghir (TODAIE-Public Administration Institute for Turkey and the Middle East, Turkey); Dr. Radwan Kharabsheh (Hashemite University, Jordan); Dr Prof Aino Kianto (Lappeenranta University of Technology, Finland); Monika Klimontowicz (University of Economics in Katowice, Poland,); Ute Klotz (Lucerne University of Applied Sciences and Arts, Switzerland); Dr Andrew Kok (Western Cape Government, South Africa); Dr Bee Theng Lau (Swinburne University of Technology, Australia); Rongbin W.B Lee (The HongKong Polytechnic University, Hong Kong); Prof. Dr Franz Lehner (University of Passau, Germany); Jeanette Lemmergaard (University of Southern Denmark, Denmark); Prof Ilidio Lopes (Polythenic Institute of Santarém, Portugal); Prof Monique Lortie (Universit du Qu bec Montreal, Canada); Dr Maria de Lourdes Machado-Taylor (CIPES, Portugal); Dr Agnes Maciocha (Institute of Art, Design, and Technology, Ireland); Avain Mannie (Dept of Finance, Port Elizabeth, South Africa); Prof Virginia Maracine (Academy of Economic Studies, Bucharest, Romania); Dr Farhi Marir (London Metropolitan University, UK); Prof Maurizio Massaro (Udine University, Italy,); Fiona Masterson (National University of Ireland, Galway, Ireland); Florinda Matos (ISCTE-IUL, Lisbon, Portugal); Prof Jane McKenzie (Henley Business School, United Kingdom); Dr. Dalila Mekhaldi (University of Wolverhampton, UK); Dr Robert Mellor (Kingston University, UK); Prof. Dr. Kai Mertins (Fraunhofer-IPK, Germany); Dr. Anabela Mesquita (ISCAP - Politechnique Institute of Porto, Portugal); Kostas Metaxiotis (National Technical University Athens, Greece); Dr Antonio Leal Millan (Universidad de Seville, Spain); Dr Kristel Miller (Queens University, Northern Ireland); Dr Sandra Moffett (University of Ulster, Londonderry, UK); Prof Samuel Monteiro (University of Beira Interior, Portugal,); Dr Mahmoud Moradi (University of Guilan, Iran); Dr Arturo Mora-Soto (Carlos III University of Madrid, Madrid,); Prof Oliver Moravcik (Slovak University of Technology, Slovakia); Aboubakr Moteleb (B2E Consulting, UK); Aroop Mukherjee (King Saud University, Saudi Arabia); Dr Birasnav Muthuraj (New York Institute of Technology, Bahrain); Arash Najmaei (MGSM, Australia); Dr Elena Irina Neaga (Loughborough University, UK); Dr. Gaby Neumann (Technical University of Applied Sciences Wildau, Germany); Dr Emanuela Alia Nica (Center for Ethics and Health Policy (CEPS) and University "Petre Andrei" Iasi, Romania); Dr Cristina Niculescu (Research Institute for Artificial Intelligence of the Romanian Academy, Romania); Klaus North (FH Wiesbaden, Austria); Dr Jamie O'Brien (St. Norbert College, USA); David O'Donnell (Intellectual Capital Research Institute of Ireland, Ireland); Gary Oliver (University of Sydney, Australia); Dr. Ivona Orzea (Academy of Economic Studies, Romania,); Dr Kaushik Pandya (Birmingham College, UK); Dr Paul Parboteeah (Loughborough University, UK); Jan Pawlowski (University of Jyväskylä, Austria); Dr Corina Pelau (Academy of Economic Studies, Bucharest, Romania); Monika Petraite (New York Institute of Technology, Lithuania); Rajiv Phougat (IBM, USA); Prof Paulo Pinheiro (Universidade da Beira Interior, Portugal); Prof Mário Pinto (Polytechnic Institute of Porto, Portugal,); Professor Selwyn Piramuthu (University of Florida, Gainesville, USA); Dr Gerald Polesky (IBM. 11425 N. Bancroft Dr, Phoenix, USA); Dr John Politis (Neapolis University, Pafos, Cyprus); Dr Nataša Pomazalová (Faculty of Economics and Management University of Defence, Czech Republic); Dr Stavros Ponis (National Technical University Athens, Greece); Prof Asta Pundzienė (Kaunas University of Technology , Lithuania); Dr Lila Rajabion (Penn State University, Mont Alto, USA); Prof Thurasamy Ramayah (Universiti Sains Malaysia, Malaysia); Dr M S Rawat (DCAC, University of Delhi, India); Dr. Carlos Raymundo (UPC, Peru); Prof. Dr. Ulrich Reimer (University of Applied Science St. Gallen, Switzerland); Dr Ulrich Remus (ACIS Department, University of Canterbury, New Zealand); Dr Alexander Richter (Bundeswehr University Munich, Germany); Gerold Riempp (EBS, Germany,); Eduardo Rodriguez (IQ Analytics, Ottawa, Canada); Dr Inès Saad (Amiens School of Management , France); Dr. Josune Sáenz (University of Deusto, San Sebastián, Spain); Prof. Lili Saghafi (Canadian International College, Egypt,); Mustafa Sagsan (Near East University, Nicosia, Northern Cyprus, Cyprus); Prof. Svetlana Sajeva (Kaunas University of Technology , Lithuania); Dr. Kalsom Salleh (Faculty of Accountancy, University Technology MARA, Malaysia); Dr. María-Isabel Sanchez-Segura (Carlos III University of Madrid, Spain,); Dr. Antonio Sandu (Mihail Kogalix


niceanu University,Romania); Prof Helena Santos-Rodrigues (IPVC, Portugal); Prof Dan Savescu (Transilvania University of Brasov, Romania); Dr Ousanee Sawagvudcharee (Stamford International University (Phetchaburi Campus) Thailand); Enrico Scarso (Università Degli Studi Di Padova, Italy); Dr Christian-Andreas Schumann (University of Zwickau, Germany); Prof. Jurgita Sekliuckiene (Kaunas University of Technology , Lithuania); Dr Maria Theresia Semmelrock-Picej (Klagenfurt University, Austria); Amani Shajera (University of Bahrain, Bahrain,); Dr Mehdi Shami Zanjani (University of Tehran, Iran); Peter Sharp (Regent’s College, London , UK); Dr Michael Shoukat (UMUC, USA); Dr Evangelia Siachou (Hellenic American University , USA); Dr Kerstin Siakas (Alexander Technological Educational Institute of Thessaloniki, Greece); Prof Umesh Kumar Singh (Vikram University, Ujjain, India); Dave Snowden (Cognitive Edge, Singapore); Dr Siva Sockalingam (Glasgow School for Business and Society, UK); Prof.Dr. Marta-Christina Suciu (Academy of Economic Studies Bucharest, Romania); Christine Nya-Ling Tan (Multimedia University, Melaka, Malaysia); Dr Llewellyn Tang (University of Nottingham Ningbo , China); Prof. Gintare Tautkeviciene (Kaunas University of Technology , Lithuania); Dr Sara Tedmori (Princess Sumaya University for Technology, UK); Claudia Thurner-Scheuerer (Community Manager of Plattform Wissensmanagement,Know-Center, Graz, Austria); Dr Eduardo Tomé (Universidade Lusiada, Portugal); Dr Zuzana Tuckova (Tomas Bata University in Zlín, Czech Republic); Prof Alexandru Tugui (Alexandru Ioan Cuza University, Romania); Geoff Turner (University of Nicosia, Cyprus); Andras Vajkai (University of Pécs, Hungary); Dr Changiz Valmohammadi (Islamic Azad University-South Tehran Branch, Iran); Dr Christine van Winkelen (Henley Business School, University of Reading, UK); Professor Jose Maria Viedma (Polytechnic University of Catalonia, Spain); Maria Weir (Independent Consultant, Italy); Christine Welch (University of Portsmouth, UK); Florian Welter (IMA/ZLW & IfU - RWTH Aachen University, Germany,); Anthony Wensley (University of Toronto, Canada); Dr Sieglinde Weyringer (University of Salzburg, Austria); Roy Williams (University of Portsmouth, UK); Dr Lugkana Worasinchai (Bangkok University, Thailand); Prof Les Worrall (University of Coventry, UK); Dr Mohammad Hossein Yarmohammadian (Isfahan University of Medical Sciences, Iran)

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Biographies Conference Co-Chairs Prof.Dr. Asta Pundziene holds doctor degree in Social Sciences (organizational psychology), defended at Vytautas Magnus University. The beginning of the career was in Vytautas Magnus University in 1993 with the responsibilities of the Administrator of the Pedagogical studies programmes. From 1996 till 1999 Asta was the Project Manager in the Centre for Vocational Education and Research at Vytautas Magnus University. From 1999 till 2003 Asta was Vice-Director of the Centre for Vocational Education and Research at Vytautas Magnus University. From 2003 till 2004 – National Seconded Expert (END) at the European Training Foundation (ETF) in Turin, Italy. From 2004 until 2006 the Director for Change Management Programme at ISM University of Management and Economics. From 2006 until 2011 Asta was the Head of the Intellectual Capital and Business Competence Department, Editor of the Baltic Journal of Management. Since 2011 to present Asta is the Vice Rector for Research at Kaunas University of Technology. Main research interests are in Change management, Human recourse development, and Career development. Prof.Dr. Monika Petraite is a dean at the Faculty of Social Sciences, and also Full Professor at the Institute of Business Strategy, Kaunas University of Technology, Lithuania. She holds doctor degree in Social Sciences (management and administration) from Kaunas University of Technology. The research focus is on innovation management (networking, open innovation, new product development, knowledge management for innovation), R&D in business and NTB firm creation, high tech (knowledge based) entrepreneurship, high tech business strategies (especially small globally born businesses), enhancement of knowledge and innovation culture and design of knowledge intensive organizations. She is a senior researcher in the national programmes for innovation and innovation cultures research, and leads a scientific group on Innovation research.

Programme Chair Dr. Brigita Janiūnaitė is professor and Head of the Department of Educational Studies at the Institute of Educational Studies, Faculty of Social Sciences, Kaunas University of Technology. She has supervised 11 PhD theses. She also is Executive Editor of the journal ‘Social Sciences’ and member of the Board of the Lithuanian Educational Research Association. Brigita Janiūnaitė is an expert of the European Science Foundation. She is a committee member of International Conference of Intellectual Capital, Knowledge Management and Organisational Learning. Her research is focused on the issues of change management and social innovation implementation; development of innovative culture at individual and organizational level; higher education; curriculum development. She is actively involved in international and national research and study projects and evaluation of study programmes. Among her publications is a monograph on ‘Educational Innovation Implementation’ (2004, in Lithuanian) and research study ‘Citizen’s innovative culture’ (2007, in Lithuanian) and “Organization innovation culture” (2011). She was elected a Visiting Fellow at St.Edmund’s College, University of Cambridge, in 2007.

Keynote Speakers Dave Snowden is the founder and chief scientific officer of Cognitive Edge. His work is international in nature and covers government and industry looking at complex issues relating to strategy, organisational decision making and decision making. He has pioneered a science based approach to organisations drawing on anthropology, neuroscience and complex adaptive systems theory. He is a popular and passionate keynote speaker on a range of subjects, and is well known for his pragmatic cynicism and iconoclastic style. His company Cognitive Edge exists to integrate academic thinking with practice in organisations throughout the world and operates on a network model working with Academics, Government, Commercial Organisations, NGOs and Independent Consultants. He is also the main designer of the SenseMaker® software suite, originally developed in the field of counter terrorism and now being actively deployed in both Government and Industry to handle issues of impact measurement, customer/employee insight, narrative based knowledge management, strategic foresight and risk management. Prof. Dr. Soumodip Sarkar received his PhD in Economics from Northeastern University, Boston in 1995. He is currently Dean of Graduate Studies at the University of Évora, Portugal where he is also the coordinator of the Program in Entrepreneurship and Innovation and a professor in the Department of Management. He is also a researcher at CEFAGE-UE and his research interests are innovation, entrepreneurship and international business. The author of Innovation, Market Archetypes and Outcome (2007 – Pringer Verlag); Empreendedorismo e Inovação (2007 - Escolar Editora) and Entrepreneurial Innovator (2008 – Elsevier Campus), Professor Sarkar has published papers in several scientific journals and is in the editorial board of four international scientific journals. The project leader in many Portuguese and European projects, Soumodip holds copyrights to the integrated innovation model developed by him along with simulation software. xi


Mini Track Chairs Prof.Dr.Constantin Bratianu is professor of Strategic Management and Knowledge Management at the Faculty of Business Administration, Academy of Economic Studies, Bucharest, Romania. He is Director of the Research Centre for Intellectual Capital, Academy of Economic Studies, Bucharest. He is a member of the American Academy of Management, Southern Association of Management, USA, and International Association of Knowledge Management. He published over 30 books, and over 200 papers in international journals and international conference proceedings. His main academic interests are: knowledge dynamics, knowledge management, intellectual capital, and strategic management. Dr Anikó Csepregi is an assistant professor at University of Pannonia, Department of Management in Hungary. Her main fields of interest include knowledge management and competence management. She has published several articles and presented her work at national and international conferences. She is an editorial board member of knowledge management journals and a committee member of knowledge management conferences. She takes part in an international knowledge management research group with research partners from Bulgaria, Croatia and Romania. Dr Alexeis Garcia-Perez holds a PhD degree in Information and Knowledge Management from Cranfield University, UK. His research focuses on the development of sustainable Knowledge Management strategies and tools to improve collaboration within organisations. He has successfully completed Knowledge Management projects with the UK Ministry of Defence and with global engineering companies such as General Electric (GE) Energy, Siemens Industrial Turbomachinery and Converteam UK. Alexeis is currently a lecturer at Coventry University. He has also worked for Cranfield University and the University of Bath in the UK. Dr Epaminondas Koronis is a Senior Lecturer at the University of Lincoln, UK and a visiting scholar at George Washington University and the University of Cyprus. He holds degrees in Business, Organization Studies and he has been awarded his PhD from Warwick Business School, UK. In the past, his research and consulting experience have focused on the areas of Knowledge Management, Crisis Management, Organizational and Supply Chain Resilience and he has published papers and book chapters on Knowledge and Outsourcing and Crisis Management. Professor Jane McKenzie has worked with the Henley Knowledge Management Forum since its inception in 2000. She has carried out applied research with this community of knowledge and learning professionals into a wide variety of topics, ranging from improving internal and external collaboration and the use of social media, to decision making, leadership and improving conversations. Jane has collaborated with academics and leading practitioners from around the world and has published extensively in academic and practitioner journals. Dr Kristel Miller is a Lecturer in Management at Queens University, Belfast. Her research interests lie in the areas of absorptive capacity, knowledge transfer and innovation within knowledge intensive contexts. She has publications in the area of knowledge transfer and technology commercialisation within Universities. Dr Sandra Moffett is a Senior Lecturer of Computer Science with the University of Ulster’s School of Computing and Intelligent Systems, Magee Campus. She is a core member of the Ulster Business School Research Institute. Her expertise on Knowledge Management contributes to her being one of the UK leading authors in this field. She has received a number of research awards and citations for her work. External funding has enabled Dr Moffett to undertake extensive quantitative/qualitative research to benchmark KM implementation within UK companies. Dr Jan Pawlowski works as Professor in Digital Media - Global Information Systems at the University of Jyväskylä, Finland jan has a Masters' Degree and Doctorate in Business Information Systems (University of Duisburg-Essen). He is a Professor of Digital Media with the specialization "Global Information Systems". This includes the research coordination of several national and European projects. Main research interests and activities are in the field of Global Information Systems, E-Learning, Modeling Learning-related Processes, Procedural Models, Learning Technology Standardization, Quality Management and Quality Assurance for Education, and Mobile / Ambient Learning. Actively involved in research organizations (AACE, GI, IEEE) and in standardization organizations (DIN, CEN, ISO/ IEC JTC1 SC36). Jan is also the acting chair of the CEN/ISSS Workshop Learning Technologies.

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Dr Stavros T. Ponis holds a Dipl. Ing. Degree (1996), and a Ph.D. (2000) in mechanical engineering from the National Technical University of Athens (NTUA), Greece. He has also conducted post doc research (2006-2008) on the field of Knowledge Management and Logistics to support Virtual Enterprise Networks. He is an Assistant Professor of Supply Chain Management in the Section of Industrial Management & Operations Research at NTUA. He has more than 70 publications in fully reviewed scientific journals, International Conferences’ Proceedings and the Commercial Press in the areas of Supply Chain Management, Knowledge Management, Production Planning and Control, Business Process Modeling, Networked and Virtual Enterprises, and their supporting Information Systems. Prof Dr Marta-Christina Suciu is a full professor and PhD supervisor at the Academy of Economic Studies Bucharest, Romania. Her main topics of interest are; Knowledge & innovative based society and economy; Creative & Innovative Management; Knowledge Management and Innovation; Intellectual Capital. She is actively involved in supporting these topics as a trainer, a PhD and Post PhD supervisor and as a researcher. She is coordinator of the national research project IDEI 1224 dedicated to the topic of “Creative economy & knowledge–based society. Challenges and opportunities for Romania”, 2007-2010. Assistant Prof Dr Evangelia Siachou holds a Ph.D. in Knowledge Management from Athens University of Economics and Business, an M.Sc. in Industrial Relations and Personnel Management from the London School of Economics (LSE) and a Bachelor’s degree in International and European Studies from Panteion University of Athens. Her past work experience include among others the Human Resource Department of CDE under the aegis of European Commission in Brussels. She joined the faculty of Hellenic American University in 2010 as an Assistant Professor of Human Resources and Management and currently serves as the Coordinator of the BSBA Program. Dr Christine van Winkelen has worked with the Henley Knowledge Management Forum since its inception in 2000. She has carried out applied research with this community of knowledge and learning professionals into a wide variety of topics, ranging from improving internal and external collaboration and the use of social media, to decision making, leadership and improving conversations. Jane has collaborated with academics and leading practitioners from around the world and has published extensively in academic and practitioner journals.

Biographies of Presenting Authors Dr. Mohd Syazwan Abdullah graduated with a PhD (Computer Science) from University of York, UK in 2006 and works in the areas of knowledge management, knowledge engineering, knowledge management technologies, knowledge-based systems and information engineering. Currently he holds the post as a senior lecture/deputy director at the School of Computing at Universiti Utara Malaysia. Adrian Adam received the Engineer degree (1990) in Engines with Internal Combustion from the politehnica University of Timisoara, Faculty of Mechanics. He is currently PhD Student in the Department of Management from the politehnica University of Timisoara, Romania. Ghosia Ahmed is a PhD student at Loughborough University’s Department of Information Science. Her research draws attention to the largely unexplored area of ‘knowledge security’. Ghosia is aiming to identify and address the intrinsic clash between knowledge sharing and information security practices, in order to nurture secure knowledge sharing in organisations. Versavia Ancusa received her PhD degree in 2009 from POLITEHNICA University of Timisoara, in Computer Science. She is currently a Senior Lecturer at the Department of Computers, Faculty of Automation and Computers, POLITEHNICA University of Timisoara, Romania. Dr. Ancusa’s main research interests are affective computing, fault tolerance and reliability, complex networks. Dimitris Apostolidis holds a Ph.D and a M.A in International Relations from Boston University, Boston, Massachusetts, and a B. Sc in Accounting and Finance from the American College of Greece, Athens, Greece. At Hellenic American University he has been teaching undergraduate and graduate courses in business and humanities and currently serves as Coordinator of Student Affairs. Andra Badea received the Master degree (2011) in Competitiveness Management and Engineering from the politehnica University of Timisoara, Faculty of Management in Production and Transport, section: Engineering and Management. She is currently PhD Student in the Department of Management of the politehnica University of Timisoara, Romania.

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Frank Bannister is a Associate Professor, information systems, Trinity College, Dublin. Prior to becoming academic worked in Irish civil service and PricewatershouseCoopers as management consultant. Researches e-government, e-democracy, on-line privacy and trust and IT value and evaluation, particularly public sector. Co Director, Permanent Study Group on eGovernment within European Group on Public Administration. Editor-Electronic Journal of e-Government; Fellow- Trinity College, Dublin; member-Institute of Management Consultants, Ireland; Fellow-Irish Computer Society; Chartered Engineer. Nicolene Barkhuizen is an Associate Professor and Head of the Department of Industrial Psychology, North-West University, and Mafikeng Campus in South Africa. She is the programme leader of an established research focus area on Talent Management. Nicolene has more than 60 peer reviewed publications which includes a book, chapters in textbooks, conference proceedings and journal articles. Denise Bedford is currently a Goodyear Professor of Knowledge Management, Kent State University. She Teaches courses in economics of information, intellectual capital management, semantic analysis methods, communities of practice, and other knowledge management topics. Research interests include communities of practice, use of semantic analysis methods and technologies, multilingual architectures, business rules engineering, search architectures and governance models, intellectual capital and knowledge economies. Marc Bettoni is Director of Research & Consulting at the Swiss Distance University of Applied Sciences (FFHS) focusing on Knowledge Cooperation and e-Collaboration. Since 1981 contributions to Radical Constructivism. From 1977 to 2005 researcher, engineer and lecturer with industrial and academic organisations in the domains of machine design, engineering education, IT development, knowledge engineering and knowledge management. Madeleine Block is a doctoral student at the Faculty of Social Sciences and Business Studies at the University of Eastern Finland in Kuopio. Her main field of interest is knowledge management; the current research is related to the issues of understanding knowledge sharing within organisations. Razvan Bogdan received his PhD degree in 2009 from POLITEHNICA University of Timisoara, in Computer Science. He is currently Senior Lecturer at the Department of Computers, Faculty of Automation and Computers, POLITEHNICA University of Timisoara, Romania. Dr. Bogdan’s main research interests are in dependability of computer systems, human-machine interfaces, embedded systems, complex networks. Pavel Bogolyubov is a Management and Business Development Fellow at Lancaster University Management School, UK. Pavel’s First degree in Physics was at Herzen University in St. Petersburg, Russia, and MBA from Bradford School of Management, UK. Pavel has spent ten years working in various Continuous Improvement roles in FMCG multinationals across Europe. Research interests are centred on “softer” aspects of Web 2.0 and its role in KM. Ettore Bolisani (“Laurea” Electronic Engineering, Ph.D. Innovation Studies - University of Padua) is Associate Professor at the Department of Management and Engineering (University of Padua). In 1997 he was UE TMR visiting research fellow at the University of Manchester, where he conducted a research project on the developments of Electronic Commerce. His research centres on ICT management and Knowledge Management. He was Chair of the European Conference on Knowledge Management held at the University of Padua in 2009. He is founder member and president of IAKM (International Association for Knowledge Managment) Constantin Bratianu is professor of Strategic Management and Knowledge Management, UNESCO Department for Business Administration and Director of the Research Center for Intellectual Capital, Bucharest University of Economic Studies, Romania. He is founding editor of the international journal Management & Marketing. His academic interests are: knowledge dynamics, knowledge management, intellectual capital, and strategic management. Valentina Burksiene – dr. of social sciences, a lecturer at Klaipeda University, Faculty of Social Sciences. Valentina research interests are organizational learning, knowledge creation, sustainable development, strategic planning, public administration. More than years practice if public administration and strategic development Christopher Burt is an Associate Professor of Industrial and Organizational Psychology at the University of Canterbury, New Zealand. His research focuses on trust, including the relationship between trust and employee safety, developing safetyspecific trust in new recruits, and the influence of trust on employee voicing. He has published over 70 journal papers. Osvaldo Cairo is a tenured professor of ITAM since 1988. He is the author of more than 50 articles published in international journals and conferences and 10 books published with McGraw-Hill, Pearson, Springer, and Alfaomega. He is a member of the Mexican National System of Researchers, and participates in evaluation committees for CONACYT, CONICET, and United Nations. xiv


Ramona Cantaragiu is a PhD candidate at the Bucharest University of Economic Studies where she studies individual and institutional instances of academic entrepreneurship in social sciences universities. She is an Editorial Assistant for the international peer-reviewed journal Management & Marketing. Challenges for the knowledge society and she also holds seminars on business management and entrepreneurship. Antonio José Carrasco-Hernandez (antonioc@um.es) is a Professor of management at the University of Murcia (Spain). His current research focuses on the relationships among innovation, human resource management and family firms. He has recently published in Family Business Review, Management Research and The Electronic Journal of Knowledge Management. Delio Ignacio Castañeda PhD (Cum Laude) in Organizational Behavior: Universidad Autónoma de Madrid, Spain. Master (with Distinction) in Education: University of Manchester, England. Psychologist: Universidad Católica de Colombia. At the moment Associate Professor at Pontificia Universidad Javeriana and invited professor in the fields of Knowledge Management and Organizational Behavior. Dr Juan Gabriel Cegarra is associate professor of the Business Administration Department of the Universidad Politécnica de Cartagena (Spain). His research interests are on the use of knowledge management to help small and medium businesses to become more competitive. As a lecturer within the Business Administration Department, he has supervised two national projects and three PhD candidates in the domain of knowledge management. Ufuk Celikkan MSc. and PhD. degrees from North Carolina State University, Raleigh, USA. Worked as Advisory Software Engineer in Server and Software Divisions of IBM, Austin, Texas and then in Smart Card Division of Gemalto Inc. also in Austin, Texas. Currently Assistant Professor in the Department of Software Engineer at Izmir University of Economics, Turkey. Maria Crema is a Phd Student of Innovation Management at Department of Management and Engineering of University of Padova (Faculty of Engineering). Her main research areas are: innovation management and risk management. Hossein Chenari is M.A. holder in MBA. He has published 20 papers in the field of computer science. He has been the head of department of Computer Graphics in Applied and Scientific University, Branch No. 24. He is the author of the 3 reference books about Graphic Softwares. Elizabeth Lorena (Tcaciuc) Croitor is from Suceava, who are a licensed in the economy and are in the final year doctoral specialization Economics. She has worked four years in banking and sales disciplines are collaborating on Marketing and Economics from the University Stefan cel Mare Suceava Dr. Anikó Csepregi is an Assistant Professor at University of Pannonia, Hungary. Her main fields of interest include knowledge management and competence management. She has published articles and presented her work at national and international conferences. She is an editorial board member of KM journals and a committee member of KM conferences. Arjan de Kok is PhD researcher at Utrecht University in The Netherlands. His research topic is ‘The New Way of Working and the role of ICT in the implementation of NWOW’. Arjan de Kok has over 20 years experience as organization & ICT consultant in engineering and maintenance environments. Dr Rachel Delbridge is Senior Lecturer in Information and Communications. Her teaching and research interests are in information and knowledge management, learning, teaching and student performance and achievement. Jaroslav Dlabač is a graduate of Tomas Bata University in Zlin. He is now Senior Consultant in API Slaný and External Assistant Professor at the Tomas Bata University in Zlin, Department Department of Industrial Engineering and Information Systems, Faculty of Management and Economics, Tomas Bata University in Zlín. Andrei Dumitrescu is an Associated Professor at the Mechanical and Electrical Engineering Faculty, Petroleum-Gas University of Ploiesti. He holds a PhD in Mechanical Engineering from the same University and is a member of the Association of Managers and Economic Engineers from Romania. His research activities include project management and production systems engineering. Sally Eaves is a Senior Manager in the IT and Telecommunications Sector with certifications in ITIL, Prince2 and Six-Sigma. A committed ‘practitioner‐researcher’, she is engaged in collaborative, intersectional projects with Sheffield Hallam University with whom she obtained a Distinctive MSc in IT and Management in 2012. Interests include knowledge management, intellectual capital and methodological innovation.

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Anandasivakumar (Siva) Ekambaram works as a research scientist at SINTEF – Technology and Society, Productivity and Project Management, Trondheim, Norway. He obtained his doctoral degree, which focuses on project management and knowledge transfer in organizations, from the Norwegian University of Science and Technology (NTNU). Besides his research work, he is involved in teaching activities at NTNU. Tiit Elenurm is head of the entrepreneurship department at the Estonian Business School. Ph. D. in 1980 for the dissertation “Management of the Process of Implementation of New Organizational Structures”. Author of more than 110 research publications. Research interests include knowledge management, innovative entrepreneurship and international transfer of management knowledge. Paweł Fiedor is from Poland. He obtained Master of Science degree in Information Management from Cracow University of Economics (Kraków, Poland) in 2010. He is currently a PhD candidate in economics therein. He works in financial industry, the press and education. His research interests include economics of information, econophysics and knowledge management. Nora Fteimi studied Information Systems (Wirtschaftsinformatik) at Otto-Friedrich University of Bamberg in Germany. Currently she works as a PhD researcher at the Chair of Information Systems II of the University of Passau in Germany. Her fields of research and interest are particularly knowledge management, business intelligence and process modeling. Alexander Galba graduated from cybernetics at Faculty of Mathematics and Physics, Charles University in Prague. Currently, he makes business in ICT and works at the Department of Systems Analysis, University of Economics, Prague, where he deals with business informatics. Aukse Galbuogiene is a doctoral student and the junior researcher at the Department of Strategic Management, Kaunas University of Technology. She is doing a PhD in the field of the development of Smart Business Systems. Smart specialisation is also an important dimension in her research. Oscar Ojeda Galicia holds master degree in Information Technology and Management, defended at Instituto Autónomo de México (ITAM). From 2002 till 2003 –Web Master Developer at AVAYA, México. From 2003 untill 2008 – Systems Management Engineer and Systems Management Leader at Telcel. Since 2010 to present – IT Executive at Mexico’s Ministry of Energy. Dr Alexeis Garcia-Perez is a Lecturer in Business Information Systems at Coventry University teaching and doing research on Knowledge Management. Experience includes collaborations with industry in elicitation of knowledge from experts from different domains. Member of IT Section of International Federation of Library and Information Professionals (IFLA) and founding member of International Association for Knowledge Management (IAKM). Faiez Gargouri is a Professor at the High Institute of Multimedia and Computer System of Sfax (Tunisia). Hi is now the headmaster of MIRACL Laboratory. Sahar Ghrab is a PhD student in the MIS (Modelisation Information System) laboratory (Amiens-France) and in the MIRACL (Multimedia, InfoRmation Systems and Advanced Computing Laboratory) laboratory (Sfax Tunisia). Ingrida Girniene is a Lector and PhD student in the Faculty of Communication, Vilnius University, and Vilnius, Lithuania. Dissertation topic: “Influence of knowledge management expressions on the organization: innovation aspect”. She has a master degree in International Communication. Practical experience: working as business information and communication manager. Scientific experience: participation in the international and national conferences. Olivia Giuca received the PhD. Degree (2012) in mechanical engineering from the „Politehnica” University Of Timisoara. She Is Currently Assistant Professor In The Department Of Management From The Politehnica University Of Timisoara, Romania. Gianna Giudicati is currently working as Knwoledge Management Specialist in eni SpA. She had her PhD in 2012 in “Economics and Management – Behavioral Studies in Management and Organizations” at University of Trento (Italy) and spent her abroad period at Harvard University-IQSS (Boston). Her fields of research covers knowledge management, innovation, social influence, and social-network methods. Maria Granados from Colombia is a PhD Candidate and Visiting Lecturer in Business Information Management and Operations at University of Westminster in London, with over nine years experience in the private, social economy and academic sectors. Her research interests and publications are in social enterprises, enterprise networks, knowledge management and sociotechnical evaluations.

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Kristina Grumadaite is a PhD student of Management and Administration at the Faculty of Social Sciences of Kaunas University of Technology. Main research interests: self-organisation based systems, organizational creativity and emotional intelligence. kristina.grumadaite@ktu.lt. Shahrazad Hadad is a first year PhD student at the Bucharest University of Economic Studies researching the field of Corporate Social Entrepreneurship. She is currently a seminar teaching assistant for the following courses: Corporate Entrepreneurship and Challenges of Growth, Decision Making Processes, and Customer Relationship Management. She is an Editorial Assistant for the international peer-reviewed journal Management & Marketing. Challenges for the knowledge society. Meliha Handzic is a Professor of Management and Information Systems, International Burch University, Sarajevo and Suleyman Sah University, Istanbul. PhD from University of New South Wales, Sydney. Research interests lie knowledge management and decision support. Meliha has published extensively on these topics in leading journals. Meliha is currently on executive board of IAKM and serves as regional editor (Asia-Pacific) for KMRP. Professor Dennis Harlow has been a vice president, director and senior manager executive for world class companies such as IBM, GE and Qualcomm in a management career that spans 25 years. He has developed over 20 new products based on technologies such as GIS, GPS GSM and CDMA(wireless). He holds a patent in GPS technology. He has published over thirty Knowledge Management and entrepreneurship articles in leading international business journals/conferences . Dr Remko Helms is an assistant professor at the Department of Information and Computing Science at Utrecht University where he teaches Knowledge Management. His researches focus on on knowledge sharing networks and social media. Dr Helms is co-founder of the International Association for Knowledge Management and departement editor for Connected Scholars at the Association of Information Systems. Ionut Viorel Herghiligiu Currently I am a PhD student in the last year at “Gheorghe Asachi” Technical University from Iasi, Romania and in the first year at University of Angers, ISTIA, France. The title of my PhD thesis is “Research On The Environmental Management System As A Complex Process At Organizations Level” Henri Inkinen, M.Sc. (Econ. & Bus. Adm.) is a Doctoral Student at the Technology Business Research Center (TBRC) at Lappeenranta University of Technology. His research interests are in the areas of intellectual capital and knowledge management practices. He has been involved with these issues through his work experience within knowledge-intensive industries. Dr Päivi Iskanius is Adjunct Professor at the University of Oulu, Department of Mechanical Engineering. Her research fields are supply chain management, information management, logistics, networking, project business management, agile business, and e-business applications. She is also interested in innovation management, knowledge management and change management issues. Currently, she has over 120 research publications in these areas. Prof. Thomas W Jackson (PhD) holds a chair in Information and Knowledge Management and is the Director of the Centre for Information Management. Research areas are Email and Information Retrieval, Knowledge Management, including their combination to realise a Natural Language Processing Email Knowledge Extraction system that has the world’s best f-ranking measure. Mahsa Mahmoud Jahantab received is PhD student doing Knowledge Management research at the Faculty of Engineering and Computing of Coventry University, UK. She has completed a BSc in Electrical Engineering from American University in Dubai (AUD) in 2008 and an MSc in Engineering Project Management at Coventry University in 2010 with outstanding results. Harri Jalonen works as Research project group leader and Principal lecturer at Turku University of Applied Sciences. Doctoral degree in knowledge management from Tampere University of Technology. Long-term research experience dealing with knowledge and innovation management issues in different organizational contexts. Recent research focused on fuzziness of innovation and role of social media in innovation processes. Kalina Jaroslav graduated from applied informatics. Currently, he is PhD student at the Faculty of Informatics and Statistics, University of Economics, Prague. He deals mainly with modelling. Dhouha Jaziri Bouagina is a doctoral student in Marketing at high institute of management of Tunis (ISG, Tunis, URMR research centre), University of Tunis. Her research concerns the customer experience and the knowledge management. She is interested in the tourism field research. Daniel Jiménez-Jiménez is a Lecturer Professor of management at University of Murcia (Spain). He has a PhD. in Management and MA in Human Resource Management from University of Murcia. Research focuses on relationships among innovaxvii


tion, human resource management and knowledge management. He has recently published in Personnel Review, Industrial Marketing Management, International Journal of Operations and Production Management, The Electronic Journal of Knowledge Management, British Journal of Management and Journal of Business Research. Palmira Juceviciene Ph. D., Habil. Dr., full professor at Kaunas University of Technology. Palmiria research interests are individual and organizational learning, knowledge creation and management, learning organizations and regions, human resource development, higher education. Dr. Juceviciene has published more than 200 scholarly articles and 10 books. Palmira is a Consultant in individual and organizational learning, learning organizations and regions, human resource development. Robertas Jucevicius is a Professor and Director of Business Strategy Institute at Kaunas University of Technology, Lithuania. Robertas has a PhD in Economics and Habilitated Doctor in Management. He is also a visiting fellow at the University of Cambridge (UK), as well as Fulbright (USA) and Wallenberg (Sweden) fellow and the member of the Council for National Progress of Lithuania. Magdalena Jurczyk-Bunkowska studied production management at Warsaw University of Technology, where she received a PhD title in 2004. Currently, she works at Opole University of Technology as a researcher and lecturer. She was a member of Polish Academy of Science. Now, her fields of research and interest are innovation management especially operational approach covering innovation process planning. Martin Katuščák is a PhD. student at the University of Žilina. Masters graduate of the Comenius University in Bratislava, specialised in comprehensive processing of written cultural and scientific heritage. He worked for 7 years in the Slovak National Library as a digital librarian participating in European projects and as a national expert in digitisation and digital preservation. Marcela Katuščáková is a Lecturer at the University of Žilina. Masters and PhD. graduate of the Comenius University in Bratislava. She is working in research and education, specializing in information and knowledge management, scientific collaboration, storytelling and text mining. She has worked in the field of knowledge management implementation in research projects such as the Memory of Slovakia and KNIHA SK. Dr. Radwan A. Kharabsheh is a lecturer in international business and the assistant dean, international affairs at the Hashemite University in Jordan. His research interests include organizational learning, knowledge management and international joint ventures. He is member of ANZIBA and ANZMAC and the Sydney University Centre for Peace Studies and Conflict Resolution. Tatiana Khvatova Ph.D., is currently employed as an Associate Professor for the Institute of Economics and Engineering at St.-Petersburg State Polytechnical University. Presently the research is focused on knowledge management, innovation policies, and innovation systems. Other disciplines of interest include cross-cultural management and using technologies in education. Monika Klimontowicz, Ph.D, is a lecturer at University of Economics in Katowice. Her latest research focuses on the role of intangibles in the process of achieving banks’ competitive advantage. Her interests include business strategy, innovation, knowledge and intellectual capital. She has been working as a marketing manager and business consultant. Epaminondas (Nodas) Koronis is a Senior Lecturer at University of Lincoln and a Visiting Scholar at the George Washington University and the University of Cyprus. In the past he has undertaken executive positions in pharmaceutical corporations and consulting roles in Greece, UK and USA working with Deloitte and Reputation Lab, leading crisis and reputation management projects for large organizations. He holds a PhD from Warwick Business School (University of Warwick). His works have been published in academic journals, edited volumes while he has presented his research and frameworks in academic and professional conferences. Jaroslava Kubátová, Ph.D. id an Associate Professor at the Philosophical Faculty of Palacký University in Olomouc, Czech Republic. Since January 2002 – to date: Head of the Department of Applied Economics. Areas of Expertise: Human Capital Management and Knowledge Management with ICTs utilization. Cooperation with scientific organizations: European Association for Security, Czech Society for Systems Integration. Kaan Kurtel has been a Professor at the Department of Software Engineering at Izmir University of Economics since 2002. He obtained his MSc in Computer Engineering from Ege University, in 2005 and his PhD degree in Computer Science from Trakya University, Turkey, in 2009. His research interests include software engineering and web technologies. Prof. Dr. Franz Lehner has been assistant professor at the Institute for Organizational Research at the University of Linz, Austria, since 1986. In 2004 he accepted a call to the University of Passau where he holds now the Chair for Information Systems xviii


(Wirtschaftsinformatik) since April 2004. His research is focusing on E-Learning as well as Information and Knowledge Management Monique Lortie Ph.D., is tenure professor at Université du Québec à Montréal in ergonomics; her initial background is in industrial engineering. She is in charge of the knowledge transfert strategic arm for the Réseau de Recherché en Santé et Sécurité au Travail (RRSSTQ) Lisa Loyo is the Manager for Information Services at the Transportation Research Board. She has a broad range of professional experience ranging from ESL instructor to research librarian and trainer for a database vendor. Before joining TRB she worked at TRB’s parent organization, the US National Academies in their IT and Communications offices for ten years specializing in search, metadata and information architecture, working on projects to improve the search experience and navigation on a number of websites. In June of 2010 she moved from the IT division to TRB to manage the TRB’s library and research databases, including the TRID Database. Edit Lukacs is Associate professor at the Faculty of Economics and Business Administration of “Dunarea de Jos” University of Galati, Romania. She finished her PhD in Management in 2001. Since then, her didactic and research activity is focused on Management science, particularly on Human Resource Management and Intercultural Management. Dr. Lukacs participated in and completed different training courses in the field of professional counseling, psychological assessment of human resources and has also experience as team member or coordinator in different projects (TEMPUS, PHARE, POS-DRU). Dr Eva Martínez Caro is an assistant professor of operations management in the Business Management Department, Universidad Politécnica de Cartagena (Spain). She served as the Head of the e-Learning Center of the Universidad Politécnica de Cartagena for 5 years. She is actually Vice Dean of the School of Industrial Engineering. Her current research interests include knowledge management, technology-based learning environments and technology management. Micaela Martínez-Costa is a Lecturer Professor of management at the University of Murcia (Spain). Her current research focuses on the relationships among Knowledge Management, Total Quality Management, EFQM and Innovation. She has recently published in Journal of Knowledge Management, International Journal of Operations and Production Management and Total Quality Management. Dora Martins did her PhD thesis on expatriates’ management on Portuguese companies and continues researching this topic. She has also attended several international conferences and she has presented the results of recent investigation issues on Portuguese expatriates/repatriates. She teaches in degree and master human resources management studies for national and international courses. Professor Jane McKenzie is Director of the Henley KM Forum, having actively contributed to the community since 2000. Her interests are summarised as: "How connections and contradictions affect knowledge work and learning capacity in organisations". She has written three books and many papers often jointly with Dr Christine van Winkelen. Kristel Miller is a lecturer in management at Queens University, Belfast. Her research interests lie in the areas of absorptive capacity, knowledge transfer and innovation within knowledge intensive contexts. She has publications in the area of knowledge transfer and technology commercialisation within Universities. Peter Mkhize completed his PhD in 2012. He is currently working for University of South Africa as a senior lecturer. He has published few journal and conference papers on e-Learning and knowledge management. Among other research interests is human capital development, social networks, communities of practice. Ludmila Mládková works as an associate professor at the University of Economics Prague, Faculty of Business Administration, and Department of Management. She specializes in knowledge management, management of knowledge workers and managerial leadership. Her activities involve lecturing, writing and work with Ph.D. students. Sandra Moffett Senior Lecturer of Computer Science, University of Ulster’s School of Computing and Intelligent Systems, Magee Campus. Sandra is a Core member of Ulster Business School Research Institute. Expertise on KM contributes to her being one of UK leading authors in this field. Sandra has a Number of research awards and citations. External funding enabled her to undertake extensive quantitative/qualitative research to benchmark KM implementation within UK companies. Mieczysław Morawski, scientific discipline: management science; workplace: Wroclaw University of Economics; position: professor since 2008; number of publications: 120, in this book: 11; research in the field: personal aspect of knowledge management, knowledge-based organizations, talent management non-work interests: travel the world, international politics, forecasts the development of civilization. xix


Andrei-Alexandru Moroşan is a second year PHD student, focusing particularly on aid economics (manifested in Romania as EU structural funds). He is a junior teaching assistant of the Faculty of Economics and Public Administration - Department of Economics, Business Administration and Tourism, "Stefan cel Mare" University of Suceava. Dr. Vyda Mozuriuniene from Comfort Heat Ltd is the Managing Director; Vyda has a Ph.D. in Management. Research interests – knowledge creation and management, process management, strategic management. Vyda is a Consultant in the areas of organization’s knowledge management, process management, and franchise. Dr. Mozuriuniene has published 4 scholarly articles. Edrisi Muñoz Mata MSc. Industrial Engineering, Instituto Tecnológico de Orizaba, Mexico. Doctor of Philosophy in Chemical Process Engineering, Universitat Politècnica de Catalunya (UPC) in Spain. Researches KM through development of ontologies and management frameworks for decision-making support in different areas. Member of Centro de Investigación en Matemáticas A.C (CIMAT), Mexico and collaborates with UPC as part of research team, participating in different Mexican/European research projects. Lilian Noronha Nassif received BS degree in Computer Science from PUC-MG, in 1990; received MS degree in Public Administration in 1997’ received PhD in Computer Science from Federal University of Minas Gerais, in 2006, Brazil. Currently she is a Director of technology at public Ministry of Minas Gerais. Fattah Nazem is an Associate Professor. He has been vice-president of the research department for the last five years. His research interests are in the field of Higher Education Management. He has written 2 books and 98 articles. He is Chief Executive of the Quarterly Journal of Educational Science. Olimpia Neagu Associate Professor at “Vasile Goldiş” Western University of Arad, Romania. I am teaching European Economy and Marketing. My interest and research areas are: human capital and economic development at micro- and macroeconomic level, determinants and consequences of human capital investments, european economy, human resources –human capital management, brain drain, knowledge management. Oscar Ojeda Galicia holds master degree in Information Technology and Management, defended at Instituto Autónomo de México (ITAM). From 2002 till 2003 –Web Master Developer at AVAYA, México. From 2003 untill 2008 – Systems Management Engineer and Systems Management Leader at Telcel. Since 2010 to present – IT Executive at Mexico’s Ministry of Energy. Gary R Oliver researches/teaches at The University of Sydney. Gary has held appointments in public corporation, with government at federal and state levels, and in retailing. PhD in economics, Master of Commerce, He has a Master of Education (Higher Education), Bachelor of Arts degree and Graduate Diploma in Social Science obtained (2012). Gary Specialises in higher education effectiveness, and researches in sharing information and knowledge (knowing). Originated field of microintellectual capital. Ivona Orzea is Assistant Professor of Knowledge Management, UNESCO Department for Business Administration, and a member of the Research Center for Intellectual Capital, Bucharest Academy of Economic Studies, Romania. She is former Associate editor for the international journal Management & Marketing. Her academic interests are: knowledge dynamics, knowledge management, intellectual capital, and strategic management. Ján Papula is an associated professor at Faculty of Management Comenius University in Bratislava, Slovak republic, where he works as a teacher and researcher since 2002. His research activities are focused on the topics of strategic management development particularly in relation to resource-oriented approach and strategies to build sustainable competitiveness. Dr Paul Parboteeah is a Research Associate in the School of Business and Economics at Loughborough University. His research spans several areas including the application of autopoiesis to KM, data quality, information management in local government and sport informatics. He is currently creating a swimming demand analysis and prediction tool for the UK. Corina Pelau is university lecturer at the Academy of Economic Studies, Bucharest Romania, at the Department for Business Administration - UNESCO. Her main research interests are marketing-controlling, customer relationship management and consumer behavior. Since October 2010, she is postdoctoral researcher in the program “Performance and excellence in postdoctoral research in Romanian economics science domain”. Carmen Petrisoaia In 2008, I obtained the Bachelor in Business Administration in French at the Academy of Economic Studies from Bucharest and two Years later I graduated the Masters. I was an Erasmus student in France, at Université de Haute Alsace between in 2006. In 2012, I had a 6 months scholarship at Université de Picardie Jules Verne. xx


Anna Pilková, MBA. is an associated professor at Faculty of Management Comenius University in Bratislava. She leads the national research team Global Entrepreneurship Monitor (coordinated by Global Entrepreneurship Research Association). Her research interests are mainly Entrepreneurship and Value Based Management. She has several years of experiences in the banking industry. Magdalena Platis is a Professor of Microeconomics, Macroeconomics and Marketing having an experience for more than 20 years. Magdalena is Involved in projects related to labour market, entrepreneurship and quality assurance. Area of interest: possibilities of integrating the practical placement in the curriculum, of developing internships and extra-curriculum activities, of industry-university connections. Dr Steve Probets is a Lecturer in the Department of Information Science at Loughborough University. He is interested in socio-technical systems and the interplay between technology and working practices. Much of this research has been focussed on the publishing sector, though he has supervised a number of postgraduate students in the wider KM area. Gabriela Proştean received the Ph.D. degree (2003) in industrial engineering from the Technical University” Gh. Asachi”, Iaşi, Romania. She is currently Professor in the Department of Management from the Politehnica University of Timisoara, Romania. Her research interests include project management, artificial intelligence, and electrical engineering. Athar Qureshi graduated with honours degree in computer sciences, Masters in ICT Management and is now pursuing his PhD in knowledge management. He started his academic career with research and teaching assistantship, lectureship and consultation. Along with his academic commitments, Athar also advises some not-for-profit academic associations. Dr Gillian Ragsdell Is a Senior Lecturer in Knowledge Management and Director of Research Degree Programme in the Department of Information Science at Loughborough University. Her interest in knowledge management practices has taken her into a wide variety of organisations; recent examples are from the voluntary sector and the energy industry. Salah Aziz Rana is the PhD research student in University of the West of Scotland. His area of research is organisation learning and knowledge sharing behaviour in organisations. He has already published a paper on Reinforcement Programming for function approximation in IEEE Xplore conference in 2012. Vaclav Reznicek graduated from information management at the Faculty of Informatics and Statistics, University of Economics, Prague. Currently, he is internal PhD student at the Department of Systems Analysis, Faculty of Informatics and Statistics, University of Economics, Prague. His doctoral thesis deals with the issue of human knowledge. Paavo Ritala, D.Sc. (Econ. & Bus. Adm.) is a Professor at the School of Business at Lappeenranta University of Technology, and an Academic Director of Master’s Programme in Strategy, Innovation and Sustainability. His main research interests are in the areas of inter-organizational networks, business models, knowledge management and innovation. Professor Jennifer Rowley is Professor of Information and Communications. She has researched and published extensively in information and knowledge management, higher education, and marketing. Her current research focuses on knowledge management, digital marketing, and entrepreneurship and innovation. Sasha Mile Rudan is a PhD candidate at the Oslo University and Entrepreneur at Serbia. His parallel research and involvement in online collaborative social system development helps him to keep his research relevant. His current research is on Trans-Technical Systems; systems that are in whole with their consumers and multi-type of activities marshaling through them. Pawel Rumniak, Adjunct in the Department ofCorporate accounting and Controlling Doctor if Econiomcs Sciences. Co-author of books on accountancy, cost accounting, managerial and controlling accounting. Numerous research papers on corporate management related subjects (accounting and controlling) Research work in finace and accouting. Ines Saad is an assistant professor in the department of Computer and Information System at Group Sup de Co Amiens Picardie. She is a researcher within the MIS Laboratory at the University of Picardie Jules Verne. Jevgeni Sahno is a PhD student of Tallinn University of Technology in Estonia. The main research directions are: Knowledge Management and Information Systems in manufacturing companies. Jevgeni is working in Estonia ABB Company of motors and generators on the position of process development engineer. The main responsibilities are: development of business process and information system, integration of PDM and ERP system.

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José Sendra Salcedo is student of Computer Engineering and Applied Maths undergraduate programs at Instituto Tecnológico Autónomo de México (ITAM). From 2010 to 2011- Systems Management Engineer at ITAM. Since 2011 to present – Administrative Chief of engineering magazine holaMundo. Evren Satici is pursuing his PhD studies in Marmara University Istanbul in Knowledge Management area. He is also working as Global Project Manager in Ericsson. Prior to his current job, he was a management consultant working on sales, marketing and organizational development areas helping companies in Middle East and Africa region. He speaks Turkish and English. Enrico Scarso (Ph.D. Industrial Innovation - University of Padua) is Associate Professor of Engineering Management at the Department of Management and Engineering, University of Padua (Italy). His research interests are in the area of technology and knowledge management, with a focus on knowledge-intensive business services in local innovation systems. He has published in International Journal of Technology Management, Technovation, International Journal of Electronic Commerce, Journal of Knowledge Management, International Journal of Knowledge Management, Knowledge Management Research and Practice. He is founder member and secretary of IAKM (International Association for Knowledge Managment) Thomas Schalow is a professor in the department of Economics and Information Science at the University of Marketing and Distribution Sciences in Kobe, Japan, where he has taught for the past fifteen years. He has also previously lectured at the National University of Singapore. His Ph.D. is from Princeton University. Christian-Andreas Schumann studied Industrial Engineering, ‘Chemnitz University of Technology’ (CUT). Doctor’s degree 1984 and 1987. Appointed associate professor plant planning and information processes, CUT (1988). Professor business and engineering information systems (1994) and Dean for distance learning at, University of Applied Sciences Zwickau. Currently director of ‘Centre for New Forms of Education’ and of Institute for Management and Information. Dr Ibrahim Seba is a police officer with the Dubai Police Force. His PhD research centres on knowledge management and sharing in police forces. José Sendra Salcedo is student of Computer Engineering and Applied Maths undergraduate programs at Instituto Tecnológico Autónomo de México (ITAM). From 2010 to 2011- Systems Management Engineer at ITAM. Since 2011 to present – Administrative Chief of engineering magazine holaMundo. Touhid Shiralipoor. Graduate of (M.A)In Education Planning. Two articles in the Journal of Research. 3 years teaching experience at the Islamic Azad University-Roudehen Branch. Four years of research experience in the field of management Mzwandile Muzi Shongwe. Is a Lecturer in the department of Information Studies, University of Zululand, South Africa. I am a PhD candidate in the department of Information Studies, University of KwaZulu- Natal, South Africa. My research interests are knowledge management, knowledge management systems and mobile technologies. Evangelia Siachou PhD. in Knowledge Management from Athens University of Economics and Business, an M.Sc. in Industrial Relations and Personnel Management from London School of Economics (LSE) and Bachelor’s degree in International and European Studies from Panteion University of Athens. Joined faculty of Hellenic American University (2010) as Assistant Professor of Management and currently serves as Coordinator of BSBA Program. Boyka Simeonova Doctoral student at School of Management, Royal Holloway, University of London. Two Masters Degrees with Distinction – the MSc Business Computing at University of Westminster in London, UK and Master’s in e-Management at Technical University of Sofia in Bulgaria – also Bachelor’s Degree in Public Administration. Researches Knowledge Sharing, Communities of Practice, and Web 2.0 Technologies. Zdenek Smutny graduated from applied informatics and media studies. Currently, he is internal PhD student at the Faculty of Informatics and Statistics, University of Economics in Prague where he deals with the problems of social informatics. Anna Sołtysik-Piorunkiewicz, Ph.D. and Mariusz Żytniewski, Ph.D. are employed at the University of Economics in Katowice as lecturers on Faculty of Informatics and Communication, at Department of Informatics. They are taking part in the research into computer science, systems analysis and computer system design, management information systems, software agents and knowledge-based organizations. Faezeh Sohrabi University of Azad Islamis Education Management Department, Roudehen, Iran. Faezeh has a MA in education management. Design and implementation IWA2 for schools and education organizations; Implementation ISO9001 for organizations. Faezeh is the Director of Education at the School of Education in Tehran for 5 years and a Quality Assurance manager for 2 years. xxii


Dimitrios-Robert I. Stamatiou is a Ph.D. candidate in the School of Mechanical Engineering in the National Technical University of Athens, Section of Industrial Management and Operational Research. He has a degree in Financial and Management Engineering. His academic interests are business process modeling and engineering, supply chain management, project management and systems reliability. Inga Stankevice PhD candidate and junior research assistant at the Department of Strategic Management, Department of Land Management, Kaunas University of Technology (Lithuania). Research stays at Bergen University (Norway), University of Geneva (Switzerland), University of Nottingham Business School (UK). Inga is a member of DRUID Society, has 20 publications, 10 scientific awards, participated in 7 research projects. Peter Steranka is a Lecturer at the University of Žilina. He’s a University of Žilina Masters graduate. He’s working at the Department of Mediamatics and Cultural Heritage and focusing his research activities in information/knowledge management and scientific collaboration. Currently finishing the dissertation thesis named Application of collaboratory principles in Library and information studies. Marta-Christina Suciu is full professor and PhD supervisor on Academy of Economic Studies Bucharest, Romania. Her main topics of interest are: Knowledge based society; Creative & Innovative Management; Knowledge Management; Intellectual Capital. She supports these topics also as a trainer (5 courses on the Post PhD School & on the Master level) and as PhD and Post PhD supervisor. Eduardo Tome made is PhD in Economics in 2001, with a Thesis on the European Social Fund. Since then we has worked in several Portuguese private universities. He published more than 20 papers in peer-reviewed Journals and attended more than 40 International conferences presenting papers. We run MSKE 2009, ECKM 2010, MSKE 2011 and UFHRD Europe 2012 at Lusiada University in Famalicão (North of Portugal). Adelfattah Triki has a PhD in Marketing, University of Northumbria, Newcastle (1998). Between 1986-87 he was at Boston University as a Fulbright Scholar. He is a Senior Lecturer of Research Methodology of Marketing Management and of Negotiation Techniques, Graduate School of Business Administration of Tunis University. He is Involved in company training and in consulting for private as well as public enterprises. He is also a Director of ARBRE (Applied Research in Business Research and Economics). David Tuček is a graduate of Brno University of Technology. He is now Associate Professor at the Tomas Bata University in Zlin, Department of Industrial Engineering and Information Systems, Faculty of Management and Economics, Tomas Bata University in Zlín and vicerector for social affairs, Affiliation: Tomas Bata University in Zlin, nám. T.G. Masaryka 5555, 76001 Zlín, Czech Republic. Zuzana Tučková PhD. doctoral studies programme, economics and business management, Tomas Bata University (TBU) Zlín. Practical experience in project management dealing with services. Solver of POST-DOC grant project no. 402/09/P406 named “Knowledge Intensive Services – their meaning and characterization” and co-author grant project no NT 12235-3/2011 “Application of modern calculation methods for optimization of costs in health care” registered at Internal grant agency of Ministry of Health Czech Republic (IGA MZ ČR). Dr. Anna Ujwary-Gil has a PhD from Warsaw School of Economics, College of Management and Finance. Anne is a Fellow of Foundation Scholarship and Training (Norwegian Funds). She is Currently Editor-in-Chief of Journal of Entrepreneurship, Management and Innovation. In 2010, book entitled "Intellectual Capital and Market Value of a Company" (Ch&Beck, Warsaw 2009) received a prestigious award granted by Polish Academy of Sciences. Mika Vanhala, D.Sc. (Econ & Bus. Adm.) is a post-doctoral researcher in Knowledge Management at School of Business, Lappeenranta University of Technology, Finland. His primary research interest is the relationship between HRM practices, organizational trust and organizational performance. Mika’s research has been published in Personnel Review and Management Research Review. Dr Christine van Winkelen has worked with the Henley Knowledge Management Forum since its inception in 2000, project managing and leading collaborative research projects. She was the Director for five years. She has published extensively in academic and practitioner journals, co-authoring “Understanding the Knowledgeable Organization” and “Knowledge Works” with Professor Jane McKenzie. Chiara Verbano is an Associate Professor of Business and Engineering Economics at the Faculty of Engineering of the University of Padua. Her major research interests are the fields of risk management and R&D management.

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Anna Yu. Veretennikova attended The Ural State Technical University (Russia, Yekaterinburg), Faculty of Physics and Technology; Specialty - Management of Innovations. She Graduated in 2008. From 2007-2010 she was at The Business School of the Ural State Technical University (Russia, Yekaterinburg), the manager. From 2010-2013 she was at the Institute of Economics, Ural Branch of the Russian Academy of Sciences (Russia, Yekaterinburg), Junior Research Fellow. Her research interests are the knowledge economy, institutional economics. John Walton is a Principal Lecturer in the Department of Computing, Sheffield Hallam University. He teaches on Postgraduate degrees in the UK, the Middle East and the Far East. His research focus is the interface between strategy and knowledge management not wealth creation but also in the regeneration of post-industrial regions. Ruzleeta Zakaria is currently a PhD candidate in Decision Sciences at School of Quantitative Sciences, Universiti Utara Malaysia, Kedah, MALAYSIA. I received a Master degree in Decision Sciences and Bachelor degree in Business Administration also at Universiti Utara Malaysia by year 2000 and 2003. My research is focused on knowledge sharing among profit oriented webloggers in Malaysia. Igor Zatsman has the PhD (Information-Computer Science). Currently, he is the head of research department at the Institute of Informatics Problems of the Russian Academy of Sciences. He has the highest research diploma, obtained after the PhD. Research interests are in the fields of Cognitive Informatics, Modeling Emerging Meanings Processes and Their Tracing by Computer. Malgorzata Zieba PhD, Eng. is an assistant professor at the Faculty of Management and Economics of Gdansk University of Technology, Poland. She has taken part in several national and international projects. Her scientific interests oscillate around knowledge management and modern concepts of management in organizations. She has a record of around 30 publications in these areas.

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Using Neuromarketing Studies to Explore Emotional Intelligence –  as a key to the Buying Decision Process  Nicolae Al. Pop, Ana Maria Iorga and Corina Pelau  The Bucharest Academy of Economic Studies, Bucharest, Romania  nicolae_al_pop@yahoo.com  ana.iorga@gmail.com  corinapelau@yahoo.com  Abstract: The recent dynamics of neuroscience is enabling and fostering the interface of this domain with others, such as:  biology, sociology and economy. The complexity of market mechanisms in general and of the buying decision in particular  increased  considerably,  demanding  thus  more  sophisticated  investigation  instruments.  During  the  last  decade,  neuromarketing has been in search of its own identity on the ambiguous field of market research.  Starting from the works  of  Ale  Smidts,  the  paper  aims  to  position  neuromarketing  as  an  independent  research  field.  The  author  reviews  the  different  opinions  articulated  by  specialists  throughout  the  contemporary  literature,  emphasizing  neuromarketing’s  capability of addressing the invisible side of neuronal connections that are situated inside the brain.  Starting from Salovey  and Mayer’s definition of emotional intelligence (EI), this paper  reviews the anatomical and physiological foundations of  the brain activity that generates the EI. We analyze the neuromarketing concepts and instruments that enable specialists  to comprehensively study people’s unconscious reactions that lead them to buy or reject a product that could satisfy their  needs. Thus, the physiological neuronal data acquired enables us to better understand externally triggered emotions and  the way they interact in order to generate the buying decision. The whole approach is circumscribed to the relationship  marketing  framework  that  relies  on  creating,  developing,  maintaining  and  perpetuating  interpersonal  ties  between  all  players in the market, in order to improve the image of a service, brand or company. We will look then at the difference  between  emotions  and  moods  and  analyze  how  they  impact  our  behavior.  Emotions  are  high‐intensity  but  transient  manifestations while moods represent rather insidious changes in our state of mind, changes that might or might not be  easily  identified  and  traced  back  to  their  origins.  Neuromarketing  research  techniques  (represented  by  electroencephalography  (EEG),  magnetoencephalography  (MEG),  functional  magnetic  resonance  imaging  (fMRI),  eye‐ tracking glasses (ET) and the galvanic‐skin response (GSR)) bring valuable insights regarding the neural substrates of EI and  allow  researchers  to  seize  the  ephemeral  interaction  between  different  brain  structures  during  the  decision  making  process. We will further discuss the findings of our original research that studied the impact of packaging on consumers’  emotional  reaction.  The  research  tested  the  impact  of  several  elements  of  the  packaging  layout  (color,  shape,  label  and  message positioning) for different packaging of competing brands in the honey market. The research was conducted at the  Doctoral School of Marketing from the Bucharest University of Economic Studies. The research results where later used in  crafting  the  product‐positioning  strategy  for  several  products  from  the  company’s  portfolio.  Conclusions  and  further  discussion topics will then be inferred and detailed.  Keywords: neuromarketing, neuroimaging, emotional intelligence, relationship marketing, new product design 

1. Introduction The more  thorough  the  decision‐making  process  responsible  for  the  consumer  behavior,  the  higher  the  chances of better meeting demand. Knowledge management studies both the way people acquire knowledge  and  the  process  itself.  The  access  to  knowledge  is  possible  both  rationally  –  using  deductive  and  inductive  reasoning  –  and  emotionally  –  throughout  a  wide  range  of  stimuli.  Our  emotional  intelligence  allows  us  to  direct our attention and actions towards a certain behavior. The more we develop this sort of intelligence, the  stronger our self‐control, allowing us to better control our decisions.  Part  of  the  human  behavior,  more  precisely  the  methods  consumers  use  to  express  purchase  or  dismissal  decisions  towards  goods  or  services  that  could  satisfy  their  needs  –  which  is  known  as  the  purchase  and  consumption behavior –, represents a vast field of study for marketing investigations. Consequently, research  in this area has seen a spectacular boost lately. Studies from the second half of the 20th century emphasized  the exploration of investigation methods in areas as clinical psychology, psycho‐sociology and even sociology  (Evrad  et  al.,  2009).  More  recent  studies,  issued  at  the  beginning  of  this  century,  bring  about  a  fresh  perspective: scientists now look deeper into the human nature; they investigate subconscious reactions that  take  place  at  a  neuronal  level,  when  consumers  are  exposed  to  different  market  stimuli  fighting  for  their  attention.  The  impressive  advances  in  neurosciences  fostered  the  better  understanding  of  the  behavioral  mechanism. (Georges and Badoc, 2011). 

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Nicolae Al. Pop, Ana Maria Iorga and Corina Pelau  Neuromarketing acts as an interface between several disciplines. It covers incontrollable and unseen moods  and  processes  that  trigger  the  reactions  influencing  the  purchase  decision  in  a  favorable  or  unfavorable  manner (Constensen, 2011). Neuromarketing research explores the way the human brain handles information  (Rouellet  and  Droulers,  2010),  in  order  to  facilitate  the  various  courses  of  action  that  are  possible  in  an  integrated marketing communication (Bruhn, 2007). Neuromarketing research is now compulsory or advisable  in a hypercompetitive market that is becoming increasingly more globalized. The more insightful the research  into the human subconscious, the more various the activation tools available in the pursuit of product sale.  

2. The anatomical substrate of emotions  We humans are able to express a wide range of emotions, often swinging from rage to happines, thus covering  the whole spectrum. Emotions are often easily desciphered when watching one’s face and there are studies  that  show  that  facial  expressions  can  have  an  emotional  impact  upon  the  viewer  and  even  influence  the  evaluation of an outcome (Ho et al., 2012). Furthermore, emotional faces can induce „approach or avoidance  behaviors”  (Chen  and  Bargh,  1999)  and  even  endow  physical  objects  with  negative  or  positive  values  (Winkielman et al., 2005).     But what do emotions look like in the brain? Are they as easily distinguishable when looking at the brain, as  they are when reading one’s face? For a decade already, there have been numerous neuroimaging studies that  attempted  to  identify  the  neural  circuits  intrinsic  to  emotions,  whether  positive  or  negative  ones.  Of  the  available  technologies,  most  of  the  studies  used  fMRI  and  positron  emission  tomography  (PET),  as  these  neuroimaging tools allow researchers to study brain structures situated deep in the brain.     One of the theory proposed was that of two systems that facilitated the existence of two completely opposite  emotions or behaviors: the approach and withdrawal behaviors (Cacioppo and Gardner, 1999; Davidson, 1995;  Gray, 1994; Lang et al., 1990). The approach behavior is linked to the occurence of positive emotions (like self‐ contentment or excitement) while the withdrawal behavior is generated by negative, rejection‐like emotions  that are induced by a stimulus (for example anxiety or repulsion). The theory proposes that these two systems  rely  on  somewhat  independent  neural  circuits.  We  will  further  review  the  most  important  components  of  those circuits and look at some studies that shed light on them.     The  prefrontal  cortex  (PFC)  is  one  of  the  areas  that  plays  a  major  role  in  the  occurence  of  emotions  (both  positive and negative) and also in the decision making process. Several studies have shown that patients with  left PFC damage had a higher rate of depression‐related symptoms than those with right PFC lesions (Gainotti,  1972;  Sackeim  et  al.,  1982;  Robinson  et  al.,  1984),  thus  implying  that  the  left  PFC  was  involved  in  the  occurence of positive affect. This finding is supported by studies performed on healthy subjects, revealing a  stronger  left  hemisphere  activation  for  stimuli  that  generate  positive  emotions  and higher  right hemisphere  activation  for  stimuli  that  generate  negative  emotions  (Davidson  et  al.,  1990;  Davidson,  1992,  1995,  1998).  Other studies performed by Bechara and his team suggested that bilateral damage of the ventromedial PFC  was responsible for patients’ impairment in forseeing the subsequent consequences of their behavior, while  they  were  able  to  assess  the  implications  of  immediate  recompense  or  penalty  (Bechara  et  al.,  1994).  Furthermore,  those  patients  were  unable  to  anticipate  risky  behavior  (Bechara  et  al.,  1997;  Bechara  et  al.,  1996).  It  is  therefore  believed  that  the  ventromedial  PFC  is  instrumental  in  predicting  future  emotional  outcomes as consequences of current behavior.     The amygdala is another neural structure that plays an important role in regulating emotions, especially in the  negative  ones  and  in  learning  associated  to  unpleasant  stimuli.  There  are  several  studies  that  highlight  the  involvement of the amygdala in the facial recognition of fear (Adolphs et al, 1995 and 1996; Calder et al., 1996;  Broks et al., 1998), where patients that had bilateral amygdala lesions were unable to identify fear expressions  from the facial expressions that they were exposed to. Nevertheless, they had no problem in recognizing other  facial  emotions.  Amygdala’s  role  in  identifying  hints  of  fear  is  not  limited  to  facial  expressions,  as  a  study  performed  by  Scott  et  al.  (1997)  showed  that  patients  with  bilateral  amygdala  damage  were  also  unable  to  recognize the vocal cues of fear.     Other brain structures involved in processing emotions are:   

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Nicolae Al. Pop, Ana Maria Iorga and Corina Pelau  ƒ

Ventral striatum – higher activation was evidenced in the nucleus accumbens, putamen and caudate, in studies that focused on addictive behavior: the brain impact of cocaine on cocaine addicts (Breiter et al., 1997) or the impact of nicotine infusion on smokers (Stein et al., 1998), thus highlighting the importance of the dopaminergic mesolibic system in regulating addictive behavior and positive emotions (Koch et al., 1996; Koob, 1992; Koepp et al., 1998).

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Anterior cingulate  cortex  (ACC)  –  is  believed  to  be  involved  in  situations  that  require  focusing  on  one’s emotional reactions rather than focusing on the given context (Lane et al., 1997; Posner, 1995).

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Insula – is involved in regulating emotions associated with autonomic, visceral manifestations (Cechetto and Saper, 1990). A large part of the amygdala is dedicated to processing gustatory stimuli, therefore its activation when subjects are faced with facial disgust emotions (Phillips, et al., 1997).

3. Moods and emotions Salovey  defined  EI  as  „the  ability  to  monitor  one’s  own  and  others’  feelings  and  emotions,  to  discriminate  among them and to use this information to guide one’s thinking and actions” (Salovey and Mayer, 1990). It is  therefore  assumed  that  people  are  able  to  understand  their  emotions,  rationalize  them  and  control  their  behavior.   Emotions lay at the foundament of interpersonal relations and represent the main motivator for our behavior  (Dolan,  2002).  They  have  a  strong  influence  on  our  reasoning  and  decision  making  process  and  are  often  exhibited as stereotyped attitudes, easily revealed through facial expressions (James, 1890).   According to Salovey, people with a high EI quotient are able to supress their negative emotions „appreciative  of the fact that temporarily hurt feelings or emotional restraint is often necessary in the service of a greater  objective”  (Salovey  and  Mayer,  1990).  The  brain  regions  that  regulate  the  negative  emotions’  inhibitory  mechanisms are the amygdala, the orbitofrontal (OFC) and lateral prefrontal (PFC) cortices (Blair and Cipolotti,  2000; Davidson, et al., 2000a; Davidson et al., 2000b; Mitchell and Blair, 2000; Raine et al., 1998).   Moods,  on  the  other  hand,  are  insidious,  internal  mental  states,  characterized  by  low  intensity,  indefinite  duration and nespecific manifestations. They are often difficult to correlate with the stimuli that caused them  and they influence our perception of surrounding events. For example, studies have shown that moods affect  the way people perceive advertising messages (Martin, 2003; Martin and Lawson, 1998) and that the impact of  moods  on  information  processing  is  gender‐related  (Martin,  2003).  Positive  moods  are  associated  with  creative thinking, enhanced attention and imaginative problem solving (Rowe et al., 2007). Nevertheless, they  can also have a negative impact on cognitive processes, as people are easily distracted when they are in a good  mood.  (Biss  et  al.,  2010).  The  negative  impact  is  only present  when  the  message  that  requires  processing  is  incongruent with the positive mood, in other words it threatens to change the mood (Ziegler, 2010). Negative  moods  have  quite  the  opposite  impact  on  cognitive  processes,  as  they  are  associated  with  depression,  low  self‐esteem  and  even  nonspecific  somatic  manifestations.  Research  has  shown  that  people  usually  perceive  objects  or  events  that  are  consistent  with  their  moods  (Niedenthal  and  Setterlund,  1994),  thus  displaying  selective attention.  

4. Emotions and decision making Although we have been taught that we should carefully analyze each option when making decisions and that  we  should  rationally  weight  the  pros  and  cons,  recent  research  revealed  that  almost  95%  of  the  decision‐ making process is undertaken at the subconscious level of our minds (Zaltman, 2003). In other words, not only  that  we  are  not  aware  of  the  process,  we  can’t  even  influence  it  from  a  rational  standpoint.  Kahneman  describes  the  mind  as  a  cohabitation  of  two  cognitive  processes,  which  he  calls  „System  1”  and  „System  2”  (Kahneman, 2011). System 1 represents the subconscious mind, which is automatic, reacts fast and relies on  well‐known patterns while System 2 symbolizes conscious cognitive processes that take longer to operate and  require  direct  attention.  System  1  operates  with  stereotypes  and  is  highly  influenced  by  emotions.  It  is  in  charge  with  automatic  actions  that  don’t  require  conscious  processing  everytime  they  are  performed  (like  writing or driving). System 2, on the other hand, is indispensable in the learning process, when aquiring new  skills requires  a lot of attention and focus. For example, learning to drive a car requires an active System 2,  while driving to the office on the same route for several years already most often relies on System 1. System 2 

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Nicolae Al. Pop, Ana Maria Iorga and Corina Pelau  operates  with  concepts,  abstract  representations  and  is  responsible  for  the  „rational”  assesment  of  our  decisions.     We can therefore infer that companies that want to persuade consumers should appeal to their subconscious  mind  (System  1)  through  memorable  and  simple  messages  (like  jingles  or  rhyming  slogans),  that  trigger  an  emotional  rather  than  rational  response.    This  hypothesis  is  supported  by  the  findings  of  Bechara  and  his  colleagues, that introduced the „Somatic Marker Hypothesis’’ concept in order to explain the impairment that  patients  with  ventromedial  prefrontal  (VM)  damage  exhibited  when  required  to  make  certain  decisions  (Bechara, 2004). In his research he found out that damage of the VM cortex (a prefrontal area that includes  the  OFC)  affects  the  proper  encoding  of  emotional  or  psihosomatic  impulses,  while  cognitive  processes  are  intact.  Still,  patients  with  VM  damage  have  difficulties  in  organizing  their  daily  routine  or  in  selecting  their  friends (Bechara et al., 2000a; Bechara et al., 2002). Furthermore, patients with VM damage were unable to  make advantageous decisions while performing a gambling task (Bechara et al., 2000b) that required selecting  between immediate versus deffered reward or punishment (Bechara, 2004). When performing the same task  while their skin conductance was measured, VM‐damaged patients showed no anticipatory skin conductance  response (SCR) before making a selection, whereas the control group displayed SCR activity before making any  decisions, with higher values preceding the risky decisions (Bechara et al., 1996).     The  above  evidence  strongly  supports  the  theory  according  to  which  emotions  (or  somatic  signals)  play  a  major role in regulating the decision making process.  

5. Honey packaging case study  Throughout communication, researchers are trying to understand the hidden features underlying the decision‐ making  process,  with  emotions  genesis  and  their  role  in  the  process  as  the  central  pieces  of  their  study.  Research  on  the  consumer  goods’  market  validates  the  assumption  that  most  buying  decisions  are  made  unconsciously. Moreover, it shows that packaging is one of the elements that trigger emotional responses.     The  objective  of  the  study  was  to  evaluate  the  emotional  reaction  that  product  packaging  had  on  the  consumers  and  to  measure  the  extent  to  which  it  influenced  their  purchasing  behavior.  We  chose  to  study  honey packaging, as the products in this field are rather undifferentiated and it was a challenge to see whether  some packages performed better than the others.  

5.1 Methodology There were 44 participants to the research, segmented based on age (2 age groups: 50% of participants <40  years of age and 50% of participants >40 years) and gender (equal split among men and women).    We used the following equipment:   ƒ

14‐channel EEG headset – records the electrical activity of subcortical neurons. Measures the decrease in  the alpha band amplitude (alpha band is dominant when the subject is awake but in a relaxed mood). The  sensors are applied on the scalp and, in order to increase conductance, we used a saline solution.  

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Eye‐tracking glasses  (ET)  –  a  pair  of  googles  especially‐designed  for  research  purposes.  They  feature  a  small camera that’s oriented towards the participant’s eye and traces the pupilar movements. They allow  researchers  to  see  where  do  people  look  first,  what are  the  elements  that gain  the most  attention,  the  order in which the elements of the layout are perceived, etc.  

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Galvanic Skin  Response  sensor  (GSR)  –  placed  on  the  skin,  it  measures  variations  in  skin  conductance.  Doesn’t offer information regading the positive or negative valences of the emotions, therefore it needs to  be associated with the EEG.  

5.2 Research design  The participant was first asked to fill‐in a short questionnaire regarding demografic segmentation (age, gender)  and consumption behavior (frequency, preffered brand, etc) and then was wired to the research equipment.  Before the actual research started, there was a calibration phase, that insured that the data that was collected  was  accurate.  The  participant  was  asked  to  watch  the  images  that  appeared  on  the  screen  in  front  of  him,  trying as much as possible not to move.  

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Nicolae Al. Pop, Ana Maria Iorga and Corina Pelau  At about half of the testing time, the research was intrerrupted and the respondent was asked to perform a  Stroop Test. The objective of this test was to assess whether the respondent was focused enough in order to  take part in the second part of the study without negatively influencing the quality of the aquired data.     Along  with  the  packaging,  we  also  studied  a  store  shelf  simulation,  in  order  to  observe  the  consumer’s  purchasing behavior and assess our product’s performance compared to its competition.     The whole research procedure lasted about 30 minutes.  

5.3 Interpreting the results  Each of the three techniques measures specific reactions. We will briefly describe each of them.    EEG  measures  Relevance  –  the  level  of  emotional  and  rational  motivation  towards  a  message.  It  shows  whether a communication message (e.g. TV commercial or product packaging) manages to convey messages  and ideas that are relevant to the target and the extent to which the target identifies itself with the featured  characters, situations or points of view. Relevance is measured by analyzing the brain activity and reflects the  intensity  of  the  subconscious  reactions  –  emotional  involvement  and  motivational  tendencies  towards  a  message or brand.     GSR  measures  the  Activation,  or  short‐term  emotion.  It  reflects  the  level  of  excitement  induced  by  a  promotional offer or a brand promise. It shows whether the participants at the study have been stimulated by  the communication message and whether they are willing to take action. GSR is considered to be a predictor  of  purchase  behavior.  Activation  is  measured  based  on  peripheral  stimulation  and  measures  the  degree  of  arousal  produced  by  a  product  or  a  brand  promise.  It  shows  whether  the  subjects  are  emotioned,  tense  or  ready to take action.     ET glasses measure Attention and collect data regarding the layout (or video) elements that draw attention.  They  provide  information  about  where  are  people  looking  first  and  for  how  long  and  estimate  how  much  attention are the participants giving to the critical elements of the communication material. Furthermore, they  can predict which words, graphical elements or layout objects determine Relevance and Activation.  

5.4 Conclusions The honey packaging that was studied manages to determine a positive reaction (represented by the red band  on the upper recording line, see Figure 1) but it requires a long time to do that (the positive reaction appears  after  three  seconds  of  staring  at  the  product).  There  is  no  positive  emotion  in  the  first  seconds  after  the  exposure and there is no activation (represented by the purple recordings on the lower band). Therefore, the  packaging  has  a  poor  shelf  performance  and  is  probably  losing  sales  to  its  competitors,  as  it  is  not  able  to  determine rapid positive emotion and activation.  

Figure 1: Emotional engagement induced by the honey packaging  Regarding the shelf simulation, the studied product doesn’t manage to draw the costumers’ attention in the  first seconds and therefore loses sales to other brands. Figure 2 shows the recording of the customers’ gaze 

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Nicolae Al. Pop, Ana Maria Iorga and Corina Pelau  while in front of the shelf. The red recording represents the younger people’s gaze pattern while the blue line  represents the recording for older people. It can be easily noticed that older people have a rather linear and  predictive attention pattern while younger people are more unpredictable in their visual flow. This represents  a big opportunity for the studied brand to grab attention from its competitor and take the second position in  the attention distribution pattern. 

Figure 2: Customers’ visual pattern in front of the shelf  Furthermore, it seems that only older people develop a positive reaction to the packaging, while the younger  audience  doesn’t  get  emotionally  engaged  with  the  product.  This  is  an  issue  that  needs  to  be  addressed  through redesigning the packaging and crafting the communication message more carefully in order to engage  with the younger segment of the target. 

6. Recommendations The brand and the packaging have a big potential of establishing an emotional bond with the customers but  the  current  design  needs  a  longer  time  to  draw  attention,  compared  to  its  competitors.  According  to  our  findings, the positive reaction only appears in the older segment of the target.     The  younger  population,  on  the  other  hand,  has  a  neutral  response  to  the  packaging,  thus  showing  no  emotional engagement whatsoever. We believe that this issue can be addressed through a packaging facelift  and  through  developing  a  communication  campaign  focused  on  emphasizing  the  beenfits  of  honey  consumption.     Further research regarding the elements of the label is needed in order to assess which design version has the  most impact on the viewers (in terms of colours, fonts and graphical elements used). Furthermore, regarding  the shelf simulation study, further research is needed in order to assess whether the same attention pattern in  young people is preserved given that the product order is changed. These findings are of general interest and  have practical applicability in the advertising and marketing fields, as they can be extrapolated to a wide range  of industries, starting from FMCG to all consumer goods.     A  highly  nutritive  product  with  a  good  prospect  for  market  expansion,  both  in  Romania  and  abroad,  honey  should be better marketed. Romania’s rich honeybee flora represents an opportunity that should be exploited  throughout  a  better  positioning.  Aiming  to  assess  and  direct  the  main  features  that  should  be  included  on  honey  packaging,  this  study  could  also  be  considered  a  humble  attempt  to  stimulate  honey  products  consumption. 

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Nicolae Al. Pop, Ana Maria Iorga and Corina Pelau 

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Enabling Knowledge Sharing in an Academic Environment: A Case  Study  Versavia Ancusa, Razvan Bogdan and Oana Caus  Politehnica University of Timisoara, Timisoara, Romania  vancusa@cs.upt.ro  razvan.bogdan@cs.upt.ro  oana.caus@cs.upt.ro    Abstract: Knowledge sharing is the foundation of the human society. Without it, the progress would be hampered and new  technologies  and  ways  to  improve  lives  would  be  threatened. Resistance  is  the  most  often  cited  reason  why knowledge  sharing  does  not  succeed.  The  wilfulness  of  the  subjects  to  share  and  the  methods  used  to  receive  and  transmit  the  knowledge  are  crucial  elements  in  assuring  high  quality  knowledge  sharing  and  a  low  resistance  to  it.  Our  aim  is  to  determine a spectrum of positive behaviours and methods that can be used to improve knowledge sharing in an academic  environment. This setting is deeply rooted in knowledge sharing, as the only valid method towards progress is based on  intensive collaboration and enthusiastic exchange of ideas. However, in our research we found out that generally, this is  not the case with our students. We set out to determine which factor is then more important to emphasize: the tonality  (affecting the wilfulness) or the modality (involving the methods used to communicate) in order to maximize the variety of  shared  reasoning.  We  devised  a  series  of  experiments  by  using  96  volunteer  students  and  2  teachers.  All  the  students  expressed  their  modality  preferences  by  using  a  VARK  (Visual,  Auditory,  Reading,  and  Kinaesthetic)  test.  The  teachers  prepared appropriate level lectures that involved one or more learning modalities and compiled them in a cohesive course.  The tonality varied from classical academic style (class‐room lectures) to a very informal approach by using social networks  to present the current course and assignments. At the end of the course the students answered a questionnaire to assess  their subjective opinion regarding the efficiency of their learning. Concluding the course all the students took an exam that  included  questions  in  order  to determine  the  knowledge  from each  lecture.  The  tonalities  and modalities  of  low‐scoring  answers were from the same lectures that the students expressed their discontentment with. Because the two results have  good overall consistency this leads us to promote several tonalities and modalities as ways to maximize knowledge sharing  in our academic environment.    Keywords: knowledge sharing, tonality, modality, VARK, social networks, academic environment 

1. Introduction Humans are, by definition, social beings, hence the inherent need to interact. Every social act in the human  society is based on communication whereas interaction can be perceived as an ensemble of verbal and non‐ verbal behaviours, whose joint purpose is to exchange knowledge. There are other means to enhance one’s  own  knowledge  such  as  self‐study,  observation,  inference,  etc.,  yet,  communication  remains  the  base  of  successful knowledge sharing. Although purposeful knowledge sharing is an important tool to make progress,  this  practice  is  not  as  common  and  widespread  as  expected.  Information  hoarding  is  the  major  obstacle  in  knowledge  sharing.  Although  data  exchange  is  part  of  any  communication,  the  perceived  quality  of  information  varies  greatly.  One’s  own  subjective  opinion  can  lead  to  information  hoarding,  and  due  to  the  communication  flow,  may  limit  the  resourcefulness  of  others.  This  proves  to  be  of  crucial  importance,  especially in academic environments, where both open information exchange and creativity are needed for the  successful accomplishment of the learning and research systems.    Although many studies have found several causes for resistance to knowledge sharing, a less explored avenue  is the one related to different communication styles. Due to the unique individuality of each party involved,  their internal representation by the subject and the context of knowledge sharing are different. If we take this  into account, can we improve knowledge sharing?    The paper is structured as follows: the literature review offers a survey of knowledge sharing techniques; the  research  design  presents  the  parameters  of  the  study,  followed  closely  by  the  findings  described  under  the  heading  results  and  discussion.  In  the  conclusion,  several  guidelines  are  proposed  that  ensure  a  higher  emotional response and an increased knowledge transfer.  

2. Literature review  Knowledge  sharing  is  a  priceless  asset  that  fosters  the  knowledge  exchange  among  a  spectrum  of  communities. It brings the creation and sustainability of competitive advantages (Miller & Shamsie, 1996). In 

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Versavia Ancusa, Razvan Bogdan and Oana Caus  spite of that, research has shown that some individuals are prone to resist sharing their knowledge (Ciborra &  Patriota, 1998), (Bock & Kim, 2002). In state‐of‐the‐art literature (Davenport & Prusak, 2000), (Partridge, 2013)  socialization  was  proposed  as  a  deterrent  of  information  hoarding.  The  location  for  socialization  may  be  a  physical place (water cooler, cafeteria, etc.) or a virtual one (telephone, Intranet, Internet or social networks).  The  same  idea  is  further  described  in  (Webster,  et  al.,  2008)  where  Dr.  David  Zweig  argues  that  knowledge  sharing is based on three principles, namely Make it Safe, Make it Count, Make it Social.    The  first  principle  (“Make  it  safe”)  aims  at  showing  that  creating  a  safe  environment  in  a  communication  network is of vital importance in knowledge sharing. The climate where individuals are collaborating should be  based  on  the  reassurance  that  they  will  be  at  no  risk  for  the  ideas  and  knowledge  that  are  shared.  Being  worried  that  other  people  will  find  out  that  you  aren’t  perfect  or  being  afraid  that  some  repercussions  are  going  to  take  place  can  be  addressed  by  creating  a  proper  setting.  The  second  principle  (“Make  it  Count”)  suggests a reward system that should be focused on the act of sharing. This view is a controversial one as the  reward system can be seen as a demotivating factor in some cultures or by certain personality types (Gurteen,  2007). The last principle (“Make it Social”) states that creativity and information sharing significantly increase  in  a  social  context.  Zweig  argues  that  knowledge  sharing  in  itself  is  a  social  experience;  therefore  humanity  should be highly prized as the social space creates a reward by the act itself.    As  previously  presented,  successful  knowledge  sharing  is  based  on  inter‐human  communication  (Figure  1).  Although communication is proven to have a strong, universal, nonverbal component (Ekman & Friesen, 1969),  the  context  and  representation  system  of  each  individual  involved  in  the  communication  act,  are  just  as  important as the nonverbal component. The nonverbal component is considered responsible for 50‐70% of the  communication  exchange,  while  the  context  and  representation  stand  for  20‐30%,  leaving  the  actual  information  with  an  insubstantial  percentage  of  10‐20%  (Ekman  &  Friesen,  1969).  Assuming  the  reality  of  a  digital world in which we can rely less on the nonverbal component, the context and representation system  begin to play a crucial role in communication. 

Figure 1: Overview of the communication structure  The  representation  system  of  individuals  is  highly  dependent  on  all  senses  (Druckmann,  1988).  The  total  number  of  senses  can,  nonetheless,  be  under  debate  (Robinson  &  Aronica,  2009).  Although  a  system  comprising at least five senses (VAKOG ‐ visual, auditory, kinaesthetic, olfactory and gustatory) is considered to  be comprehensive enough, there are at least three others to consider: equilibrioception, thermoception and  nociception. However, the question arises if all these senses are important when it comes to communication.  There are several research papers that suggest that this is a valid hypothesis (van Servellen, 2009) (Downar, et  al.,  2002),  however,  with  the  added  caveat  that  not  all  senses  are  equally  important.  The  representation  system, or as it may be otherwise known, the sensory modalities used in communication have been subjected  to extensive studies (Druckmann, 1988), (Hawk & Shah, 2007), (van Servellen, 2009), (Wolfe, et al., 2011). As  shown in (Downar, et al., 2002), the representation system has clear biological connections with the neuronal  pathways. This makes it highly quantifiable by means of MRI but the exposure to radiation is undesirable for an  extended  period.  Consequently,  in  order  to  assess  sensory  preferences,  there  are  several  available  methods  (Bandler & Macdonald, 1989). Of these methods, Neil Flemming’s VARK test is among the most widely‐spread,  given  its  simplicity  and  efficiency  when  testing  academic  performance  attributes  (Leite,  et  al.,  2009).  This 

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Versavia Ancusa, Razvan Bogdan and Oana Caus  provides easy means to measure the modalities in which communicators carry a dialog, yet it does not address  the socio‐cultural suprasystem.     According to (van Servellen, 2009) the socio‐cultural suprasystem in which communication is performed can be  identified as one of the functional components of the communication process and it has two sub‐components:  the  environment  and  the  interpersonal  context.  The  information  exchange  is  influenced  mutually  by  these  two, but the most easily controllable is the environment.    The  previously  presented principles:  “make  it  safe”  and  “make  it  social”  offer,  in fact,  ways  to  influence  the  environment  and  the  interpersonal  context,  thus  influencing  the  whole  communication  context.  It’s  worth  mentioning that the most debated principle “make it count” does not directly influence any structure in Figure  1.    In academic communication, the environment can be usually perceived in connection with its formality. The  formal  approach  is  most  frequently  used    in  academic  settings,  in  the  form  of  direct  teaching,  but  informal  approaches  have  been  widely  tested  as  well  (Ellis,  1982),  (Cooper  &  Others,  1990),  (Kaufman,  et  al.,  1997),  (Peklaj,  2006).  The  former  includes  inquiry‐based  learning,  cooperative  learning  and  media‐based  learning.  Although  these  ideas  have  been  advanced  for  several  decades,  the  technological  advancement  has  lately  changed  our  possibilities  in  implementing  informal  approaches.  According  to  a  study  by  Intel  (Intel  Corp.,  2012), in 2012, in an Internet minute, 1.3 million videos are viewed on YouTube, 6 million views of Facebook  pages  and  277,000  Facebook  logins  are  performed,  more  than  320,000  Twitter  accounts  are  created  and  100,000 tweets are published; additionally 20 million photo are viewed and 3000 photos uploaded on Flickr  and  6  new  Wikipedia  articles  are  published  –  all  in  just  one  minute.  In  the  same  study  of  Intel  Corp.,  the  current number of networked devices is estimated to equal the total globe population and expected to double  by the end of 2015.     The  deduction  that  follows  these  data  is  that  we  live  in  a  society  in  which  networks,  networking  and  interaction through networked devices becomes more and more ubiquitous. Working with this hypothesis, it is  clear that the amount of information an individual is immersed in every single minute is massive and it is only  going to increase.    Another  part  of  our  working  hypothesis  is  the  academic  environment  and  the  requirements  of  such  a  profession.  As  an  educator,  besides  teaching,  part  of  the  job  is  to  make  sure  that  students  have  the  information they need, ready to be assimilated.    Bringing together these ideas, it becomes obvious that: (a) you have to go where your students go – namely  involving social networks and (b) you have to work to make information as attractive and easy to assimilate as  possible in order to survive information‐distracting sources. In the context of sensory modalities, this implies  knowledge transfer between the educators’ internal sensorial representation of information and the students’  internal representation, while taking into account the context in which this takes place.    With  regard  to  the  large  assortment  of  networks  available  to  choose  the  social  network  to  pursue  for  our  experiment, we have taken into account the largest social network site – Facebook. More and more people,  mainly  adolescents,  are  creating  for  themselves  an  on‐line  “life”  that  intersects  with  their  real  life  and  Facebook  is  a  means  to  an  end  for  them.  This  new  “life”  creates  many  learning  opportunities  coined  as  “emerging  digital  learning  styles”  (Saeed  &  Yun,  2008).  In  December  2012,  Facebook  marked  more  than  1  billion  active  users  (Facebook  Corp.,  2013);  though  considering  its  teaching  potential,  we  may  observe  a  cautious  approach  from  educators.  While  Facebook  was  created  in  2004,  only  in  2006  research  started  focusing  on  the  possible  advantages  of  using  it  as  an  instrument  for  teaching  (Mathews,  2006).  Since  then,  many authors and Universities have considered that teacher training programs should incorporate a guide to  using Facebook to connect with the students (Muñoz & Towner, 2009), (Fogg Phillips, et al., 2009). The precise  methods used to connect with the students via Facebook vary, but there are several choices: profile page for  the  teacher,  group  page  for  the  class,  replicating  web  course  functions  on  Facebook  or  incorporation  of  Facebook Applications into current pages (Muñoz & Towner, 2009).     Using a social network site raises the problem of etiquette. The discussion of best practice policies is a very  ardent  one.  Many  viewpoints,  especially  from  the  “Old”  World  (Robinson,  2012)  are  against  the  use  of 

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Versavia Ancusa, Razvan Bogdan and Oana Caus  Facebook  by  teachers,  citing  as  main  reasons  the  dangers  of  inappropriate  behaviour  and  the  necessity  to  maintain  a  distance  between  students  and  teachers.  Many  schools  do  not  allow  Facebook  access,  prohibit  social‐media contact between staff and students or even forbid their teachers to have a Facebook account. On  the  other  side  of  the  Atlantic,  Stanford  and  Berkley  are  among  the  front‐runners  for  using  Facebook  as  an  instrument  for  teaching.  For  the  first  time  ever,  in  2007  a  class  at  Stanford  (Standford  Persuasive  Tech  Lab,  2013) created an application on Facebook, being closely followed by another class, this time from Berkley. All  the  undergraduate  students  enrolled  in  2008  at  Stanford  University  were  active  on  Facebook.  A  study  in  another American University (Jackson & Porter, 2009) showed that at the end of 2008, more than 90% of the  students checked Facebook every day, twice as often as their educational e‐mail. Stanford University marked  another first by publishing its first course on Facebook, in 2009. Confirming this trend, the U.S. Department of  Education  through  their  2010  U.S.  National  Technology  Education  Plan,  entitled  “Transforming  American  Education: Learning Powered by Technology” is asking to apply “the advanced technologies used in our daily  personal and professional lives to our entire education system to improve student learning.” The social‐media  policy is set by each university and is more casual in the US, as well as updated periodically in order to manage  the emerging realities of social media.     One important contention related to using Facebook regards the copyright of the materials posted. Facebook  owns all the data posted by users until users delete it. This means that all the courses (slides, videos, photos)  and student assignment posted are owned by Facebook and that may violate the university’s copyright claim  on it. A way to circumvent this situation would be by posting links to external resources.     Another  discussion  is  around  the  term  “friend”  –  in  Facebook  context  it  does  not  literally  mean  “friend”,  it  would be more like a “contact” or “Aristotelian version of a utilitarian friend”. It is impossible to have 300 very  good friends, but the term “friend” creates a negative reaction from people that do not understand the digital  meaning of the word. A factor not usually taken into consideration is the fact that many companies nowadays  look  at  the  future  employee’s  web  presence  and  the  Facebook  account  comes  definitely  under  scrutiny.  By  linking Facebook and teaching, prospective employers can see workmanship, involvement and thus motivate  even further students to interact positively on Facebook.    To  conclude,  we  claim  that  Facebook  is  just  a  communication  medium  that  connects  people,  with  privacy  controls that can be used to separate and layer private and professional life experiences; it is convenient as it  provides  digital  records,  generates  fast  responses  and  is  widely  spread  (1  billion  active  users  in  December  2012), thus making it a formidable tool for education. 

3. Research design  This  paper  presents  an  experiment  conducted  during  the  academic  years  2011  –  2012  and  2012  ‐  2013  at  “Politehnica” University of Timisoara, while teaching the “Fault‐tolerance of Computer Systems” course to 4th  year  and  final  year  students  enrolled  in  the  Computers  and  Information  Technology  Bachelor  program.  The  course registered a total of 96 students and was conducted in both digital and real‐life classroom forms, using  a Facebook closed group and traditional academic settings. 

Figure 2: Controlled research variables (values presented in italics) in the communication structure 

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Versavia Ancusa, Razvan Bogdan and Oana Caus  It should be mentioned that there is no official Facebook policy of the University, but the former Chancellor  and other high‐level teachers have accounts and befriend students, without any quandary. A Facebook group,  however, allows members to post on the blackboard without them having to be friends with each other. It is  our  belief  that  in  doing  this,  we  maintain  a  more  considerate  level  of  privacy  for  everybody  involved,  to  be  layered with the privacy settings on each person’s profile. New courses were posted each week, using different  approaches (YouTube video, Facebook notes, external link to slides/ articles, audio files, animations) and thus  mapping  various  modalities  (visual,  auditory,  kinaesthetic  or  reading).  The  tonality  of  the  posts  /  actual  lectures  varied  from  informal  to  highly  formal  academic  lectures  and  readings.  Referring  to  Figure  1,  our  research  varied  the  parameters  presented  in  Figure  2;  basically,  we  controlled  the  environment  and  the  representation system.    After  the  end  of  the  course  students  were  asked  to  express  their  opinion  and  submit  it  via  an  anonymous  questionnaire,  thus  making  it  a  safe  environment  to  knowledge  sharing,  as  suggested  by  Dr.  David  Zweig  in  (Webster,  et  al.,  2008).  The  questionnaire  was  designed  to  assess  students’  subjective  viewpoint  regarding  their  learning  efficiency.  Each  question  was  duplicated  in  two  different  ways,  as  a  means  to  ensure  a  more  accurate measurement. We also included a free‐comment section that proved to add valuable insight.  The final exam included several items and each item was correlated with a specific teaching modality.    Our aim was to test the ability, preference and assimilation for each major modality (V, A, R, K) in two different  contexts: formal and informal. 

4. Results and discussion  The  initial  students’  assessment  using  VARK  has  led  to  the  data  presented  in  Table  1.  There  was  a  marked  preference  for  auditory  and  reading  modalities.  These  two  preferences  could  be  approximated  by  a  normal  distribution  (kurtosis  and  skewness  close  to  0).  It  should  be  noted  that  no  student  obtained  a  maximum  possible score (16) at any category. Moreover, the mean suggests limited capabilities for modelling data: 25%  for visual, 38.5% for auditory, 40.31% for reading, 35.81% for kinaesthetic. Data dispersion (taking into account  range  and  sample  variance)  for  the  visual  modality  is  reduced  compared  to  the  auditory  and  kinaesthetic  modalities. Interestingly, the reading column presents a medium dispersion because it may imply all the three  senses, as we found in the comments section of the final questionnaire in the first year of the experiment. One  of the students described the reading as “speaking the text in my head”. After further investigation with the  students  from  the  second  year  of  the  experiment,  their  description  of  reading  varied  and  was  usually  a  composite of the other senses. The internalization of these processes – converting the reading into modalities  – varied greatly and often the students could not explain the process.  Table 1: General statistic data after VARK testing 

Data Mean  Standard Error  Median  Mode  Standard Deviation  Sample Variance  Kurtosis  Skewness  Range  Minimum  Maximum  Confidence Level (95.0%) 

V 4.00  0.26  4.00  4.00  1.75  3.07  0.80  0.63  8.00  1.00  9.00  0.53 

A 6.16  0.39  6.50  7.00  2.60  6.74  0.10  0.32  12.00  1.00  13.00  0.79 

R 6.45  0.35  6.00  5.00  2.32  5.37  ‐0.15  0.58  9.00  3.00  12.00  0.70 

K 5.73  0.40  6.00  6.00  2.63  6.90  0.70  0.75  12.00  1.00  13.00  0.80 

The final exam consisted of a written individual paper in which students had to answer several problems. The  problems  reflected  parts  of  the  course  that  were  taught  using  different  modalities.  We  converted  the  percentage of correct answer from each question to a percentage in the VARK analysis. The data are presented  in Table 2.  

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Versavia Ancusa, Razvan Bogdan and Oana Caus  Table 2: General statistic data after exam items  Data 

V

A

R

K

Mean

4.32

6.27

6.08

5.13

Standard Error 

0.68

0.42

0.58

0.46

Median

2.40

6.78

7.11

5.63

Mode

0.00

8.80

8.89

6.93

Standard Deviation 

4.28

2.66

3.69

2.93

Sample Variance 

18.35

7.10

13.61

8.57

Kurtosis

‐0.58

‐0.47

‐1.20

‐1.30

Skewness

0.89

‐0.76

‐0.40

‐0.31

Range

12.80

9.60

10.67

9.53

Minimum

0.00

0.53

0.00

0.07

Maximum

12.80

10.13

10.67

9.60

1.37

0.85

1.18

0.94

Confidence Level (95.0%) 

At the beginning of the course, there was a marked preference for auditory and reading modalities and the  final exam showed that lectures that promoted those preferences had the highest rate of correct answers. This  comes to show the importance of modality preference pre‐checking prior to the actual beginning of teaching.  Regarding  tonality,  the  Facebook  environment  versus  traditional  location  for  the  course,  the  final  questionnaire  revealed  that  the  on‐line  portion  of  the  course  was  not  easier  to  graduate  than  the  more  traditional part as students found the same level of difficulty, but it was easier to ask details, easier to retrieve  information and much easier to understand than the traditional methods.    Of  the  total  of  96  students,  47.92%  checked  their  Facebook  account  more  than  once  a  day,  37.5%  checked  their  account  once  a  day,  8.3%  entered  their  account  once  every  two  days  and  the  remaining  3  persons  accessed the platform at least once a week. 

Figure 3: Course reflection – students’ poll data (5 – highest, 1 – lowest)  When asked to describe their opinion in relation to the interaction during the course in comparison (Figure 3)  with more traditional teaching methods, the ease and rapidity of access as well as the ease of interaction were  particularly  appreciated,  while  loss  of  privacy  was  not  a  concern  for  students.  It  should  be  noted  that  the  interaction  with  the  teacher  was  not  as  important  as  the  overall  ease  of  interaction.  In  supporting  this,  we  should  mention  that  in  more  than  one  occasion,  when  questions  were  posted  by  students,  other  students  replied with the answer, the teacher intervening only when more clarification was needed. This aspect is highly  significant  to  individuals’  human  development:  they  learn  to  promote  a  positive  digital  citizenship  while  developing  a  sense  of  teamwork.  Also,  this  introduces  collaborative  learning,  proven  by  other  professionals 

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Versavia Ancusa, Razvan Bogdan and Oana Caus  (Bruffee, 1999), (Cohen, et al., 2004) to be one of the most efficient learning methods. On the other hand, in  terms of question answering, the traditional setting is highly dependent on the teacher and questions can be  asked only during the course or office hours.    With  respect  to  the  types  of  materials  used  during  this  course  (Figure  4),  the  video  was  the  most  enjoyed,  followed closely by informal notes, using Facebook notes and pdf course slides. The least liked by the students  was the scientific article, though interestingly it was the only type of material that did not receive a “totally  reject’ vote. 

Figure 4: Students evaluation of information presentation methods  In terms of the material tone, more informal methods like video recordings and Facebook notes were enjoyed  the most, the least enjoyable being, again, the scientific article. 

5. Conclusions After conducting experiments for two years, the authors advance the following guidelines: prior testing using  VARK (or a similar tool) is essential, followed by splitting students into groups based on their preferences (e.g.:  visual group, auditory group, etc.). Students should be allowed to choose between groups if their preferences  score  high  enough.  A  special  mention  concerns  teacher’s  intervention,  namely  the  teacher  must  ensure  students that one group or the other is not better/worse. Furthermore, it is helpful to keep the groups flexible,  as one student may “migrate” from one group to another. This is highly probable to happen with students that  have  several  strong  modalities.  These  groups  are  now  ready  to  perform  various  collaborative  learning  techniques because using the same modality will provide faster concept understanding and integration. As a  teacher,  remember  to  present  the  concept  using  modality‐specific  words  and  teaching  aids  to  each  of  the  groups. Another academic targeted conclusion is that test items should be presented in all modalities, since  understanding  requirements  is  the  first  step  towards  finding  the  solution  to  a problem.  Individuals with  low  scores  in  a  modality  may  find  it  difficult  to  adapt  the  internal  representation  of  the  test  item  to  their  best  modality.Regarding  the  opposition  academic  vs.  social  network  settings,  we  have  discovered  that  Facebook  usage favours more informal teaching methods that achieve a higher emotional response from students. This  enables  adequate  premises  for  deepening  the  learning  process,  which  is,  unquestionably,  our  mission  as  educators.  

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Filling the Knowledge gap: How Relevant is University Programmes  to Industry Needs?  Nicolene Barkhuizen  North‐West University, Mmabatho, South Africa  nicolene.barkhuizen@nwu.ac.za    Abstract:  The  past  two  decades  have  seen  a  proliferation  of  publications  debating  the  roles  of  Human  Resource  Management  (HRM)  practitioners  in  the  South  African  work  context.  These  publications  highlighted  a  great  deal  of  confusion  and  uncertainty  relating  to  the  contributions  of  HRM  practitioners  in  the  workplace.  Higher  Education  Institutions  should  therefore  examine  their  roles  and  academic  programmes  to  ensure  that  a  new  generation  of  HRM  practitioners are adequately prepared and relevant for the workplace. The main objective of this research was to analyse  the content of the undergraduate HRM programmes as currently being offered at a merged South African Higher Education  Institution.  This  research  first  aimed  to  analyse  the  similarities  and  differences  between  the  programmes.  Secondly  this  research aimed to compare the curricula of the merged institution with the undergraduate HRM curricula of other South  African  HEIs.  Finally  this  research  aimed  to  determine  the  extent  to  which  the  programme  contents  are  in  line  with  the  competency requirements for HRM practitioners in the workplace. A case study approach was followed in this research.  This  case  involved  the  comparison  of  three  undergraduate  programs  focusing  on  HRM  in  a  merged  higher  education  institution.  In  addition  the  programmes  of  the  current  institution  were  also  compared  with  seven  other  South  African  Higher  Education  Institutions  (HEIs)  that  offer  a  Bachelors  Degree  in  HRM.  The  institutions  were  chosen  based  on  their  access and availability of information as well as their status in the field of HRM. These HEIs also represented newly formed  South  African  comprehensive  universities  as  well  as  traditional  higher  education  institutions.  Curriculum  data  such  as  yearbooks  and  subject  guides  were  analysed.  The  findings  for  the  merged  institution  showed  that  the  undergraduate  programme in HRM differed significantly in terms of the content offered. This presents some significant challenges in the  alignment of programmes across the three campuses of the institution which is a requirement of the Department of Higher  Education and Teaching. Students are thus unable to move between the three campuses in terms of studying HRM. Only  one campus offers HRM on all three year levels whereas the other two campuses seem to focus more on Labour Relations.  This  is  limiting  the  students  on  the  latter  campuses  in  terms  of  pursuing  a  further  professional  career  in  HRM.  Similar  results were observed between the HRM programme offerings of the other HEIs. The knowledge contents of the current  HRM programmes only meet the new competency requirements for HRM professionals to some extent.     Keywords: human resource management, undergraduate curricula, higher education institutions, mergers, workplace  competencies  

1. Introduction A country's international competitiveness and growth of the knowledge community depends on its population  having  a  strong  and  sustainable  higher  educational  sector.  South  African  higher  education  institutions  in  particular  are expected  to  play  a  critical  role  in  human  resource  development  and  stimulate  innovation  in  a  ‘knowledge  economy’  (Council  of  Higher  Education  –  CHE,  2011;  Baloyi  &  Phago,  2012).  The  South  African  higher educational landscape however has undergone significant changes post 1994. The collapse of apartheid  has lead to the transformation and re‐structuring of higher education institutions with the aim of correcting  historical  inequalities  (Chipunza  &  Gwarinda,  2010;  Lalla,  2009).  As  a  result  the  number  of  higher  education  institutions  were  reduced  and  placed  into  three  categories:  universities,  universities  of  technology  and  comprehensive/ merged institutions (Muller, 2008). Comprehensive universities emerged as result of a merger  between the technicon and the traditional university (Reddy, 2004).     Bester and Scholtz (2012) maintain that the transformation of higher education in South Africa has resulted in  an  ongoing  need  to  reflect  critically  on  the  relevance  and  responsiveness  of  higher  education  curricula.  Comprehensive universities for example are expected to offer a diverse range of university programmes (i.e.  vocational,  career‐focused,  professional  and  general/formative)  of  both  the  university  and  technicon  type  (Reddy,  2004.  This  posed  a  number  of  thought  provoking  and  provocative  questions:  How  will  programme  diversity be maintained? At what levels is integration possible and desirable? Where is it possible to construct  articulation  pathways,  and  what  form  will  they  take  (CHE,  2004)?  To  this  end  comprehensive  and  merged  institutions have to consider whether to retain, redesign, consolidate or discontinue existing qualifications or  alternatively develop new qualifications (Muller, 2008). Qualification structures should therefore be developed  that  will  allow  comprehensive  and  merged  institutions  to  define  their  roles  within  the  restructured  South  African higher educational landscape (Baloyi & Phago, 2012; Higgs & Keevy, 2009).  

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Nicolene Barkhuizen  Against this background, the main objective of this research was to analyse the content of the undergraduate  Human  Resource  Management  (HRM)  programmes  as  currently  being  offered  at  a  merged  South  African  Higher Education Institution. This research first aimed to analyse the similarities and differences between the  programmes.  Secondly  this  research  aimed  to  compare  the  curricula  of  the  merged  institution  with  the  undergraduate HRM curricula of other South African HEIs. Finally this research aimed to determine the extent  to which the programme contents are in line with the competency requirements for HRM practitioners in the  workplace.     This  research  is  motivated  from  the  fact  that  the  Department  of  Higher  Education  and  Training  requires  all  merged HEIs to present curricula that are similar in content (Baloyi & Phago, 2012). Therefore the need to do  an  in  depth  analyses  of  the  types  of  modules  that  are  offered  as  part  of  the  undergraduate  programmes  in  HRM and the possible implications for vertical and horizontal articulation. In addition universities are expected  to  produce  workplace  ready  individuals  who  can  lead,  produce  new  knowledge,  see  new  problems  and  imagine new ways of approaching old problems (CHE, 2011; Heerde & Murphy, 2009; Nduna, 2012; Njozela,  2012).    This research thus aimed at answering the following research questions:  ƒ

What are  the  similarities  between  the  undergraduate  HRM  programmes  as  offered  by  a  merged  South  African HEI? 

ƒ

What are  the  differences  between  the  undergraduate  HRM  programmes  as  offered  by  a  merged  South  African HEI? 

ƒ

How do  the  current  curricula  offered  by  the  merged  institution  compare  with  undergraduate  HRM  curricula of other HEIs?  

ƒ

To what  extent  do  the  current  programme  offerings  of  the  merged  institution  comply  with  the  competency requirements for HR Professionals in the workplace?  

In what follows next a brief description of the competency requirements for HRM Practitioners is presented.  Thereafter the methodology used to answer the empirical research questions and the results are presented,  ending with a discussion and, finally, the conclusion and value‐add of the research. 

2. Theoretical framework  2.1 Competency requirements for HRM practitioners   Since  its  inception  nearly  a  century  ago,  the  field  of  HRM  has  been  subjected  to  immense  scrutiny  by  questioning  its  value  add  to  organisations  (Ulrich,  2011).  Applied  within  the  South  African  context,  the  past  two  decades  have  seen  a  proliferation  of  publications  which  highlighted  the  confusion  and  uncertainty  regarding the exact contributions of HRM practitioners in the workplace.  Higher Education Institutions should  therefore  examine  their  roles  and  academic  programmes  to  ensure  that  a  new  generation  of  HRM  practitioners  are  adequately  prepared  and  relevant  for  the  workplace  (Bester  &  Scholtz,  2012;  Maila,  2012;  Meyer & Bushney, 2008).     Some  research  for  example  showed  that  HEIs  are  failing  to  produce  workplace  ready  graduates  (CHE,  2011;  Pop  &  Barkhuizen,  2010).  Generally,  organisations  are  not  able  to  use  new  graduates  to  fill  their  skill  requirements because of a lack knowledge, skills and experience. Applied within the field of HRM, this can be a  result of the role confusions that exist between Industrial Psychologists and HRM Practitioners. The primary  task  of  IO  Psychology  is  the  application  of  psychological  principles  and  research  to  workplace  phenomena  (Rothmann  &  Cilliers,  2007;  Schreuder  &  Coetzee,  2010)  whereas  Human  Resource  Management  involves  a  more strategic approach to acquire, develop and manage people in the organisation (Ulrich, 2011). According  to Schreuder and Coetzee (2010) Industrial Psychologists are mostly fulfilling the roles of HRM practitioners in  the workplace as opposed to their own envisaged roles. This situation can be explained by the fact that some  universities  in  South  Africa  still  accept  an  academic  dispensation  where  I/O  Psychology  is  taught  under  the  discipline of HRM (Rothmann & Cilliers, 2007; Schreuder & Coetzee, 2010).     The  new  qualification  mix  in  comprehensive  and  merged  institutions  also  seems  problematic  as  far  as  the  programme  outcomes  for  HRM  are  concerned.  Technicons  traditionally  focused  on  practical  career‐focused 

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Nicolene Barkhuizen  and  work‐integrated  learning  that  combined  theoretical  knowledge  with  applied  competence  (CHE,  2011).  University  qualifications  provided  general  formative  and  career‐orientated/  professional  education  that  focused on teaching and in‐depth research. A study comparing both types of qualifications in a comprehensive  university, showed that only minor differences existed in terms of the knowledge and skills acquired, teaching  and  learning  methods  and  assessment  procedures  (Barkhuizen,  Goosen,  van  Loggerenberg  &  Malan,  2009).  None of the two qualifications focused on the development of technical skills. Merged institutions on the other  hand have to deal with programme standards and the subsequent development of common curricula across all  delivery  sites  (Goddard,  2009).  Research  evidence  suggest  that  the  mergers  of  HEIs  did  not  result  in  the  “favourable” environment that the South African government envisaged and have left scholars with numerous  challenges  and  obstacles  relating  to  curriculum  design  and  alignment  (Baloyi  &  Phago,  2012;  Ntshoe,  2012).  These results have important implications for the type of HRM practitioners that comprehensive and merged  universities produce for the labour market as well as compliance with professional HRM standards.    The SABPP is the professional body for the registration and competency guidance of HRM practitioners in the  South  African  workplace  (Meyer,  2012).  The  SABPP  recently  launched  a  new  competency  model  for  HR  professionals  in  the  workplace  (Meyer,  2012).  The  competencies  include  amongst  others  Leadership  and  Personal  Credibility,  Organisational  Capability,  Solution  Creation  and  Implementation,  Interpersonal  and  Communication  Skills  and  Citizenship  for  the  future.  From  the  model  it  is  clear  that  HR  Professionals  at  the  basic level already need to possess the necessary business acumen, soft and technical skills to execute HRM  roles in the workplace effectively (Meyer, 2012). This new competency model fills an important gap as a recent  survey  among  HRM  practitioners  showed  that  only  20%  of  South  African  organisations  have  a  HRM  competency  model  in  place  (Knowledge  Resources,  2011).  In  addition  most  of  the  organisations  surveyed  utilise HRM competency models that do not take the South African labour market context into account.     Furthermore, in many incidences the considerable lack of soft and technical skills training and work integrated  learning practices at the undergraduate level are key reasons why organisations have to implement internship  programmes to make graduates more workplace ready (Pop & Barkhuizen, 2010). One of the key goals in the  establishment  of  comprehensive  Institutions  was  to  introduce  work  or  career‐focused  orientation  in  some  programmes with the possibility of cooperative or in‐service learning (CHE, 2011). Comprehensive institutions  and  merged  institutions  are  required  to  contribute  to  students’  ‘graduateness’  in  various  forms  and  should  thus  focus  on  “Programmes  that  promote graduates’  successful  integration  into  the  world  of  work  and  that  enable  graduates  to  make  meaningful  contributions  in  contexts  of  development”  (CHE,  2011:  3).  The  effectiveness  of  work  integrated  learning  programmes  in  the  transfer  of  work  related  knowledge  and  subsequent increase in graduate employability has been widely documented (CHE, 2011; Eigst, 2009; Griesel &  Parker,  2008;  Pop  &  Barkhuizen,  2010).  The  implementation  of  WIL  programmes  however  will  require  innovative curricular, teaching, learning and assessment practices (CHE, 2011).     In  sum,  the  above  discussion  highlighted  the  challenges  relating  to  the  knowledge  acquisition  of  HRM  practitioners  and  the  subsequent  impact  thereof  on  their  ability  to  perform  their  envisaged  roles  in  the  workplace.  This  section  also  showed  the  important  role  of  HEIs  in  providing  sound  teaching  and  learning  practices  for  HRM  graduates  that  comply  with  the  competency  requirements  of  professional  registration  bodies.  

3. Research method  A  case  study  approach  was  followed  in  this  research.  This  case  involved  the  comparison  of  three  undergraduate programs focusing on HRM in a merged higher education institution. The institution came into  existence  as  a  result  of  a  merger  between  a  traditional  South  African  university  and  two  historically  disadvantaged  universities.  The  newly  formed  higher  education  institution  consists  of  three  campuses.  All  three  campuses  offer  postgraduate  programmes  in  HRM  which  flows  from  the  undergraduate  programmes.  The  undergraduate  programmes  are  presented  over  a  period  of  three  years.  Each  year  is  divided  into  two  semesters with modules presented over 14 weeks per semester.     In  addition  the  programmes  of  the  current  institution  were  also  compared  with  seven  other  South  African  Higher  Education  Institutions  (HEIs)  that  offer  a  Bachelors  Degree  in  HRM.  These  institutions  were  chosen  based on the access and availability of information and also their status in the field of HRM. These HEIs also 

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Nicolene Barkhuizen  represented  newly  formed  South  African  comprehensive  universities  as  well  as  traditional  higher  education  institutions.     Data  was  collected  and  analysed  with  a  view  to  identifying  similarities  and/or  differences  in  programs  traditionally offered by the three campuses. This research was executed over three phases. Phase 1 include a  document analyses on the content of all the HRM undergraduate and postgraduate programmes as currently  presented  by the  merged  institution. Curriculum  data  such  as yearbooks and subject guides were analysed..  Phase 2 includes interviews with stakeholders (i.e. academics, employers, HRM professional bodies) and Phase  3  surveys  (academics,  employers  and  students).  This  paper  reports  on  the  document  analyses  of  the  comparison between the programmes under investigation.  

4. Findings 4.1 Comparison of the current undergraduate curricula at the merged institution  The  findings  of  the  analyses  are  reported  next.  Tables  1  to  3  display  the  similarities  and  differences  of  the  undergraduate  curricula  as  presented  on  the  three  campuses  per  academic  year.  The  analysis  of  the  undergraduate programme for the first year of study is reported in Table 1 below.   Table 1: Comparison of undergraduate curricula – first year of study   Modules  1  2 

3 4  5  6 

Campus 1  IOPS111  (Intro to IOPS)  HRM 111  (Intro to HRM) 

X X  X  IOPS121  (Ergonomics & OH)  HRM 121  (Functions of HRM)  X  X  X  X 

7 8  9  10  11 

Campus 2  IOPS 111   (H)  (Intro to IOPS)  Labour Relations  Management 111  (H)  (Intro to Workplace  Relations)  X  X  X  IOPS 121  (H)  (Ergonomics & OH)  Z 

Campus 3  IOPS111  (Intro to IOPS)  Labour Relations Management  111  (Intro to Workplace Relations) 

X X  X  X 

X X  X  X 

X X  X  IOPS121  (Ergonomics & OH)  Z 

X indicates similarities in modules across the three campuses  Z indicates similarities modules between Campuses 2 and 3     The findings in Table 1 show that the modules presented over the three campuses are mostly similar in the  first  year  of  study.  There  are  no  differences  in  the  modules  presented  on  Campuses  2  and  3.  Campus  1  presents  Human  Resource  Management  whereas  the  other  two  campuses  focus  on  Labour  Relations  Management  in  the  first  semester  and  Psychology  in  the  second  semester.  Campus  1  presents  a  basic  introduction to HRM and the functions thereof. The findings of the analysis of the undergraduate programme  for the second year of study are reported in Table 2 below.   Table 2: Undergraduate curricula  – second year of study  Modules  1 

3

Campus 2  IOPS 211   (H)  Personnel Psychology  Labour Relations  Management  211  (H)  Occupational Management  Z 

4 5 

Z X 

2

Campus 1  IOPS212  (Consumer Psyc)  HRM 211  (Training and Development) 

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Campus 3  IOPS 211   (H)  Personnel Psychology  Labour Relations  Management 211  (H)  Occupational Management  Z  Z  X 


Nicolene Barkhuizen  Modules  6  7  8 

9 10  11  12 

Campus 1  Y  IOPS221  (Career Psyc)  HRM 221  (Performance Management  and Rewards)    X  Y  Y 

Campus 2    IOPS221 (H)  (Occupational Psyc)  Labour Relations  Management  221 (H)  (Work Group Dynamics)  Z  X     

Campus 3  Y  IOPS221 (H)  (Occupational Psyc)  Labour Relations  Management 221 (H)  (Work Group Dynamics)  Z  X  Y  Y 

X indicates similarities in modules across the three Campuses  Y indicates similarities in modules between Campus 1 and 3  Z indicates similarities modules between Campuses 2 and 3     The findings in Table 2 showed that the modules presented on Campus 2 and 3 in the second year are mostly  similar.  Again  there  are  significant  differences  between  the  modules  offered  on  Campus  1  compared  with  other two campuses. Campus 1 is the only campus offering Human Resource Management whereas the other  two  campuses  are  presenting  Labour  Relations  Management.  Campus  1  presents  Training  and Development  and Performance Management and Rewards Management as key HRM functions. The findings of the analysis  of the undergraduate programme for the third year and final year of study are reported in Table 3 below.  Table 3: Undergraduate curricula – third year of study   Modules  1  2 

3 4  5  6  7 

8 9  10 

Campus 1  IOPS311  (Organisational Psyc.)  Human Resource  Management  311  (Employee Relations)  X 

Campus 2  IOPS 311   (H)  Organisation Psychology  Labour Relations  Management  311  (H)  Theory & Practice of LR  X 

Campus 3  IOPS 311   (H)  Organisation Psychology  Labour Relations  Management  311  (H)  Theory & Practice of LR  X 

X  IOPS321  (Psyc & Research Meth)  Human Resource  Management 321  (Stragic Human Resource  Management)  D  D   

Z X  IOPS321    (H)  (Psyc & Research Meth)  Labour Relations  Management  322   ** 

Z X  IOPS321    (H)  (Psyc & Research Meth)  Labour Relations  Management  322   ** 

D LARM321  (H)  Z 

D LARM321  (H)  Z 

X indicates similarities in modules across the three Campuses  Y indicates similarities in modules between Campus 1 and 3  Z indicates similarities modules between Campuses 2 and 3     The findings in Table 3 showed that the modules presented on Campus 2 and 3 in the second year are mostly  similar. Again there are significant differences between the modules offered on Campus 1 compared with the  rest of the campuses. Campus 1 is the only campus offering Human Resource Management whereas the other  two  campuses  are  presenting  Labour  Relations  Management.  Campus  1  presents  an  Introduction  to  Labour  Relations Management as well as module of Strategic Human Resource Management. Table 4 below presents  a summary of the results in Table 1 to 3.     The results in Table 4 show that in general there are significant differences in the module offerings of Campus  1 compared with Campus 2 and 3. The module contents of the Campus 2 and 3 are more aligned. Campus 1 is  the  only  campus  that  focuses  on  HRM  for  all  three  academic  years.  Campus  2  and  3  only  includes  on  introductory  module  on  HRM  in  the  second  year  of  study.  Furthermore  campuses  2  and  3  focus  more  on 

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Nicolene Barkhuizen  Labour Relations Management on all three year levels whereas Campus 1 only presents one module Labour  Relations Management on third year level.   Table 4: Comparison of the results of the analyses of the undergraduate curriculum      Year 1  Year 2  Year 3 

Comparison Campuses 1 and 2  %  %  Similarities  Differences  85%  15%  33%  67%  30%  70% 

Comparison Campuses 1 and 3  %  %  Similarities  Differences  85%  15%  58%  42%  30%  70% 

Comparison Campuses 2 and 3  %  %  Similarities  Differences  100%  0  75%  25%  90%  10% 

The results of the analyses also showed that none of the three campuses offer work integrated learning as part  of the undergraduate curricula. The results also revealed a lack of soft skills and technical skill training as part  of  the  undergraduate  curricula.  Finally  the  results  showed  that  Campus  1  to  some  extent  comply  with  the  theoretical part of the competencies required from the SABPP but not the practical part. Campuses 2 and 3  comply with the requirements of the SABPP as far as competence in employment relations is concerned. 

4.2 Comparison between other South African Higher Education Institutions   The results of the comparative analyses between the seven HEIs showed the following:  ƒ

Less than half of the HEIs that were involved in the analyses offer separate undergraduate qualifications in  Human Resource Management and Industrial Psychology.  

ƒ

Two of the HEIs offered Industrial Psychology and Human Resource Management as one qualification.  

ƒ

One of the HEIs in the sample offers an undergraduate qualification in Human Resource Management, but  80% of the modules include contents relating to the field of Industrial Psychology.  

ƒ

Four of  the  HEIs  included  in  the  analyses  present  modules  with  HRM  content  but  label  it  as  Industrial  Psychology Modules.  

ƒ

The analyses also showed that there is a discrepancy in terms of the type of modules offered per year of  study at the different Higher Education Institutions.  

ƒ

Most of  the  HEIs  investigated  offered  commerce  modules  such  as  such  as  Business  Management,  Economics,  Stats,  Accounting,  Computer  Literacy,  and  Law  are  a  common  trend  in  the  Commerce  qualifications. 

ƒ

Interestingly however most of the HEIs do not focus or address contemporary HRM issues such as Talent  Management,  Diversity  Management,  Organisational  Behaviour,  Remuneration  Management,  Organisational  Development  and  Change  Management,  Strategic  HRM  as  part  of  their  programme  offerings.  

5. Discussion Human  Resource  Management  is  a  profession  in  rapid  transition.  This  means  that  we  need  to  take  stock  of  what we teach our students in order to prepare them adequately for the workplace. The main focus of this  research  was  to  investigate  the  similarities  and differences  in  the undergraduate curricula  as presented  in  a  merged institution and whether the current programme offerings are relevant to workplace requirements.     From the results it is evident that the undergraduate programmes as currently being presented on the three  campuses are about 80% the same in content in the first year of study. The results further indicated indicate  that  there  are  major  differences  in  the  programme  as  students’  progress  to  their  second  and  third  year  of  study. This is problematic as it first becomes challenging to align the programme across the three campuses  which is a requirement of the Department of Higher Education and Training (Muller, 2008). Secondly students  are unable to move between the three campuses in terms of studying Human Resource Management. Campus  1  is  the  only  campus  that  includes  Human  Resource  Management  as  part  of  its  curriculum  across  all  three  academic  years  whereas  the  other  two  campuses  seem  to  focus  more  on  Employment  Relations.  This  is  limiting  the  students  on  Campuses  2  and  3  in  terms  of  pursuing  a  further  professional  career  in  Human  Resource Management as they have limited exposure to the basic principles of Human Resource Management. 

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Nicolene Barkhuizen  Likewise  the  students  on  Campus  1  are  limited  in  terms  of  their  career  progress  in  Labour  Relations  Management.     The  results  further  showed  that  there  is  limited  consistency  in  undergraduate  curricula  offerings  in  HRM  as  offered by other Higher Education Institutions in South Africa. As with the curricula in the merged institution  other  universities  also  seem  to  include  Industrial  Psychology  as  an  integral  part  of  the  Human  Resource  Management Programme (see Rothmann & Cilliers, 2007; Schreuder & Coetzee, 2010). This in turn can lead to  an identity crisis for both HRM Practitioners and Industrial Psychologists relating to their envisaged roles in the  workplace.  The  results  further  showed  a  the  lack  of  more  strategic  HRM  modules  such  as  Diversity  Management, Remuneration Management, Organisational Development and Change Management in most of  the undergraduate curricula of the South African Higher Education Institutions under investigation. This is in  contrast with some of the basic workplace competencies as highlighted by the SABPP (Meyer, 2012). One can  argue that most HEIs may reserve these modules for postgraduate qualifications. However, it is important to  note  that  very  few  undergraduate  students  pursue  a  postgraduate  qualification  in  HRM.  As  a  result  employment  opportunities  are  limited  for  HR  undergraduate  students  as  they  do  not  meet  workplace  requirements. Campus 1 focuses to a limited degree on some of the modules that are highlighted as part of  the  competency  model  of  the  SABPP.  The  results  further  showed  that  none  of  the  three  campuses  have  a  work‐based  component  as  part  of  the  undergraduate  programme  offerings.  This  is  in  contrast  with  the  requirements of the Department of Higher Education (CHE, 2011).     The  findings  of  this  research  provided  valuable  inputs  into  curriculum  redesign  and  alignment  in  a  merged  institution as well as the different South African HEIs. In addition, the findings of this research also contribute  to  the  development  of  HRM  programmes  that  are  more  aligned  with  employer  needs.  As  regards  the  programme  offerings  of  the  current  institution  it  is  recommended  that  Campuses  2  and  3  include  HRM  Modules  on  all  three  levels  of  the  undergraduate  programme  to  provide  students  with  a  more  thorough  foundation  to  enter  postgraduate  programmes  in  HRM.  It  is  also  advisable  that  these  Campuses  align  the  curriculum  content  with  the  requirements  of  the  SABPP.  Moreover  it  is  also  recommended  that  all  three  campuses  introduce  a  work‐based  learning  component  into  the  undergraduate  curricula  to  enhance  the  employability of undergraduate students.     This research had some limitations. First the findings of the results cannot be generalised to all South African  Higher Education Institutions as only seven institutions were included in the analyses. Secondly this paper was  only  limited to  document  analyses.  The  envisaged  research  in  phases 2  and  3  will  allow  for  a  more  detailed  opinion of the relevant stakeholders on the current curriculum offerings of the three campuses.     In conclusion this research showed that there are vast differences not only in the undergraduate curricula in  HRM  offered  at  one  merged  comprehensive  institution  but  also  across  institutions  in  South  Africa.  This  is  problematic as it can limit student movement to pursue further postgraduate studies at other South African  HEIs. In addition, the naming of the HRM programmes as well as the modules can be confusing. For example in  the  case  where  modules  offered  content  in  Human  Resource  Management,  it  was  labelled  as  Industrial  Psychology.  This  contributes  to  the  confusion  as  to  what  the  roles  of  Industrial  Psychologists  and  HRM  practitioners  should  be.  There  should  thus be  a  clearer  differentiation  between  what  is  offered  in  Industrial  Psychology and what should be offered in Human Resource Management.  

References Baloyi, M.C., and Phago, K.G. (2012) “Structural functional analysis of Tshwane University of Technology: Post merger  implications”, South African Journal of Higher Education, Vol 26, No. 5, pp. 873–890.  Bester, M., and Scholtz, D. (2012) “Mapping our way to coherence, alignment and responsiveness”,  South African Journal  of Higher Education, Vol 26, No. 2, pp. 282–299.  Barkhuizen, E.N., Goosen, X., Van Loggerenberg, E., and Malan, B. (2009) “Rethinking Undergraduate Curricula in  Comprehensive Universities: A South African Case Study”, Peer reviewed conference proceedings of the London  International Conference on Education, pp. 178‐184, Infonomics Society.  Chipunza, C., and Gwarinda, S.A. (2010) “Transformation Leadership in Merging Higher Education Institutions”, South Africa  Journal of Human Resource Management, Vol 8, No. 1, pp. 1‐10.  Council of Higher Education (2004) Creating Comprehensive Universities in South Africa: A Concept Document, Pretoria  Council of Higher Education (2011) Work Integrated Learning: Good Practice Guide, Pretoria.   Eigsti, J.E. (2009) “Graduate nurses’ perceptions of a critical nurse internship programme”, Journal for Nurses in Staff  Development, Vol 25, No. 4, pp 191‐198. 

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Nicolene Barkhuizen  Goddard, K. (2009) “Some observations on higher education in the Humanities in South Africa with special reference to  Nelson Mandela Metropolitan University as a post‐merger institution”, South African Journal of Higher Education, Vol  23, No. 2, pp. 293‐308.   Griesel, H. and Parker, B (2008) Grappling with youth employability in South Africa. Employment, growth and development  initiative, Pretoria: HRSC Press.  Heerde, J. and Murphy, B. (2009) Work Integrated Learning: An Annotated Bibliography of published refereed journal  articles (2000 – 2008).  Higgs, P. and Keevy, J. (2009) “Qualifications frameworks in Africa: A critical reflection”, South African Journal of Higher  Education, Vol 23, No. 4, pp. 690–702.  Knowledge Resources (2011) National HR Survey. Pretoria.   Lalla, V. (2009) The impact of the Merger on the Employees of Tswane University of Technology, Unpublished Masters  Thesis, University of Pretoria.   Maila, M. W. (2012) “Re‐thinking complex, fluid and contradictory knowledge(s) in higher education”, South African Journal  of Higher Education, Vol 26, No. 6, pp 1159–1169.  Meyer, M. (2012) HR Competency Model. www.sabpp.co.za  Meyer, H.M. & Bushney, M. (2008) “Towards a multi‐stakeholder‐driven model for excellence in higher education  curriculum development”, South African Journal of Higher Education, Vol 22, No. 6, pp 1229–1240.  Muller, J. (2008) In search for coherence:  A conceptual guide to curriculum planning for comprehensive universities, Report  prepared for the SANTED project, Centre for Education policy development, University of Cape Town, Cape Town.   Njozela, D. (2012) “Mental models’ that students possess about Work Integrated Learning (WIL) with reference to the new  curriculum framework”, South African Journal of Higher Education, Vol 26, No. 2, pp 249–267.  Ntshoe, I. (2012) “Reframing curriculum and pedagogical discourse in universities of technology”, South African Journal of  Higher Education, Vol 26, No. 2, pp 198–213.  Pop, C.A., and Barkhuizen, E.N. (2010) “The relationship between skills training and retention of graduate interns in a South  African Information, communication and technology company”, Literacy Information and Computer Education  Journal, Vol 1, No. 2, pp 113‐122.  Rothmann, S. and Cilliers, F.v.N. (2007) “Present challenges and critical issues for research in Industrial/Organisational  Psychology in South Africa”, South African Journal of Industrial Psychology, Vol 33, No 1, pp  8‐17.   Schreuder, D., and Coetzee, M. (2010) “An overview of industrial and organisational psychology research in South Africa: A  preliminary study”, SA Journal of Industrial, Vol 36, No 1, pp 1‐11.     South African Qualifications Authority (2012) www.regqs.saqa.org.za  Ulrich, D. (2011) “Celebrating 50 years: An Anniversary Reflection”, Human Resource Management, Vol 50, No. 1, pp. 3‐7.    

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Embedding Knowledge Management in Public Sector Procurement – Redesigning for the Knowledge Economy Denise A. D. Bedford College of Communication and Information, Kent State University, Kent Ohio, USA Dbedfor3@kent.edu Abstract: There is a perception in the public, political and trade discourse that private sector procurement performs “better” than does public sector procurement. This research considers whether this perception is justified. This paper proposes a conceptual framework for assessing Issues that influence procurement performance. The framework takes into account the organization’s business goals, its procurement principles, the design of its procurement capability, the intellectual capital or knowledge that are used to support procurement operations, and the use of knowledge management methods. To represent these factors, the framework adapts the conceptual framework proposed by McElroy (2002), leverages Andriessen’s (2005) characterization of intellectual capital, and adopts Bedford’s (2012) description of the practice of knowledge management. The results, though preliminary and exploratory, suggest that factors which are more often practiced in the private sector than the public sector contribute to higher performance. Keywords: Private sector procurement, public sector procurement, knowledge management, intellectual capital management, procurement life cycle, procurement principles

1. Research context Procurement is defined as the acquisition of goods and services from an external source. Procurement is an enabling activity. Procurement is an essential business capability of all organizations, regardless of whether their financial position is for-, not for- or non-profit. Organizations across all economic sectors procure products and services to fulfill their business goals. It provides day to day institutional support for those business activities that deliver value to the organization’s stakeholders. How well procurement performs may influence how well the organization can deliver to its stakeholders and how well it can achieve its business goals. There is a perception in the public, political and trade discourse that private sector procurement performs “better” than does public sector procurement, and that procurement in the private sector is much easier to perform than it is in the public sector. Is this perception justified? If not, what is the reason for this perception? This research focuses on knowledge management factors that may influence procurement performance in any kind of organization.

1.1 The research questions This paper proposes a conceptual framework as a foundation for assessing factors that might influence procurement performance (Figure 1). The framework takes into account the organization’s business goals, its procurement principles, the design of its procurement capability, the intellectual capital or knowledge that is used to support procurement operations, and the use of knowledge management methods. To represent these factors, the framework adapts the conceptual framework proposed by McElroy (2002), leverages Andriessen’s (2005) characterization of intellectual capital, and adopts Bedford’s (2012) description of the practice of knowledge management. This research explores whether differences in five factors can be associated with variations in procurement performance. The five factors are:

Issue 1: The alignment of the procurement capability with the organization’s business goals

Issue 2: The alignment of procurement principles and business goals

Issue 3: The design of the procurement capability and its alignment with procurement principles

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Denise A. D. Bedford 

Issue 4: The extent to which the procurement capabilities leverage appropriate forms of business focused intellectual capital?

Issue 5: The extent to which the procurement capability leverages knowledge management strategies and methods.

The research further considers how we might leverage these factors to improve procurement performance in the future.

1.2 Literature review The literature provides several perspectives on procurement relevant to this research. These citations are illustrative rather than exhaustive. There is extensive treatment of procurement process improvement methods in the literature (Bovis 2010) (Drobrzykowski Hong and Park 2012) (Frodell 2010) (Guth 2010). Many recent authors and practitioners have compared public and private sector procurement methods (Amaral Saussier Yvrande-Billon 2009) (McKenzie and Culliford 2011) (Smith 2011) (Tadelis 2012) (Teng and Liao 2011). While there is little direct discussion of knowledge management in the procurement literature, aspects of knowledge management are addressed, including use of collaboration methods (Allal-Cherif and Maira 2011) (Gunther and Scheibe 2006) (Nakata and Im 2010) (Plane and Green 2011). The influence of culture and ethics in procurement receives attention (Ntayi 2012) (Saini 2010) (Brandmeier and Rupp 2010) (Brandon-Jones Ramsay and Wagner 2010). The value of intellectual capital is treated (Brandmeier and Rupp 2010) (Ordanini and Rubera 2008). The use of smart knowledge technologies is also covered in the procurement literature (Webb 2010). Despite this coverage, there is no conceptual framework for the use of knowledge or knowledge management in procurement.

2. Research methodology The research methodology involves a manual review of six use case scenarios to explore what role the five factors might have played in achieving a positive procurement outcome. We chose six use cases based on a common procurement activity – the selection and acquisition of semantic technologies to meet a business goal. Each of the organizations considered the same set of tools which were available on the commercial market. Each procurement process was unique to the organization. Organizations made different choices and had different procurement and implementation outcomes. Controlling the context allows us to manage other variables and to focus on the five factors.

2.1 Issue 1: Alignment of procurement with organization’s business goals For most organizations, procurement is an enabling capability. This means it provides internal products and services to those business activities that deliver value to stakeholders – to core and operational business activities. As such, procurement should always be aligned with the organization’s business goals. This is the case regardless of whether we are talking about public or private sector procurement. We want to know whether procurement activities that achieve good outcomes have strong alignments with business goals at the organizational level. We want to know whether there are variations in alignment of goals and activities between public and private sector procurement activities. Do public and private sector organizations working in these sectors have common or different goals? Private sector business goals may focus on gaining market share, meeting consumer demands, generating profits, achieving financial goals, meeting shareholder and stakeholder expectations – in short anything related to doing business in the private economy. Public sector goals are to promote competition, support open access to markets, to safeguard the public funds, serve the public good, and uphold the public trust. Exploratory Expectation: Variations in performance may be expected where procurement activities are not well aligned with an organization’s business goals.

2.2 Issue 2: Alignment of public and private sector procurement principles Procurement is guided by governing principles which support and align with business goals. Given the expectation of different business goals, we also expect differences in procurement principles. Public sector

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Denise A. D. Bedford procurement principles derive from legal and regulatory frameworks. They include: accountability, consistency, effectiveness, efficiency, fair dealing, integrity, legality, informed decision-making, responsiveness, and transparency. Public sector principles derive from legal and regulatory sources, and from public policy.. In the past thirty years, the public policy focus on cost efficiency has influenced public sector procurement decisions. The strong public policy focus on low cost rather than high value may be causing a rift in alignment between public sector organizationsâ&#x20AC;&#x2122; business goals and procurement principles.In sharp contrast, there are no legislative or regulatory requirements that govern private sector procurement processes. Private sector procurement principles derive from the business conduct and practices of the organization, and may include accountability, mutual respect, teamwork and integrity. Whereas public policy drives principles for public sector organizations, stakeholders and corporate policies drive private sector procurement principles. Exploratory Expectation: Variations in performance may be expected where there are misalignments between business goals and procurement principles.

2.3 Issue 3: intended design of procurement capability to support business goals The procurement process is essentially the same in private and public sector organizations (Figure 3). However, there may be variations in how procurement activities are carried out within organizations, and how the procurement function is designed to support the organization. Larger organizations may have centralized procurement capabilities, whereas smaller organizations may assign procurement tasks to an individual along with other responsibilities. Some organizations may embed procurement officers within business units to ensure strong support for business needs. Public sector organizations may intentionally separate these activities to reduce a risk of corruption and to ensure transparency. Private sector organizations, though, are more likely to embed procurement officers within business units to ensure procurement decisions do reflect business goals and needs. Private sector procurement officers may have strong subject matter ties to the market, an advantage that those organizations would leverage. Exploratory Expectation: Variations in performance may be observed depending on whether or not the procurement capability is designed to support business.

2.4 Issue 4: use of knowledge in procurement activities Knowledge, in the form of intellectual capital, is a fundamental capital asset for both private and public sector st organizations in the 21 century knowledge economy. Organizations that leverage their intellectual capital work smarter than those that see their intellectual capital as billets or salary expenses. Andreissen (2005) has defined intellectual capital to include human knowledge (tacit knowledge, skills, attitude), structural knowledge (explicit knowledge, procedural knowledge, culture), and relational knowledge (networks, reputation, brand). We suggest there are three types of intellectual capital of value to procurement: (1) subject matter knowledge â&#x20AC;&#x201C; knowledge of the product or service that is being procured, its status in the market, and of procurement sources; (2) knowledge of procurement principles and processes; and (3) knowledge of laws and regulations that govern the procurement process. In the private sector environment, the subject matter knowledge is the most highly valued of the three. Private sector procurement relies on knowledge of markets, players, risks, quality of products, and a deep understanding of the nature of the products. Relational capital â&#x20AC;&#x201C; who you know and what they know - is very important in the private sector. Business intelligence and networks are essential. Subject matter experts are more likely to drive the procurement decision. Subject matter experts are more likely to lead a procurement process with procurement personnel supporting the business lead effort. From a business perspective, this represents higher procurement performance. In the public sector environment, all three types of knowledge are valuable. Given the public policy influence and the regulatory environment, knowledge of laws and regulations carries high value. Subject matter knowledge may carry a lesser value than in the private sector. A preference for procurement-rather than subject matter expertise may produce suboptimal business decisions, and lead to lower procurement performance. Where the goal is to acquire a product or service at the lowest cost and in the most transparent

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Denise A. D. Bedford manner, the product chosen may not be best aligned with business goal. In the public sector, the procurement office is likely to take the lead, with input provided from subject matter experts. This aligns with principles and procurement activity design. It may not result in an effective procurement result from a business perspective. Exploratory Expectation: Variations in procurement performance may be attributed to greater or use of subject matter expertise and lesser procurement knowledge.

2.5 Issue 5: Use of knowledge in procurement activities For the purpose of this research we adopt Bedfordâ&#x20AC;&#x2122;s (2012) description of the scope of knowledge management practice. As McElroy (2002) suggests, aligning knowledge processes with procurement processes will lead to improved performance. Each step in the procurement life cycle can benefit from knowledge management methods, regardless of the type of organization or the economic sector. Private sector organizations have the flexibility and incentive to integrate these methods into their procurement practice as they are not bound by legal, regulatory and policy constraints. Knowledge management methods are not as widely used in public sector procurement due to preference for cost efficiency over business value. In addition, regulatory compliance processes may be resistant to new methods.

Table 1: Alignment of Knowledge Management Methods and Procurement Life Cycle Procurement Life Cycle Stage

Knowledge management factor

Research Expectation

Business Requirements Analysis

Structural capital management, organizational learning, communities of practice and collaboration, knowledge embedded business, knowledge technologies

Business goal aligned, higher quality requirements, increased business buy-in, fewer failed or siloâ&#x20AC;&#x2122;d procurement efforts

Market & Supplier Research

Organizational learning, relational capital management, communication, organizational learning

Improved understanding of markets, alignment of requirements with solutions

Procurement Strategy Development

Structural capital management, communities of practice and collaboration

Procurement strategy supports rather than drives business needs

Solicitation - Evaluation Process Management

Structural capital management, relational capital management, communities of practice and collaboration, organizational learning, knowledge technologies, knowledge assessment and evaluation

Business driven selection, extensive internal-external learning, best choice for value results, fewer failed implementations

Procurement DecisionContract Negotiation

Structural capital management, organizational communication

Higher business confidence in and satisfaction with decision

Procurement Award

Communities of practice, organizational culture and communication, knowledge embedded business

Higher probability of successful implementation

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Denise A. D. Bedford There may be dependencies between Issues 3 and 5. The ability to leverage knowledge management methods may depend the design of the procurement capability. Exploratory Expectation: Greater use of knowledge management methods may contribute to increased procurement performance.

3. Research data This exploratory research is designed to determine whether these factors can be observed to have an effect on procurement performance. We explored the role these factors might play in six use cases drawn from practical experience. While the use cases do not constitute a reliable sample from which to generalize, they provide insights into the behavior of the five issues. Three use case scenarios represent private sector organizations. Three represent public sector organizations. The use cases represent for profit, non-profit and not for profit organizations. Each has represents different business goals, procurement principles, procurement designs, and approaches to knowledge management. Each use case is summarized below. Use cases are described generically and anonymously.

3.1 Use Case 1. Non-profit large public sector organization Use Case 1 represents procurement in a large non-profit public sector organization. This organization has more than 200 years of information in archival preservation. For this organization the procurement of semantic technologies could support effective access to millions of historical records. The procurement goal was to acquire the most effective solution at the most affordable price. To achieve this goal, the agency brought in a team of information management experts and put the procurement requirements and evaluation tasks in their hands. Although this agency is in the public sector, this division clearly operates in a businessoriented manner. The procurement experts were supportive but did not run or dominate the procurement process. In addition, the business team was well trained in procurement rules and guidelines and were able to build those considerations into the lifecycle without sacrificing business knowledge or expertise. This organization made good use of knowledge management methods, including participation in and leveraging knowledge of communities of practice. The organization reviewed the technology market, consulted with communities of practice and user groups for different technologies prior to formulating requirements, and considered the knowledge architecture implications of different choices. The organizational learning was initially constrained due to heavy reliance on a published industry review of commercial products. This constraint was overcome by the use of external subject matter expertise. The fact that the business team demonstrated a strong knowledge of the market, and had strong knowledge of and respect for the procurement process helped them to gain the trust of both management and procurement. As a result, they were able to lead the procurement effort and ensure an successful result.

3.2 Use Case 2. Large non-profit public sector academic organization Case Study 2 represents a procurement action in a large non-profit academic environment. This organization sought a solution to support cross-organization digital archiving and business-oriented access to historical and current records. The organization has very well designed administrative business process. Records management for selected processes was well managed according to professional disciplines (e.g. financial data management, human resource management, etc.) but there was not a single enterprise solution supporting robust access to archived records. The organization has a tradition of independent decision making and independent and uncoordinated procurement activities. This is an enterprise level solution, but individual business managers need to buy into and adopt the solution to support their unitâ&#x20AC;&#x2122;s work. Enterprise level goals are formulated at the highest level of the administration and adopted by business units. Defining business goals bottom-up and through consensus building methods is challenging due to the organizational culture of independence. In this case, business goals for the procurement were based on the needs of the business critical units. In this case, external consultants and faculty members with relevant expertise were called in to advise the enterprise and business critical unit managers. Enterprise level requirements had to take precedence in order to satisfy the universityâ&#x20AC;&#x2122;s goals for cross-organizational support and access. The enteprirse level manager driving the procurement was well versed in procurement methods and policies and was able to ensure they were integrated into the requirements and selection process. Because business drove the process, an effective decision was made. It was very important, though, to bring in external expertise on

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Denise A. D. Bedford the state of the market. The implementation was effective in meeting the enterprise goals even if it might not meet the needs of all business units.

3.3 Use Case 3. For-profit small private organization Use Case 3 represents a complex but low budget procurement action in a medium sized not for profit organization that is operating within increasing budget constraints. The organization’s primary stakeholders are medical professionals and secondary stakeholders are the general public. The procurement action was undertaken by one small unit whose primary role was to manage the organization’s information. This use case focuses improving access to a collection of historical publications. The business unit was responsible for setting business goals. Procurement principles were established at the organization level. However, the overall low budget for the project supported a simple procurement process. This use case was interesting because it involved multiple in depth consultations with academic experts, and a strong working relationship with a selected vendor. The internal subject matter expertise was pertained to the content of the historical collection, not to procurement. There was a broad opportunity and strong incentives to leverage knowledge management methods. The business team solicited subject matter expertise throughout the project. A small private company can ill afford to make a bad decision. Resources are much more scarce in this size of an organization than in larger organizations. There is a smaller baseline against which to recover from a bad decision. The incentive to go with a “safe” procurement decision is strong. This organization crafted a procurement approach to achieve an affordable and effective procurement decision. The business unit drove the procurement decision, though the organization managed the procurement process. The process was ideally suited to the context because the “seller” and the “buyer” were able to work closely to define a solution that met the buyer’s expectations. The result has been successful on several levels. Not only did the deliverable meet expectations, but both parties were able to learn through the process. Both the buyer and the seller expanded their capacity to work in this area. The seller has had an opportunity to expand the performance of their products. The buyer has had an opportunity to share experience with other small and medium-sized organizations. In this case it was very important for the business units to be in control of the procurement decision, and to have the flexibility to refine requirements as the project moved forward.

3.4

Use Case 4. Not for Profit Public Sector Organization

Use case 4 represents a formal procurement effort to acquire semantic technologies to support the consistent generation of metadata across the organization. For this organization transparency and fair process are critical to maintaining its international reputation. While an overall matrix of weighted factors determined the final selection, financial considerations were heavily weighted. This use case represents a traditional public sector procurement design and illustrates traditional procurement roles. The organization had internal subject matter experts who defined the business requirements and assembled the team of stakeholders who would evaluate proposals and make a recommendation to the procurement office. A bottom-up business requirement and recommendation process worked well for both selection and for implementation. Had there not been subject matter experts involved in defining the business requirements and had those requirements not reflected knowledge of the market, there would have been a different result. Because the process allowed stakeholders to be involved in the decision making process, there was widespread adoption of the solution in the implementation phase. Because there were internal experts in semantic technologies, there was strong knowledge of the market. The procurement experts managed all communication with external stakeholders and providers. Ultimately, procurement made the procurement decision but it was in line with the recommendations of the business units. In the end, the selection supported business goals because the subject matter experts defined the requirements. In the end, the implementation was successful and there was broad adoption of the solution. Because the procurement process is tightly scripted, as is the case in most public sector organizations, it was not possible to leverage many knowledge management methods.

3.4 Use Case 5. Large global for-profit private sector organization Use Case 5 represents a large, global, for-profit organization. This organization competes in a global product market, provides products and service around the world, has sales offices in most countries. Operates in multiple legal and commercial jurisdictions. Its primary business goals are profit, market share, product quality

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Denise A. D. Bedford and assurance. The organization is interested in achieving best value for the dollar. For this organization, the procurement of semantic technologies would support enterprise level access to content stored in multiple repositories. Relevant subject matter expertise includes several hard and applied scientific disciplines. While there is extensive expertise in the core business areas, internal subject matter expertise on semantic methods and technologies is scarce. While procurement may be driven by business units and subject matter experts, the organization does not have the needed expertise to make an effective decision. In this case, the organization wisely leveraged knowledge management methods to obtain external subject matter expertise. Extensive internal consultations were conducted to understand the semantic needs and practices of the critical business units. External consultations drew in a broad set of viewpoints, including vendors and current users of the technologies. For this procurement to be successful, though, it must be usable in several business contexts. The procurement process must allow for extensive stakeholder involvement and signoff, and a learning context similar to that described in Use Case 2.

3.5 Use Case 6. Quasi- for and not for profit global private sector organization This organization is a not for profit organization which serves the private sector. To better support its private sector stakeholders, this organization often adopts private sector methods of working. While this is a not-forprofit organization, profit or at least lowest cost solution is an important business goal. The organization also values its networks and maintains its knowledge of the market through its network contacts. This may or may not provide an accurate picture of the market. If there is no validation of network-acquired product information, the selection may not be optimal. The organization has a low tolerance for solutions that take more than six months to implement, and prefers solutions that are sufficient rather than robust. The business goals by definition will result in a different kind of decision than we have seen in the other five use cases. While a procurement team is in place, business units drive the procurement process and make the procurement decision. Given the time-sensitiTTvity of business decisions, broad input and consultation are generally not sought. Knowledge management methods are not typically leveraged to improve the procurement decision. This organization considered semantic technologies as a quick solution for cross enterprise access to information. In this case the business experts driving the program did not prepare a robust set of business requirements to drive the procurement process. Because the procurement process was driven by business managers, the procurement decision was ineffective. In the end, the solution implemented was not successful. In the end the use of financial resources did not support business goals. In this case, procurement was a weak function and the business unit did not fill the gap.

4. Influence of issues on procurement results Keeping in mind that this is exploratory work intended to set a foundation for a larger research effort, we offer observations about the influence of the five factors on procurement results. A summary of the role of the five factors in each use case is provided in Tables 2a-2b. Four of the six use case scenarios resulted in effective procurements and effective choices. What these use case scenarios had in common are the alignment of procurement capabilities with business goals (Issue 2), design of procurement capabilities to support business goals (Issue 3), and the dominant use and reliance on business-subject matter expertise (Issue 4).

Table 2a: Observations of role of Issues by Use Case No.

Sector

Issue 1

Issue 2

Issue 3

1

Public Sector

Department level

No explicit procurement principles

Segregated from business units

2

Public Sector

No alignment

Enterprise level principles; not tied to goals

No standard design, integrated into business units

3

Private Sector

Company level

Fully aligned with business goals

Tasked to one person, aligned with goals and

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Denise A. D. Bedford No.

Sector

Issue 1

Issue 2

Issue 3 principles

4

Public Sector

Company and Division Level

Enterprise level principles not tied to goals

Strictly defined at enterprise level, procurement lead activities at certain dollar level

5

Private Sector

Company and Division Level

Fully aligned with business goals

Driven by business needs integrated with business unit level

6

Private Sector

Organization and Division Level

Fully aligned with business goals

Driven by business needs integrated with business unit level

Table 2b: Observations of role of issues by Use Case No.

Issue 4

Issue 5

Result

1

Procurement knowledge prevails; SME is solicited

Some use in later stages of life cycle

Effective and efficient procurement, effective choice

2

SME knowledge drives but is internal to organization

Some use in later stages of life cycle

Effective procurement, effective choice

3

Pulled through external network, focused on subject matter expertise

Extensive use throughout the life cycle

Effective procurement, effective choice

4

Subject Matter Expertise leveraged; Final decision made by procurement

Little use throughout the procurement process

Effective procurement, ineffective

5

Subject Matter Expertise leveraged; External expertise leveraged

Extensive use throughout the lifecycle

Effective procurement, Effective choice

6

Subject Matter Expertise predominates; External expertise heavily used

Moderate use throughout the life cycle

Ineffective procurement, ineffective choice

Issue 1. Alignment with Business Goals Business goals are critical for a successful procurement result. We can only judge the goodness of a procurement decision by how well it aligns with an organization’s business goals. Our experience in this limited set of use cases suggests that where the procurement is not aligned – formally or informally – with business goals, there is a lower probability of success. The base of use cases must be expanded to

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Denise A. D. Bedford include a broader range of products and services, and greater variation in the business areas supported by the procurements. Issue 2: Procurement Principles. Where principles are grounded in regulatory and legal issues, there is not strong alignment with business goals. While it is important to align with regulatory and legal issues in the public sector organization, these do not have to be driving forces. Every public sector organization has a business mission which should be reflected in its procurement principles. Our observation from the limited number of case studies is that public policy priorities have constrained public sector procurement principles. This is a way of working that has developed in response to public policy pressures. It is not an absolute constraint for public sector procurement. It is possible to balance public sector business goals and procurement principles. This alignment sets the stage for procurement designs, use of knowledge and knowledge management methods. Expanded future research must also include greater variation in size of organizations and value of the procurement decision. Issue 3: Procurement Capability Design. Where procurement principles are dominant and outweigh business goals, there may be a tendency to segregated procurement activities, and to routinize the process. Flexibility st of process design and location supports the 21 century business need for agility and results in positive outcomes. Embedding procurement in business operations seems to align with positive outcomes. Where procurement is readily and easily available to business units, business can drive the design and placement of procurement capabilities. Issue 4: Use of Knowledge. The role of subject matter knowledge appears to be very important to achieving positive procurement outcomes. When subject matter expertise is not available internal to the organization, the organization should make every effort to acquire it externally. Externally sought advice should be solicited within the context of business goals, not simply knowledge of markets. While it is important to ensure that procurement knowledge is accessible to every procurement effort, this does not mean that procurement officials must manage or control the effort. This also suggests an opportunity to rethink how we package and make procurement knowledge available. Procurement knowledge may be transformed into knowledge bases through semantic analysis and supported by role-based and problem-oriented searching. Procurement managers must respect the knowledge of subject matter experts. Issue 5. Use of Knowledge Management Methods. This was a very limited set of use cases from which generalizations cannot be made. And, there are inherent restrictions to how knowledge management methods may be used in the formal procurement portion of the process. However, we can draw observations from the use cases which suggests that where knowledge management methods are built into the requirements portion of the process, a stronger and more effective choice will be made.

5. Research results and observations The results, though preliminary and exploratory, do not support the perception that private procurement, by definition, performs at a higher level than does public sector procurement. The results would tend to suggest that it is not the private or public sector nature of organizations, nor is it the for-, not-for or non-profit status that leads to successful procurement. Rather, the results suggest that procurement performance will be greater where Issues 2, 3, ad 4 are observed in an organization. It appears to be the case that these factors are more often observed in private than in public sector organizations. Three of the private sector organizations and one public sector organization which exhibited these characteristics reported positive procurement outcomes. Two public sector organizations did not demonstrate these characteristics and did not achieve an effective outcome. Observations for these three factors are summarized below. In this limited research there was not sufficient evidence of the use of knowledge management methods within the procurement life cycle to draw any conclusions about their effect on procurement performance. However, we have learned enough about the interplay of issues to begin an open conversation with procurement actors across the world. The results of this exploratory research are a broad based survey on the role of these five issues in successful procurements.

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Denise A. D. Bedford Further investigation into each of these three issues is needed to develop a deeper understanding of their role in achieving effective and efficient procurement results. The next step in this research effort will be to extend the research to a larger set of organizations to expand the representation of types of organizations, to extend the case studies to represent a broader range of procurement activities, and to deepen the review of knowledge management methods in each case. We believe that further research based on these exploratory observations may psuggest best practice approaches for procurement design.

References Allal-Cherif, O. and Maira, S. (2011). “Collaboration as an Anti-Crisis Solution: the Role of the Procurement Function,” International Journal of Physical Distribution & Logistics Management Vol. 41, No. 9, 860-877. Amaral, M., Saussier, S. and Yvrande-Billon, A. (2009). “Auction Procedures and Competition in Public Services: The Case of Urban Public Transport in France and London,” Utilities Policy Vol. 17, 166-175. Andriessen, D. (2005). “Making Profit from Intellectual Capital,” Intellectual Capital Conference, Jakarta, March 8, 2005. Bovis, C. (2010). “Public-Private Partnerships in the 21st Century,” ERA Forum Vol. 11, 379-398. Brandmeier, R.A. and Rupp, F. (2010). “Benchmarking Procurement Functions: Causes for Superior Performance,” Benchmarking: An International Journal Vol. 17, No. 1, 5-26. Brandon-Jones, A., Ramsay, J., and Wagner, B. (2010). “Trading Interactions: Supplier Empathy, Consensus and Bias,” International Journal of Operations & Production Management Vol. 30, No. 5, 453-487. Drobrzykowski, D. D., Hong, P.C. and Park, J.S. (2012). “Building procurement capability for firm performance:a servicedominant logic view,” Benchmarking: An International Journal Vol. 19, No. 4/5, 567-584. Frodell, M. (2010). “Criteria for Achieving Efficient Contractor-Supplier Relations,” Engineering, Construction and Architectural Management Vol. 18, No.4, 381-393. Gunther, E., and Scheibe, L. (2006). “The Hurdle Analysis. A Self-evaluation Tool for Municipalities to Identify, Analyse and Overcome Hurdles to Green Procurement,” Corporate Social Responsibility and Environmental Management Vol. 13, 61-77. Guth, S. (2010). “Implementing Best Practices: The Procurement Maturity Model,” 96th ISM Annual International Supply Management Conference, April 2010. (Accessed online at: http://www.ism.ws/files/Pubs/Proceedings/2010ProcCHGuth.pdf on April 1, 2013). MacKenzie, N. and Culliford, S. (2011). “What Now for Public Sector Procurement?” Business Insights (Accessed online at: http://www.uk.atoscosulting.com/en- uk/business_insights/points_of_view/what_now_for public_sector_ procurement/default.htm on April 1, 2013). McElroy, M. (2002). The New Knowledge Management. Routledge, 2002. Nakata, C. and Im, S. (2010). “Spurring Cross-Functional Integration for Higher New Product Performance: A Group Effectiveness Perspective,” Journal of Product Innovation Management Vol. 27, 554-571. Ntayi, J. M. (2012). “Emotional Outcomes of Ugandan SME Buyer-Supplier Contractual Conflicts,” International Journal of Social Economics Vol. 39, No. ½, 125-141. Ordanini, A. and Rubera, G. (2008). “Strategic Capabilities and Internet Resources in Procurement: A Resource-Based View of B-to-B Buying Process,” International Journal of Operations & Production Management Vol. 28, No. 1, 27-52. Plane, C.V. and Green, A.N. (2011). “Buyer-Supplier Collaboration: The Aim of FM Procurement?” Facilities Vol. 30, No. ¾, 152-163. Saini, A. (2010). “Purchasing Ethics and Inter-Organizational Buyer-Sup;lier Relational Determinants: A Conceptual Framework,” Journal of Business Ethics Vol. 95, 439-455. Smith, G.C. (2011). “Leveraging Private Sector Practices in the Public Sector,” Supply Chain Quarterly 3 2011. (Accessed online at: http:www.supplychinquarterly.com/topics/procurement/201103Public/ on April 1, 2013) Tadelis, S. (2012). “Public Procurement Design: Lessons from the Private Sector,” International Journal of industrial Organization Vol. 30, 297-302. Teng, W. and Liao, T.-T. (2011). “Exploration of Market Competition in Governmental Procurement on the Basis of Supplier Segments,” Systems Engineering Procedia Vol. 2, 406-411. Thompson, M. (1996). ”Effective purchasing strategy: the Untapped Source of Competitiveness,” Supply Chain Management Vol. 1, No. 3, 6-8. Webb, J. (2010). “Private Sector Procurement Expertise Can Lower Government Spend,” (Accessed online at: http://www.procurement-iu.com/blog/2010/7/private_sector_procurement_expertise_can _lower_government_spend on April 1, 2013).

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Topology of Knowledge and Information in the Transportation Sector Denise A. D. Bedford1 and Lisa Loyo2 1 Goodyear Professor of Knowledge Management, Kent State University, Kent Ohio 2 Manager, Information Services, Transportation Research Board, National Academy of Sciences, Washington DC Dbedfor3@kent.edu lloyo@nas.edu

Abstract: Transportation is an important economic sector, a professional area of practice and a robust academic discipline. The knowledge and information that is produced and consumed in transportation comes from research, from development, teaching and learning, and everyday practice. Transportation is also a multifaceted discipline â&#x20AC;&#x201C; drawing from engineering, chemistry, physics, materials science, computer science, finance, policy development, project management, etc. Transportation has legislative, regulatory and policy implications at the international, national, state and local level. The transportation information environment is complex, reflecting these facets, levels and perspectives. Managing, finding, accessing and preserving transportation information is a challenge. This research explores the full landscape of transportation information, including informal primary, primary, secondary and tertiary information. This research leverages a methodology developed for the Library of Congress to produce a richly populated topology of knowledge and information produced and consumed in the transport discipline. The topology provides a comprehensive framework that can be used by knowledge and information managers working in transport for strategic planning, and for the development of tools to support multifaceted access to knowledge and information in the field. Keywords: Information topologies; transportation information; information types; information scatter; information organization; knowledge management

1. Research challenge and goal Transportation is a complex discipline. The discipline is broad in its coverage of modes of transportation, including air, rail, road, water, cable, and space. It has a broad scope in terms of the aspects in which it interacts with society, including (1) transportation policy analysis, formulation and evaluation; (2) transportation planning; (3) interaction with the political, socioeconomic and physical environment; (4) transportation infrastructure finance, ownership and access; (5) design, management and evaluation of transportation systems; (6) constituencies and stakeholders; and (7) regulatory systems). The project life cycle introduces new stakeholders, new roles and new types of information that are not traditionally managed by libraries and information centers. The international, national, regional, state and local aspect of its implementation also contributes to its broad scope. The discipline is deep in terms of the range of activities performed by transportation stakeholders. Consider, for example, the tasks involved in two important transportation life cycles â&#x20AC;&#x201C; the transportation research life cycle, and the transportation project life cycle. The simple representation of the two life cycles (Figure 1) illustrates the richness of the transportation information environment. Research, project planning, construction, maintenance and operations give rise to many roles, many different areas of expertise, and many types of impacts. The transportation project life cycle has a long path from ideation to research to implementation, and ultimately to impacts on peoplesâ&#x20AC;&#x2122; everyday lives. There are many stakeholders involved in both of these life cycles. The environment in which transportation information is produced, consumed and managed is complex. Managing transportation information is not a trivial task, though (Baldwin 2007) (Borin and Hua 2008) (Cambridge Systematics 2013) (Corbin 2007) (CTC & Associates 2006) (Dresley 1998) (Evans 2007) (Harder and Tucker 2003) (Ingbar 2010) (Lefchik Beach and Holt 2007) (MacDonald 2007) (Oman 2007) (Osif 2000). st Transportation information professionals face a new challenge in the 21 century. The challenge in 2013 to define a methodology that leverages but adapts the traditional information management methods to apply to st information needs in the 21 century. Technology now makes it possible for everyone working in the discipline of transportation to create, find, use and manage data and information before it reaches the traditional primary published state. Informal primary information represents all of the original ideas, data, source th information that a stakeholder might use to do their work. In the 20 century, this type of information would not have been in the purview of the professional information management professional. Informal primary information in the discipline of transportation might include data collected by the geologist evaluating a site,

35


Denise A. D. Bedford and Lisa Loyo crash site information captured by first responders or law enforcement, traffic engineer, the coast guard personnel patrolling shorelines, the railroad engineer collecting data about track quality, traffic flow and congestion data recorded by traffic controller, or air traffic control and monitoring data. What was traditionally considered purely informal information may now be accessible to peers, research or work teams, or even publicly available on the Web. Who manages this traditionally informal information is changing. The owners and creators of informal primary information are now de facto information managers. Before transportation information professionals can take up this new challenge, though, they need to have a “big picture” of today’s transportation information landscape. This research paper takes up that challenge. Transportation Research Life Cycle

Transportation Project Life Cycle

Figure 1: Two Life Cycles of Import to Transportation

36


Denise A. D. Bedford and Lisa Loyo

2. Research methodology This research builds leverages innovative work completed under contract for the Library of Congress (Carroll Bedford Jones 1991). The intent of that innovative work was to lay the foundation for services that might be provided by a national digital library that would support undergraduate science, technology, mathematics and engineering (NENGIS) (National Research Council 1998). It was important to understand the information landscape in order to develop a picture of these services. Like any library, the proposal began with collection development and management policies. An extensive search was conducted for a model, a methodology and/or a well defined landscape of the field of science, technology, engineering and mathematics information types and sources. No existing models, methods or landscapes were found. To fill this need, a comprehensive review of the formal and informal information sources serving the field, a methodology was developed and validated within the scientific, engineering, and information science communities. A five-step methodology was proposed based on well-established collection development policy methods used in academic and research libraries (Baughman 1977) (Baldwin 1973) (Ferguson Grant and Rutstein 1988) (Munroe 2004) (White 2008). It was important to begin with a methodology that would align with the Library of Congress’ approach to collection development and management. The five steps in the methodology included: (1) identification of stakeholders and roles that involved the production or consumption of information; (2) high level framework for categorizing information types; (3) defining breakout categories of information by types of systems that may support them; (4) elaboration of brand name types and sources for each category; and (5) validation of the topology with stakeholders; and (5) extensive validation of the structure through consultation with stakeholders. Step 1. Collection development methods begin with a description of stakeholders and their information needs. The original research team conducted extensive interviews with scientists and engineers at the national level to develop the stakeholder framework (Step 1). The interviews provided valuable input to the coverage and structure of the information topology. The new methodology was an extension of the tradition in that it focused on what stakeholders produced as well as what they consumed. It also considered how and where stakeholders stored and accessed the information they produced. This extension leads to the creation of a new layer in the traditional model. Step 2. It was apparent to the research team and through interviews as early as 1991 that it would be necessary to expand the traditional library collection development model’s characterization of three layers of st information (Figure 2 – Traditional Model) to include a fourth layer - informal primary types (Figure 2 – 21 Century Model). Primary information includes original materials – materials that contain raw, original or unevaluated information. Primary sources have not been formally or officially filtered through interpretation, condensation, or evaluation by a second party. Primary information traditionally has included journal articles, books, reports, patents, theses, diaries, letter, photographs, and so on. Secondary information is information about primary information which has been modified, extracted, or rearranged for a particular audience or purpose. Secondary information sources might include biographies, histories, reviews, textbooks, indexes or bibliographies. Tertiary information is a distillation or collection of information, for example encyclopedias, almanacs, guidebooks, handbooks, abstracting and indexing services or sources. This was an important discovery in 1991 for information professionals who were trying to adapt collection development policies to the new environment. However, this expansion introduced many new collection and management challenges. In an invited paper Lynch (1998) identifies some of these challenges, including ownership, quality, discoverability, access and persistence. The observation continues to be important today, and particularly so for the field of transportation. Step 3. The Library of Congress project team identified 25 categories of information sources to support the lower level framework. These categories are identified in Tables 1 through 4.

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Denise A. D. Bedford and Lisa Loyo st

Traditional Model

21 Century Model

Figure 2: Models of Information Types Table 1: Informal Primary - Functional Category Breakdown and Descriptions Functional Category R&D Informal Records Research Data Policy Decision Systems Authoring & Composition

Description Personal records systems, Interpersonal communication systems, Group communication systems, Administrative systems, Informational announcement systems. Experimental data acquisitions systems, Observational data acquisition systems, Computation science results, Research planning Policy formulation, Policy discussion, Policy analysis Data organization systems, Manuscript development systems, selection and review systems

Table 2: Formal Primary - Functional Category Breakdown and Descriptions Functional Category Preliminary Communication Publishing Group Communication R&D Management Statistical Information Stakeholder & Market Information Product Information Policy & Legal Information Infrastructure Information

Description Preliminary formal reporting, Preliminary formal discussion Serials, Dissertations and theses, Research publications, Monographic publications, Conferences and meetings, Workshop and seminars, Trade shows and exhibits, Partnership programs Research proposals, Ongoing research and contracts information, Research financial information, Organizational research information, Proprietary information systems, Organizational records systems Demographic information, Resource data Survey research, Communications research, Professional statistics Manufacturer information, Production and maintenance information, Engineering and process design information, Engineer and process control information, Engineering and process data Legislative and policy information, regulatory information, Monitoring and compliance information Infrastructure status and condition information, Infrastructure planning information, Infrastructure finance information, Infrastructure economic models and information, Infrastructure communications, Infrastructure reports,

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Denise A. D. Bedford and Lisa Loyo Intellectual Property Information Compatibility Information Education & Training Information

Patent information, Trademarks, Copyright applications, Copyright registries, Domestic patents, Foreign patents Proprietary standards, De facto standards, Industry standards, National standards, International standards, Product specifications, Construction specifications Educational materials, Lectures, Education awareness information

Table 3: Formal Second - Functional Category Breakdown and Descriptions Compilation Systems Surrogation Systems Analysis & Evaluation Delivery Systems Technology Transfer Secondary Market Research Customized Information Systems

Biographical information, Historical information, Ready reference, Directories, Inventories, Formal instructional information, Bibliographic systems, Scientific metadata, Library catalogs, Search systems, Vocabulary systems, Knowledge organization systems Peer review information, Evaluated scientific data, Evaluative communication systems, Synopsis and reporting information Online bookstores, Interlibrary lending/borrowing systems, Information brokers and subscription services Technology descriptions, Transfer experiences, Transfer investigations, Translation information Market research, Market surveys, Reference centers, Search strategies, Canned Queries, Reference Q&A, FAQs, Executive information, Corporate management information

Table 4: Formal Tertiary - Functional Category Breakdown and Descriptions Secondary Compilation Sources Secondary Surrogation Systems Archiving Systems

Current awareness information, Update services, SDI services Information referral, Management information systems Document preservation, Records management, Artifact preservation

Step 4. The research team then populated the framework with references to individual and brand name sources for scientific and engineering disciplines generally. Step 5. Finally, the methodology and the topology were further validated through focus groups held at the National Institutes of Standards and Technology in 1991. In 1997, the methodology was put through a further test at the University of Southern California where it anchored initial brainstorming for a digital science and engineering library.

3. Research results In this paper, the Kent State University and National Academy of Sciences collaborative research team reports on the use of the Library of Congress methodology to develop an information topology for the field of transportation. The research is now in Step 5 – the validation of the framework and topology an open national and international survey.

3.1 Step 1. Identification of transportation information stakeholders An important starting point for the research was understanding the discipline from a stakeholder perspective. The universe of stakeholders helped us to see the full landscape of information sources, products and services. We began with two lists. The first list was a classified list, arranged by the nature of the user’s relationship to transportation (Table 5), including individuals who: Table 5: Transportation Stakeholder Roles Stakeholder Relationship to Transportation Do transportation work Support those who do transportation work Develop transportation policy, finance and planning

Stakeholder Example Train conductors, Air traffic controllers, Port authority officials, Aircraft maintenance teams, Freight engineers, Pilots, Law enforcement… Local government officials, Librarians, Machinery manufacturers, Geologists, Chemists, First responders… Legislators, Local government officials, Policy analysts, Infrastructure economists, Transport economists, Infrastructure banks, Private financial institutions, City planners, Regional economic advisers….

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Denise A. D. Bedford and Lisa Loyo Stakeholder Relationship to Transportation Apply transportation to everyday business and living Teach and learn transportation Study transportation science and transportation policy

Stakeholder Example Rail passengers, Automobile drivers, Truckers, Cyclists, Pedestrians, Flight attendants… Professors, Teachers, Research institutes, Private corporate research, Professional associations, Consultants, Students…. Professional associations, Students, researchers, Policy analysts, Legislators, Regulatory agencies, Inspectors

The second list considered the level of stakeholder scientific or technical expertise. For example, an aeronautical engineer has greater expertise in aeronautics than does a high school science teacher or the general public deciding whether to fly or take a train from New York to Los Angeles. This second perspective helped us understand the different levels of synthesis and interpretation transportation information might take on, and the systems through which it might need to be filtered and accessed. Both of these lists were used to identify types of information that would be produced or consumed in the normal course of a stakeholder’s day.

3.2 Step 2. Build out a high level framework for the topology st

The research team leveraged the expanded model (Figure 2 – 21 Century Model) to include a fourth information type to represent the extended information environment of transportation stakeholders. The extension of the traditional library collection development framework provided a more accurate representation of the types of transportation information produced and consumed by stakeholders today. It also provides a more accurate representation of the degree of originality of transportation information, and of the level of expertise required of users of transportation information.

3.3 Step 3. Define low level category structure The next step in the research process involved identifying the categories of information within each of the four layers. The original structure proposed to the Library of Congress and NENGIS included twenty-five categories organized by types of information systems. The original model was tested for use in the transportation discipline through a rigorous review of the transportation literature, interviews with information professionals, through a rigorous review of sources referenced in transportation research, to transportation policy documents, and everyday references to transportation information.

Figure 4: Transportation Information and Knowledge Topology Functional Category Breakdown The categories were cross-checked against the stakeholder lists (Table 1). . The resulting topology for the transportation discipline validated the original twenty-five categories in the Library of Congress foundation, but added one new category – Infrastructure Information. This new category was added to the Secondary

40


Denise A. D. Bedford and Lisa Loyo Information layer. The research team believes that while the category name may vary, the new category will be relevant for all other scientific and technical disciplines. In addition to testing and adapting the categories, the research team expanded the scope of the original descriptions. For example, Commercial Product Information was expanded to include documentation for, maintenance reports and parts information for all forms of transportation machinery (Carroll Bedford and Jones 1991). As Figure 4 suggests, twelve categories – a majority of categories - aligned with Formal Primary Information. Seven of the functional categories represent Secondary Information. Tertiary information has the fewest categories – three. While research to date indicates that Informal Primary includes only four categories, we expect further breakdowns as we complete the validation in Step 5.

3.4 Step 4. Mapping transportation information to the topology The final working version of an information topology should illustrate specific information sources, products and services in each functional category. Ideally, the topology produces an information inventory that information management professionals can use to develop strategic plans for managing transportation information. The research team undertook an extensive review of transportation literature to validate the categories and to begin to build out the full topology. The literature review surfaced 518 examples. The research team was able to map each type to a class without confounding. Table 6 illustrates the distribution of examples across the four high level classes. Functional Category Informal Primary Formal Primary Formal Secondary Formal Tertiary Total Examples

Number of Examples 105 297 80 36 518

Table 6: Distribution of Transportation Information Types Discovered in the Literature Review Examples of formal primary information sources predominated in the transportation research literature. Informal Primary sources were referenced more frequently than either formal secondary or formal tertiary. The researchers expect that the results of the literature review will reflect the use patterns of individual respondents in the open survey. The final survey results will be presented as both a visual representation of the topology and a classified inventory.

3.5 Step 5. Validation and elaboration of the topology with transportation stakeholders While the proposed topology is grounded on a strong precedent, it is important to validate the model with stakeholders from the transportation discipline. To this end, the research team has developed an open survey instrument (http://kentstate.qualtrics.com/SE/?SID=SV_739VBN3O1eCDCAt ). The survey follows the structure of the topology. The survey offers respondents the opportunity to describe the kinds of information they use, the frequency with which they use them, and to provide specific examples. The survey is on-going. The results will be used to further populate the Transportation Information and Knowledge Topology. The final version of the topology will be presented at a future Transportation Research Board Annual Meeting.

4. Findings and observations The exploratory research produced a working framework and a graphical representation of an information topology for the transportation discipline. The topology is comprised of four layers, representing (1) Informal Primary Information; (2) Formal Primary Information; (3) Secondary Information; and (4) Tertiary Information. Twenty-six functional categories were identified across the four layers. The categories were useful for organizing individual and name brand information sources, products and services. The methodology that was developed by Carroll Bedford and Jones in 1992 proved to be robust. This is only the second formal application of the conceptual methodology and framework. The research team believes that the application of the framework and methodology to the transportation discipline provided another rigorous test. The researchers noted that the first step – identification of stakeholders – continues to be a critical step in defining the scope of the topology. The research team plans to test the framework against other science and technology disciplines in the future.

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Denise A. D. Bedford and Lisa Loyo The research team has begun an open and public survey-based validation of results with stakeholders from the transportation discipline. We expect the survey results will provide an extended inventory of specific sources, products and services. We expect the extended inventory to uncover examples that will help us to further elaborate the categories aligned with the Informal Primary layer. One challenge that remains is to provide an easily navigable view of the topology when it is fully populated with individual sources and brand name systems. A fully populated topology includes thousands of references. The current representation of the topology is a wall-sized poster. A digital map of the survey-validated results will be displayed at the ECKM 2013 conference. We believe that the resulting topology provides a comprehensive view of the transportation information landscape. The goal of the research was to develop an information topology that could be used by transportation information professionals to expand the application of information management practices. We believe that the topology will serve this purpose. The full graphic presentation enables an information professional to identify functional categories of value to his/her stakeholders, to define policies and methods that are suited to his/her stakeholders’ specific sources, products and services. In the future, we believe that transportation information professionals will use the topology to scope the services that might be supported by transportation libraries. Our hope is that the topology will help transportation information professionals to meet the challenge. Ultimately, we hope the topology will enable stakeholders in the discipline to develop a common understanding and mental model of the information landscape.

References Baldwin, C. A. (1973). Library use by civil engineers at the Minnesota department of highways. University of Minnesota, 1973. Baldwin, J. C. (2007). “Making Information Accessible: Beyond the Internet" TRB 86th Annual Meeting, January 22, 2007. Retrieved online on March 31, 2013 at: http://www.dot.state.mn.us/library/PDF/TRB-2007-Baldwin-Final.pdf Bullis, D. R. and Smith, L. (1975). Looking back, moving forward in the digital age: a review of the collection management and development literature, 2004-8. Library Resources and Technical Services Vol. 55, No. 4, 205-220). Carroll, B. J., Bedford, D. A. D., and Jones, K. A. (1992). Interim Report. Identification & Graphical Representation of Major S&T Information Systems Project. Science and Technology Information Special Project Team Briefing to Dr. William W. Ellis, Associate Librarian for Science and Technology, Library of Congress. March 27. 1992. Cambridge Systematics (2013). Transportation Research Board. Improving Management of Transportation Information. Draft Interim Report. Case Studies and Examples. NCHRP 20-90. Committee for a Future Strategy for Transportation Information Management Transportation Research Board (2006). st Transportation Knowledge Networks: A Management Strategy for the 21 Century. Special Report 284. National Academies of Science. Corbin, J. M. (2007). “Information Flow: Key to Traffic Engineering”. TRB 86th Annual Meeting, January 22, 2007. Retrieved online on March 31, 2013 at: http://www.dot.state.mn.us/library/PPT/Corbin-TRB 2007.ppt CTC & Associates LLC (2005). Transportation Information Management. Transportation Synthesis Report. Wisconsin Department of Transportation, 2005. Dresley, S. C. (1998). Value of Information and Information Services. Publication No. FHWA-SA-99-038. Prepared for the Office of Technology Applications, Federal Highway Administration, 1998. Evans, R. (2007). Beyond Google – Finding the Transportation Information You Need. Presentation for the DRI Research Connections Series. September 26, 2007. Harder, B.T., and Tucker, S. L. (2003). Scoping Study for a National Strategic Plan for Transportation Information Management. Final Report. Project No. 20-7/Task 142. National Cooperative Highway Research Program, Transportation Research Board, National Research Council, 2003. Ingbar, E.E. (2010). A Case Study of Enterprise Historic Resources Information Management in Large Transportation Agencies MTI Report 09-06. Mineta Transportation Institute, College of Business San José State University, 2010. Lefchik, T., Beach, K., and Holt, M. (2007). Development of a National Geotechnical Data Management System for Transportation Applications”. TRB 86th Annual Meeting, Monday, January 22, 2007. Retrieved online on March 31, 2013 at: http://www.diggsml.com/system/files/TEL+GeoCongress+2006+GMS+v1.pdf Lynch, C. (1998). Some Technical and Economic Issues in the Design of a National Library for Undergraduate Science, Mathematics, pp. 90-94 in Developing a Digital National Library for Undergraduate Science, Mathematics, Engineering and Technology Education. Report of a Workshop. Retrieved online on May 15, 2013 at: http://www.nap.edu/catalog.php?record_id=5952

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Denise A. D. Bedford and Lisa Loyo th

MacDonald, D. B. (2007). Improving Information Accessibility TRB 86 Annual Meeting, January 22, 2007. Retrieved online on March 31, 2013 at: http://www.wsdot.wa.gov/NR/rdonlyres/78501AAA-8851-41C9-8F19074A04B428E2/0/KnowledgeManagement.pdf Munroe, M. and Ver Steeg, J.E. (2004). The decision-making process in Conspectus evaluation of collections: the quest for certainty. Library Quarterly Vol. 74 No. 2, 181-205. National Research Council (1998). Developing a Digital National Library for Undergraduate Science, Mathematics, Engineering, and, Technology Education. Report of a Workshop. National Academy Press, Washington, D. C. 1998. Oman, L. (2007). "Improving Access to Information Resources at Washington State DOT" TRB 86th Annual Meeting, January 22, 200 Retrieved online on March 31, 2013 at http://www.dot.state.mn.us/library/PPT/oman-informationresources.ppt Osif, B. A. (2000). Transportation Information: a Review of Grey Literature by Format, Language and Availabilityâ&#x20AC;?, International Journal on Grey Literature Vol. 1 Issue: 1, pp.12 â&#x20AC;&#x201C; 17. White, H. D. (2008). Better than brief tests: coverage power tests of collection strength. College & Research Libraries Vol. 69, No. 2, 155-174.

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Collaborative Solutions Quick&Clean: The SFM Method   Marco Bettoni, Willi Bernhard and Nicole Bittel  Swiss Distance University of Applied Sciences (FFHS), Brig, Switzerland  marco.bettoni@weknow.ch   willi.bernhard@ffhs.ch  nicole.bittel@ffhs.ch     Abstract: The SFM method (Solution Finder Model) is a structured, formal procedure to be applied during interactions in  small, medium or large multidisciplinary groups where there is a need to collaboratively develop shared solutions of a high  quality  standard  (“clean”)  and  in  a short  period  of  time  (“quick”).  The  SFM  was  developed  within  the  context  of  various  successful  knowledge  management  projects,  where  different  kinds  of  knowledge‐intensive  problems  or  tasks  (such  as  specification,  conception,  design  etc.)  had  to  be  solved  collaboratively  by  a  multidisciplinary  group.  The  first  part  of  the  paper  will  explain  the  SFM  by  describing  its  theoretical  foundations,  terminology,  components  and  principles,  the  procedure for applying it and examples of practical application.  The second part will then describe 3 cases in which the  SFM  has  been  applied  for  developing  a  solution  to  3  kinds  of  knowledge‐intensive  problems:  design,  specification  and  conception. The first example features the collaborative design of a Community of Practice by potential members of the  planned community who interact in the context of a series of design workshops.  The second example includes employees  from all over the company who interact in terms of the specification of ideas within the context of a collaborative online  ideas  management  system.  Last  but  not  least,  the  third  example  is  the  conception  of  a  didactical  model  for  analysing  logfiles in learning management systems. At this point, the reader will have enough information to apply the method to  his/  her  own  cases.  In  the  conclusion,  we  will  briefly  look  ahead  to  further  planned  research  covering  theoretical  foundations and experimental investigations, especially at SMEs.    Keywords: collaborative problem solving, knowledge‐intensive tasks, multidisciplinary collaboration, communities of  practice, SME 

1. Introduction   Today enterprises increasingly need to be flexible and quick in revising, updating and extending their business  practices and processes. Such reorganization processes can be considered as knowledge‐intensive, in the sense  that  they  “involve  human  judgment  and  experience,  complex  decision  making,  and  very  often,  creativity.  In  fact,  they  are  now  being  recognized  as  the  most  important  processes  for  organizations  today  (Davenport,  2005)” (Marjanovic & Freeze, 2012). The high numbers of tasks, their unpredictable nature, and the difficulty  of remodelling the entire knowledge of the domain are further aspects of knowledge‐intensive processes. 

1.1 Some knowledge‐intensive processes  In this sense, processes or tasks like requirement specification, system modelling or interaction design can be  regarded as knowledge‐intensive, especially in those cases where the experience of stakeholders from many  departments or groups (multidisciplinary collaboration) is needed and must be combined in order to generate  a shared solution. Furthermore, as regards the resources involved, it is important to consider that since a large  group of people collaborating simultaneously on the same task has a high specific cost (cost/hour), there is a  compelling  need  for  efficient  interactions;  last  but  not  least,  the  interactions  also  need  to  be  effective,  particularly  in  the  sense  that,  regardless  of  the  short  time  available,  the  quality  of  the  solution  must  nonetheless be high.    This is where the SFM method for knowledge‐intensive tasks comes in with its value proposition: its procedure  is simple (lightweight), it can be executed in a short space of time (quick), it is designed to guarantee a high  quality of the solution (clean) and it allows and promotes multidisciplinary collaboration in groups of any size.  

1.2 Analogy with the Harvard negotiation method   In a famous story about negotiation, the essential difference between interests and positions (Fisher, Ury &  Patton 1991) is illustrated by two children holding one and the same orange, bringing it to an adult and stating:  “I  want  it!”  The  adult  asks  them  to  explain  the  reason  why  they  want  the  orange.  One  child  is  hungry  and  wants to eat it; the other instead needs to bake a cake and wants to have the orange because he needs grated  peel for the recipe. Negotiation succeeded! By focusing on the complementary interests (needs) rather than  on the conflicting positions (solutions), both children gain a much better solution: orange to eat and orange for 

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Marco Bettoni, Willi Bernhard and Nicole Bittel  the grated peel (Schwarz et al., 2005, p. 145). In this distinction between interests and positions, which forms  the foundation of the famous Harvard model of negotiation, one can see a strong analogy with the distinction  that  the  SFM  makes  between  needs,  objectives  and  solutions  in  the  context  of  solutions  development  and  supports  the  author’s  conviction  that  their  model  also  has  inherent  potential  and  could  become  equally  successful on a large scale. 

2. SFM method  The  essential,  core  characteristic  of  the  SFM,  which  has  its  theoretical  foundations  in  cybernetics,  system  engineering and radical constructivism, is the idea of the unity of 3 relevant elements: needs, objectives and  solutions. The term unity refers here to the guiding principle of SFM: in order to find a high quality solution,  the 3 elements should always be explicitly connected to build a coherent triad (the unity). This is accomplished  by  determining  the  3  elements  and  their  3  relations  (R1:  need  Ù  objective;  R2:  objective  Ù  solution;  R3:  solution Ù need) in a suitable manner.    The SFM is constituted in essence by a set of basic principles or ideas, divided into two groups. The first group  are  structural  principles  which  determine  the  model  of  a  structure  which  allows  thoughts  and  ideas  to  be  ordered in a specific, peculiar way; this structural model (which is the “what” of the method, the substance of  the  tool)  is  the  reason  why  the  method  has  been  allocated  the  term  “model”.  The  second  group  are  procedural principles which determine how to obtain a structure which complies with the structural principles  in a concrete situation; this part is the “how” of the method, the “know‐how” needed for using the structural  model in a situation where a solution must be conceived. 

2.1 SFM structural principles  When  one  considers  the  multiplicity  and  variety  of  all  aspects  that  determine  a  solution,  she  suddenly  understands that if, on the one hand, looking at them and taking all of them seriously contributes to obtaining  a  very  good,  complete  solution,  on  the  other  hand,  this  approach  would  require  a  lot  of  work  on  many  different  items  and  this  would  present  an  obstacle  to  an  efficient  and  effective  solution  development,  especially when this development must happen collaboratively and in a short space of time. Since the authors  wanted (and needed) their method to be not only clean (high quality) but also able to deliver results within a  short  time  frame  (quick),  they  had  to  find  a  different  solution.  Intuitively,  their  approach  was  to  search  and  identify  the  smallest  required  set  of  elements  determining  a  solution,  i.e.  an  essential  set.  This  search  was  conducted  based  on  the  background  of  their  experience  and  their  theoretical  interest  in  the  fields  of  cybernetics,  system  engineering  and  radical  constructivism  (Bettoni  1990;  Bettoni  1991;  Bettoni  &  Bernhard  1993; Bettoni 1997). As a result they devised and formulated the following 4 principles, i.e. the “Tetractys” of  their method:  ƒ

The Triadic principle: there are three essential elements to any solution and they must form a unity. 

ƒ

The Connectivity  principle: in order to form a unity , the three essential elements must be connected with  each other one by one, thus forming three essential connections. 

ƒ

The Interdependence  principle:  each  connection  between  two  elements  is  a  connection  of  interdependence. 

ƒ

The Solution  principle:  one  of  the  elements  must  be  a  solution  (to  our  problem)  and  the  two  further  essential elements, with which it has interdependence, are the need (something we are missing) and the  objective (what we can attain). 

By combining these principles, we obtain the following model of a structure (see Figure 1) where we see three  main paths for moving between the nodes which correspond to three main uses of the SFM method:  ƒ

Path P1 from need to objective to solution = goal‐oriented problem solving 

ƒ

Path P2 from solution to objective to need = goal‐oriented solution analysis 

ƒ

Path P3 from solution to need = justification. 

45


Marco Bettoni, Willi Bernhard and Nicole Bittel 

Figure 1: SFM method ‐ the structural model  This structure can be used to organise a set of thoughts (and related statements) generated in the search for a  solution to a problem; specifically, the ordering of the statements (that we call “triadic order”) will be achieved  by operating in terms of a triadic sequence composed of three specific elements :  ƒ

Need: the  first  SFM‐element,  a  need,  can  be  anything  we  are  missing:  new  interests,  hopes,  concerns,  dissatisfaction  with  a  situation,  defects  to  be  corrected,  new  wishes  to  be  supported,  etc.  which,  in  general, can be met or satisfied by more than one solution. For example, when dealing with knowledge  and  learning,  the  focus  could  be  on  knowledge  needs;  in  this  case,  to  identify  a  knowledge  need,  the  question to ask is: “what do we need or wish to know? (know what?)”. When we identify needs we are on  a functional level. 

ƒ

Objective: The second SFM‐element, the objective, comes in because a need is usually not an end in itself:  the goal it aims at can be used to achieve some effect (goal, objective). When the need is given, in order to  identify a related objective the question to ask is: “what effect should be achieved in order to satisfy the  need?” Then, when the objective has been found, the question of “why this objective?” is answered by  the  needs  connected  to  it.  In  this  step,  we  move  from  the  specific  functional  level  of  the  needs  to  the  general, explanatory level of the objectives (rationale). 

ƒ

Solution: Finally, the third SFM‐element, the solution, is the instrument, tool or method that enables you  to reach the objective and satisfy the related need. A solution should be an answer to the question: by  which measures (means) can the objective (end) be attained? In this step, we move from the explanatory  level  to  an  instrumental  level.  Vice  versa  the  question  of  “why  this  solution?”  is  answered  by  the  objectives and the needs connected to it. 

According to SFM the triadic order of the given thoughts or statements is obtained by identifying in the given  set of thoughts one or more unique combinations of three fundamental elements, i.e. a solution to a problem,  a need in terms of the essence of the problem to be solved and an objective as the rationale for the need.    As a result of  organising a set of statements based on this structural model, a diagram of a solution system  emerges which we call a “Solution Map” (see Figure 3) where each element can have multiple connections. 

2.2 Exploring the SFM on a practical example  The  SFM  is  used  as  an  analytical  tool,  where  the  starting  point  appears  in  form  of  a  problem  for  which  you  want to find a solution. This little example shows how the method works:  ƒ

Problem (starting point): “I'm hungry” 

ƒ

You may think, that “eat” is the solution to the given problem. But this is only the case if “I’m hungry” is  the need and “be satisfied” is the objective.  

ƒ

But if the objective is “to reduce weight”, then the solution will be “do not eat” and the need occurs still as  “I’m hungry”.  

ƒ

It is also possible, that “I’m hungry” is the objective, then the need can be “loss of appetite” and a solution  could be “serious sport”. It is also possible, that “I’m hungry” is a solution, then “treatment of anorexia”  could be the need and “eat” would be the objective. 

As shown  in  the  example  above,  “I’m  hungry”  can  be  need,  objective  or  solution.  By  applying  the  Solution‐ Finder‐Method, you will easy find the combination that best fits to your case. 

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Marco Bettoni, Willi Bernhard and Nicole Bittel 

2.3 Procedural principles  As the name “Solution Finder” suggests, in general the SFM method can be applied to any situation in which a  solution needs to be found. We will later see a situation of Collaborative Design (case A, section 3.1) in which  the contributions of a multidisciplinary group of people resulting from three World Café sessions in a “Problem  Meeting”  needed  to  be  structured  and  systematised  in  order  to  make  the  best  use  of  them  during  the  following “Solution Meeting”. In another situation called Collaborative Specification (Case B, section 4.1), we  will see how in various phases of an online collaboration, a group of employees contribute to the development  of an idea with a great variety of statements made during online discussions. At a certain point in the ideas  development process (phase 4), the solution ideas need to be compared and evaluated. Finally we will see a  situation of Conceptual Modelling (Case C, section 5.1) in which a great variety of statements originating both  from  theory  (e‐Learning  functions)  and  from  practice  (e‐Learning  requirements)  had  to  be  integrated  into  a  consistent model.     In all these cases, there is a search for solutions, the collection of a wide variety of contributions to this search  and the need to use the available materials in the best possible way in order to find what we are searching for  (see Figure 2).  Wide variety of solution-related statements

SFM Method

Best quality, quick solutions

Figure 2: Generic application case  In Case A, the procedure, a variation of the Grounded Theory approach (Charmaz 2006), was as follows. First of  all,  due  to  the  authors’  underlying  epistemology,  before  the  meetings  they  had  decided  to  facilitate  the  sessions and collect data in an unstructured way (unstructured interaction). In fact, they hold a constructivist  point  of  view  (von  Glaserfeld  1995)  and  believe  that,  in  order  to  make  the  most  sense  of  the  participants’  contributions, you have to approach their world from their own perspective and reify these contributions in  our documents based on their own terms. Secondly, during the Problem Meeting the authors’ team collected  detailed notes of the individual statements which the participants had contributed in three different sessions:  1)  actual  situation,  2)  vision  &  feasibility,  3)  priorities.  Since  they  as  the  facilitators,  following  their  unstructured interaction approach, did not use predefined questions and did not have any hypotheses about  the  possible  contributions,  the  content  of  the  notes  is  similar  to  those  which  can  be  obtained  as  part  of  unstructured  interviews  (Zhang  &  Wildemuth  2009).  Coding  of  the  material  was  carried  out  between  two  meetings  in  terms  of  the  concepts  of  our  Solution  Finder  Model;  the  analyst  read  the  statements  from  the  minutes,  demarcated  segments  within  them  by  comparing  similar  expressions  (similarity  of  content  and  category) and then labelled each segment with a "code"; codes were mainly “need”, “objective” and solution”,  but  also  other  words  or  short  phrases  that  emerged  as  frequent  categories  when  various  statements  were  collected  into  a  cluster.  Next  are  examples  of  statements  taken  from  the  minutes  of  a  Problem  Meeting  (August 2011); first comes the statement number, as second the person’s acronym, third is the statement and  finally the code (N= need, O= Objective, S=Solution, D=Defect, M=Measure):  ƒ

09, SK, “Information about HW parts is missing”, D 

ƒ

10, CS, “for magnets we need a database”, S 

ƒ

13, JA, “each employee has data and should be able to upload them”, N 

ƒ

15, JA, “it was planned to manage data with a CMS”, M 

ƒ

62, ME, “avoid that anyone calls the development team for support”, O 

ƒ

66, SC, “Tools that we have developed should gain better visibility”, O 

ƒ

73, DM, “we have lot of tools but application oriented information is missing”, N 

ƒ

90, RS, “Contact persons could be found if we had a directory appropriately organized”, S 

After the  coding  and  ordering  of  the  statements  into  clusters  with  the  same  code,  the  analyst  was  able  to  compile triads each composed of a need, an objective and a solution following the structural model presented  above (Figure 1). An example of a small part of such a solutions map is reproduced in Figure 3. 

47


Marco Bettoni, Willi Bernhard and Nicole Bittel  In  Case  B  and  C,  the  authors  were  basically  able  to  use  the  same  fundamental  approach  except  for  some  variations needed to adapt the procedure to the different settings. In case B, one main difference was that the  statements  analysed,  interpreted  and  coded  originated  from  postings  in  discussion  forums,  i.e.  from  asynchronous,  written  interactions;  in  case  C,  the  origin  of  the  statements  was  different,  resulting  from  a  literature  search  and  analysis  by  a  researcher  and  requirements  elicitation  by  means  of  an  online  survey,   workshops and face‐to‐face interviews.  who in the unit is responsible for data who in the unit is responsible for subject

avoid jumping from person to person for 1 question

who is working on the dossier competence about subject is in NaC

Tria

YELLOW TOOL (internal contacts)

increase transparency of people involved

contact person for registration in NaC

need?

objective?

solution?

NaC = National Company

Figure 3: Solution map case A (excerpt) 

3. Case A: Collaborative design  At  a  pharmaceuticals  company,  an  SME  (for  reasons  of  discreteness  we  will  call  it  “Phar  AG”)  with  its  headquarters  in  Switzerland  and  about  30  worldwide  independent  national  offices,  the  “Phar  International  Regulatory  Affairs”  (PIRA)  department  based  at  the  company’s  headquarters  oversees  and  supports  drug  registration  processes  worldwide  in  collaboration  with  the  aforementioned  national  offices.  The  drug  registration  process  is  the  process  of  preparing,  submitting  and  correcting  a  drug  application  for  obtaining  approval of its use from the national consumer protection agency of the specific country in which the drug will  be sold.  Success in registration projects depends heavily on having an optimal flow of information, and the  increasing  internationalisation  of  Phar  AG  had  created  new  demands  on  their  communication  and  collaboration processes, particularly knowledge‐sharing.     After  evaluating  various  kinds  of  knowledge  management  solutions,  it  was  the  concept  of  an  Online  Community of Practice (CoP) that the authors proposed which raised the interest of PIRA. After its launch, the  CoP  generated  a  new  means  of  collaboration  within  the  PIRA  department.  All  employees  dealing  with  the  registration of pharmaceutical products were able to collaborate worldwide in forums and wikis, for example  discussing new legislative requirements or developing a shared FAQ about them. In addition, documents could  be shared and viewed worldwide on the platform. Finally, the CoP enabled transparency: by means of a wiki  using personal profiles designed according to the “Yellow Tool” concept (Bettoni, Bernhard et al. 2007), it was  easy to find out who was working on what subject, where the expertise was available and how to contact the  person. 

3.1 Needs and objectives  As  preparation  for  the  actual  participatory  design  of  the  community  elements  (domain,  community  and  practice, see Wenger et al. 2002, p. 27 ff.), the authors conceived two full‐day meetings: a so‐called “Problem  Meeting” and a “Solution Meeting” for dealing with actual situation, visions, feasible solutions and priorities in  two stages. Since both meetings required the participation of employees representing the major groups that  would become members of the CoP, finally what came together was a multidisciplinary team of people with a 

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Marco Bettoni, Willi Bernhard and Nicole Bittel  variety  of  nationalities,  backgrounds,  experiences,  roles,  tasks  and  countries  of  affiliation.  Based  on  this  diversity  and  with  the  objective  of  making  the  meeting  effective  (relevant  outcomes)  and  efficient  (limited  time), an adapted version of the “World Café” was selected as main method of interaction.    It was between the aforementioned two meetings of this project that the SFM was invented (end of 2007). In  fact, since each of the three World Café sessions (actual situation, visions, and priorities) had delivered a huge  and  complex  mix  of  statements  belonging  to  a  variety  of  categories,  simply  listing  these  statements  in  the  minutes or also organising them in a huge mind‐map would have caused the reader to become lost. In order to  facilitate  the  activities  planned  in  the  solution  meeting,  a  very  good  orientation  knowledge  had  to  be  provided, something like a structured, systematic view of the outcomes of the problem meeting. But how to  structure such a huge, complex, intertwined mix of statements? Which system could be used to bring order to  this variety? By applying the SFM method to itself, we could say: the SFM has been the solution that builds a  stable triad together with the needs and objectives of this case. 

4. Case B: Collaborative specification  Like  the  previously  mentioned  pharmaceutical  company,  the  Swiss  Distance  University  of  Applied  Sciences  (FFHS)  is  also  an  SME  with  about  260  employees;  nearly  60  of  them  (administration,  technical  services,  research, education managers) have a permanent contract and about 200 lecturers have a part‐time, teaching  contract. In 2008, the Board of Directors at the FFHS sought ways to encourage employee participation in the  development  and  improvement  of  the  university;  ideas  management  was  selected  as  the  most  promising  opportunity and the Research Management Unit (RMU) of the FFHS (which at that time included the first two  authors of this paper) was allocated the responsibility for conceiving, designing, implementing and running this  new initiative and developed an innovative, collaborative model of enterprise ideas management based on a  human‐centred approach and supported by a Moodle online space (Bettoni, Bernhard et al. 2010).  

4.1 4.1 Needs and objectives  The innovative ideas management process, based on the authors’ approach called “Seven Phases Tendril” (Op.  cit., Table 1) supports not only the conventional process (submission of ideas, testing, decision, award) but also  a  specific,  facilitated  and  collaborative  “cultivation  process”  which  serves  to  unfold  an  individual  idea  and  further  develop  it  (together  with  the  idea‐giver)  during  the  course  of  an  online  collaborative  process  (e‐ collaboration) leading to a workable, shared solution.     How  does  it  work?  The  online  collaboration  is  enabled  by  a  suitably  designed  and  equipped  Moodle  space.  After publishing the new idea in a news forum and forming a group of employees interested in that specific  issue and wishing to contribute to its development, the group interacts via a specific discussion forum and is  guided by a facilitator through up to 7 phases of the ideas development process.     Phase  2  is  a  convergent  thinking  phase  which  results  in  a  mind‐map  that  visualises  a  more  detailed  understanding  of  the  problem  to  be  solved  and  of  related  tasks  in  its  branches  and  nodes.  Phase  4  is  the  filtering  process,  where  ideas  from  phase  3  are  structured  and  evaluated.  The  convergent  thinking  style  of  phase 4 allows criticism and leads to results ready for phase 5 where improvements will be the goal.     How can one evaluate the solution ideas derived from phase 3? Similarly to case A, we have here a situation in  which  a  wide  variety  of  statements  originating  from  discussions  about  the  idea  under  development  (in  this  case online discussions, not f2f) have to be put in some kind of order. Since we need to compare the various  solutions  as  part  of  the  evaluation,  what  was  needed  here  was  generalisation  knowledge  in  the  sense  of  a  structure or framework in which all items to be evaluated can be placed (interpreted) as specifications of the  same generic paradigm. A suitable generic paradigm for this was found in the SFM structural model (Fig. 1) by  considering that a great part of the contributions could be viably interpreted as direct or indirect assertions  either about needs or about objectives or solutions. 

5. Case C: Conceptual modelling  When  teaching  and  learning  are  supported  by  learning  management  systems  (LMS),  then  the  logfiles  (user  interaction  traces)  of  the  LMS  offer  opportunities  for  understanding  the  activities  of  students  and  teachers;  this  understanding  then  provides  a  good  basis  for  devising  ways  of  improving  the  quality  of  teaching  and  learning.  Unfortunately,  the  logfiles  provided  by  a  LMS  are  seldom  used;  one  of  the  main  reasons  for  this 

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Marco Bettoni, Willi Bernhard and Nicole Bittel  shortcoming  is  the  fact  that  data  is  not  aggregated  from  a  didactical  perspective.  As  a  contribution  to  overcoming this difficulty, an inter‐university team (directed by the main author of this paper)  has developed  MOCLog, a monitoring system that helps to analyse the logfiles of the LMS Moodle by interpreting the data  based on a suitable didactical model that we call “MOCLog model” (Mazza, Bettoni et al., 2012).    Unlike case A and B, in which the sources of the highly diverse statements to be organised were of a synthetic  type (group discussions), in this case C, the sources are of an analytical type, namely the analysis of research  literature and a requirements analysis that were performed as a basis for the creation of the MOCLog model.  

5.1 Needs and objectives  Based on the research review and requirements analysis, the development of the model began by creating a  concept map that had the function of clarifying the concepts involved and their relationships. Next it became  evident that one needed to integrate theory and practice with the aim of producing a solution: a) theory in the  shape of a framework of didactical objectives and related means obtained from our literature review; and b)  practice in the shape of stakeholder requirements (obtained from the requirements analysis) and LMS metrics  (log codes, logfile entry formats) of the Moodle system.    As  a  consequence,  the  question  that  had  to  be  answered  here  was  of  a  methodological  type:  which  set  of  concepts and which methodology would allow the integration of theory and practice available in the form of a  very diverse set of statements provided by two analytical sources? As in the previous two cases A and B, the  SFM  method  has  been  the  solution  that  builds  a  stable  triad  together  with  the  needs  and  objectives  of  this  case C. 

6. Conclusion The SFM method originated from the need to solve an unexpected problem which arose during a consulting  project (case A). It was further developed in the context of similar knowledge‐intensive processes like that of  case  A  (collaborative  design)  as  well  in  new  types  of  knowledge‐intensive  processes  like  collaborative  specification  (case  B)  and  conceptual  modelling  (case  C).  As  a  result  of  these  and  other  successful  project  experiences, we have now at our disposal a practical method which promises to have the potential to become  a  major  tool  of  organisational  consulting  for  enterprises  which  increasingly  need  be  flexible  and  quick  in  collaboratively revising, updating and extending their business practices and processes.    The next steps that the authors are planning consist of developing an explicit theoretical foundation, revising  the method by adapting it to this explicit foundation and after that, evaluating its application in practical cases.  For the theoretical inquiry, it is planned to extend the existing theoretical foundations by looking in particular  at  various  theories  of  needs  (Maslow,  Herzberg,  McClelland  etc.),  at  action  research  (actor‐network  theory,  theory of structuration, etc.) and knowledge management research (Bettoni 2005). 

Acknowledgements   We would like to thank Gabriele Schiller for her contributions to the first applications of the SFM method that  we  successfully  implemented  in  the  context  of  collaborative  community  of  practice  design  workshops  (consulting projects 2007‐2010). 

References   Bettoni, M. (1990) "Cognition, Semantics and Computers", in: R.A. Zwaan, D. Meutsch (eds.) Computer Models and  Technology in Media Research, 65‐98, Elsevier Science Publ., Amsterdam.  Bettoni, M. (1991) "Cybernetics Applied to Kant's Architecture of Mind", In: G. Funke (Hrsg.) Akten des 7. Internationalen  Kant‐Kongress, vol. II.2, 723‐741, Bouvier Verlag, Bonn.  Bettoni, M. & Bernhard, W. (1993) "General Purpose Enterprise Simulation with MASTER". In:G.W. Evans et. al. (eds.), Proc.  of the 1993 Winter Simulation Conference, WSC '93, 1290‐1295, Los Angeles.  Bettoni, M. (1997) "Constructivist Foundations of Modeling. A Kantian Perspective", Intern. Journal of Intelligent Systems,  Vol.12, No. 8, 577‐595, New York, 1997.  Bettoni, M. (2005) “Wissenskooperation – Die Zukunft des Wissensmanagements”. Lernende Organisation – Zeitschrift für  Systemisches Management und Organisation, No. 25, May/June 2005, pp. 6‐24.   Bettoni, M., Bernhard, W., Borter, F., Dönnges, G. (2007) The Yellow Tool – Making Yellow Pages More Social and Visible.  In: Martin, B., Remenyi, D. (eds.) Proc. of the 8th European Conference on Knowledge Management, ECKM 2007,  Consorci Escola Industrial de Barcelona (CEIB), Barcelona, Spain, Sept. 6‐7, 2007, 118‐124. 

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Marco Bettoni, Willi Bernhard and Nicole Bittel  Bettoni, M., Bernhard, W., Eggs, C. & Schiller G. (2010) Idea Management by Role Based Networked Learning. In: E. Tomé,  Proc. 11th European Conference on Knowledge Management, Universidade Lusíada de Vila Nova de Famalicão,  Portugal, 2‐3 September 2010, Vol. 2, pp. 107‐116. Reading: Academic Publishing Ltd.  Charmaz, K. (2006) Constructing Grounded Theory: A Practical Guide through Qualitative Analysis. London: Sage.  Fisher, R., Ury W. L. & Patton, B. (1991) Focus on interests, not positions. In Getting to YES: negotiating agreement without  giving in (2nd Ed.). Penguin Books USA Inc.: New York, NY. pp. 40‐56.  Mazza, R. Bettoni, M., Faré, M. & Mazzola, L. (2012) MOCLog – Monitoring Online Courses with log data. In: S. Retalis & M.  Dougiamas (eds.) Proc. of the  1st Moodle Research Conference, Heraklion, Crete, Greece, Sept. 14‐15, 2012, pp. 132‐ 139.  Davenport, T. (2005), Thinking for a Living, Harvard Business School Press, Boston, Massachusetts.  Marjanovic, O. & Freeze, R. (2012), Knowledge‐Intensive Business Process: Deriving a Sustainable Competitive Advantage  through Business Process Management and Knowledge Management Integration. Knowl. Process Mgmt., 19: 180 ‐  188. doi: 10.1002/kpm.1397.  Schwarz et al. (2005) The Skilled Facilitator Fieldbook. San Francisco: Jossey‐Bass.  von Glasersfeld, E. (1995). Radical Constructivism: A Way of Knowing and Learning. London: Falmer Press. Wenger, E.,  McDermott, R., & Snyder, W. (2002). Cultivating Communities of Practice: A Guide to Managing Knowledge. Boston:  Harvard Business School Press.  Zhang, Y. , & Wildemuth, B. M. (2009). Unstructured interviews. In B. Wildemuth (Ed.), Applications of Social Research  Methods to Questions in Information and Library Science (pp.222‐231). Westport, CT: Libraries Unlimited.    

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Intra‐Organisational Knowledge Sharing: Scenarios and  Corresponding Strategies   Madeleine Block¹ and Tatiana Khvatova²  ¹Faculty of Social Sciences and Business Studies, University of Eastern Finland, Kuopio,  Finland  ²Institute of Economics and Engineering, Saint‐Petersburg State Polytechnical University,  Saint‐Petersburg, Russia  madeleineblock@gmx.net  tatiana‐khvatova@mail.ru    Abstract:  In  the  knowledge  management  literature  knowledge  and  knowledge  sharing  issues  are  widely  discussed;  however,  a  comprehensive  understanding  of  how  intra‐organisational  knowledge  sharing  actually  occurs  has  not  been  reached  yet.  Therefore,  nurturing  the  theoretical  foundation  for  intra‐organisational  knowledge  sharing  analysis  and  actualisation  is  relevant  and  of  particular  importance.  Contemporary  theoretical  research  into  intra‐organisational  knowledge sharing predominantly focuses on how knowledge sharing functions, whether on asking why it does not happen  naturally, and finding appropriate solutions. In this article three inherent characteristics of intra‐organisational knowledge  sharing  are  examined  from  systemic  perspective,  and  further,  corresponding  strategies  for  knowledge  sharing  within  organisational environment are developed. At first, a classification of knowledge and its relevance for knowledge sharing  within organisational context is discussed. Organisation is understood as a social system, and it becomes plausible that a  subsystem  such  as  knowledge  sharing  cannot  be  organised  and  controlled  mechanically;  it  rather  reflects  a  complex  system. Accordingly, the starting point of our analysis represents two specific characteristics which must be addressed by  any type of analytic‐deliberative process: complexity and uncertainty. Ambiguity, which is particular for complex systems,  is added as the third characteristic. Analysis of the interrelations and dynamics between those three features creates the  ground  for  a  much  better  understanding  of  the  relationships  and  patterns  of  intra‐organisational  knowledge  sharing.  Subsequently, the reasons why such features as complexity, uncertainty and ambiguity appear are investigated, and based  on this the boundary scenarios of intra‐organisational knowledge sharing are developed. Beyond, scenarios are not studied  separately; they are context‐related towards organisational subsystems and elements. As a result, four knowledge sharing  strategies  corresponding  to  the  organisational  environment  are  proposed:  linear,  complex,  high  uncertainty  and  high  ambiguity knowledge sharing strategies.    Keywords: knowledge sharing; organisation; complexity; uncertainty; ambiguity 

1. Introduction Intra‐organisational  knowledge  sharing  often  refers  to  enterprises´  ability  to  create  knowledge  in  order  to  develop  new  products  and  services.  According  to  Nonaka  and  Takeuchi  (1997,  p.  71),  knowledge  creation  within organisations is a process which facilitates individual knowledge, and shares it organisationally wide. On  the  other  hand,  organisations  are  influenced  by  the  environment,  e.g.  market  competition,  and  they  are  stimulated to discover and mobilise knowledge `on‐the‐spot´ (cf. Nonaka and Nakeuchi 1997, pp. 85).    In current knowledge management and knowledge sharing literature the focus of research mainly lies on the  influencing factors of knowledge sharing. Not considering all relevant things, this focus inherits the danger of a  `too narrowed picture´. This paper aims at bringing knowledge sharing closer to reality by enlarging the view of  intra‐organisational knowledge sharing. We suggest studying knowledge sharing as a complex subsystem of its  superior  system  organisation  from  systemic  perspective.  Here,  organisations  are  studied  as  social  systems  characterised  by  more  precisely  (formally)  defined  targets  and  more  differentiated  structure  in  comparison  with  other  social  systems  such  as,  for  example,  family  (cf.  Endruweit  2004,  pp.  21‐22).  The  organisation’s  internal environment, as any complex system, is characterised by such features as complexity, uncertainty and  ambiguity which are the challenges confronting and hindering intra‐organisational knowledge sharing. These  challenges are related to the state and quality of the available knowledge and to the different targets among  organisational members including the management. Before studying those three features of complex systems  related to knowledge sharing in more detail, knowledge sharing within organisations is discussed. 

2. Central insights into knowledge sharing within organisations  In  this  chapter,  the  guiding  question  is:  what  actually  makes  knowledge  sharing  a  complex  system?    How  is  knowledge sharing characterised? 

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Madeleine Block and Tatiana Khvatova  According to systemic thinking, every system is a subsystem of another larger system, and at the same time  every system in turn consists of subsystems. In this paper the relevant system is knowledge sharing which is  embedded  in  its  superior  complex  system  organisation,  and  organisations  in  turn  are  subsystems  of  larger  systems such as society and economy. In other words, the complex social system organisation influences and is  influenced by its subsystem of knowledge sharing.     Nowadays, the process‐oriented view on knowledge sharing has become accepted in scientific literature. The  general  mode  of  knowledge  sharing  process  is  similar  in  every  knowledge  management  initiative  and,  as  described in Figure 1, consists of three phases: a) initiating and sending, b) social interaction, and c) receiving  and applying knowledge.     For a successful knowledge sharing process all three phases are equally important. Difficulties in one of those  three  phases  lead  to  hindering  or  rather  breaking  the  knowledge  flow,  even  so  the  other  two  parts  of  the  knowledge  sharing process are  operating optimally.  The  human  ‐  as  original  carrier of  knowledge ‐  occupies  the central role in the phases `initiating and sending knowledge´ and `receiving and applying knowledge´ of the  knowledge  sharing  process.  The  `social  interaction´  phase  reflects  mainly  social  relations  within  networks  of  organisations. 

Figure 1: Three phases of knowledge sharing process (own composition; cf. Köhne 2004, p. 64)  In the `initiating and sending´ phase an organisational actor intends to get or to provide knowledge. Basically,  the knowledge sharing process can be initiated by the sender or by the receiver (cf. Köhne 2004, pp. 64). If the  sender  (e.g.  management,  expert)  initiates  the  process,  s/he  pushes  knowledge  to  potential  receivers  expecting that receivers can use that knowledge. According to this push‐principle, knowledge sharing suits for  central  storage  and  distribution  of  the  stored  knowledge  within  the  organisation  (cf.  North  1998,  pp.  237).  Accordingly,  the  biggest  disadvantage  of  the  push‐principle  is  the  danger  of  intensive  circulation  of  non‐ relevant  knowledge.  It  can  happen  that  employees  receive  too  much  of  irrelevant  knowledge  or  too  little  relevant knowledge. As a result, receivers might be overloaded by information which inhibits the employees’  willingness  to  accept  this  approach;  thus,  transaction  costs  increase.  On  the  other  hand,  the  process  of  knowledge  sharing  can  be  initiated  by  the  receiver  according  to  the  pull‐principle  (cf.  Probst  and  Romhardt  1998,  pp.  237).  It  means  that  the  receiver  localises  what  kind  of  knowledge  is  relevant.  Therefore,  the  probability  that  one  gets  the  relevant  knowledge  is  higher,  and  employees  are  more  likely  to  accept  this  approach.  However,  the  availability  of  the  required  knowledge  and  the  infrastructure  are  the  important  preconditions for the pull‐principle. Moreover, at first the receiver has to understand that there is a deficit of  knowledge; otherwise, no knowledge sharing takes place. Both principles have disadvantages; therefore, some  scholars  advise  to  combine  them  (e.g.  North  1998),  while  others  (e.g.  Probst  et  al.  1999)  point  out  that  the  pull‐principle should be preferred because of the higher degree of acceptance by the counterparts and greater  probability that the shared knowledge will be used.    The  initiating  and  sending  phase  is  essential  for  knowledge  sharing  and  demands  the  support  by  the  management.  The  management  decides  on  how,  and  to  which  extent  knowledge  sharing  process  is  vitally  developed  within  organisations.  We  argue  that  knowledge  sharing  initiatives  should  be  oriented  or  rather  interlinked with the organisational target.    In  the  phase  of  `social  interaction´  knowledge  is  actually  shared  through  interaction  between  at  least  two  actors  with  the  help  of  information  and  communication  technology  (cf.  Köhne  2004,  p.  65).  Only  one‐sided  knowledge  transfer  does  not  happen  in  practice;  thus,  knowledge  sharing  reflects  bilateral  knowledge  flows  between  the  sharing  partners  (the  sender  and  receiver  positions´  are  reciprocal).  Therefore,  the  phase  of 

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Madeleine Block and Tatiana Khvatova  `receiving and applying knowledge´ follows. In this phase the receiver (individual or group) takes in knowledge,  interprets  it.  This  experience  leads  to  modification  and/or  enlargement  of  their  knowledge  base  (cf.  Köhne  2004, p. 65). Certainly, such bilateral knowledge flows stimulate the combination and creation of knowledge  for both receiver and sender. This brings us back to the conclusion of Nonaka and Takeuchi (1995, 2004) who  argue that the process of organisational knowledge sharing and creation is a dynamic and iterative process.    Concluding,  knowledge  sharing  takes  place  in  the  social  environment  and  the  quality  of  knowledge  sharing  process  depends  on  the  involved  human  beings,  and  the  capability  of  involved  actors  to  share  and  to  apply  knowledge play significant role. Therefore, knowledge sharing process cannot be looked at separately from its  nearest  environment;  it  is  embedded  in  the  organisational  environment.  This  circumstance  underlines  our  suggestion  to  examine  knowledge  sharing  with  the  help  of  system  approach  as  a  subpart  of  organisations.  Beyond, intra‐organisational knowledge sharing takes place on the individual, group and organisational levels  reflecting different social layers with their own interests which can contradict each other. 

3. Research into knowledge sharing perception  As pointed out in chapter two, intra‐organisational knowledge sharing is mainly a social process supported by  information  and  communication  technology.  Therefore,  knowledge  sharing  is  closely  connected  to  human  beings and thus, the decision whether to take actively part in the action knowledge sharing is made by them.  At this stage, we would like to refer to Renn (2008, p. 93) and emphasise that `human behaviour is primarily  driven by perception and not by facts´.     Recent studies in the field of brain research have uncovered especially deep insights into explaining  human  perception. Human beings perceive things with the help of their five senses (seeing, smelling, tasting, hearing  and touching). Their perception is also influenced by individual thoughts, feelings, memories and social as well  as  cultural  background.  Things  are  perceived  because  they  differ.  If  the  world  were  single‐coloured,  human  being would not have any criteria for this single colour (cf. Ebeling et al. 2012, p. 27). In other words, every  individual  perceives  and  creates  own  reality  which  in  turn  determines  the  pattern  of  perception  and  interpretation and filters for information suiting to own world (Figure 2).  

Figure 2: Human perception process (own composition)  Superimposed  onto  knowledge  sharing,  it  means  that  based  on  their  perception,  individuals  give  their  own  meaning to information and unconsciously communicate their reduced perception in the form of information  to others. This may explain why misinterpretation and misunderstanding in communication often happen.    In recent studies, brain researchers highlight the significant meaning of social environment for the perception  process.  Empirical  studies  could  prove  that  `soft  facts´,  related  to  social  relationships  such  as  working  environment, are  an  important  biological  health  factor  (cf.  Bauer  2008,  p.  33).  From  the  neuropsychological  point  of  view,  human´s  perception  and  also  the  brain  itself  are  dependent  on  social  relationships  (cf.  Bauer  2008,  p.  71).  In  other  words,  social  relationships  have  an  impact  on  human´s  subjective  perception,  while  perception lays the ground for action.    Further, individual and social factors that shape the knowledge sharing perception are discussed.    Knowledge sharing reflects a social process among actors of organisations. In organisations social relationships  are  based  on  structures  of  mutual  dependencies  which  make  the  actors  vulnerable  to  each  other´s  actions  such  as  knowledge  sharing  which  is  inherently  risky.  In  the  context  of  knowledge  sharing,  risk  refers  to  the  potential for giving benefit to another without receiving something similar valued or expected in return. The  uncertainty  of  a  risky  exchange  depends  on  the  amount  and  quality  of  knowledge  that  an  actor  has  for 

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Madeleine Block and Tatiana Khvatova  estimating  the  probability  of  the  outcome.  For  example,  missing  knowledge  can  be  about  the  partner´s  intentions or past behaviour (cf. Kollock 1994, pp. 317‐318), or the shared knowledge can reflect just not the  (full) truth. On the other hand, if risk is absent, trust is irrelevant because there is no vulnerability. However,  organisations and their personnel cannot possess all and true information; therefore, the notion of uncertainty  and  risk  is  always  present.  According  to  our  presumption  of  humans  acting  with  bounded  rationality  and  aiming at maximising their individual interests, knowledge sharing refers to an action that is stimulated by the  returns they expect to get, and is not based on the wish just to share with somebody (cf. Esser 2000, pp. 149).  As  far  as  knowledge  in  the  core  is  an  interpretation  of  experience  and  perception  arising  from  the  environment, the sharing of knowledge between individuals gets very complex and ambiguous.    Furthermore,  the  perception  process  within  organisations  is  complex  because  there  is  abundance  of  information,  plurality  of  views  and  interests.  However,  organisations  create  a  picture  and  develop  the  dominating  patterns  which  act  as  filters  and  influence,  change  or  even  hinder  individual’s  perception.  For  example,  if  individuals  perceive  the  organisation  as  a  machine  in  which  the  attention  is  given  to  permanent  functioning, this perception becomes a normal pattern for individuals within that organisation. On the other  hand,  if  employees  perceive  the  organisation  as  supportive  and  vital  system,  in  which  central  patterns  are  immanent responsibility and openness, then this can become normal for the organisational members as well  (cf.  Ebeling  2012,  pp.  42).  Every  employee  incorporates  pictures  of  organisation,  management  and  working  together. Those perceptions of individuals do not change easily, only if individuals change their perception by  themselves. This in turn can only happen through experience. Ideally, individual perceptions harmonise with  the collective perception which supports and utilises individual differences. Accordingly, every individual with  own  perceptions  would  be  ready  to  discover  different  perceptions,  and  the  management  would  support  an  open and fearless sharing of perceptions (and further information) among organisational members.    For a comprehensive knowledge sharing management it is necessary to consider perceptions. What can be the  criteria  for  classifying  knowledge  sharing  perceptions?  From  this  study,  we  can  conclude  that  knowledge  sharing process and its perception are characterised by three features: complexity, uncertainty and ambiguity.     The  term  complexity  refers  to  a  ‘multifaceted  web  of  causal  relationships  where  many  intervening  factors  interact  to  affect  the  outcome  of  an  event  or  an  activity’  (WBGU  2000,  pp.  194,  in  Renn  2008,  p.  186).  Complexity  supposes  difficulties  of  identifying  and  assessing  causal  links  between  a  multitude  of  potential  causal agents and specific observed effects while the causal relationship between them are known (cf. Renn  2008, p. 75). The nature of this difficulty can be illustrated by continuum of a complexity scale. On the one end  of the complexity scale, knowledge is more explicit and formalised, few factors of the environment interact,  and  the  pathway  of  knowledge  sharing  is  well  understood  and  linear.  On  the  other  end  there  are  highly  complex  relationships  between  the  environmental  factors,  which  are  also  multiple.  Change  in  one  or  two  factors might have an effect on the whole system of knowledge sharing.     The  second  feature  of  knowledge  sharing  process  is  uncertainty.  Uncertainty  refers  to  a  lack  of  clear  understanding  and  confidence  about  the  postulated  cause‐effect  relationships  (RG,  page  165).  In  studying  knowledge  sharing  it  is  essential  to  realise  that  held  knowledge,  for  example,  about  the  organisational  environment is always incomplete and selective. It is not possible to track all relationships among employees  or predict with high probability, for instance, a cultural clash. Human knowledge in general is dependent upon  assumptions, assertions  and  predictions  (cf.  Funtowitz  and Ravens 1992,  in  Renn 2008, p.  75). Furthermore,  human´s decision whether to take actively part in knowledge sharing is connected with uncertainties related to  receiving benefit.    Ambiguity  is  the  third  recognised  feature  of  knowledge  sharing  process  and  refers  to  multiple  possible  interpretations  of  things.  For  example,  actors  perceive  input  and  outcome  of  knowledge  sharing  controversially. In regard to knowledge sharing among organisational members, ambiguity plays an important  role  because  differences  in  how  individuals  value  some  input  or  outcome  of  knowledge  sharing  system  are  difficult to reconcile and a consensus might be hard to find (cf. Renn 2008, p. 186).    Probably certain knowledge sharing situations are usually characterised by a mixture of those three features.  Table  1  shows  two  main  types  of  knowledge  sharing  systems:  a)  sequential  knowledge  sharing  referring  to  routine  work  and  b)  complex  knowledge  sharing  in  which  the  characteristics  of  complexity,  uncertainty  and  ambiguity are quite present and require to plan and schedule flexible knowledge sharing systems. 

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Madeleine Block and Tatiana Khvatova  Table 1: Knowledge sharing systems with regard to the main knowledge sharing characteristics  Type of knowledge sharing  system  Sequential knowledge  sharing system  Complex, flexible  knowledge sharing system 

Explanation

Characteristics

Linear process taking place in pre‐determined  time and space with defined outcome, for  instance, a product  Knowledge pieces and flows can follow different  roots with undefined outcome or a variety of  different outcomes 

Relatively low level of complexity,  uncertainty and ambiguity  High complexity, relatively high  level of uncertainty and ambiguity 

In linear  processes,  knowledge  plays  a  less  significant  role  for  new  developments,  but  rather  as  direct  productivity power. Linear processes refer to routine with low level of complexity, uncertainty and ambiguity  because  they  are  well‐known  and  usually  easy  to  quantify.  In  opposite,  for  flexible  complex  processes  knowledge  gets  a  different  meaning.  In  this  context,  knowledge  and  the  sharing  of  knowledge  among  organisational members is the prerequisite of process development and creating various different outcomes.  Depending on organisations´ target, they may lay the focus of attention on sequential or flexible knowledge  sharing systems. 

4. Development of corresponding knowledge sharing strategies  The  knowledge  management  literature  provides  different  strategies  and  methods  for  the  actualisation  of  knowledge sharing. Basically, there are two central strategies of knowledge sharing. They regard to Nonaka´s  and  Takeuchi´s  conceptualisation  and  aim  at  facilitating  either  explicit  knowledge  or  tacit  knowledge  (e.g.  Bauer et al. 2007, Mentzas et al. 2001, Hansen et al. 1999). Those are:   ƒ

Strategy of codification: sharing of codified, explicit knowledge; 

ƒ

Strategy of personalisation: sharing of mainly tacit knowledge through face‐to‐face contacts within social  networks. 

According to  the  strategy  of  codification,  knowledge  is  codified  and  stored  in  databases  which  allow  organisational members to easily access and (re‐) use the accumulated knowledge (cf. Hansen et al. 1999, pp.  107).).  On  principle,  information  technology  systems  for  storage  and  transfer  of  explicit  knowledge  are  the  basis for the strategy of codification. The advantage of this strategy is clearly the feature that once codified  knowledge can be theoretically reused oftentimes. By this, employees enlarge their individual knowledge base.  On  the  other  hand,  employees  need  to  be  willing  to  codify  their  knowledge  and  to  use  the  knowledge  of  others. But why employees should explicate their knowledge, which is often a time‐consuming process, when  its  codification  does  not  generate  a  direct  benefit  for  them?  Beyond,  for  human  beings  the  explication  of  individually  held  knowledge,  for  example,  expressing  thoughts  and  ideas,  is  difficult  and  limited.  From  the  organisational point of view, disadvantages of codifying knowledge are connected with the risk of overlooking  much valuable knowledge besides codified knowledge and the circumstance that stored knowledge becomes  quickly overdue while it is detached from certain situation (cf. Huysman and de Wit 2004, pp. 83‐86).    On  the  contrary,  the  strategy  of  personalisation  refers  especially  to  knowledge  sharing  between  people.  `Knowledge  is  closely  tied  to  the  person  who  developed  it  and  is  shared  mainly  through  direct  person‐to‐ person contacts.´ (Hansen et al. 1999, p. 107). Therefore, the strategy of personalisation concentrates more on  sharing  tacit  knowledge  and  is  based  on  the  network  of  experts  and  communities  of  practice.  There  are  appropriate  organisational  pre‐conditions  to  be  made,  for  example,  mentoring,  discussion  forums,  chatting  rooms  or  creation  of  communities  of  practice.  The  advantage  of  the  strategy  of  personalisation  is  that  it  is  generally easier to put sharing of knowledge into practice, because of closer relations. On the other hand, the  main disadvantage in regard to the strategy of codification is that for every sharing process the knowledge has  to be provided newly which means that the scalability and, therefore, the reuse of knowledge is comparably  little.    Both  theories  narrow  the  view  on  sharing  either  explicit  or  implicit  knowledge,  but  as,  for  example,  Polanyi  (1985, p. 36) stated, knowledge inherits both of these forms which are interwoven with each other. We argue  that it is not helpful to separate knowledge, for example, into explicit and implicit, and this separation cannot  lay the foundation of designing knowledge sharing strategies. In this paper, we propose to develop strategies  according  to  the  three  main  characteristics  of  knowledge  sharing  system:  complexity,  uncertainty  and  ambiguity. So, we offer the following four scenarios: 

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Madeleine Block and Tatiana Khvatova  ƒ

Strategy for sequential, linear knowledge sharing process; 

ƒ

Strategy for knowledge sharing with high complexity; 

ƒ

Strategy for knowledge sharing with high uncertainty; 

ƒ

Strategy for knowledge sharing with high ambiguity. 

The strategy  for  sequential  and  linear  knowledge  sharing  processes  aims  at  optimising  clear  routes  with  defined outcome and at making sure that the process is running within accepted and determined frame. The  knowledge  is  mainly  explicated  in  forms  of  standards,  and  instructions.  Therefore,  there  is  little  uncertainty  about the process, other´s behaviour or potential harm because those situations are well‐known to the actors  involved.  This  strategy  is  applied  to  mass  production,  for  example,  car  production  where  knowledge  is  understood just as a production input factor (cf. Renn 2008, pp. 189‐191).    Furthermore, we differ between three strategies for complex knowledge sharing system with the emphasis on  one of the three main features: complexity, uncertainty and ambiguity.     The first knowledge sharing scenario with high complexity but low uncertainty and ambiguity refer to complex  problems linked to specific causal paths. This strategy needs more systemisation and experience in order to  get  an  overview  of  the  complex  relationships  behind.  In  this  case,  specific  actions  may  mislead,  complexity  demands complex methods (cf. Renn 2008, pp. 191‐193).     Knowledge  sharing  scenario  of  high  uncertainty  but  less  complexity  and  ambiguity,  refers  to  too  little  information,  for  instance,  about  the  counterpart´s  behaviour  or  about  the  potential  risk  or  output  of  knowledge  sharing.  Accordingly,  uncertainty can  be  reduced  by  increasing  complexity  through  acquisition  of  additional information. The central issue is finding an adequate balance between investing all efforts (costs) to  acquire wide‐ranged information keeping cautious about uncertainty. Alternatively, one can try to coexist with  uncertainties  taking  certain  efforts,  trusting  that  additional  damages  will  be  reasonable  and  learning  to  be  more  flexible  and  adaptive  to  surprises.  In  this  context,  the  question  arises:  what  is  reasonably  justifiable?  What are the suitable instruments for dealing with high uncertainty? In regard to knowledge sharing, it can be  asked how much uncertainty one is willing to accept (cf. Renn 2008, pp. 193‐197)    The third scenario characterised by high ambiguity requires attention to different and conflicting targets and  perceptions. In regard to knowledge sharing, ambiguity is very present because knowledge sharing requires at  least two actors and thus, there are multiple views and targets among organisational members.    In order to illustrate how the suggested general strategies of knowledge sharing can be applied in real life, let us  consider an example of university landscape in Russia. A short introduction to the context is needed in order to  understand  the  degree  of  complexity,  uncertainty  and  ambiguity  of  the  knowledge  sharing  process.  At  the  moment  Russia’s  education  system  as  a  whole  is  experiencing  tremendous  reforms  and  downsizing  when  departments and the whole universities are merging, obsolete connections between people and departments are  disassembled and then assembled again, but in a new order. During the last 5‐7 years university life in Russia has  turned  from  a  ‘safe  harbour’  into  a  turbulent  environment;  professors  are  now  required  to  be  not  only  knowledgeable, but also entrepreneurial, modern, mobile, international, etc. Furthermore, there is an increasing  number  of  subjects  taught  at  the  same  time,  sometimes  in  both  native  and  foreign  languages;  growing  interdisciplinary approach of subjects which are getting more and more interwoven with each other; emerging  distance‐learning and vocational programmes of different kinds. Another trend – developing ICT based learning,  introducing  e‐learning  platforms  in  educational  institutions.  These  circumstances  suggest  that  explicit  and  especially tacit knowledge exchange between people is needed – to keep track of the networks trying to preserve  relationships and expertise.     The  abovementioned  features  prove  that  the  knowledge  sharing  process  within  universities  in  Russia  is  highly  complex.  Knowledge  sharing  process  in  a  university  is  also  uncertain  which  means,  according  to  the  definition  given earlier, that there is no clear understanding about the cause‐effect relationships within the system. People  are  uncertain  about  getting  benefit  which  discourages  them  from  knowledge  sharing.    The  third  feature  of  knowledge sharing process – ambiguity – is very present. When we speak about teachers and their intellectual  property, which is e‐books, PowerPoint slides, case studies, it is always hard to find a consensus about what is  more  valuable  in  knowledge  sharing  because  perceptions  highly  differ.  The  well‐known  peculiarity  of  Russian 

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Madeleine Block and Tatiana Khvatova  society is low trust among people of the same organizational level and low trust of people to the management (to  the government) (cf. House et al. 2004). According to the survey of Levada Center held in 2010, two thirds of the  respondents answered that one should not trust the majority of people and be careful. Younger people aged 25‐ 39 with higher education were especially cautious (71% said one should not trust to people). This partly explains  the results of another survey held in a business school in Saint‐Petersburg (Russia) showing why many attempts  to introduce e‐learning and to make teachers upload their teaching materials to the platforms fail: many people  think that their materials will be used by somebody else (cf. Khvatova and Lichy 2012, p. 97). In the same survey  most people stated that they would share knowledge in the e‐learning system if they received monetary benefits  from that. This example also emphasizes the ambiguity of knowledge sharing process in universities.    So, we observe that all three features of knowledge sharing process are present in the university environment.  However, in our opinion, ambiguity is the highest influencing dimension in the discussed context. It is very much  combined  with  uncertainty.  People  are  mostly  afraid  that  their  knowledge  is  misused,  that  they  do  not  get  anything valuable in return for sharing their knowledge, or they transfer their competence to others and become  redundant, etc.    What  can  be  recommended  to  make  the  knowledge  sharing  work?  Usually  in  systems  with  high  degree  of  ambiguity a socially acceptable development path should be chosen which means ‘resolving value conflicts and  ensuring fair treatment of concerns and visions’ (Renn 2008, p.188). The consensus should be reached through  stakeholder  dialogs  aimed  at  harmonizing  organizational  targets  with  members’  own  interests.  There  are  probably various perceptions of unfairness in the distribution of benefits linked to the risk of being in the end the  foolish among the organisational members. Therefore, a consensus considering all interests is difficult or rather  impossible to put into practice because of the plural views of organisational members. However, the different  views of the involved actors need to be reflected to be able to find a solution which is accepted by at least the  critical  mass  or  to  find  an  agreement  on  a  certain  objective  with  which  everybody  would  agree.  Finally,  the  goal  might  be  to  find  an  appropriate  objective  and  consensus  between  those  who  believe  the  knowledge  sharing  is  worth  doing  and  those  who  believe  it  is  not,  due  to  various  reasons.  How  to  determine  the  basic  conditions  and  to  harmonise  organisational  targets  with  members´  own  interests?  In  this  connection,  organisational  value  and  norm  system  seems  to  play  an  important  role.  In  regard  to  knowledge  sharing  it  means that the main task in reducing ambiguity is to find regulatory norms, values and rules acceptable for  most of the involved actors. It is a search for a win‐win strategy perceived as giving benefit to all parties within  organisations. One option is to emphasise the mutual benefits which are brought by knowledge sharing as a  vision  which  in  turn  is  conditioned  by  the  acceptance  of  the  shared  values  and  vision  by  all  the  actors.  An  alternative  is  to  provide  bonuses  to  potential  sufferers  of  knowledge  sharing  process,  for  example,  to  employees  who  are  mainly  involved  in  routine  work  and  cannot  actively  participate  in  knowledge  sharing  in  sense of learning and applying situational and problem‐related knowledge.    In particular, this strategy requires involvement and communication which would help to search for solutions  dealing with the interests and values of organisational members and to resolve conflicts among them. In this  context, face‐to‐face methods tend to be more suitable for the sharing of knowledge which come along with  higher information richness and reduce the ambiguity of implicit knowledge. Ambiguity is usually coupled with  high degree of uncertainty and complexity and thus, must be combined with the other two strategies (cf. Renn  2008, pp. 197‐199). 

5. In conclusion  In  this  paper  the  angle  of  view  for  studying  knowledge  sharing  within  organisations  has  been  turned  away  from  focusing  on  common  types  of  knowledge  (explicit  and  implicit  knowledge)  towards  understanding  knowledge sharing as a subsystem of complex social system of organisations. The focus of this study is put on  inherent  features  of  knowledge  sharing  which  are  complexity,  uncertainty  and  ambiguity.  Based  on  those  features, we developed strategies for managing intra‐organisational knowledge sharing.    Figure 3 shows graphically the four knowledge management strategies. The first strategy (I) regards knowledge  sharing process with very low level of complexity, uncertainty and ambiguity and thus, represents one of the  extreme  strategies.  Such  linear  processes  demand  only  routine  procedures  for  knowledge  sharing  with  specialised  knowledge  acting  as  direct  production  input  factor  as,  for  example,  in  mass  production.  High  complexity  is  a  result  of  many  interacting  factors  given  by  the  environment.  For  high  complex  knowledge 

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Madeleine Block and Tatiana Khvatova  sharing process with low uncertainty and ambiguity (II) the causal relationships between the factors are known  and there are little ambiguous opinions. If uncertainty is high in knowledge sharing process while complexity  and  ambiguity  are  low  (III),  the  strategy  proposes  to  prepare  organisational  members  for  unknown  and  unpredictable happenings. Furthermore, the uncertainty can be reduced by increasing the information base as  well as transparency within the process and among the roles and duties of the employees. In the fourth case  (IV), the ambiguity is high, which goes along with high uncertainty and complexity; otherwise, such a plurality  of  views  would  not  exist.  This  strategy  represents  the  other  extreme  case  of  possible  knowledge  sharing  strategies. Ambiguity reflects conflicts of interests and values which need to be reconciled, for example, with  vest of a knowledge sharing culture represented by the management who give example of knowledge sharing  and transparency of decision‐making. 

Figure 3: `Knowledge sharing cube´: knowledge sharing strategies and the features of complexity, uncertainty  and ambiguity  It is difficult or rather impossible to control complex economic and social systems because today´s actions lead  to  unknown  future  results  and  to  possible  clashes  of  different  perceptions  and  targets.  We  consider  that  knowledge system is not an autonomous system, but rather connected to other organisational subsystems and  beyond.  A  starting  point  for  future  studies  would  be  researching  into  different  states  and  the  dynamics  of  knowledge sharing system. In this context, oscillations may occur due to environmental influences or delays in  applying  strategies  and  methods.  Another  fruitful  way  of  further  research  would  be  determining  proper  instruments  based  on  the  formulated  strategies  which  could  serve  as  a  guideline  for  organising  an  iterative  process of navigation through the complex and dynamic system of knowledge sharing within organisations. In  particular,  we  consider  that  development  of  effective  communication  instruments  for  managing  knowledge  sharing is relevant.  

References Bauer, J. (2008) Das Gedächtnis des Körpers. Wie Beziehungen und Lebensstile unsere Gene steuern, 2nd edition, Munich:  Piper Verlag.  Ebeling I., Vogelauer, W., Kemm, R. (2012) Die Systemisch‐dynamische Organisation im Wandel. Vom fließenden Umgang  mit Hierarchie und Netzwerk im Veränderungsprozess,  Bern, Stuttgart, Wien: Haupt Verlag.  nd Endruweit, G. (2004) Organisationssoziologie, 2  edition, Stuttgart: Lucius & Lucius.  Köhne, M. (2004) Die Bedeutung von intra‐organisationalen Netzwerken für den Wissensaustausch in Unternehmen,  Bamberg: Difo‐Druck.  Esser, H. (2000) Soziologie. Spezielle Grundlagen, Band 3, Soziales Handeln, Mannheim: Campus Verlag.  Hansen, M.T., Nohria, N., Tierney, T. (1999) `What´s your Strategy for Managing Knowledge?´, Harvard Business Review,  vol. 77, no. 3, pp. 105‐116.  House et al. (2004) Culture, Leadership, and Organizations: the GLOBE study of 62 societies, Thousand Oaks: Sage  Publications.  Huysman, M., de Wit, D. (2004) `Practices of Managing Knowledge Sharing: Towards a Second Wave of Knowledge  Management´, Knowledge and Process Management, vol. 11, no. 1, pp. 81‐92.Nonaka, I. and Takeuchi, H. (1995) The  Knowledge‐Creating Company: How Japanese Companies Create the Dynamics of Innovation, New York: Oxford  University Press. 

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Madeleine Block and Tatiana Khvatova  Khvatova, T. and Lichy, J. (2012) `Exploring Technology to Modernize Undergraduate Teaching´, proceedings of EDiNEB  International Conference `The Role of Business Education in a Chaotic World´, Haarlem, the Netherlands, May 2012,  pp. 93‐99.  th Levada Center (2010) Analytical Center of Yuri Levada, Аналитический центр Юрия Левады, viewed 11  of May 2013,  URL=www.levada.ru.  Nonaka, I. and Takeuchi, H. (1997) Die Organisation des Wissens. Wie japanische Unternehmen eine brachliegende  Ressource nutzbar machen, Frankfurt am Main: Campus Verlag.  North, K. (1998) Wissensorientierte Unternehmensführung: Wertschöpfung durch Wissen, Wiesbaden: Gabler.  Polanyi, M. (1985) Implizites Wissen, Frankfurt am Main: Suhrkamp, translated by Horst Brühmann (original version `The  Tacit Dimension´, 1966).   Probst, G.B., Romhardt, K. (1998) Bausteine des Wissensmanagements – ein praxisorientierter Ansatz, in: Handbuch  Lernende Organisation, Wiesbaden: Gabler, pp. 129‐143.  Probst, G.B., Raub, S., Romhardt, K. (1999) Wissen managen – Wie Unternehmen ihre wertvollste Ressource optimal nutzen,  rd 3  edition, Wiesbaden: Gabler.  Renn, O. (2008) Risk Governance. Coping with Uncertainty in a Complex World, London, Sterling: Earthscan. 

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Organizational Culture vs. Structure: An Academic Case Study  Razvan Bogdan, Versavia Ancusa and Oana Caus  Politehnica University of Timisoara, Timisoara, Romania  razvan.bogdan@cs.upt.ro  vancusa@cs.upt.ro  oana.caus@cs.upt.ro    Abstract:  In  order  to  implement  knowledge  management  in  an  organization,  a  first  step  is  assessing  the  readiness.  The  readiness is directly influenced by the organization culture, structure and infrastructure. This paper aims to assess the first  two  factors  in  a  particular  case,  the  Politehnica  University  of  Timisoara  (UPT).  Due  to  the  fact  that  the  organization  structure is well‐defined, our efforts centred mainly in determining the organizational culture. The UPT, due to the various  faculties  and  administrative  divisions  has  created  a  non‐linear  organizational  culture.  Apart  from  the  established  way  of  assessing organizational culture, the Organizational Culture Profile (OCP), based on Q‐sort, we focused on analysis of social  networks  interactions  in  order  to  determine  organizational  culture.  We  correlated  the  collected  data  with  the  age  distribution, in order to investigate possible discrepancies. In the organizational structure the most influential were higher  level academics with an older bias. Unlike the organizational structure, on a cultural level, the most influential were middle  level,  young  to  middle  age  individuals  that  showed  the  highest  availability  for  communication.  This  non‐congruency  was  even  further  illustrated  when  paired  with  student‐teacher  relationship  data.  The  same  middle  level  individuals  had  the  highest  communication  strength,  thus  the  highest  influence  on  the  students.  Even  the  total  number  of  connections  indicated  the  same  individuals  as  the  most  influential.  An  interesting  fact  implied  the  gender  distribution.  While  in  the  organizational  structure  there  is  a  clear  partiality  towards  the  males,  in  the  organizational  culture  there  is  no  such  bias,  both sexes being (almost) equally influential. Further analysis including all the data, put under scrutiny the readiness for  knowledge management in UPT. As a result, a guideline and several tactics are proposed in order to improve the readiness.    Keywords:  social  network  analysis,  organizational  culture,  organizational  readiness,  number  of  connections,  centrality,  communication strength, influence 

1. Introduction Knowledge  management  (KM)  readiness  was  previously  defined  (Mohammadi,  et  al.,  2009)  as  successfully  adopting,  using  and  benefiting  from  knowledge  management  in  a  certain  organization,  department  or  team  work. Readiness is an attribute of organization’s ability in attaining all these factors. It should be applied in the  early  planning  strategies  of  the  knowledge  management  approaches.  Previous  papers  like  (Holt,  2000)  state  that  readiness  is  an  essential  precondition  for  an  organization  that  aims  at  succeeding  when  faced  with  organizational change. In order to successfully implement KM plans, organizations need to assess if they are  properly prepared to face such a challenge. KM initiatives involve costly investments in the infrastructure, as  well as in personnel. Failure to assess organizational KM readiness might cause major time and money loss.    “Politehnica” University of Timisoara has benefited recently from major investments in the infrastructure with  budgets of approx. 12 million Euros in the past 3 years. The new library construction as well as the material  base revitalization guarantees that the infrastructure is up‐to‐date and favourable to implementing knowledge  management.    The  university’s  hierarchical  structure  is  well‐defined  and  can  be  modelled  using  a  tree  topology,  with  the  Chancellor as the top node. Essentially, it is a classical rigid structure which underwent only minor changes in  the  past  50  years.  These  changes  relate  more  to  the  addition  of  new  branches  (such  as  new  faculties  or  departments),  yet  they  do  not  alter  the  original  nature  of  the  structure.  On  the  other  hand,  the  university  culture  has  undergone  a  definite  transformation  process  especially  in  the  last  24  years,  since  the  fall  of  the  communist regime. Fuelled by the new cultural influences of the West, the social aspects have slowly changed.  Those changes reach now a point in which a knowledge management system is needed and this paper aims at  evaluating if the current situation is compatible with such a capitalist practice.    This paper is structured as follows: the literature review offers a survey of knowledge management techniques  used to asses readiness, the research design presents the parameters of the exploration, followed closely by  the  results  and  discussion  of  the  study.  In  the  end,  in  the  conclusion  section  several tactics  are proposed  in  order to improve readiness. 

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2. Literature review  The readiness of an organization is a guideline for the management in order to establish if the organization is  ready to face and implement assorted KM initiatives (Desouza & Raider, 2006).      A  spectrum  of  studies  proposes  various  methods  to  be  used  in  order  to  assess  the  readiness  of  different  organizations. A study related to the USA air force readiness for successful KM implementation is presented in  (Trent,  2003).  The  research  method  presented  in  this  article  is  based  on  Change  Content  Variables,  Process  Variables,  Contextual  Variables  and  Individual  Variables.  Each  of  these  parameters  is  following  different  degrees of change that occur in the organization during the KM implementation.    In  (Holt,  et  al.,  2004),  individual,  context,  content,  process  measures  and  KM  attitudes  are  taken  into  consideration  in  order  to  assess  KM  readiness.  In  2009,  (Mohammadi,  et  al.,  2009)  proposed  a  study  to  determine KM readiness based on five organizational antecedents for effectiveness such as vision for change,  infrastructure,  structure,  support  for  change  and  culture  of  knowledge.  Further  on,  (Jalaldeen,  et  al.,  2009)  suggests  that  organizational  readiness  can  be  assessed  by  taking  into  consideration  both  organizational  and  individual factors. Beig et al. (2011) advance a modality of assessing KM readiness in a learning environment  based  on  10  dimensions  that  should  be  considered:  knowledge  and  learning  strategy,  learning  dynamics,  organizational culture, technological infrastructure, organizational structure, customers, partners and suppliers  (external  sources  of  knowledge),  tacit  and  explicit  knowledge  process,  collective  learning‐based  incentives,  performance and knowledge sharing.    In all these cases, two main coordinates are assessed: structure and culture, and based on the correlation of  the  two, a  conclusion  is  drawn.  Table  1 presents  the clustering  of  the previous  studies’  parameters  into  the  structure and culture columns. A third column was added to present the mixed variables, such as support for  change that needs both culture and structure assistance.   Table 1: Structure and culture categories in KM readiness studies  Study  (Trent, 2003)  (Holt, et al.,  2004)  (Mohammadi, et  al., 2009)  (Jalaldeen, et al.,  2009)  (Beig, et al.,  2011) 

Structure‐related process variables, contextual  variables  context, content, process  measures  various structure  measurements  organizational factors  organizational structure,  customers, partners and  suppliers,  collective learning‐based  incentives, performance and  knowledge sharing 

Culture‐related individual variables 

Other / mixed  change content variables 

individual measures,  KM attitudes  culture of knowledge 

individual factors  tacit and explicit knowledge  process,   learning dynamics,   organizational culture 

support for change,  infrastructure    knowledge and learning  strategy, technological  infrastructure 

While usually organisational structure is easily measured, assessing organizational culture can be viewed as a  problem of evaluating the interrelationships’ exceptional structure among different individuals and programs.    Qualitative methods such as interviews of the employees and/or observations of their interactions are most  commonly  used  in  measuring  organisational  culture.  More  traditional  KM  approaches  include  General  Demographics, Organizational Culture Assessment Instrument (OCAI), Organizational Culture Profile (OCP) and  Organizational  Commitment  (OC).  Lately,  due  to  the  development  of  virtual  interactions,  Social  Network  Analysis  (SNA)  is  also  a  valuable  instrument  in  assessing  organisational  culture.  Table  2  presents  a  methods  summary.    While  General  Demographics  is  a  simple,  indirect,  yet  effective  method  of  statistically  assessing  the  respondents’  profile;  OCAI,  OCP  and  OC  need  direct  interaction  with  the  employees.  The  survey  complexity  varies  among  these  three  methods  and  there  are  several  pointers  (Kulkalyuenyong,  2012)  that  such  direct  approaches  might  not  be  extremely  accurate.  Conversely,  SNA  is  an  indirect  approach  that  measures  employees’ past interactions, thus providing a more truthful cultural context image. 

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Razvan Bogdan, Versavia Ancusa and Oana Caus    Table  2:  Methods  used  to  assess  organisational  culture  –  a  comparison  (modified  from  (Kulkalyuenyong,  2012))  Methods  General Demographics  OCAI  OCP  Organizational Commitment  Social Network Analysis 

Collection methodology  Database access – statistical pack  Employees survey –  sort 100 items  Employees survey –  sort 28/40/54 items  Employees survey –  answer 6 questions  Social network access and SNA tool 

Purpose To know respondents’ profile  To test current and preferred  organizational culture type  To test employees’ perceived  organizational culture  To test employees’ commitment level  To quantify past employees’  interactions 

In (Lurie,  et  al.,  2009)  the  authors  have  taken  into  consideration  three  possible  settings:  team  function,  interdisciplinary  composition  of  advisory  committees  and  relationships  between  key  function  directors.  Applying  social  network  analysis  reveals  precise  aspects  from  team  functioning  and  proves  summary  descriptions  of  the  various  departments’  interdisciplinary  degree.  When  applied  to  relationships  realm,  SNA  emphasizes potential problem regions in dealings among academic departments. Measuring such aspects in an  objective way, if SNA is not applied, is a difficult endeavour.    Waldstrøm  (2003)  argues  that  one  of  the  social  networks  main  contents  is  the  cultural  aspect  as  it  is  responsible  for  the  values  transfer  and  general  information  flow.  Furthermore,  the  author  emphasizes  that  social  networks  are  the  main  information  carriers  that  assure  the  organizational  culture’s  adjustment  and  maintaining.  For  this  reason,  identifying  and  defining  social  networks  in  an  organization  is  highly  important.  Social networks in organizations are compared in (Krackhardt & Hanson, 1993) with a living organism’s nervous  system,  where  the  bones  stand  for  the  formal  organization,  while  the  organization’s  formal  and  informal  structures  have  been  presented  as  the  de  jure  and  the  de  facto  correspondingly.  It  has  been  discussed  in  (Waldstrøm, 2003) that in state‐of‐the‐art literature there is a dichotomy regarding formal/informal structures  in  organizations,  described  as  official/unofficial,  prescribed/emergent  issues.  These  terms  can  be  used  interchangeably to a large extent, therefore formal structures and social networks are primarily used among  organizational  terminology.  The  formal  structures  are  mainly  normative  due  to  the  fact  that  the  individual’s  position  in  the  formal  organization  is  determined  by  a  certain  structure,  namely  the  organizational  chart.  Conversely,  the  social  network  has  a  descriptive  property  because  such  networks  can  be  just  observed  and  influenced at best.     The  informal  organization  is  dependent  both  on  formal  structure  and  organization  culture  (Stevenson  &  Bartunek, 1996). However, it has been proved that there is a slice of difference between organizational culture  and  the  informal  organization:  “An  organisation’s  culture  develops  over  time,  is  slow  to  change,  and  is  reinforced by the practice of people recruiting others whom they ‘like’. The informal organization, by contrast,  is quick to grow and transmute according to changing circumstances and the interaction of individuals within  the organisation” (Waldstrøm, 2003).  

3. Research design  In order to evaluate the university’s structure, this study used the Human Resources Department data to plot  an organisational chart of the management level, adding to that network, data regarding the age and gender  of each individual. The data was also analysed using traditional statistical analysis.    The university culture was assessed using two avenues: OCP and social networks. The OCP test was taken by a  statistically significant fraction of the employees using an on‐line form. For the social network assessment the  authors  used  a  Facebook  application  developed  for  academic  purposes  (snacorse.com/getnet)  in  order  to  capture  one’s  network  of  friends.  Several  colleagues  allowed  the  capture  of  their  networks  and  using  only  university‐related  data  from  them.  The  social  networks  were  plotted  using  a  dedicated  tool,  Gephi,  which  additionally  allowed  to  determine  clustering  as  well  as  several  other  pertinent  coefficients  (centrality,  betweeness). Both data sets were correlated in order to render a comprehensive cultural dimension picture. 

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4. Results and discussion  The  university’s  upper and  middle  level  general  demographics  statistical data  is  presented  in  Table  3.  When  split between the administrative and the strictly academic community, the data paints a clear picture of the  imbalance between those two. The research and teaching management community is highly male dominated  (90.16%), while the administrative group is much more balanced (46.34% males).   Table 3: Upper and middle level general demographics statistics  Parameter 

Whole university 

Administrative

Research & teaching 

Male subjects 

74

19

55

Female subjects 

29

22

7

Age Mean 

54.70

50.56

57.48

Age Median 

57.00

51.00

59.00

Age Standard Deviation 

8.53

8.46

7.43

Age Kurtosis 

‐0.19

‐0.78

0.75

Age Skewness 

‐0.73

‐0.48

‐1.00

Age Range 

35

31

34

Age Minimum 

32

32

33

Age Maximum 

67

63

67

The age marks another division between the two communities. Mean values are, to some extent, the same,  although the kurtosis parameter suggests a significant difference in the distribution of values. As presented in  Figure 1, the comparative age histogram shows that academia management falls highly in the aged category  and  the  following  generation  of  management  is  not  yet  developed.  Meanwhile,  although  the  administrative  community presents a peak at around 60, the next age generations are starting to develop more freely.  

Figure 1: Comparative age histogram between the administrative and teaching & research communities  In  order  to  fully  understand  what  caused  such  differences  inside  the  same  organisation  the  Organizational  Culture  Profile  (OCP)  40  cards  version  was  used  in  order  to  test  the  employees’  perceived  organizational  culture, and the average results are presented in Table 4.     The most important dimensions are stability (r=.85 p<0.05), performance orientation and competitiveness. The  results  seem  to  be  conflicting  since  stability  is  not  the  best  environment  for  competitiveness.  Moreover,  innovation, which should be one of the leading dimensions in an academic environment, does not make Top 3.  Another  dimension  which  one  would  expect  to  matter  in  an  academic  environment  –  social  responsibility  –  ranks  only  4th.  The  supportiveness,  which  knowledge  sharing  readiness  measures,  ranks  only  5th  among  the  cultural dimensions of OCP.    The  results  from  OCP  were  in  some  way  ambiguous  and  therefore  further  study  of  our  colleagues’  social  networks was required.   

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Razvan Bogdan, Versavia Ancusa and Oana Caus    Table 4: Median OCP              2  30 

        37  10  38  Most Characteristic 

      4  24  22  26 

3  14  34  27  15  39  9 

36   5  17  33  16  32  12  8  29  35  25  19  23  15  28  Neither Characteristic   Nor Uncharacteristic 

      1  7  18  31 

                  21    11  6  13  40  Least Characteristic 

Legend: 1. Adaptability  2. Stability  3. Being reflective 

21. Decisiveness  22. Being competitive  23. Being highly organized 

4. Being innovative  5. Being quick to take advantage of opportunities  6. Taking individual responsibility 

24. Achievement orientation  25. Having a clear guiding philosophy  26. Being result‐oriented 

7. Risk taking  8. Opportunities for professional growth  9. Autonomy 

27. Having high performance expectations  28. Being aggressive  29. High pay for good performance 

10. Being rule‐oriented  11. Being analytical  12. Paying attention to detail  13. Confronting conflict directly 

30. Security of employment  31. Offers praise for good performance  32. Being supportive  33. Being calm 

14. Being team‐oriented  15. Sharing information freely  16. Being people‐oriented 

34. Developing friends at work  35. Being socially responsible  36. Enthusiasm for the job 

17. Fairness  18. Not being constrained by many rules  19. Tolerance 

37. Working long hours  38. Having a good reputation  39. An emphasis on quality 

20. Informality 

40. Being distinctive / different from others 

In Figure 2 the university structure is plotted using complex networks. Node colour is used to represent age:  the  darker  the  node,  the  greater  the  age.  The  node  size  is  linearly  correlated  with  the  closeness  node  centrality,  i.e.:  “the  efficiency  of  each  vertex  (individual)  in  spreading  information  to  all  other  vertices”  (Okamoto,  et al.,  2008).  The  complex  network  was  rendered  using  a Force  Atlas  layout  which  facilitates  the  cluster visualization. No further manual adjustments were used to present the layout. In order to depict data,  Gephi (www.gephi.org) was used. 

Figure 2: University’s complex network 

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Razvan Bogdan, Versavia Ancusa and Oana Caus  On the right side of the network is the administration community whereas the teaching and research group is  on the left side. The largest node represents the Chancellor and is shown to be the only way of interfacing the  administration and academia.    Using  a  type  of  analysis  characteristic  of  complex  networks,  the  number  of  nodes  versus  node  degree  was  plotted  and  Figure  3  shows  the  result.  The  power‐law  distribution,  characteristic  to  real‐life  systems  is,  as  expected, identifiable.  

Figure 3: The number of nodes versus node degree  It can be observed that the university’s chancellor has the utmost node degree meaning that is highly linked.  Subsequently, the vice‐chancellors cover the following node degree values. The obtained distribution shows a  skewed node‐degree distribution in which most nodes have only few links. The contrast is represented by the  chancellor and vice‐chancellors who are extremely linked. This shows that, in the organizational structure, the  most influential are the higher level academics with an older bias.    In  Figure  4  we  mapped  the  structure  with  the  upper  and  middle  level  management’s  gender.  Node  size  is  proportional with closeness centrality and a community detection favourable layout was used. 

Figure 4: University managements’ complex network correlated with gender 

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Razvan Bogdan, Versavia Ancusa and Oana Caus    In  the  administrative  community,  similar  levels  of  management  (denoted  by  similar  node  sizes)  show  a  balanced  gender  distribution,  while  in  the  academia  community,  the  females  tend  to  have  low‐level  management  positions.  The  previously  found  imbalance  using  demographics  distribution  is  added  a  new  dimension when using the complex networks representation. The “glass ceiling” in the academia is depicted  fairly obvious.    Using SNA to study the organisation culture, we analysed a number of Facebook complex networks from our  colleagues, both from research and administrative staff. The aim of these experiments was to determine the  most  influential  individuals  from  a  cultural  point  of  view  and  not  from  the  organizational  structure.  Two  Facebook representations are presented in Figure 5. Dark nodes represent females, light nodes males. Node  size is again correlated with closeness centrality. No clear separation can be seen between the administrative  and teaching & research community. The gender distribution is relatively balanced, notwithstanding the size of  one’s social network. 

Figure 5: Various social networks  It should be mentioned that the most influential individuals were the young to middle age ones who have the  highest availability for communication. Almost none of the university’s higher‐level management is present in  the network. A further analysis of these networks reveals that the same non‐congruency is maintained when  paired  with  student‐teacher  relationship.  The  highest  communication  strength  is  maintained  by  the  middle  level individuals. Therefore the highest influence on students can be claimed by the middle level academics. 

5. Conclusions After conducting the previously‐presented experiments, it can be noted that the administrative part is ready to  implement knowledge management whereas the teaching and research community is not yet ready for such  initiatives. In order to improve this status, several guidelines can be suggested and targeted at the academia,  where  the  rift  between  culture  and  structure  is  most  severe.  Since  change  starts  at  the  top,  the  higher  management team should be more available for communication with the middle and low level communities.  This  might  be obtained  through:  classical all‐hands  meetings,  higher‐management discussions  with  low‐level  structures/departments and effective dialogues between HR staff members and academic and administrative  staff. Social networks such as Facebook can be an important tool in improving communication and openness  between  various  hierarchy  levels.  Another  point  to  be  addressed  is  the  employees’  age  distribution.  In  this  respect,  this  study  proposes  the  creation  of  programs  that  allow  responsibilities  to  be  assumed  by  any  university  staff  member  and,  equally  important,  that  encourage  younger  personnel  to  express  opinions,  proposals  and  act  on  them  properly.  Envisaged  changes  should  not  be  implemented  all  at  once,  a  certain  gradual  increase  would  allow  for  a  gentle  inter‐generation  exchange.  A  key‐point  in  implementing  this  measure is to create a safe environment in which anyone can speak their mind. By doing this, the gender bias  should  also  be  solved  since  a  safe  environment  provides  equal  opportunities  for  both  females  and  males  to  succeed. 

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Razvan Bogdan, Versavia Ancusa and Oana Caus 

Acknowledgements The authors would like to thank Mrs Nicolina Adamescu, UPT staff member, for the provision of the human  resources data and all university fellows that spent precious time answering quizzes and allowing permission  to use their Facebook networks images. 

References Beig, L., Mirian, M. S., Ghazi, T. M. S. & Kharrat, M., 2011. A Framework for the Assessment of Knowledge Management  Readiness of an organization while transferring into a Learning Organization. Passau, Germany, Proceedings of the  12th European Conference on Knowledge Management, pp. 74‐87.  Desouza, K. C. & Raider, J. J., 2006. Cutting Corners: CKOs and Knowledge Management. Business Process Management  Journal, 12(2), pp. 125‐135.  Holt, D., 2000. The Measurement of Readiness for Change: A Review of Instruments and Suggestions for Future Research.  Toronto, Canada, The Annual Meeting of TheAcademy of Management.  Holt, D. T., Bartczak, S. E., Clark, S. W. & Trent, M. R., 2004. The Development of an Instrument to Measure Readiness for  Knowledge Management. Hawai, IEEE Computer Society.  Jalaldeen, R., Karim, N. & Mohamed, N., 2009. Organizational readiness and its contributing factors to adopt KM processes:  A conceptual model.. Communications of the IBIMA, Volume 8, pp. 128‐136.  Krackhardt, D. & Hanson, J. R., 1993. Informal networks: The company behind the chart. Harvard Business Review, 71(4),  pp. 104‐113.  Kulkalyuenyong, P., 2012. Analysis of Organizational Culture and Commitment to the Ministry of Public Health under the  Central Administration: A Comparative Study of Service Agents and Policy Agents, School of Public Administration,  Chulalongkorn University, Thailand: PhD Thesis.  Lurie, S., Fogg, T. & Dozier, A., 2009. Social network analysis as a method of assessing institutional culture: three case  studies. Academic Medicine, 84(8), pp. 1029‐1035.  Mohammadi, K., Khanlari, A. & Sohrabi, B., 2009. Organizational Readiness Assessment for Knowledge Management.  International Journal of Knowledge Management, 5(1), pp. 25‐45.  Okamoto, K., Chen, W. & Li, X.‐Y., 2008. Ranking of closeness centrality for large‐scale social networks. Changsha, China,  Proceedings of the 2nd International Frontiers of Algorithmics Workshop (FAW'2008).  Stevenson, W. B. & Bartunek, J. M., 1996. Power, Interaction, Position and the Generation of Cultural Agreement in  Organizations. Human Relations, 49(1), p. 75.  Trent, M., 2003. Assessing organization culture readiness for knowledge management implementation: the case of  Aeronautical systems, Ohio: Air university.  Waldstrøm, C., 2003. Understanding Intra‐organizational Relations through Social Network Analysis, Department of  Organization and Management Aarhus School of Business: PhD Thesis.   

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Entropy vs. Organizational Learning and Dynamic Capabilities: The  Thermodynamic Analogy  Pavel Bogolyubov1, Evgeniy Blagov2 and Boyka Simeonova3  Dpt. of Management Learning and Leadership, Lancaster University Management School,  UK  2 Dpt. of Information Technologies in Management, Graduate School of Management, St.  Petersburg University, St. Petersburg, Russia  3 School of Management, Royal Holloway, University of London, London, UK  p.bogolyubov@lancaster.ac.uk  blagove@gsom.pu.ru  Boyka.Simeonova.2010@live.rhul.ac.uk 

1

Abstract:  The  paper  offers  a  theoretical  framework  bringing  together  the  matters  of  organizational  knowledge,  dynamic  capabilities,  organizational  learning,  knowledge  creation  and  innovation  by  drawing  parallels  with  thermodynamics  and  informatics  and  making  use  of  such  concepts  as  entropy,  chaos  and  disorder,  equilibrium  and  uncertainty.  The  idea  of  entropy originated in the XIX century as a means of explaining the basic principles governing the operation of – at the time  – steam engines, but gradually developing into one of the most fundamental concepts in modern Physics. Being effectively  a  measure  of  disorder  in  a  system  (and  thus,  in  its  original  sense,    explaining  the  system’s  inefficiency  through  the  dissipation  of  ‘useful’  energy),  it  made  its  way  into  quite  a  few  other  fields,  often  quite  remote  from  thermodynamics,  wherever the notions of uncertainty and/or chaos and disorder could be made use of. In informatics and cybernetics, for  example,  it  is  used  to  describe  how  the  act  of  acquiring  information  reduces  uncertainty  (e.g.,  if  one  checks  out  the  weather  forecast,  their  own  predictions  of  the  next  day’s  weather  are  likely  to  become  somewhat  more  accurate  in  probability terms). In economics and sociology it was in use, sometimes avoiding the direct application of the term, from  mid‐XX  century,  appearing  in  the  works  of  scholars  such  as  Shannon  and  Weaver,  Pareto,  Capecchi,  Möller,  McFarland,  Carvat and Kucera as well as others, leading to the formulation of the unified Social Entropy Theory in 1990 ((Bailey 1990)).  Somewhat  surprisingly,  no  examples  of  its  use  can  be  found  in  the  area  of  organizational  knowledge  and  capabilities;  it  would appear that the leap somehow has not yet been made. In this paper we attempt to bridge the gap by highlighting  the  analogy  between  an  organization  and  a  black  box  process  with  inputs,  internal  process  and  outputs,  not  entirely  dissimilar  from  Carnot’s  engine.  It,  in  turn,  lets  us  draw  parallels  and    make  a  number  of  propositions  concerning  the  relationships between capabilities, learning, knowledge and other related matters. The resulting framework allows further  elaboration  in  two  directions,  both  towards  the  development  of  more  advanced  mathematical  apparatus  and  its  operationalization with high applied potential. Although relying to a degree on some basic knowledge of scientific concepts  and making fairly limited use of mathematical notation, the paper is aimed at the general audience and, hopefully, will be  of interest to scholars and practitioners alike.     Keywords: entropy, organizational learning, learning organization, organizational capabilities, dynamic capabilities 

1. Introduction: The use of entropy and related concepts in social sciences  Although  originally  a  natural  sciences  concept,  entropy,  as  well  as  related  matters  such  as  equilibrium,  uncertainty,  information  and  various  re‐formulations  of  uncertainty  measures  avoiding  the  direct  use  of  the  term  (e.g.,  such  as  Shannon  and  Weaver’s  H  measure  ‐  (Shannon  and  Weaver  1949)  has  been  used  in  economics  and  sociology  beginning  from  the  first  half  of  the  XX  century.    For  example,  Pareto’s  work  on  equilibrium (Pareto 1935) has arguably paved the way for the development of the field, and it became quite  popular in functionalism (e.g., (Parsons and Shils 1951)). The application of the entropy in the statistical sense  begun  in  the  1960s  (Coleman  1964)  and  gradually  intensified  through  the  work  of  such  sociologists  as  Capecchi,  Möller,  McFarland,  Charvat  and  Kucera  and  so  on  (Capecchi  and  Möller  1968),  (McFarland  1969),  (Charvat and Kucera 1970) to give a fairly random  few examples. Several decades of development culminated  in formulation of the unified Social Entropy Theory in 1990 (Bailey 1990).    It is, however, somewhat surprising that despite its close link to the general systems theory and the popularity  of the systems approach to organizational learning  ‐ first and foremost due to Senge’s work (Senge 1992), as  well as the connection with the information theory, entropy as a concept remains virtually unused in relation  to the organizational learning. To the best of our knowledge, so far there have been only two papers published  on  it:  (Bingquan,  Likai  et  al.  2009)  used  an  entropy‐like  approach  to  measuring  the  learning  organization’s  effectiveness,  and  the  other  one  (Xueguo  2008),  apparently  uses  a  similar  approach  towards  organizational 

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Pavel Bogolyubov, Evgeniy Blagov and Boyka Simeonova  learning, although it is only published in Mandarin in a journal that does not appear to be in wide circulation in  the West.     In this paper, we attempt to bridge the gap and to outline a number of possibilities for the use of entropy and  the related concepts based on thermodynamics, statistical mechanics and information theory, to describe and  measure various processes associated with organizational learning.   

2. Entropy: the basic definitions  The  concept  of  entropy  developed  in  the  mid‐XIX  century  with  the  advent  of  a  branch  of  physics  called  thermodynamics – a field (in its classical form), according to Merrian‐Webster’s Dictionary ‐  ‘that deals with  the  mechanical  action  or  relations  of  heat’  (Anonymous  2012).  At  the  beginning,  the  thermodynamic  understanding  of  entropy  came  out  of  Carnot’s  work  related  to  the  ideal  ‘heat  engine’  –  a  machine  (steam  engines  originally)  that  utilises  a  flow  of  thermal  energy  from  a  heat  reservoir  to  a  heat  sink,  producing  mechanical  work  as  a  consequence,  and  where  entropy  increases  if  a  portion  of  the  energy  is  made  unavailable  to  produce  work.  Closer  to  the  end  of  the  century  the  work  of  Boltzmann  on  developing  the  statistical mechanics’ understanding of entropy begun treating it as a measure of order or disorder, and this is  still a popular understanding of its fundamental meaning (Anonymous 2012).    The ‘disorder’ meaning of the concept could be more easily explained by examining the following formula for a  system with a set of i discrete energy states Ei (the so‐called Gibbs entropy):   

where S stands for entropy, kB  is Boltzman’s constant, pi is a probability of the system to be in the given state,  and the summation is across all possible states. As follows from the formula, the entropy is at zero if the only  one state is possible ‐ i.e., the perfect order, and it reaches maximum if all states are equally probable, i.e.,  p1=p2=…=pn=1/n.     Putting  together  the  two  definitions  of  entropy,  we  would  arrive  at  a  conclusion  that  the  more  chaotic  a  system is, the greater becomes its ability to distribute energy evenly making it unavailable to do the work.    Arguably one of the most fundamental laws of physics is the second law of thermodynamics which states that  the entropy of closed system cannot decrease, or:    ∆S ≥ 0      (2)    In other words, a closed system will always gravitate towards the state of the maximum disorder.    Another  understanding  of  entropy  came  later  on  from  the  information  theory  (discrete  Shannon  entropy  ‐  (Frigg and Werndl 2010):    

  which,  the  obvious  exclusions  of  the  constant  and  the  logarithm’s  base,  is  identical  to  (1).  The  probabilities  included in this formula, although somewhat open to interpretation, mean the ‘belief’ that a system can be  found  in  a  particular  state,  the  word  itself  being  employed  here  in  a  ‘justified  true’  meaning,  rather  than  anything more subjective.     The meaning of the information science’s definition of entropy follows directly from the formula: the more we  know  about  the  system,  the  more  certain  we  can  be  about  its  state,  thus  acquiring  information  leads  to  a  reduction of uncertainty and, as a consequence, entropy. If we don’t have any information about the system,  all  states  are  equally  probable,  p 1=p2=…=pn=1/n,  and  the  entropy  is  at  its  maximum  value,  S(P)=log  n;  conversely, if we have acquired enough data to be certain about its state, only one pi=1, and  S(P) = 0. 

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3. The application of the concepts to organizational learning  In order to illustrate the possibilities the thermodynamic analogy opens up, we shall refer to the mathematical  metaphor  suggested  by  (Winter  2003)_ENREF_14,  as  cited  in  (Vera,  Crossan  et  al.  2011).  To  illustrate  it,  we  shall  use  a  crude  schematic  representation  of  a  model  organization  as  an  entity  that  takes  resources  (A),  processes them (B) and produce outputs (C) (Fig. 1): 

Inputs (A)

Resource processing (B)

Outputs (C)

Figure 1: The schematic representation of a firm  (Winter 2003), defines operational capabilities as such B that leads to constant C, i.e., C’s first derivative being  zero  (although it’s worth pointing out that it is the A/C ratio that we are predominantly interested in, i.e., we  would be expecting the same outputs from the same inputs):        If a company exhibits dynamic capabilities, it should be able to produce more outputs with constant inputs,  and the derivative of the A/C ratio over the time will be non‐zero:         which  conceptually  equates  to  single‐loop  learning,  i.e.,  that  the  organization  is  getting  better  and  doing  its  ‘day job’. Should things go really well, they will challenge their fundamental assumptions and will also become  better at learning how to improve, thus leading to the second derivative being greater than zero:        What is important, however, is the obvious similarity between the representation on Fig. 1 and Carnot’s heat  engine: both have some inputs (heating up the heat reservoir), a recombination process (heat transfer from  the reservoir to the sink) and the output (mechanical work).      The thermodynamic analogy – the Carnot engine metaphor, basic principles of thermodynamics and especially,  the application of the entropy as a concept allows us to come up with a number of propositions:  P1:  In  an  organization  that  acts  as  a  closed  system  –  i.e.,  without  significant  amounts  of  information and knowledge exchange with the outside world – the entropy will increase over the  time  and  eventually  reach  its  maximum.  This  is  what  Argyris  referred  to  as  ‘dry  rot’  (Argyris  1970),  although  we  would  rather  relate  it  to  a  notion  of  spontaneous  organizational  forgetting/unlearning without making a value judgement. This leads to:  P2:  In  an  organization  as  a  closed  system,  the  operational  capability  will  deteriorate  over  the  time:         unless counteracted with external inputs decreasing system’s entropy, i.e., negentropy  

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Pavel Bogolyubov, Evgeniy Blagov and Boyka Simeonova  P3:  The  organizational  learning  of  any  kind  in  a  ‘closed’  company  is  impossible,  and  it  requires  interaction  with  the  outside  world,  which  closely  resonates  with  such  models  of  learning  organization  as,  e.g.,  Dixon’s  (Dixon  1999),  which  relies  heavily  on  external  acquisition  and  internal  dissemination  of  knowledge  and  challenges  the  approaches  such  as  Kaizen,  whereby  operational improvements are expected to originate predominantly from within   P4: An influx of information and knowledge from outside the company will decrease the entropy  and increase capabilities, thus leading to (5), but not necessarily (6), as well as that   P5:  In  the  long  run,  that  is  to  say,  beyond  the  timeframes  of  mere  fluctuations,  the  only  innovation  possible  is  that  of  the  open  kind,  i.e.,  the  process  of  innovation  requires  a  sufficient  degree of negentropy brought from the outside.  Following the Carnot’s Theorem that states that no engine can work in the same conditions more efficiently  than the ‘ideal’ one, the following can be proposed:   P6: Theoretically, there is an upper limit for the operational capability (expressed in the A/C ratio)  in the set of given circumstances. 

4. Challenges, limitations and further steps  The propositions outlined above are theoretical and rely on a rather idealistic view on organizations as closed  systems, which is hardly a reality (Bailey 1990). In this sense, given that virtually any social system will be open  to a degree, it would be more useful to think about it in terms of a dynamic equilibrium between the influx of  knowledge and learning from the outside and the organizational forgetting/unlearning, whereby the sum total  of the two will be zero, thus approximating the closed system state.     Furthermore,  at  this  stage  we  are  not  making  a  distinction  between  the  definitions  of  entropy  arising  from  thermodynamics, statistical mechanics and information theory, and although a fair amount of work has been  done  to  prove  fundamental  similarities  between  the  three  ‐  e.g.  (Frigg  and  Werndl  2010)_ENREF_8,  we  are  fully  aware  of  the  differences  between  them.  Instead  of  elaborating  on  it,  we  are  making  use  of  the  understanding  of  entropy  as  a  measure  of  disorder  and  its  link  to  (in)efficiency  of  a  system  in  terms  of  its  capability of producing outputs.     The question arising from this is that of the link between the degree of orderliness in an organization and its  capabilities. Does it mean that a rigidly structured organization will have better capabilities than a ‘free‐form’  one? The intuitive answer would be a no, or at least a not necessarily, although whether this is true and the  reasons  for  that  –  one  way  or  another  –  would  need  further  development.  There  is  also  the  question  of  emergence  and  self‐organization,  which  may  potentially  link  to  such  matters  as  swarm  intelligence,  neural  networks and all phenomena related to chaos; e.g. (Gleick 1987).    Besides,  all  points  discussed  above  relate  to  the  ‘classical’  thermodynamics  and  ignore  its  non‐equilibrium  variety, which in itself poses a number of questions and has a variety of exciting opportunities to explore, such  as the applicability of phase transitions metaphor and so on.    The  next  challenge  for  all  propositions  would  be  testing  them,  which  will  inevitably  involve  their   operationalization. How exactly can entropy and the flows of knowledge and learning be measured? What can  the practical implications be? What are the applicability boundaries, apart from the obvious limitations of the  model? All these represent potential areas for further research. 

References Anonymous. (2012). "Definition of Entropy."   Retrieved 23/10, 2012, from  http://oxforddictionaries.com/definition/english/entropy?q=entropy.  Anonymous. (2012). "Definition of Thermodynamics."   Retrieved 23/10, 2012, from http://www.merriam‐ webster.com/dictionary/thermodynamics.  Argyris, C. (1970). Intervention Theory and Method: a Behavioral Science View. Reading, Mass., Addison‐Wesley.  Bailey, K. D. (1990). Social Entropy Theory. New York, State University of New York Press.  Bingquan, H., B. Likai, et al. (2009). Evaluation of learning organization applying the entropy method. 2nd International  Conference onPower Electronics and Intelligent Transportation System (PEITS).  Capecchi, V. and F. Möller (1968). "Some Applications of Entropy to the Problems of Classification." Quality and Quantity 2:  63‐84. 

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Pavel Bogolyubov, Evgeniy Blagov and Boyka Simeonova  Charvat, F. and J. Kucera (1970). "On the Theory of Social Dependence." Quality and Quantity 4: 325‐353.  Coleman, J. (1964). Introduction to Mathematical Sociology. New York, The Free Press.  Dixon, N. (1999). The Organizational Learning Cycle: How We Can Learn Collectively. London, Gower Publishing.  Frigg, R. and C. Werndl (2010). Entropy – A Guide for the Perplexed. In Probabilities in Physics. B. C. and S. Hartmann.  Oxford, Oxford University Press.  Gleick, J. (1987). Chaos: Making a New Science, Vintage.  McFarland, D. D. (1969). "Measuring the Permeability of Occupations Structures: and Information‐Theoretic Approach."  American Journal of Sociology 75: 41‐61.  Pareto, V. (1935). The Mind and Society. New York, Harcourt, Brace.  Parsons, T. and E. A. Shils (1951). Toward a General Theory of Action. New York, Harper and Row.  Senge, P. M. (1992). The fifth discipline: the art and practice of the learning organization, Century Pubs.  Shannon, C. and W. Weaver (1949). The Mathematical Theory of Communication. Urbana, The University of Illinois Press.  Vera, D., M. Crossan, et al. (2011). A Framework for Integrating Organizational Learning, Knowledge, Capabilities, and  Absorptive Capacity. Handbook of Organizational Learning and Knowledge Management. M. Easterby‐Smith and M.  Lyles. Chichester, John Wiley and Sons.  Winter, S. (2003). "Understanding Dynamic Capabilities." Strategic Management Journal 24: 991‐995.  Xueguo, X. (2008). "Study on the Evaluation of Organizational Learning Based on Entropy Value." Contemporary Economy &  Management 11. 

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A new Marketing Audit Tool for Knowledge Intensive Business  Services  Ettore Bolisani and Enrico Scarso  Department of Management and Engineering, University of Padua, Vicenza, Italy  ettore.bolisani@unipd.it  enrico.scarso@unipd.it    Abstract:  The  paper  focuses  on  knowledge  marketing  in  Knowledge‐Intensive  Business  Services  (KIBS)  companies.  Marketing  is  a  special  challenge  for  KIBS,  and  requires  a  shift  from  traditional  strategies  –  generally  applied  to  manufacturing sectors and mostly based on the classic notion of marketing mix (i.e., product, price, promotion, and place)  –  to  new  approaches  that  stress  the  importance  of  customer‐provider  interactions.  Since  KIBS mainly  deliver  knowledge  (embedded  in services,  consulting  activities,  and  problem solving  capability),  marketing  activities  must  communicate  the  company’s ability to manage knowledge exchanges with customers effectively. Integral part to the implementation of an  appropriate marketing strategy is the need for companies to audit their marketing activities. Marketing audit has its place  in the management literature but is generally targeted to manufacturing or retailing companies. In light of this, the paper  proposes  a  novel  approach  to  marketing  audit  for  knowledge‐based  companies  that  focuses  on  relational  and  cognitive  capabilities, and consists of a questionnaire‐based tool subdivided in sections, each of which considers a particular stage of  the  customer‐provider  relationship.  It  is  assumed  that  the  effective  delivery  of  these  services  requires  intense  and  continuous  exchanges  of  knowledge  between  customer  and  provider,  and  must  be  connected  to  the  specific  business  environment (in terms of markets, competitors, etc.). Consequently, the marketing capability of a company is seen in terms  of  its  ability  to  fruitfully  interact  with  customers  in  the  conditions  of  the  particular  operating  environment.  The  questionnaire can help executives of KIBS companies to self assess the “marketing positioning”  of their firms. Due to its  easiness  of  use,  it  is  particularly  suitable  for  small  companies.  The  paper  describes  the  particular  example  of  a  questionnaire developed for ICT services firms. This tool has been tested with two small companies, and the results of this  assessment are reported.    Keywords: knowledge marketing, marketing audit, knowledge‐intensive business services, ICT companies, knowledge  exchanges 

1. Introduction The  paper  deals  with  marketing  approaches  adopted  by  Knowledge‐Intensive  Business  Services  (KIBS)  companies.  According  to  the  extant  literature,  unique  features  denote  these  companies  (Strambach,  2008;  Muller  and  Doloreux,  2009;  Landry  et  al,  2012):  these  strongly  affect  the  effectiveness  of  their  marketing  strategies.  First,  their  main  production  input  and  output  consist  of  knowledge,  directly  delivered  under  the  form  of  consulting,  or  embedded  in  artefacts  and  services.  Second,  their  business  is  mostly  based  on  the  exploitation of knowledge possessed by their employees. Third, the provision of knowledge‐intensive services  requires an in‐depth interaction between supplier and user, who are both involved in cognitive exchanges and  learning  processes  (Bettencourt  et  al,  2002).  Fourth,  services  are  generally  delivered  under  the  form  of  a  process  of  problem  solving  in  which  KIBS  companies  adapt  their  knowledge  to  the  specific  requirements  of  individual clients. Fifth, they often act as interfaces between the global sources of knowledge and the cognitive  needs of end users (Smedlund, 2006). Sixth, their innovative capability is directly connected to the acquisition,  processing, capitalisation and delivery of new knowledge (Amara et al., 2009).    As  highlighted  in  previous  studies  (Bolisani  and  Scarso,  2012a;  Bolisani  et  al,  2012),  these  features  make  marketing  a  special  challenge  for  KIBS,  and  call  for  a  shift  from  traditional  marketing  strategies  –  generally  applied to manufacturing sectors and mostly based on the classic notion of marketing mix (i.e., product, price,  promotion, and place) – to new approaches that stress the importance of customer‐provider interactions (see  e.g.  the  new  “service‐dominant”  paradigm  of  marketing  proposed  by  Vargo  and  Lusch,  2004).  Indeed,  since  KIBS mainly deliver knowledge (embedded in services, consulting activities, and problem solving capability) to  their  clients, marketing activities  should  communicate  a  company’s  ability  to  provide  valuable  knowledge  to  customers.    Integral part to the implementation of an appropriate marketing strategy is the need for companies to adopt  proper  procedures  to  audit  all  the  aspects  of  their  marketing  activity.  In  light  of  this,  the  paper  proposes  a  novel  approach  to  marketing  audit  for  KIBS  companies,  which  focuses  on  their  peculiarities.  Especially,  it  considers  their  relational  capabilities,  i.e.  the  capabilities  to  provide  valuable  knowledge  to  customers 

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Ettore Bolisani and Enrico Scarso  throughout the whole trading relationship. The approach consists of a questionnaire‐based tool subdivided in  sections,  each  of  which  focuses  on  a  particular  stage  of  the  typical  customer‐provider  relationship.  It  is  assumed  that  the  effective  delivery  of  services  requires  an  intense  exchange  of  knowledge  in  repeated  interactions  between  customer  and  provider.  Accordingly,  the  marketing  capability  of  a  KIBS  company  is  evaluated  in  terms  of  its  capability  to  fruitfully  interact  with  customers,  in  relation  to  the  particular  environment  (i.e.,  markets,  competitors,  etc.)  in  which  it  operates.  The  questionnaire  can  help  company  executives to self assess their “marketing positioning”; due to its easiness of use, it is particularly suitable for  small companies, as many KIBS are.    The paper presents a particular version of the marketing audit tool specifically developed for ICT services. The  tool has been tested with two small companies. The results of this assessment are reported, and its application  prospects are discussed.    The paper articulates as follows. In the next section, the main notions and tools of marketing audit are briefly  recalled.  The  third  section discusses  the  significance  of  a relational  marketing  approach  for  KIBS  companies,  and  how  the  adoption  of  this  approach  can  influence  the  design  of  appropriate  marketing  audit  tools.  The  following sections describe the audit tool developed in this study, how it has been built, and tested. The last  section proposes a final evaluation of the work conducted so far. 

2. Marketing audit  Marketing audit (MA) is an established notion that dates back to late 1950s (Schuchman, 1959), when the first  definitions  and  elements  (goals,  issues,  types  and  contents)  were  given.  MA  can  be  defined  as  a  comprehensive,  systematic,  independent  and  periodic  examination  of  a  company’s  marketing  environment,  goals, strategies and activities, for determining problematic areas and opportunities, and for recommending an  action plan to improve the company’s marketing performance (Kotler et al, 1977). This definition points out  that MA: a) is broad, covering all marketing aspects of a company; b) should be conducted by an independent  person;  c)  is  systematic,  since  it  involves an orderly sequence of steps; d) should be performed periodically.  MA  bases  on a  three‐step  procedure consisting  of:  a)  setting  its  objective  and  scope; b)  getting  the data;  c)  preparing and presenting the report. The second step, collecting the data, is generally the most time‐spending.    Over the years, MA has evolved, and has assumed a prominent place in the marketing management literature  (Rothe et al, 1997). However, even though evaluating the marketing effectiveness of an organisation can be  important  both  for  manufacturing  and  service  companies,  the  current  state  of  the  art  of  the  marketing  discipline  generally  neglects  the  latter  (Pimenta  da  Gama,  2011).  Little  attention  is  given  to  the  peculiar  characteristics  of  services,  with  the  only  remarkable  exception  of  Berry  et  al  (1991)  who  developed  an  integrative audit framework for service marketing (i.e., ISME ‐ Index of Services Marketing Excellence). Beyond  any judgement on the usefulness of this framework, an unquestionable contribution of these authors is that  they underline the need for a novel approach to MA that takes into account the distinctive characteristics of  services. 

2.1 MA tools  The most popular marketing audit tools consist of a checklist of diagnosis questions that are submitted to one  or several “key people” in a company. These questions can be open‐ended or closed‐ended (often Likert‐type),  and range from a few dozen to more than 1,000 (Wilson, 2002). Questions are often grouped into categories  or  topic  areas,  in  relation  to  the  main  aspects  on  which  one  wants  to  focus  the  assessment.  There  is  no  consensus about these aspects, and different authors propose different dimensions of analysis (see e.g., Berry  et al, 1991; Kotler et al, 1977; McDonald, 1982; Wilson, 2002). As well underlined by Pimenta da Gama (2012),  the logic behind the creation of a checklist is the effort to offer a comprehensive set of questions covering all  the  aspects  of  marketing  that  may  need  improving.  In  principle,  the  more  detailed  and  complete  a  list  of  question is, the more likely the relevant points are covered. However, too many questions can require much  time to be answered, and what’s more the analysis becomes complex. A trade‐off between easiness of use and  completeness must be sought. In addition, it is extremely difficult to design a checklist that works well in all  situations, and local adaptations to the single case might be necessary. Finally, it must be noted that almost all  the checklists that can be found in the literature are based on the traditional manufacturing marketing logic  that refers to the well established 4Ps approach.   

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Ettore Bolisani and Enrico Scarso   

3. KIBS, knowledge marketing, and implications for MA  To develop a checklist that can be appropriate to KIBS companies, it is first necessary to recall some distinctive  features of those firms. First of all, as the literature stresses widely, delivering a knowledge‐intensive business  service  requires  several  interactions  between  client  and  provider,  during  which  continuous  knowledge  exchanges occur (Figure 1). The nature of these interactions is affected by the knowledge‐intensive nature of  those services that produces information asymmetry, so that clients can be unable to fully evaluate the quality  of service delivered. This raises special challenges for marketing. In particular, as Bagdoniene et al (2007) and  Aarikka‐Stenroos  and  Jaakkola  (2012)  affirm,  KIBS  companies  should  adopt  a  “relationship  marketing”  approach. This means understanding the dynamics of supplier‐customer relationships, how they evolve, and  what factors affect their development, with the ultimate purpose of re‐organising of the company’s processes,  and  re‐framing  the  traditional  marketing  approach  based  on  the  4Ps.  Secondly,  many  KIBS  companies  (and  particularly  those  considered  in  this  paper)  have  a  very  small  size,  and  this  impacts  significantly  on  their  marketing approaches and activities, including auditing. 

Figure 1: Knowledge exchanges between KIBS and clients (from: Martinez‐Fernandez and Miles, 2006)  Useful suggestions to re‐frame the traditional marketing approach can be drawn from the recently proposed  “service‐dominant” (SD) logic (Vargo and Lusch, 2004) that considers services (defined as the primary unit of  any economic exchange) as the application of specialized knowledge and skills for the benefit of clients. This  logic suggests that what a firm provides to clients is not simply manufactured outputs, but rather knowledge  inputs of a continuing value‐creation process (Lusch et al, 2008). In view of that, the goal of any company is to  customize  its  offering  and,  by  recognising  that  clients  are  always  value  producers,  to  maximise  their  involvement in the customisation effort, to better fit their needs. Conforming to this logic, marketing is more  than just a functional area of a company: it represents a firm’s distinctive capability, whose functions are to  identify  and  develop  the  company’s  core  competences,  and  deliver  them  as  value  propositions  that  offer  potential  competitive  advantage.  Accordingly,  building  useful  relationships  with  clients,  where  intense  knowledge exchanges occur, becomes vital. In the SD logic, all employees are involved in delivering services,  with  the  ultimate  goal  of  satisfying  the  costumer,  and  this  extends  marketing  well  beyond  the  marketing  department (Ballantyne and Varey, 2008).    Ultimately,  the  proponents  of  the  SD  logic  claim  that  the  role  of  marketing  should  consist  of  managing  communicative  interactions  and  facilitating  key  relationships  and  knowledge  exchanges  with  clients.  Accordingly, companies should focus on the value‐in‐use that their products/services can have for their clients  rather than just on their features (Payne et al, 2008). This requires understanding the client’s value generating  process,  and  implies  a  reversal  of  the  traditional  “making,  selling  and  servicing”  approach,  to  a  “listening,  customising  and  co‐creating”  approach,  where  encounter  processes  play  a  crucial  role.  To  sum  up,  the  capability to acquire and share knowledge with clients becomes integral to any marketing process.    When it comes to MA, three aspects should be considered. Firstly, it is unlikely that small companies (as KIBS  often are) can resort to independent external auditors or consultants. Hence, it is essential that they can utilise 

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Ettore Bolisani and Enrico Scarso  methods  and  tools  directly  on  their  own.  Secondly  (and  consequently),  a  MA  tool  should  be  as  simple  as  possible, both in data collection and interpretation. So, it would be preferable to have a checklist with a limited  number  of  easy‐to‐answer  questions.  Thirdly,  the  goal  of  MA  should  be  not  to  push  all  marketing  activities  towards  a  “maximum  score”:  as  a  matter  of  fact,  and  especially  considering  the  small  size  of  KIBS,  it  is  not  always true that “more is better”. On the contrary, in some situations, to push marketing efforts over a certain  threshold can be even counterproductive, or in any case uselessly expensive. 

4. Building a MA tool for KIBS   In this section, we present a version of the new tool that was compiled for a particular category of KIBS, i.e. ICT  services.  The  MA  tool  illustrated  here  is  based  on  the  points  previously  discussed  and  in  particular  the  following:  ƒ

marketing is a process that involves all the stages of a provider‐customer relationship; an analysis of each  of these stages is therefore essential; 

ƒ

in each stage, providers must have the capability to deliver valuable knowledge inputs to customers (so  that they can utilise them profitably) and to “learn” from customers (i.e., to acquire fresh knowledge from  them); 

ƒ

knowledge exchanged  concerns  not  only  technical  aspects  (e.g.  features  of  the  delivered  services,  or  customer requirements) but also to managerial or relational issues (for  example: how clients assess the  delivered services, how they select providers, how much they consider reputation as a key element, etc.). 

Based on these points, a checklist of questions was prepared. The purpose of this checklist is to enable a self‐ assessment  by  companies  for  revealing  weak  areas  and  opportunities  of  improvement,  and  facilitating  adjustment of marketing strategies to strengthen provider‐customer relationships. The design of the MA tool  was based on the following steps:    a)  Building  a  model  of  interactions  and  knowledge  exchanges  during  the  typical  relationships  between  ICT  companies  and  their  clients  that  occur  in  the  services  delivery  process;  for  this  purpose,  it  was  possible  to  exploit the results of previous studies (Bolisani and Scarso, 2012b);    b)  Identification  of  a  number  of  “critical  areas”  for  MA.  Specifically,  the  ICT  delivery  process  was  split  into  different stages, ranging from the early formulation of a sales strategy to the after‐sales activities; each stage is  characterised  by  specific  relational  issues  that  call  for  appropriate  marketing  approaches,  where  the  firm  needs to acquire knowledge from the market and to deliver knowledge to clients;    c) For each stage, formulation of a number of questions that assess the capability and maturity of relational  marketing by a company;    d)  Once  a  preliminary  version  of  the  MA  checklist  was  ready,  a  test  was  run  with  two  pilot  companies.  The  checklist  was  tested  by  two  small‐sized  ICT  services  firms.  This  helped  to  evaluate  its  easiness  of  use  and  usefulness, and to correct errors;    e) A final version of the tool (which was named “AUTOMARK”) was then compiled.    AUTOMARK  consists  of  a  questionnaire  with  around  80  questions  that  can  be  submitted  to  a  company  executive  (or  to  more  executives)  in  a  single  company,  and  serves  as  a  self‐diagnosis  tool  for  ICT  services  marketing. Actually, when the design of AUTOMARK was being considered, different options arose.    The  first  was  to  evaluate  answers  to  questions  in  absolute  terms.  This  approach  is  popular  in  MA  tools  and  consists of measuring the maturity of a company by calculating “how high” the marks in each question and/or  in all questions are. In other words, it is assumed that a company can be successful only if it excels in all areas.  We considered this approach unsuitable. First of all, KIBS are often small companies, so it is unlikely or difficult  that they can reach top ranks in all areas: hence, this way of using AUTOMARK can be misleading. Secondly, it  may  be  useless  (and  costly)  to  reach  top  marks  in  all  marketing  activities,  because  their  usefulness  and  effectiveness may depend on peculiar market conditions or competitive environments. In other words, it is not  always true that “more is better”.   

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Ettore Bolisani and Enrico Scarso    The second option was to perform a benchmarking analysis. This means that the same questionnaire has to be  submitted  to  several  companies  with  similar  characteristics  (for  example,  in  the  case  of  ICT  services,  ERP  producers  in  the  same  market).  In  this  case,  a  company  can  assess  its  relative  positioning  and  marketing  capabilities in comparison with others. This is a potentially interesting approach, but difficult to perform: it is,  in fact, necessary that several companies accept to use the same MA tool and that they share their answers.    The third option was to apply MA as a standalone tool, employed in the single company. This means that the  questionnaire is used as a self‐diagnosis tool. Although it does not assess the absolute or relative positioning of  a  company  compared  to  others,  its  usefulness  is  that  it  allows  to  measure  the  way  a  company’s  marketing  activities are aligned to its own expectations or perceptions of “what should be done” in a particular market or  environment.    For reasons of convenience and simplicity, the last option was preferred. So, AUTOMARK can be seen as a self‐ diagnosis MA tool that allows a single company to assess its relational marketing capabilities compared to its  own expectations or perceptions of what should be done in that particular environment. 

5. AUTOMARK: Description and use  The  questionnaire  consists  of  two  symmetric  parts  (Table  1).  The  first  part  regards  the  marketing  activities,  tools,  and  approaches  that  currently  characterise  the  company,  and  particularly:  the  way  knowledge  is  exchanged from and to the clients, the way this knowledge is used to implement marketing‐related activities  and sell services, the way marketing usefulness is measured, etc. The second relates to the way markets and  competitive  environments  (and,  consequently,  marketing  requirements  deriving  from  the  environment)  are  currently seen by the company executives.    Each part splits into 8 sections that focus on the different stages of a provider‐customer relationship, namely  (see appendix; the complete questionnaire is omitted for reasons of space, the authors can be contacted for  further details):  ƒ

knowledge about competitive environment 

ƒ

markets and marketing/commercial strategy  

ƒ

commercial image 

ƒ

first contact with clients 

ƒ

customer needs 

ƒ

proposal formulation 

ƒ

implementation of a service/product/solution 

ƒ

after‐sales

Table 1: Structure of AUTOMARK  Questions regarding the company’s actual approaches to  relational marketing  1. collection of knowledge about market/environment  2. marketing/commercial strategy  3. commercial image  4. management of first contacts with clients  5. collection of customer needs  6. proposal formulation  7. implementation of service/product/solution  8. after‐sales activities 

Questions regarding the relational needs in the  market/environment where the company operates  1. complexity of knowledge about environment  2. complexity of market  3. relevance of image in markets  4. importance of first contacts with clients  5. difficulty of collecting customer needs  6. difficulty of proposal formulation  7. complexity of services/products/solutions  8. relevance of after‐sales relationships 

The questionnaire  is  designed  to  be  self‐used  in  a  single  company  that  is  willing  to  understand  how  its  relational marketing activities are actually implemented and conducted, and how they match the company’s  perceptions of the competitive environment. For example, the average marks given to the section “collection  of customers needs” in the first part measure the way knowledge about customers needs is currently collected  by  the  company:  approaches  used,  tools  implemented,  procedures  followed,  etc.;  conversely,  the  average  marks  given  to  the  corresponding  section  in  the  second  part  (“difficulty  of  collecting  customer  needs”) 

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Ettore Bolisani and Enrico Scarso  measure how this issue is considered to be important given the particular environment where the company  operates. If the marks are comparable, this means that the company’s marketing strategy is aligned with the  “requirements”  that  come  from  the  market;  if  marks  of  the  first  part  are  higher,  the  company  has  invested  “too much” in these activities than it might be required; if they are lower, the company should invest more.    Each section is compounded by a number of questions (between 4 and 7). To each question, respondents are  requested to express the number (ranging from 1 to 7 in a Likert scale) that best represents the appropriate  answer. The questionnaire can be submitted to just one company executive (for example, the sales director or  the  marketing  director),  or  to  different  executives  in  the  same  company  (for  example,  part  1  of  the  questionnaire  can  be  submitted  to  the  sales  director,  and  part  2  to  the  CEO,  etc.).  Average  marks  are  then  calculated for each sub‐section, and compared to one another as previously described. The tool easily allows  to build a radar chart, which is a powerful way to display the results of the analysis (as an example, see Figure  2). The radar chart presents the average marks for each section listed in Table 1: it is possible to compare the  assessments  of  the  internal  relational  marketing  activities  with  those  of  the  perception  of  the  external  environment,  point  by  point.  These  results  can  be  used  by  executives  to  verify  the  alignment  of  marketing  strategies to the perceived external environment, and to take corrective actions. It can also be used as a tool  to promote self awareness in the company, and can more generally be seen as an opportunity for discussing  the state of the company with employees. 

Key of questionnaire sections:  1 = knowledge about environment 2 = markets & commercial strategy 3 = commercial image 4 = first contact with clients 5 = customer needs 6 = proposal formulation 7 = implementation of a service/product/solution 8 = after-sales Plain line = company’s internal activities Dotted line= perception of the environment

Figure 2: Example of radar chart resulting from a test of AUTOMARK self‐assessment 

6. Testing and results  The  questionnaire  was  initially  discussed  with  a  consultant  that  highlighted  critical  questions  that  may  have  been  difficult  to  understand  by  a  typical  ICT  executive.  Since  the  questionnaire  should  be  used  by  company  executives with no assistance, it is important that questions are clearly understood. From the discussion, it also  emerged that questions in the questionnaire should be randomly mixed, in order to reduce the possibility that  the answer given to a question influences the answer to the following one of the same section.    The first complete version of AUTOMARK was then tested with an ICT services company, but in presence of  one  of  the  researchers.  This  highlighted  residual  understanding  difficulties  and  minor  errors.  After  that,  AUTOMARK  was  revised  and  submitted  to  a  second  company,  where  3  executives  (CEO,  marketing  director  and communications director) compiled the questionnaire independently from one another. The results made  it possible to correct minor mistakes and to revise an entire section that provided contrasting results. 

7. Conclusion The  assumption  on  which  AUTOMARK  is  based  is  that  KIBS  companies  must  necessarily  enhance  their  relational marketing capabilities in order to successfully place their knowledge‐based services on the market.  Implementing relational marketing in an SD logic implies that companies have to develop capabilities and tools 

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Ettore Bolisani and Enrico Scarso    to  exchange  knowledge  with  customers  effectively  during  the  various  stages  that  generally  compound  the  service delivery process.    Compared to other MA tools, AUTOMARK is still a questionnaire, but its setting is different. Instead of a focus  on  the  classic  4Ps  and,  more  generally,  the  typical  activities  that  characterise  marketing  in  manufacturing,  AUTOMARK takes into account the specific knowledge‐based interactions that occur between a KIBS company  and its clients.    Having  said  that,  the  tool  has  some  limitations.  First  of  all,  it  is  designed  for  ICT  services  specifically:  other  categories  of  KIBS  need  different  questionnaires.  In  any  case,  AUTOMARK  can  represent  a  “model”  for  the  development of other versions, all based on the same guidelines.    In addition, the tool has been tested with two companies so far. There is therefore the need for more testing  to verify if it represent the true state of affairs and to improve the tool accordingly. In particular, although we  are  talking  about  ICT  companies,  nonetheless  these  can  be  very  different  to  one  another,  and  so  can  be  marketing  approaches.  The  capability  of  AUTOMARK  to  assess  different  companies  effectively  has  to  be  demonstrated.    Finally, it should be remembered that AUTOMARK is a self‐diagnosis tool. Hence, its results have not a value  “in absolute”, but can only be intended as alarm signals that must inspire a discussion in the company. More  than  number  themselves,  it  is  this  discussion  that  can  provide  managers  with  ideas  for  improving  relational  marketing activities of their companies. 

Appendix: Details of AUTOMARK questions  Questions regarding the company’s current approaches to relational marketing  collection of knowledge about market/environment  seven questions about the capability of companies to collect knowledge of the competitive environment, the resources  used for that, and how this knowledge is employed  marketing/commercial strategy  five questions about the centrality of marketing in the company, and the resources used for this  commercial image  four questions about how the commercial image of the company is made explicit, and how this knowledge is  transmitted to clients  management of first contacts with clients  seven questions about how the company seeks and manages contacts with new clients  collection of customer needs  six questions about how knowledge about customer needs is collected and capitalised internally  proposal formulation  five questions about how the elements of knowledge of markets and clients are transferred into a formally structured  commercial proposal that must be understandable by clients  implementation of service/product/solution  four questions about how company and clients interact and exchange knowledge during the implementation and  delivery of a service/product  after‐sales activities  six questions about how the company collects precious knowledge for improving services, by exploiting the interactions  in after‐sales activities 

Questions regarding the relational needs in the market/environment where the company operates  complexity of knowledge about environment  five questions about the complexity of the competitive environment, by assuming that the more complex is the  environment the more knowledge is necessary to manage it  complexity of market  six questions about the complexity of the markets, by assuming that the more complex is the market the more  knowledge has to be collected to establish an appropriate marketing strategy  relevance of image in markets  four questions about how clients consider the image of a provider as a “substitution” of achieving detailed knowledge  of it  importance of first contacts with clients  six questions about how critical the first contact is for clients 

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Ettore Bolisani and Enrico Scarso  difficulty in collection of customer needs  six questions about the need for provider‐client knowledge exchanges for defining customer needs  difficulty in proposal formulation  five questions about the capability of clients to acquire useful knowledge from a commercial proposal and how this  enables them to decide properly  complexity of implementing service/product/solution  six questions about the complexity of services/products and the need for provider‐client interactions to manage their  delivery  relevance of after‐sales relationships  six questions about how relevant after‐sales is in the particular market where the company operates 

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Emotional Knowledge: The Hidden Part of the Knowledge Iceberg  Constantin Bratianu and Ivona Orzea  Bucharest University of Economic Studies, Bucharest, Romania  cbratianu@yahoo.com  ivona.orzea@gmail.com    Abstract.  According  to  Daniel  Kahneman  (2011),  our  thinking  process  is  based  on  two  systems:  system  1  operates  automatically and quickly, with little awareness of voluntary control, system2 operates slowly and constructs thoughts in a  logic  order.  System  1  processes  actually  emotional  knowledge  using  our  unconscious  cognitive  capability.  Cognitive  scientists  discovered  that  we  are  primarily  emotional  decision  makers,  which  means  that  managers  and  leaders  need  to  rely  on  their  emotional  knowledge.  The  purpose  of  this  paper  is  to  present  a  qualitative  and  quantitative  research  concerning the paradox of emotional knowledge. That means that on one hand most of us ignore emotional knowledge by  identifying knowledge with cognitive knowledge, and on the other hand by using emotional knowledge in decision making.  The  qualitative  research  has  been  done  by  reflecting  on  knowledge  management,  strategic  management  and  change  management literature concerning emotional knowledge and emotional intelligence, while the quantitative research has  been done  by  conceiving  a  questionnaire  and  using  it  in  an academic  environment.  A  total  of  1200  questionnaires  were  distributed  to  the  students  of  Bucharest  University  of  Economic  Studies,  and  we  got  a  response  rate  of  37%.  Each  questionnaire  contains  40  questions  concerning  the  awareness,  education,  transfer,  and  management  of  emotional  knowledge. The data has been processed with the help of the specialized software SPSS version 19, and AMOS version 18.  Statistical analysis includes both exploratory and confirmatory factorial analysis. The results of the statistical analysis reveal  the main influence factors affecting our understanding of emotional knowledge, the way we learn through education about  emotional knowledge, the way this knowledge is transferred, and the importance of using it by managers and leaders.    Keywords: emotional knowledge, emotional intelligence, explicit knowledge, cognitive knowledge, tacit knowledge 

1. Introduction It is well known the metaphor of the knowledge iceberg: knowledge may be conceived as an iceberg whose  visible part represents explicit knowledge, and the hidden part representing tacit knowledge. The hidden part  is much larger than the visible part of the iceberg, fact that reflects the ratio between the tacit knowledge and  explicit  knowledge.  As  Polanyi  used  to  say,  we  may  know  much  more  than  we  can  tell.  “I  shall  reconsider  human knowledge by starting from the fact that we can know more than we can tell. This fact seems obvious  enough; but it is not easy to say exactly what it means. Take an example. We know a person’s face, and can  recognize it among a thousand, indeed among a million. Yet we usually cannot tell how we recognize a face we  know. So most of this knowledge cannot be put into words” (Polanyi, 1983, p. 4). However, tacit knowledge is a  fuzzy concept containing a mixture of experience, subjective insights, intuitions, hunches, ideals, values, and  emotions. In order to make a step forward in understanding knowledge nature we may change the old dyad of  explicit knowledge‐tacit knowledge (Nonaka, 1994; Nonaka & Takeuchi, 1995) into a new dyad composed of  cognitive knowledge‐emotional knowledge (Bratianu & Andriessen, 2008; Bratianu, 2011).    The  Cartesian  dualism  of  body  and  mind,  expressed  so  clearly  by  the  famous  dictum  Cogito,  ergo  sum  !,  promoted  two  ideas  about  human  nature  (Kahneman,  2011):  (a)  people  are  rational,  and  (b)  emotions  measure the departure from rationality. The explanation comes mostly from the Newtonian perspective use  by the Western science and culture. By contrast, the Eastern perspective (Kaufman, 1994; Nonaka & Takeuchi,  1995; Nonaka & Zhu, 2012; Ohmae, 1982) emphasizes the oneness of mind and body. Research performed in  cognitive  science  demonstrates  that  the  gap  between  thoughts  and  emotions  is  narrowing,  and  that  they  represent two fundamental components of our inner representation of the world we are living in (Damasio,  1994; Damasio, 1999; Fauconnier & Turner, 2002; Frith, 2007; Immordino‐Yang & Damasio, 2007; Kahneman,  2011; LeDoux, 1999). Moreover, as underlined by Hill (2008), in the process of making decisions as consumers,  emotions are central and not peripheral. In change management, emotions are dominant in influencing people  (Kotter,  1996;  Kotter  &  Cohen,  2002;  Kotter,  2008).  As  a  result  of  all  this  research,  emotional  knowledge  is  emerging  as  a  new  and  powerful  concept  with  many  implications  in  decision  making  and  knowledge  management.     The  purpose  of  this  paper  is  to  present  a  qualitative  and  quantitative  research  concerning  the  paradox  of  emotional  knowledge.  That  means  that  on  one  hand  most  of  us  ignore  emotional  knowledge  by  identifying  knowledge  with  cognitive  knowledge,  and  on  the  other  hand  by  using  emotional  knowledge  together  with 

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Constantin Bratianu and Ivona Orzea  cognitive knowledge in decision making. The qualitative research has been done by reflecting on knowledge  management,  strategic  management  and  change  management  concerning  emotional  knowledge  and  emotional intelligence, while the quantitative research has been done by conceiving a questionnaire and using  it in an academic environment. This research has been stimulated by the following questions: (a) How much  are  students  aware  of  the  importance  played by  emotional  knowledge  in  decision  making  and business?  (b)  What  are  the  specific  ways  of  transferring  emotional  knowledge?  (c)  How  much  education  helped  them  to  understand  emotions  and  emotional  knowledge?  and  (d)  How  important  is  to  use  efficiently  emotional  knowledge? 

2. Emotional knowledge  Nonaka and Takeuchi consider tacit knowledge the hidden part of the iceberg, and that emotional knowledge  is  an  important  part  of  it.  Subjective  insights  and  intuitions  belong  to  this  category  of  emotional  knowledge  (Nonaka  &  Takeuchi,  1995).  Emotional  knowledge  is  created  by  emotions,  and  integrated  together  with  cognitive knowledge into our mental representation of the world. Emotions can be simply described as being  specific  reactions  to  events,  agents  and  their  actions,  and  objects  (O’Rorke  &  Ortony,  1994).  Moreover,  emotion  is  fundamental  in  decision  making,  being  like  a  spectrum  of  know‐how  that  allows  people  to  have  adequate  reactions  to  different  external  forces.  Emotions  contain  emotional  knowledge  generated  by  emotional triggers (Immordino‐Yang & Damasio, 2007).    Although emotion and cognition have been treated most of the time as two separate fields of research and  two separate entities, they “are inextricably intertwined. Feelings influence thoughts and actions, which in turn  can  give  rise  to  new  emotional  reactions”  (O’Rorke  &  Ortony,  1994,  p.  283).  Immordino‐Yang  and  Damasio  (2007) use the concept of emotional thought to describe the overlapping between the emotion and cognition  domains. This is extremely important for understanding the real functioning of memory, decision making, and  creativity.  Thus,  reflecting  especially  on  the  knowledge  management  literature  we  found  three  main  approaches: (1) knowledge is basically cognitive knowledge, and it is generated in the rationality domain; (2)  thoughts  and  ideas  are  different  entities  and  there  is  no  interaction  between  them;  (c)  thoughts  and  ideas  reflect same complex reality and they interact in the decision making.    Based on the metaphor of thermodynamics, especially on the transformation between mechanical energy and  thermal energy, Bratianu makes a step forward and advances the idea of a continuous dynamics between the  cognitive knowledge and emotional knowledge (Bratianu, 2011). That means that cognitive knowledge can be  transformed  into  emotional  knowledge,  and  emotional  knowledge  can  be  transformed  into  cognitive  knowledge, respectively. This dynamics represents actually the engine of the decision making, powered by the  two systems of thinking, as shown by Kahneman (2011, p. 21): “System 1 operates automatically and quickly,  with little or no effort and no sense of voluntary control. System 2 allocates attention to the effortful mental  activities  that  demand  it,  including  complex  computations.  The  operations  of  System  2  are  often  associated  with  the  subjective  experience  of  agency,  choice,  and  concentration”.  Knowledge  dynamics  is  important  also  for the way we are aware of our emotions and we manage them in our personal and professional life (Fenton‐ O’Creevy et al., 2011; Koole, 2009; Lagattuta & Wellman, 2001; Lindquist & Barrett, 2008; Miller et al., 2005;  Reus  &  Liu,  2004).  Understanding  and  using  efficiently  emotional  knowledge  is  an  important  capability  of  managers and leaders (Bass & Riggio, 2006; Daft, 2008; Ekman, 2003; Hess & Bacigalupo, 2010; Jordan et al.,  2013; Madden et al., 2012; Miller et al., 2012; Nag & Gioia, 2012). Although Kotter (2012) is discussing the dual  management system, his argument for using emotions in decision making may be considered as a generic one.  Emotional  knowledge  is  also  essential  in  complex  organizational  processes  like  strategies  implementation  through change management (Kotter, 1996; Mohrman & Lawler, 2012; Rafferty et al., 2013). Our qualitative  research leads to a challenging result: the existence of knowledge dynamics, as a continuous transformation  process of cognitive knowledge into emotional knowledge, and vice versa.    A  critical  analysis  of  the  emergency  of  the  emotional  knowledge  as  a  major  player  in  decision  making,  with  direct  implications  in  management,  marketing,  leadership  and  entrepreneurship  rises  the  question  of  its  awareness, and its development through education. Our research is trying to evaluate the degree of such an  awareness at students in economics and business, and how much they consider that education in schools and  university helped them to master their emotions and emotional intelligence.   

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Constantin Bratianu and Ivona Orzea 

3. Research methodology  The instrument used in our research was the questionnaire. The design and elaboration of this questionnaire  to  collect  the  quantitative  data  went  through  four  phases:  (1)  literature  analysis;  (2)  elaboration  of  the  first  draft of the questionnaire; (3) testing the questionnaire, and (4) improving its content, and elaboration of the  final  version.  Literature  analysis  helped  us  to  understand  different  perspectives  in  interpreting  emotional  knowledge,  and  the  way  we learn  and use this  kind  of  knowledge.  The main  ideas  of this  research we  have  presented  in  the  first  part  of  this  paper.  In  the  second  phase  we  design  the  basic  structure  of  the  questionnaire,  considering  four  main  pillars:  awareness  of  emotional  knowledge,  the  specific  way  of  transferring  emotional  knowledge,  education  for  emotional  knowledge  and  using  emotional  knowledge.  We  designed  the  first  draft  of  the  questionnaire  with  40  questions  able  to  capture  the  respondents  views  concerning  emotional  knowledge  as  the  hidden  part  of  the  knowledge  iceberg.  This  first  draft  of  the  questionnaire was tested within a group of experts in knowledge management. The testing phase had as the  main purpose the evaluation of the accuracy of the questions used and possible suggestions for improving the  questionnaire.  Based  on  the  received  suggestions  we  elaborated  the  final  version  of  the  questionnaire.  The  first part of the questionnaire contains items to describe the general profile of the respondents (age, gender,  and level of education). The second part contains 40 assertions aiming at measuring respondent’s agreement  level with each of them using a Likert scale with five divisions: 1 (strongly disagree), 2 (disagree), 3 (neither  agree  nor  disagree),  4  (agree),  and  5  (strongly  agree).  For  our  research  we  considered  the  academic  environment, and we distributed by mail 1200 questionnaires to undergraduate and graduate students from  the  Bucharest  University  of  Economic  Studies,  from  all  its  11  faculties.  The  rate  of  response  was  of  37%,  resulting  in  444  valid  questionnaires,  which  means  a  sufficiently  large  volume  of  data  to  obtain  relevant  results. The results obtained through the data collection process were analyzed using the specialized statistical  software SPSS version 19, and AMOS version 18. 

4. Results analysis and discussions  The  statistical  analysis  of  the  collected  data  had  four  main  directions  of  thinking:  (1)  what  is  the  students  awareness about the emotional knowledge they have; (2) how much do they know about the specific way of  transferring  emotional  knowledge;  (3)  how  much  they  learned  about  emotional  knowledge  in  schools,  as  a  direct  result  of  school’s  curriculum,  and  (4)  how  much  do  they  know  about  knowledge  dynamics  and  the  importance of emotional knowledge in decision making. We have chosen as methods of analysis exploratory  factorial analysis and confirmatory factorial analysis. Exploratory factorial analysis has the role of underlining  the  factors  that  could  be  identified  from  the  sentences  under  analysis.  Furthermore,  to  validate  the  exploratory factorial analysis and to obtain an exact measure of the processes of learning and using in business  emotional knowledge a confirmatory factorial analysis was undergone.    The  structure  of  the  statistical  population  we  investigated  can  be  characterized  by  the  followings:  81.56%  undergraduate students with ages belonging to the interval of 19‐23 years old, and 18.44% graduate students  with ages belonging to the interval of 24‐30 years old. This composition reflects the general structure of the  undergraduate and graduate programs offered by our university. Among all the respondents, 63% are young  ladies and 37% are young men. Some significant results from the descriptive statistics are presented in Table 1.  For all the 40 variables the minimum value is 1, and the maximum value is 5.  Table 1: Descriptive statistics  No. 

Variables

Q01 Q02  Q03  Q04  Q05  Q06  Q07  Q08  Q09  Q10  Q11  Q12 

Emotions are important in understanding individuals behavior  Emotions are important in decision making  We are primarily emotional decision makers  Emotions are based on emotional knowledge  Emotional intelligence is processing emotional knowledge  Thinking is based on both cognitive and emotional knowledge  Emotional thinking is faster than rational thinking  Leaders influence their followers mostly through emotional knowledge  In business one must use his/her emotions  Basic emotions result in same facial expressions for everybody  Emotional knowledge can be transferred through facial expressions  Emotional knowledge can be transferred through body language 

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Mean Statistic  4.33  3.36  3.46  3.50  3.77  4.11  4.20  3.76  2.75  3.06  3.76  4.02 

Std. Deviation  0.834  1.136  0.997  1.117  0.983  1.007  1.048  1.028  1.084  1.469  1.068  0.890 


Constantin Bratianu and Ivona Orzea  No. 

Variables Emotional knowledge can be transferred through the tone of the voice 

Mean Statistic  4.03 

Std. Deviation  0.922 

Q13 Q14 

Emotional knowledge can be transferred through the verbal language 

3.80

1.016

Q15

Emotional knowledge can be transferred through images 

3.68

0.965

Q16

Emotional knowledge can be transferred through dancing 

3.64

1.056

Q17

Emotional knowledge can be transferred through music 

3.93

0.972

Q18

Emotional knowledge can be transferred through touching 

3.77

1.049

Q19

Most of our communication is done through emotional knowledge 

3.50

0.918

Q20

Communicating emotional knowledge depends on the context much more than  communicating cognitive knowledge 

3.55

0.957

Q21

We learn about emotional knowledge in family 

3.86

0.974

Q22

We learn about emotional knowledge in primary and secondary schools 

2.95

1.152

Q23

We learn about emotional knowledge in high schools 

3.11

1.175

Q24

We learn about emotional knowledge in university 

3.00

1.216

Q25

We learn about emotional knowledge directly from our own experience 

4.58

0.758

Q26

We learn in schools and university how to understand, and to manage  emotional knowledge 

2.66

1.215

Q27

We learn in schools and university how to communicate efficiently our  emotional knowledge 

2.74

1.196

Q28

We had in schools and university special courses about emotions and emotional  knowledge 

2.38

1.323

Q29

We can understand other people emotions only if we understand our own  emotions  Education in schools and university should contribute much more to  understanding and using efficiently our emotional knowledge 

3.91

1.093

4.11

0.980

Using emotional knowledge we can understand much better people we work  with  We can improve decision making by using our emotional knowledge 

4.26

0.837

3.70

1.058

Q33

In negotiations we communicate better by using consciously both cognitive and  emotional knowledge 

3.98

0.968

Q34

In our mental process cognitive knowledge can be transformed into  emotional  knowledge and vice versa 

3.49

0.951

Q35

Positive thinking is based on positive emotional knowledge 

3.92

0.968

Q36

Negative thinking is based on negative emotional knowledge 

3.76

1.068

Q37

Leadership involves both emotional knowledge and cognitive knowledge 

4.29

0.878

Q38

Emotional knowledge is more important than cognitive knowledge in  motivating people 

3.82

0.986

Q39

Emotional knowledge is more important than cognitive knowledge in change  management 

3.24

1.006

Q40

Using emotional knowledge may contribute to generating consumers  enthusiasm 

4.10

0.877

Q30 Q31  Q32 

Analyzing the statistic mean of the first 10 variables we remark a relatively low awareness of the importance of  emotional  knowledge  in  decision  making  (ex.  Q02=3.36  and  Q03=3.46).  Furthermore,  respondents  are  students  in  economics  and  business,  and  most  of  them  cannot  understand  the  practical  importance  of  emotional  knowledge  in  doing  business  (Q09=2.75).  That  means  that  for  most  of  them  the  cognitive  knowledge  is  the  dominant  kind  of  knowledge  in  decision  making  and  solving  business  problems.  From  the  next  group  of  10  variables  we  learn  that  most  of  the  students  know  how  emotional  knowledge  can  be  transferred  (ex.  Q12=4.02  and  Q13=4.03),  but  they  don’t  know  the  relative  high  importance  of  it  in  our  communication  (ex.  Q19=3.50  and  Q20=3.55).  This  conclusion  comes  as  a  logic  consequence  of  the  low 

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Constantin Bratianu and Ivona Orzea  awareness they have about the emotional knowledge. Examining carefully the next group of 10 variables we  get  the  explanation  for  the  above  conclusions.  Students  learn  very  little  about  emotions  and  emotional  knowledge in schools and universities (ex. Q22=2.95 and Q26=2.66). There is a lack of such kind of courses in  their  curriculum  (Q28=2.38),  and  they  learn  about  this  emotional  knowledge  from  their  direct  experience  (Q25=4.58).  Performing  a  detailed  analysis  of  all  the  courses  offered  in  the  undergraduate  and  graduate  programs in our university we found only one course in the curriculum of the Business Administration graduate  program  about  Knowledge  Management,  while  such  kind  of  courses  are  extremely  important  for  educating  future specialists in economics and business. This assertion is supported by the respondents perception of the  need of using efficiently emotional knowledge, as we see in the last group of 10 variables (ex. Q31=4.26 and  Q37=4.29).    The method chosen to process in more details the collected data is factorial analysis, that allows identification  of the most significant factors able to describe the statistical behavior of the considered population. To verify  the accuracy of the method we have applied the Bartlett and Kayser‐Meyer‐Olkin (KMO) tests (Table 2). The  KMO test allowed us to determine the efficiency of the application of factorial analysis onto the data collected.  A small value of the KMO test (i.e. less than 0.7) underlines an inadequacy in utilizing the method of analysis  onto the considered variables, whereas a large value of the test, converging to one, encourages the utilization  of the method to sum up the information comprised in the variables. Both the Bartlett test and the KMO test  suggested a very good accuracy for using the factorial analysis for the present research.  Table 2: KMO and Barlett test  Kaiser‐Meyer‐Olkin test  Barlett test  Approx. Chi‐Square  Df.  Sig. 

0.831 5878.471  780  0.000 

The first  step  in  the  application  of  factorial  analysis  onto  the  set  of  data  was  the  principal  components  extraction, by using the varimax orthogonal rotation. This rotation tries to maximize the variance of the factors  components, leading to a smaller loading of variables onto every factor, and making the interpretation of the  identified factors more facile. Thus, through the varimax orthogonal rotation we have obtained 11 identifiable  factors comprising 60.243% of the information embedded in the original set of data (Table 3).  Table 3: Total variance explained for the first extraction  Items    1  2  3  4  5  6  7  8  9  10  11 

Eigenvalues % of Variance  17.348  7.894  7.701  4.722  4.224  3.993  3.270  3.012  2.816  2.718  2.545 

Total 6.939  3.158  3.080  1.889  1.690  1.597  1.308  1.205  1.126  1.087  1.018 

% Cumulative  17.348  25.242  32.943  37.665  41.889  45.882  49.152  52.164  54.980  57.698  60.243 

By analyzing  the  composition  of  each  factor  in  terms  of  initial  variables,  and  the  main  four  directions  of  investigation, we performed a second extraction of the main components, focusing on the first four factors.  The structure of each factor in terms of the initial variables is presented in Table 4. The first factor contributing  to 17.348% of the total variance, contains 16 variables and shows the level of awareness of respondents about  emotional knowledge and its importance in management and leadership (Q01, Q05‐Q08, Q31‐Q33, Q37). The  second factor is contributing to 7.894% of the total variance and contains 8 variables. It focuses on the specific  ways of transferring emotional knowledge (Q11‐Q18). Most of the respondents know the fact that emotional  knowledge can be transferred mainly through the body language and the tone of the voice.    The third factor contributes to the 7.701% of the total variance, and contains 8 variables. It focuses mainly on  the  importance  of  emotional  knowledge  in  our  communication,  and  the  ability  we  have  in  handling  it.  The  fourth factor contributes only to 4.701% of the total variance, and contains 4 variables. It focuses mainly on 

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Constantin Bratianu and Ivona Orzea  the way formal education contributes to understanding and development of emotional knowledge. As we have  seen  from  the  descriptive  statistics,  formal  education  has  almost  no  contribution  to  our  understanding  and  using efficiently emotional knowledge.  Table 4: Rotated component matrix for 4 factors extracted  Factor 1  Q01 = 0.592  Q05 = 0.473  Q06 = 0.486  Q07 = 0.448  Q08 = 0.467  Q20 = 0.371  Q25 = 0.490  Q29 = 0.333  Q30 = 0.541  Q31 = 0.664  Q33 = 0.533  Q35 = 0.371  Q36 = 0.355  Q37 = 0.633  Q38 = 0.437  Q40 = 0.606 

Factor 2  Q11 = 0.785  Q12 = 0.786  Q13 = 0.768  Q14 = 0.649  Q15 = 0.687  Q16 = 0.700  Q17 = 0.719  Q18 = 0.703                 

Factor 3  Q02 = 0.418  Q04 = 0.358  Q09 = 0.517  Q19 = 0.410  Q26 = 0.619  Q27 = 0.663  Q28 = 0.589  Q32 = 0.454                 

Factor 4  Q21 = 0.459  Q22 = 0.838  Q23 = 0.873  Q24 = 0.724                         

A Cronbach  coefficient  alpha  test  was  conducted  on  all  four  factors  to  test  the  reliability  of  all  of  the  item  variables.  This  was  to  determine  the  internal  consistency  of  the  scale  used.  The  test  results  indicate  higher  values than 0.7 for factors 1, 2 and 4, and less but very close to 0.7 for the third factor. That means a good  enough consistency of these factors, and consequently an adequate correctness (Table 5).  Table 5: Reliability statistics  Factors  1  2  3  4 

Cronbach’s Alpha  0.813  0.882  0.663  0.764 

No. of items  16  8  8  4 

To validate the results obtained we have run a confirmatory factorial analysis. Unlike the exploratory factorial  analysis, in a confirmatory factorial analysis the variables are already observed and the aim of the analysis is to  refine  the  influence  measurement  scale  of  each  sentence  comprised  in  the  identified  factors  (Figure  1).  We  abbreviate with EKF – Emotional Knowledge Factor. As we can see there are three variables that do not have  any direct influence on the four factors. They are: Q03 – We are primarily emotional decision makers, Q10 –  Basic  emotions  result  in  same  facial  expression  for  everybody,  and  Q34  –  In  our  mental  process  cognitive  knowledge can be transformed into emotional knowledge and vice versa. That means that these variables have  a  generic  value  for  the  whole  emotional  knowledge  management,  and  not  just  for  one  of  the  main  factors  identified using the explanatory factorial analysis.     From the confirmatory factorial analysis using the software AMOS version 18, we obtained the synthetic data  presented in the Table 6 that shows a good concordance with the exploratory factorial analysis. 

5. Conclusions Emotional knowledge has been recognized as a distinctive component of the tacit knowledge and the hidden  part of the knowledge iceberg only recently, when research in cognitive science revealed the role of emotions  in  the  decision  making  and  mental  processes.  As  that  research  demonstrates,  cognitive  knowledge  and  emotional  knowledge  are  inextricably  intertwined.  There  is  a  powerful  dynamics  of  thoughts  and  emotions,  that can  be understood  by using  the  thermodynamics metaphor.  That  means  that cognitive  knowledge  may  transform  into  emotional  knowledge  and  vice  versa,  like  energy  from  one  form  into  another  one.  This  is  a  challenging hypothesis based on metaphorical analysis that cognitive scientists have yet to prove.    

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Constantin Bratianu and Ivona Orzea 

Figure 1: Confirmatory factorial analysis model  Table 6: Confirmatory analysis results with AMOS version 18  Variables  Q01  Q05  Q06  Q07  Q08  Q20  Q25  Q29  Q30  Q33  Q35  Q36  Q37  Q38  Q40  Q11  Q12  Q13  Q14  Q15  Q16 

Factors EKF1  EKF1  EKF1  EKF1  EKF1  EKF1  EKF1  EKF1  EKF1  EKF1  EKF1  EKF1  EKF1  EKF1  EKF1  EKF2  EKF2  EKF2  EKF2  EKF2  EKF2 

Estimate 1.359  1.195  1.186  1.001  1.207  0.950  1.007  1.000  1.352  1.429  1.350  1.409  1.459  1.136  1.464  1.457  1.225  1.259  1.000  0.956  1.077 

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S.E. 0.235  0.228  0.230  0.214  0.234  0.199  0.186    0.246  0.255  0.245  0.261  0.251  0.222  0.251  0.112  0.093  0.096    0.091  0.101 

C.R. 5.782  5.232  5.163  4.671  5.156  4.765  5.415    5.488  5.616  5.510  5.400  5.813  5.113  5.820  13.047  13.112  13.051    10.461  10.694 


Constantin Bratianu and Ivona Orzea  Variables  Q17  Q18  Q02  Q04  Q09  Q19  Q26  Q27  Q28  Q32  Q39  Q21  Q22  Q23  Q24 

Factors EKF2  EKF2  EKF3  EKF3  EKF3  EKF3  EKF3  EKF3  EKF3  EKF3  EKF3  EKF4  EKF4  EKF4  EKF4 

Estimate 1.010  1.004  1.420  1.751  2.436  1.293  8.862  8.922  6.779  1.786  1.000  1.000  2.707  3.168  2.453 

S.E. 0.093  0.099  0.820  0.935  1.199  0.714  4.023  4.050  3.104  0.934      0.393  0.456  0.368 

C.R. 10.839  10.184  1.733  1.873  2.031  1.811  0.028  2.203  2.184  1.912      6.885  6.943  6.666 

The purpose of our research is to evaluate the degree of awareness of importance of emotional knowledge,  and the contribution of education to that awareness at students in economics and business. We used both a  qualitative and quantitative research. The qualitative research has been done to get the state‐of‐the‐art in this  field of emotional knowledge from literature in the field of knowledge management and leadership. For the  quantitative  research  we  developed  a  questionnaire  comprising  40  questions,  and  distributing  to  1200  of  students. Finally, we processed 444 valid questionnaires by using the specialized software SPSS and AMOS. We  performed  an  exploratory  factorial  analysis,  and  then  a  confirmatory  factorial  analysis.  Results  show  that  students  have  a  level  of  awareness  about  the  importance  of  emotional  knowledge  just  above  the  statistical  average of the analyzed population, and that education contributed very little to it. Education in schools and  universities  is  based  heavily  on  objective  and  scientific  knowledge,  as  a  result  of  European  tradition  of  the  Cartesian dualism of body and mind. Education should consider also the hidden part of the knowledge iceberg,  and to introduce into its curriculum disciplines dedicated to emotional knowledge. Many students still consider  cognitive knowledge to dominate their decision making and their understanding of life and society. It is time to  reconsider  these  students  curriculum,  especially  to  students  in  economics  and  business  by  introduce  new  courses  about  behavior  economics  and  complex  decision  making,  with  emotional  knowledge  playing  an  important part. 

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Managerial Factors of Organizational Learning for Sustainable  Development  Valentina Burksiene1 and Palmira Juceviciene2  1 Department of Public Administration, Faculty of Social Sciences, Klaipeda University,  Klaipeda, Lithuania   2 Institute of Educational Studies, Kaunas University of Technology, Kaunas, Lithuania  v.burksiene@gmail.com  palmira.juceviciene@ktu.lt    Abstract: Effective results of organizational learning for sustainable development (OLSD) can be achieved when the process  is  well  organized  and  managed.  However,  organizations  frequently  confront  managerial  problems  of  organizational  learning.  The  appropriate  learning  environment  Ba  enabling  OLSD  can  be  created  if  using  complex  of  appropriate  managerial factors. The aim of this article is to reveal the complex of managerial factors guaranteeing OLSD and present  results  of  empirical  research  proving  the  efficiency  of  those  managerial  factors.  A  field  experiment  was  carried  out.  Its  results  illustrate  the  effectiveness  of  the  managerial  factors  and  provide  rationale  for  a  discussion  whether  the  conventional SECI model should be supplemented by an introductory stage.    Keywords: organizational learning, organizational knowledge creation, sustainable development, managerial factors for  sustainable development 

1. Introduction In  the  contemporary  world  organizations  face  the  challenge  of  how  to  adapt  successfully  to  the  turbulent  environment and to improve the performance. The globally accepted concept of sustainable development (SD)  urges to follow the principles of sustainability.    Porter  (2008),  Williams  (2008)  point  out  that  the  most  efficient  way  to  adapt  the  changing  environment  is  learning  in  an  organization,  when  the  organizational  knowledge  is  created  and  developed.  Epstein  (2008),  Williams  (2008)  claim  that  organizational  learning  (OL)  helps  embedding  SD.  Thus,  aiming  for  SD  in  organizational  activities,  organizational  learning  for  sustainable  development  (OLSD)  has  to  take  place.  It  means  creation  and  acquisition  of  knowledge  of  SD  per  se,  the  development  of  system  thinking  which  integrates economic, social (including culture) and environmental aspects as well as SD dimensions highlighted  for a particular organization (Burksiene 2012).     Aiming  for  effective  results  of  OLSD,  the  process  has  to  be  properly  organized  and  managed.  However,  organizations often encounter the managerial problems of OL. The managers are mainly result (knowledge)‐ oriented, instead of putting their efforts for developing relevant learning environment important for successful  OL.    With  reference  to  knowledge  creation  model  proposed  by  Nonaka,  Toyama  and  Byosiere  (2001),  we  emphasized the significance of Ba (learning environment) and agreed that OLSD takes place in four different  Ba where specific SD knowledge is created in each of them and successfully applied in other learning stages  (Juceviciene and Burksiene 2009). Success of OLSD mainly depends on arrangement and management of every  Ba using appropriate learning methods.     A number of authors (Bell and Morse 2003; Epstein 2008; Zink 2008) in their analysis of OLSD suggest using the  methods  of  reflection,  discussion,  dialogue  or  other  ways  of  acting  that  permit  sharing  the  individual  knowledge and constructing collective knowledge. These scholars, however, have not provided rationale for a  complex  of  methods  relevant  for  successful  creation  of  organizational  knowledge.  We  argue  that  successful  OLSD  requires  a  complex  of  methods  that  may  be  regarded  as  managerial  factors  empowering  successful  OLSD. According  to  the  theoretical  model  of  OLSD  (Juceviciene  and  Burksiene  2009),  organizational  learning  for  sustainable  development  takes  place  in  different  Ba.  Thus  each  Ba  calls  for  different  managerial  factors.  What managerial factors can be used to empower successful OLSD? The aim of the paper is to reveal, what  managerial factors should be used in every Ba guaranteeing successful OLSD.    

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Valentina Burksiene and Palmira Juceviciene  First  of  all,  the  managerial  factors  important  for  OLSD  are  revealed  drawing  on  literature  analysis.  Later,  empirical  testing  of  OLSD  managerial  factors  is  provided:  the  methodological  background  of  the  empirical  research  is  introduced,  field  experiment  is  described,  research  results  are  analysed  and  discussed.  Finally,  conclusions are drawn.  

2. Organizational learning for sustainable development and its managerial factors  Organizational learning for sustainable development is a complex process that may be explained by describing  the  characteristics  inherent  in  OL.  Nonaka  and  Takeuchi  (1995)  describe  OL  and  view  the  process  as  transformations of tacit and explicit knowledge among the individuals and their groups when they interact. It  is  a  never  ending  and  spiral  process  of  socialization,  externalization,  combination  and  internalization  (SECI).  Easterby‐Smith and Lyles (2003) note that OL consists of actions, actors, symbols and processes. Kolb (1984)  points out that the learner moves in a spiral way through different learning experience within the iteration of  acting, reflecting, conceptualizing and practicing.  Thus, these ideas enable to refer to organizational learning  as a spiral process characterised by learning of individuals and their groups.    DiBella (2003) points out that OL is related to the time and situation in which certain knowledge was created  and  applied.  In  other  words,  learning  is  contextualized.  Nonaka,  Toyama  and  Byosiere  (2001)  claim  that  knowledge creation takes place in a particular space referred to as Ba (this is a Japanese concept that might be  translated as ‘space’). Ba is described as a context where knowledge resides, is created, shared and embedded.  Thus, organizational learning is related to the learning space or environment.     Pasteur,  Pettit  and  van  Schagen  (2006)  argue  that  a  successful  environment  for  OL  is  created  with  a  special  focus  on  learning  processes.  Aiming  to  ensure  successful  OLSD,  relevant  managerial  factors  have  to  be  employed that enable to create a comfortable and safe environment for OLSD.     Nonaka, Toyama and Byosiere (2001) reveal four Ba as learning environments: Originating Ba; Dialoguing Ba,  Systemizing Ba, Exercising Ba applied, accordingly, to the stages of socialization, externalization, combination  and internalization in organizational learning (SECI model).      A specific issue of OLSD is that it tends to involve people that lack personal (basic) knowledge of SD. This article  analyses  the  situation  of  employees  with  knowledge  and  experience  of  SD  only  from  environmental  perspective who encounter the task of addressing SD as a systemic environmental, economic and sociocultural  approach. Here OLSD has to take place by re‐conceptualizing the knowledge on SD. This task should be solved  in the very process of OLSD. Thus a new phase of OL starts with the stage of externalization. It embraces the  heritage  of  tacit  knowledge  from  the  previous  stage  of  socialization  with  the  conventional  approach  to  SD.  What  managerial  factors  should  be  in  place  when  a  group  of  employees  has  received  a  task  to  draft  a  new  strategic  plan  based  on  a  new  systemic  approach  to  SD  rather  than  the  old  one  (based  on  exclusively  environmental approach) and to convince all the organization to adopt this change?      Juceviciene and Burksiene (2009), Burksiene (2012) note that specific managerial factors have to be used for  developing  Ba  that empower  OLSD.  If  the managerial  factors  are  successful,  one  may  expect  that  successful  OLSD will occur in all Ba and SD knowledge that is significant for organization will be created.     Originating  Ba  is  necessary  for  socialization.  This  means  that  a  common  space  has  to  be  developed  were  people  are  comfortable  to  create  common  but  tacit  knowledge  (Nonaka  and  Takeuchi  1995).  In  this  sense  managerial factors are those that help to create a physical (or virtual, which is beyond the scope of the present  research) space for being and acting together. But in terms of socialization result in the context of OLSD, we  should remember that it contains the tacit knowledge of the conventional SD approach, which has to be re‐ conceptualized before entering the stage of externalization of the new OLSD phase.      Here reference should be made to the stage of initiation which is between the processes of the former OLSD  socialization phase and the new OLSD phase of externalization (see Figure 1). The following managerial factors  are  relevant  in  the  initiation  stage:  1)  interview  as  a  dialogue  between  expert  and  informant  to  identify  personal SD knowledge and to discuss the task for shifting to a new approach to SD; 2) organizing Focus group  to discuss common understanding on SD in order to prove readiness for the OLSD. These, however, are only 

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Valentina Burksiene and Palmira Juceviciene  preparatory  activities,  as  it  is  not  likely  that  group  members  will  acquire  collective  knowledge  based  on  the  new SD approach as a result.    The physical and psychological environment for dialoguing Ba has to be created in the externalization stage to  make  the  group  members  able  to  reveal  their  own  knowledge  and  develop  explicit  collective  knowledge  (a  shared vision on SD, strategy, etc.). In developing this Ba, reflection that is emphasized in Kolb’s (1984) model  has to be encouraged. Reflection enables to effectively share the knowledge that is necessary for constructing  collective explicit understanding on vision of SD and strategy. The method of concept mapping (both individual  and group maps) has to be used for making SD knowledge explicit. It also helps to develop system thinking.  Focus  group  may  be  applied  to  make  sure  that  consensus  is  reached.  In  these  activities,  interpretation  and  integration proposed in Crossan 4 I model (Stevens and Dimitriadis 2004) can be encouraged. Interpretation  helps revealing the individual SD knowledge; it is then interpreted by group members in the light of their own  understanding.  The  interpreted  knowledge  is  integrated,  since  the  group  seeks  for  shared  attitude  to  SD  in  their organization’s strategy. With this knowledge the group is ready for drafting the project of organization’s  new SD strategic plan by applying the method of PDCA (plan, do, check, act) cycle (Epstein 2008) (see Figure 1).    Systemizing Ba is necessary in the combination stage for transforming the explicit collective SD knowledge into  the  organization’s  formal  knowledge  (documents).  The  main  methods  used  are  a)  presentation  of  the  draft  prepared by the workgroup; b) discussion of the workgroup and other groups in an organization; c) application  of PDCA.     In this stage the interpretation of knowledge on SD of other groups and the workgroup takes place, as well as  collective  knowledge  of  higher  level  is  created.  The  process  has  to  be  supported  by  the  allocation  of  time,  organizational and other resources (setting the workgroups meetings, their schedule, facilities, etc.).   Organization’s  formal  knowledge  may  be  expected  as  a  result  which  is  an  approval  of  a  new  strategic  plan  based on the new approach to SD.      Exercising Ba embraces organizational and educational tools applied in the concrete time period. These tools  ensure that the officially approved organization’s documents for SD would take employees’ mind and senses  and  become  their  daily  knowledge  and  motivation  for  sustainable  activities.  In  this  phase  the  learning  Ba  is  created by training and application of PDCA cycle.   Initiation stage: 1) Interview in the form of dialogue between expert and informant to identify personal SD knowledge and to discuss the task for shifting to a new approach on SD. 2) Organizing Focus group to discuss common understanding on SD in order to prove readiness for the OLSD.

Dialoguing Ba 1) Construction of individual concept maps to disclose SD strategy essence. 2) Construction of group concept map that reveals the essence of SD strategy. 3) Organization of Focus group in order to confirm the consensus of group decision on SD. 4) Applying PDCA cycle and combining the solutions at each stage for preparation of draft SD strategy.

Originating Ba 1) Physical environment for being and acting together is created. 2)Favourable organizational atmosphere is maintained.

Exercising Ba 1) Organization of training to introduce the employees to the decisions on SD. 2) Applying PDCA cycle for the groups and i\individuals.

Systemizing Ba 1) Applying PDCA cycle for all groups in organization and combining the solutions at each stage of PDCA for preparation of draft SD. 2) Final SD strategy version is formalized.

Figure 1: Managerial factors for Ba enabling OLSD 

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Valentina Burksiene and Palmira Juceviciene  The  four  Ba  environments  of  OLSD  and  the  managerial  factors  applied  for  their  creation  are  presented  in  Figure 1. Theoretically validated managerial factors were tested in Neringa Municipality.  

3. Empirical testing of OLSD managerial factors   In this part we will present the methodology employed for the research. The field experiment will be described  introducing its logical structure and methods. The results will be presented and discussed. 

3.1 Methodological background   The  most  suitable  environment  to  test  the  theoretically  validated  OLSD  managerial  factors  empirically  is  considered to be a natural organizational environment where OLSD is taking place. Therefore, field experiment  was  carried  out.  The  possibility  to  observe  OLSD  process  from  inside  is  considered  to  be  an  advantage.  The  field experiment was carried out at the administration of Neringa Municipality, which is the only municipality  in Lithuania located in the territory of the national park. This national part is on the UNESCO world heritage list  as  an  object  of  cultural  landscape.   However,  for  a  long period  of  time  SD has been considered  from  a  very  narrow  perspective  and  treated  as  an  environmental  protection  issue.  The  new  understanding  that  environmental protection has to be related to the solution of economic and social‐cultural problems (and vice  versa)  influenced  the  necessity  to  develop  a  new  document  –  Neringa  strategic  plan  based  on  the  system  approach. A workgroup was formed to draft this document. The municipality administration was aware that  the organizational competence in SD area had to be developed. It was useful for us as researchers to join the  practitioners’  performance  for  carrying  out  the  field  experiment.  The  permission  from  the  administration  to  use their organization’s name while presenting the research results has been received.    One  of  the  co‐authors  of  this  paper  had  worked  in  the  administration  of  Neringa  municipality.  The  considerable degree of trust between the researcher and the experiment participants helped to carry out the  observation of OLSD process from inside and to combine this observation with other research methods. The  specific  feature  of  this  research  is  that  some  OLSD  managerial  factors  served  as  the  methods  of  empirical  research.  

3.2 The field experiment   The main experiment lasted eleven months. It started when the executives of the municipality administration  set up a workgroup (9 employees, all involved in the experiment) for drafting a new strategic plan.     Using  managerial  factors  (see  Figure  1),  two  Ba  were  created:    Dialoguing  and  Systemizing.  There  was  no  opportunity to create the other two Ba:     1. Because of the specific circumstances that are beyond the scope of the researchers’ influence, Exercising Ba  was not implemented. This was a limitation of the research that was impossible to avoid: the situation in the  organization changed after the local governance elections, the implementation of the third phase of SECI cycle  –  combination  –  ran  over  and  some  of  the  organization  members  terminated  their  employment  contracts  (because of the changes after the elections).     2.  Another  environment  (Originating  Ba),  that  should  take  place  in  a  new  approach  to  SD  learning  and  adoption phase, could not be observed either: we could only start the experiment from the introductory stage  between the processes of socialization and externalization.     Introductory  stage.  During  the  experiment  the  initial  SD  knowledge  was  defined  by  the  method  of  semi– structured interview. Since this interview helped reflecting and making tacit knowledge explicit, the interview  may  be  considered  at  the  same  time  as  research  method  and  as  the  managerial  factor  in  transition  from  Originating  Ba  to  Dialoguing  Ba.  Focus  group  was  also  employed  for  the  this  stage.  Bell  and  Morse  (2003)  argue that this method is a relevant managerial factor of learning SD. The same Focus group, simultaneously,  served as the method of defining group’s initial collective knowledge.     Dialoguing  Ba  was  developed  aiming  to  empower  each  group  member  and  all  together  to  structure  their  individual  thinking  on  SD,  to  construct  collective  knowledge  on  SD  and  to  prepare  the  strategic  plan  draft  based on a new approach to SD. Firstly, an individual reflection takes place and the individual concept maps 

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Valentina Burksiene and Palmira Juceviciene  are constructed. Later on, group members present their own concept maps for discussions and idea exchange  and, as a result, a common understanding on Neringa SD is achieved in the group; collective concept map is  created. The application of this method, as Bell and Morse (2003) argue, enables directing the learning process  towards  the  integrated  usage  of  economic,  ecological  and  socio‐cultural  means.  Concept  mapping  (as  a  research  method)  also  enables  revealing  the  structure  of  existing  and  obtained  knowledge.  Tautkeviciene  (2005)  argues  that  concept  mapping  is  an  excellent  diagnostic  tool  for  defining  the  conceptual  changes  in  understanding and knowledge. This method is also used for revealing system thinking and the problem solving  skills in teams.     The method of PDCA was used to prepare the draft of a strategic plan based on a new approach to SD. This  method also was applied for the Combination and Internalisation stages (the systemic application of PDCA for  OLSD is presented in Table 1).  Table 1: Systemic application of PDCA: theoretical approach and its implementation at Neringa Municipality  PDCA in Epstein’s (2008) theory  PDCA in Neringa Municipality field experiment  Plan: revise the existing documents from SD perspective,  The workgroup drafted (externalization) a new strategic  define aims and objectives that integrate SD dimensions,  plan (and programmes of its implementation), which  create development programmes.  was presented to politicians for discussions and  corrections indifferent committees and approval in the  Council (combination).  Do: identify organization’s structures and responsible  In the process of developing programmes, there was a  people relevant for the implementation of SD strategy;  suggestion (after  externalization) to revise the  initiate training for responsible people and other SD‐related  structure of implementation of the plan and responsible  members in the organization; carry out programmes.  people. A new structure and people were approved  after the debates in political committees/ groups  (combination)  The workgroup was learning in the course of developing  the strategic document (externalization), politicians in  the committees/ groups were learning in discussions on  the drafts of documents (combination) that were  approved by the Council.  Check:  carry out internal audit by monitoring and  The workgroup identified the indicators of monitoring  measuring the indicators of SD performance (drawing on  and evaluation with reference to SD (externalization);  the approved system of monitoring and evaluation).  they were discussed in committees/ groups  (combination) and formalised by the approval of the  Council.  Act: to carry out management audit and improve the  The administration executives and committees  process of SD by appointing persons responsible for  continuingly interacted with the workgroup to improve  continuing performance monitoring and results evaluation. the draft of the strategy, its monitoring system and    evaluation indicators (combination). 

Aiming for formalization of SD knowledge, Systemizing Ba is initiated and the managerial factor of PDCA (plan,  do,  check,  act)  cycle  (Epstein  2008)  is  applied.  In  this  learning  environment  the  workgroup  presents  the  strategic  plan  to  the  other  groups  (departments)  in  municipality  administration.  The  group  discussion  is  moderated until the final decision on the strategic document of Neringa Municipality based on SD principles is  reached.     The observation from inside allowed defining the influence of each member on others.     As the research strategy focussed on qualitative research, the results were processed by descriptive content  analysis. 

3.3 Empirical findings: analysis and discussion   Introductory  stage.  Before  starting  the  main  experiment,  we  needed  to  find  out  what  knowledge  the  employees bring from the previous stage in the SECI model   (socialization). In other words, we were interested if group members have the initial knowledge necessary for  drafting a new SD strategic plan.    

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Valentina Burksiene and Palmira Juceviciene  It  was  revealed  (see  Table  2)  that  the  learners  of  the  group  had  some  initial  knowledge  of  SD  but  this  knowledge  was  inconsistent.  The  majority  of  respondents  were  not  able  to  define  explicitly  the  SD  concept  based on a new (systemic) approach. However, all of them understood the necessity of the systemic approach  to SD as the basic for the strategic plan development and even used it while talking about the strategic actions  in Neringa municipality.      The interview also resulted in the finding that the members of workgroup had unequal conditions for informal  discussions  in  the  socialization  stage  of  the  previous  phase  of  OLSD,  where  SD  knowledge  of  the  traditional  approach  is  developed.  To  paraphrase  Nonaka,  Toyama  and  Byosiere  (2001),  the  differences  in  knowledge  largely depend on the extent people are involved into common organizational issues and on the possibility to  work together (in the same space: office, workshop room, etc.).      The dialogue with the researcher in the interview and the Focus group discussion soon afterwards (both of the  methods  may  be  considered  as  managerial  factors  helping  a  very  smooth  transition  from  socialization  to  externalization  stage)  enabled  individuals  to  expand  their  understanding  of  SD  significance  and  to  gain  new  individual knowledge by reflecting. A common understanding was born in Focus discussion: it is necessary to  agree  on  the  goal  of  Neringa  Municipality  SD  and  the  interrelated  development  issues.  The  group  also  achieved the consensus that the main issues to be integrated are the following: tourism, social development  and  care,  environmental  development,  education,  health,  housing  and  environment,  recreation,  social  infrastructure,  economics,  business,  workplaces  and  cultural  heritage.  These  issues  may  be  considered  as  essential dimensions of Neringa Municipality SD. The Focus group started the conceptualization of collective  knowledge  on  SD  about  the  necessary  implementation  of  environment  protection  requirements  for  further  successful development.     Dialoguing Ba was devoted to the researching of individual and collective SD knowledge that was made explicit  with  the  help  of  individual  and  group  concept  maps.  This  knowledge  served  as  an  indicator  hat  OLSD  took  place. In their individual concept maps each group member mentioned from 4 to 10 possible dimensions of  Neringa  SD  generated  by  the  Focus  group.  Six  people  mentioned  three  essential  SD  issues  (environmental,  social  and  economic).  The  collective  concept  map  showed  seven  dimensions  generated  by  the  Focus  group.  Thus  we  may  note  that  the  group  concept  map  has  been  created  reflecting  the  collective  vision  of  SD  (stimulate, develop and improve the quality in the economy; to guarantee, maintain and organize the social  issues;  to  protect  and  save  the  environment)  and  reveal  the  suggested  strategic  directions  for  SD.  In  other  words, the collective explicit knowledge of the workgroup about sustainable development has been created.  This knowledge, however, was not formalized yet.  Next Focus group later on highlighted that learners were  positive  on  the  concept  mapping  which  enabled  to  expand  their  individual  knowing,  to  understand  the  significance of other SD dimensions and to come to collective understanding. The group members agreed that  the  increased  individual  knowing  and  improved  system  thinking  let  them  to  prepare  a  more  detailed  and  systematic concept map of the group. Later, the work group prepared the draft of the strategic plan through  the PDCA activities.    In Systemizing Ba the group was working together with other groups of the municipality on the preparation of  planning document on SD. The PDCA and discussions as the managerial factors were used. It is worth noticing  that  the  greatest  initiative  was  exerted  by  the  group  which  had  passed  the  externalization  phase.  Having  achieved  the  common  agreement,  SD  knowledge  was  formalized  by  approving  the  prepared  planning  document on organizational level. Thus, the empirical findings show that the relevant managerial factors in the  Ba  environment  under  research  helped  to  initiate  and  maintain  OL;  the  SD  knowledge  was  constructed,  developed and finally integrated into the organization’s strategic document.     The relevance of managerial factors is illustrated by the fact that in the process of OLSD, the SD knowledge  was created, shared and improved in each Ba empirically researched (see Table 2).    Exercising  Ba  and  Originating  Ba  (in  the  phase  of  the  OL  for  shifting  on  a  new  approach  to  SD)  were  not  implemented due objective reasons and this is some limitation of the experiment. Therefore, the managerial  factors grounded for these two Ba need to be tested in future research.     We have noticed that sometimes the transition from socialization to externalization, especially when knowing  has  to  be  re‐conceptualized,  requires  a  supplementary  stage.  We  refer  to  it  as  an  introductory  stage,  when 

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Valentina Burksiene and Palmira Juceviciene  specific managerial factors, involving experts, help employees to see that they need to reconceptualise their  knowledge  on  individual  and  collective  levels.    One  may  question  if  this  is  not  part  of  externalization  and  Dialoging  Ba.  But  Toyama  and  Nonaka  (2000)  note  that  this  Ba  is  associated  with  dialogues  between  the  participants  (our  observation:  but  not  the  experts  and  participants).  The  above  may  be  used  to  confirm  the  relevance  of  the  introductory  stage  in  some  cases  of  organizational  learning.  In  our  case,  this  is  a  need  for  reconceptualization.  Further  research  is  of  course  necessary  to  find  out  if  the  SECI  model  may  be  supplemented  with  the  introductory  stage.  Another  question  is  if  in  those  cases  the  introductory  stage  is  relevant  only between  the  stages  of  socialization  and  externalization  or  if  other  needs  may  exist;  it  remains  open.   Table 2: Knowledge on SD generated by managerial factors during the experiment  Ba  Introductory  stage: shifting  from  Originating Ba  to  Dialoguing Ba 

Dialoguing Ba 

Systemizing Ba 

Managerial factor  semi‐structured interview  between the  expert and informant to identify initial   individual SD knowledge    Focus group in order to reveal what kind of  SD knowledge each member of the group  has; how it is different or common; to  motivate for reaching a new level of  knowledge for new SD  Construction of individual concept maps  (ICM) to reveal the individual knowledge on  SD of a new approach.      Construction of group concept maps (GCM)  while reaching consensus in the group on  collective understanding of SD based on a  new approach  Focus group in order to reveal what kind of  SD knowledge has each member of the  group; how it is different or common; to  motivate for reaching a new level of  knowledge for new SD  4) PDCA cycle is used for drafting the  strategic plan  1) Conditions created for group‐initiator to  present its project to other groups for  common discussion  2) Applying the PDCA cycle 

Result 1) Individuals were encouraged to externalize  their knowledge.  It turned out that they had  different knowledge, almost sufficient for  starting OLSD  2) The group and individual members pointed  out that their knowledge is different, it should be  presented more precisely to each other for  reaching common understanding. This was the  preparation for OLSD  1) ICM  Each group member pointed out from 4 to 10  possible dimensions of Neringa SD; 6 people out  of 9 referred to three essential SD issues  2) GCM  The collective concept map shows 7 SD  dimensions generated by the Focus group and  reflects the group vision of SD  3) Focus group  The consensus on SD has been confirmed      4) PDCA cycle  A draft of the strategic plan was developed 

1) The consensus on SD has been confirmed in all  groups    A strategic plan on SD prepared and approved:   SD new knowledge is formalized on  organization’s scale 

Further research is necessary to answer the question on OLSD: what level and extent of specific knowledge is  sufficient for each group member for a successful process of externalization when  reconceptualization takes  place in organization?  

4. Conclusions Organizational  learning  for  sustainable  development  is  difficult  to  implement  when  employees  lack  relevant  experience, especially when a narrower concept of SD is conventional in the stage of socialization.  In this case  shifting  from  socialization  to  externalization  stage  requires  additional  managerial  factors  based  on  external  expert competence. These factors may be a) a semi‐structured interview for identifying the SD knowledge of  every  member  of  future  externalization  group;  b)  Focus  group  for  approximate  identification  of  collective  knowledge,  understanding  an  SD  task  with  a  new  wider  approach  and  motivating  for  seeking  new  SD  knowledge.    The following challenges and managerial factors for addressing them are characteristic of the externalization  stage:  

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ability to  externalize  individual  knowledge  in  a  structured  way:  construction  of  individual  concept  maps  may be used for this;  

ƒ

ability to present individual knowledge to other group members, find a consensus on common collective  knowledge:  a  group  concept  map  may  be  developed,  drawing  on  dialogues  and  discussion,  consensus  decisions on SD.   

In the stages of externalization and combination, an important managerial factor is the method of Focus group  which helps workgroups to summarise the results by raising and answering targeted questions.     The method of PDCA cycle is a successful managerial factor for bringing together workgroups in the process of  externalization,  organization’s  groups –  at  the  stage  of  combination,  and  reaching  a  new  approach  to  SD  in  groups and on the level of organization. The PDCA method is also relevant in the stage of internalization.       The  executives  of  organizations  implementing  a  systemic  SD  approach  vs  a  narrow  environmental  approach  should consider the need for additional managerial factors, like inviting experts on a systemic SD approach for  diagnosing the employees’ knowledge on SD and encouraging them for understanding the new approach to  SD. For OLSD, the following methods may be used successfully as managerial factors: developing individual and  group  concept  maps,  Focus  groups  and  PDCA.  Thus  the  first  step  is  to  make  sure  that  employees  are  competent to employ these methods.     This research was funded by the European Social Fund under the Global Grant measure 

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Capturing Safety Knowledge: Using a Safety‐Specific Exit Survey  Christopher Burt, Cassandra Cottle, Katharina Näswall and Skye Williams  University of Canterbury, Christchurch, New Zealand  Christopher.burt@canterbury.ac.nz  Ckc34@student.canterbury.ac.nz  Katharina.Naswall@canterbury.ac.nz  Sdw69@student.canterbury.ac.nz    Abstract: Organizations not only create knowledge, but also have a need to capture knowledge before it is lost with exiting  employees. Safety related knowledge is relevant to many organizations, but is particularly hard to capture from employees  due  to  the  many  variables  which  constrain  employees’  willingness  to  voice  safety  issues.  Some  of  these  constraining  variables, such as management and co‐worker support and trust issues, and fears around a ‘blame culture’, are removed  when an employee makes the decision to leave an organization. With these constraints on voicing safety issues removed,  organizations may have an opportunity to capture valuable safety knowledge from exiting employees. The use of a safety‐ specific  exit  survey  process  was  examined.  This  post  employment  safety  voicing  strategy  was  examined  in  relation  to  perceived  management  and  co‐worker  support  for  safety  and  trust  issues.  One  hundred  and  one  individuals  who  had  recently resigned from a job were questioned about their need to voice safety information at the time they resigned, and  their willingness to voice safety issues in an exit survey process. Results show that perceived support and trust for safety  are positively associated with on‐the‐job voicing. More importantly, when a participant had left a job where support and  trust were perceived as low, they indicated a higher desire to complete a safety‐specific exit survey process. That is when  the contextual constraints posed by a lack of support and low trust are removed due to voluntary withdrawal from the job,  participants wished to voice their safety concerns. Overall, the results strongly suggest that the introduction of a safety‐ specific  exit  survey  process  has  the  potential  to  capture  valuable  safety  information,  and  as  a  consequence  potentially  improve workplace safety.    Keywords: turnover, safety, exit‐survey, voicing, trust, support 

1. Introduction Poor  workplace  safety  can  result  in  employee  turnover  (Bell  &  Grushecky,  2006;  Cree  &  Kelloway,  1997;  Kincaid,  1996;  Ring,  2010;  Viscusi,  1979).  Workers  that  leave  a  job  because  of  safety  concerns  may  leave  without voicing their safety concerns. Indeed, they may leave because they feel they are unable to voice their  safety concerns, or because they feel that if they do voice safety concerns nothing will be done about them  (Cree, & Kelloway, 1997; Hirschman, 1970; Reason, 1997). If employees leave their job due to safety concerns,  but these concerns are not voiced, important safety knowledge is being lost. In an attempt to capture safety  knowledge from exiting employees, we propose the use of a safety‐specific exit survey. The primary question  addressed  in  this  research  was  whether  participants  were  willing  to  complete  a  safety‐specific  exit  survey.  Furthermore, in an attempt to explain why a safety‐specific exit survey might be necessary, the research also  examined  predictions  about  relationships  between  management  and  co‐worker  support  and  trust  (variables  which have been found to be associated with employee voicing), and willingness to complete a safety‐specific  exit survey.     Research suggests that the failure to report safety incidents may result from a lack of management support,  sometimes  labelled  a  ‘blame  culture’,  where  voiced  safety  information  is  used  to  assign  blame  and  take  disciplinary  action  against  those  believed  responsible  (e.g.,  Clarke,  1998;  Probst  &  Estrada,  2009;  Webb,  Redman, Wilkinson, & Sanson‐Fisher, 1989). Withey and Cooper (1989) also suggested that employees weigh  up  the  possible  benefits  and  costs  when  deciding  whether  or  not  to  voice  their  concerns.  Reason  (1997)  argued  that  to  counter  this  constraint  on  voicing  it  is  essential  to  protect  informants  and  colleagues  from  disciplinary actions taken on the basis of their safety reports. In contrast to the constraining influence that a  lack of management support appears to have on employee voicing, research has also found that employees  who  perceived  management  as  supportive  and  open  to  suggestions  were  more  likely  to  engage  in  voicing  behaviour  (Elizabeth  &  Phelps,  1999).  Furthermore,  research  has  found  that  management  openness,  and  supportive leadership were significant determinants of safety voicing (Neal & Griffin, 2002; Withey & Cooper,  1989).    Management support, while important for voicing safety issues, appears to interact with co‐worker support.  Research by Tucker, Chmiel, Turner, Hershcovis, and Stride (2008) found that co‐worker support for safety fully 

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Christopher Burt et al.  mediated the relationship between management support for safety and safety voicing behaviour. This result is  consistent with other research which has suggested that supportive group norms are a significant determinant  of safety voicing (Neal & Griffin, 2002; Withey & Cooper, 1989). This may reflect the possibility that without co‐ worker  support,  the  worker  voicing  the  safety  concern  is  taking  a  risk  that  their  co‐worker  will  respond  unfavourably.    Management  and  co‐worker  support  for  safety  are  clearly  associated  with  trust  as  an  influencing  factor  in  safety  voicing.  Flin  and  Burns  (2004)  applied  Mayer,  Davis  and  Schoorman’s  (1995)  trust  model  to  safety  behaviours,  observing  that  the  challenging  of  a  peer’s  potentially  unsafe  work  practice  requires  trusting  behaviour.  Thus  trust  between  all  levels  of  the  organisation  is  paramount  to  facilitate  the  voicing  of  safety  issues (Flin & Burns, 2004; Mayer et al, 1995). If an employee has low trust for management, perhaps because  they consider that voicing safety concerns would negatively influence their relationship with the organisation  or not result in any action (whether justified or not), they may not voice their safety concerns.    Research  on  trust  has  frequently  noted  that  trust  development  is  associated  with  positive  organisational  outcomes  (e.g.,  increased  communication  and  knowledge  exchange,  Andrews  &  Delahaye,  2000;  enhanced  mutual  learning,  Gubbins  &  MacCurtain,  2008).  Furthermore,  safety‐specific  trust  benefits  include  increased  communication about safety, shared safety perceptions, positive safety attitudes, reduced incident rates and  increased  personal  responsibility  for  safety  (e.g.,  Hofmann  &  Stetzer,  1998;  Reason,  1997;  Watson,  Scott,  Biship & Turnbeugh, 2005; Zacharatos, Barling & Iverson, 2005).     Collectively, the discussion above suggests that the contextual issues of management and co‐worker support,  and employee trust in both management and co‐workers, can enhance or place constrains on the voicing of  safety concerns. The constraining factors may also reach a point where the employee decides to leave, as to  remain  is  seen  as  too  risky.  When  an  employee  makes  the  decision  to  leave  a  workplace,  contextual  constraints  on  voicing  may  be  largely  removed,  as  management  has  little  ability  to  assign  blame  or  take  disciplinary  action  against  an  employee  that  has  resigned.  Similarly,  an  employee  that  has  resigned  has  essentially left the social unit or group they worked with, and as such co‐workers responding unfavourably to  the employee’s voicing may no longer be a constraining factor. Free of the contextual constraining influences,  a safety‐specific exit survey process may provide an employee with an opportunity to voice safety concerns,  and data from such a process may provide an organization with valuable safety knowledge.   This study addressed the general questions noted above, and tested 2 hypotheses:  ƒ

Management and  co‐worker  support  and  trust  measures  will  be  positively  correlated  with  on‐the‐job  safety voicing. 

ƒ

Management and co‐worker support and trust measures will be negatively correlated with a need to voice  at exit measure. 

2. Method 2.1 Sampling, procedure and participants   A haphazard sampling approach (Weisberg & Bowen, 1977) was used to locate 101 individuals who had exited,  within the last 36 months (mean = 12.3 months, SD = 10.4), a job which they considered had a degree of safety  risk. Sampling focused on this population, as obtaining exit related information sometime after the actual job  exit has been found to positively influence the amount, specificity, and validity of information obtained (e.g.,  Lefkowitz  &  Katz,  1969).  From  the  job  title  provided  by  the  participant  they  had  worked  in  the  following  industries:  22  in  construction,  20  in  manufacturing,  10  in  forestry,  5  in  mining,  2  in  transportation,  8  in  agriculture, 8 in adventure tourism, and 26 in miscellaneous industries (which includes 13 who indicated they  worked in a trade).    The  research  survey  was  distributed  via  post,  email,  or  by  hand.  The  101  participants  were  made  up  of  79  males  (mean  age  =  26.8  years),  and  22  females  (mean  age  =  29.5  years).  Responses  relating  to  the  job  the  participant  had  exited  (that  for  which  they  completed  the  exit  survey)  indicated  a  mean  job  tenure  of  38.9  months (SD = 62.7), a mean number of co‐workers of 27.0 (SD = 46.4), scores on the Hayes, Perander, Smecko  and Trask (1998) Job Safety Risk Scale ranging from 1 to 4.8, mean = 3.0, median = 3.1, SD =.71, and Pearce and  Gregersen  (1991)  Team  Member  Interaction  Scale  scores,  ranging  from  1  to  5,  mean  and  median  =  4.0,  SD  =.77. 

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2.2 Materials The front page of the survey provided information regarding informed consent, and participant instructions.  Section  one  contained  demographic  and  background  questions,  and  section  two  listed  40  workplace  safety  issues (see Table 3). The remaining sections were presented in a number of different orders to help control for  common  method  variance,  and  included  measures  of  perceived  organizational  support  for  safety,  and  perceived co‐worker support for safety, management trust, co‐worker trust, team member interaction and job  safety risk. Participants responded to items in these measures on five‐point Likert scales (1 = strongly disagree  to 5 = strongly agree). Scale scores were obtained by summing ratings across scale items, and dividing the sum  by the number of items. It was also necessary to adapt items from the scales into the past tense to correspond  with the procedure which required the participant to respond for the last job they had exited: their previous  job.    In the demographic section participants were asked their age, gender, the date they had left their previous job,  the date they filled out the survey, tenure in their previous job, number of co‐workers in their previous job,  and  job  title.  Four  further  questions  were  asked:  Please  rate  how  much  ‘safety  concerns’  prompted  you  to  leave your previous job? (0 = ‘Not at all’ to 7 = ‘Very much’), and At the time you left your previous job did you  feel there were safety issues/concerns which you wanted to tell someone about before you left? (0 = ‘No’ to 7 =  ‘Yes there were a lot of issues’). If participants responded with a rating greater than 0 to the latter question  they were asked If you now had an opportunity to sit down with management from your previous job and voice  your safety concerns how willing would you be to do that? (0 = ‘Not willing at all’ to 7 = ‘Would be very keen to  do that’), and If you now had an opportunity to sit down with co‐workers from your previous job and voice your  safety concerns how willing would you be to do that? (0 = ‘Not willing at all’ to 7 = ‘Would be very keen to do  that’).     Section two of the survey was comprised of 40 statements of safety issues (e.g., Work speed pressure from  supervisors which reduced safety) designed to measure the extent and type of actual safety voicing on the job,  and extent and type of safety issues exited employees might need to voice. For each safety issue, participants  were required to tick one or more response options. Response options were defined by four columns placed to  the  right  of  the  listed  safety  issues  and  headed:  Not  Applicable:  The  safety  issue  was  not  relevant  to  your  previous job; Did: you talked about the issue in your previous job; Yes Management: It is an issue you would  have liked to talk to management about but never did; and finally Yes Co‐worker: It is an issue you would have  liked to talk to co‐workers about but never did.     Three scores were calculated from the section two responses. Firstly, the number of applicable safety issues  that  could  be  talked  about  for  each  participant  was  calculated  by  subtracting  the  total  Not  Applicable  responses  from  the  40  described  safety  issues.  Next,  an  actual  voicing  score  was  calculated  by  dividing  the  number  of  did  responses  by  the  number  of  applicable  safety  issues  which  could  have  been  talked  about.  Finally, two need to voice measures were calculated (one for management and one for co‐workers) by dividing  the Yes Management and the Yes Co‐worker totals by the number of applicable safety issues which could be  talked  about.  Each  of  the  three  variables  could  range  from  1  to  100,  and  represent  the  percentage  of  applicable safety issues participants did talk about, and the percentage of applicable safety issues they would  have liked to talk about with management and with co‐workers.     Participants perceived job risk was measured using the 10‐item Job Safety Risk scale, developed by Hayes, et  al., (1998). This scale was included to ensure that the research had sampled participants who were responding  for a job where safety was a real concern in the workplace. Participants were required to indicate the extent to  which they agreed that words and phrases (i.e. “dangerous”) described their previous job (alpha = .76).     The  five  item  Team  Member  Interaction  scale  developed  by  Pearce  and  Gregersen  (1991)  were  used  to  measure  job  interdependence.  The  scale  was  included  to  ensure  the  study  had  sampled  individuals  whose  previous job had provided an opportunity to interact with co‐workers, and thus potentially an opportunity to  talk with co‐workers about safety issues (alpha = .86).     The three item Perceived Organizational Support for Safety and Perceived co‐worker support for safety scales  developed by Tucker et al. (2008) were adopted to measure the degree to which the company and co‐workers  encouraged  workers  to  express  concerns  about  safety,  and  responded  to  workers  safety  concerns, 

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Christopher Burt et al.  respectively.  Twelve  items  from  the  Interpersonal  Trust  at  Work  (ITW)  scale  developed  by  Cook  and  Wall  (1980)  were  adopted,  six  items  to  assess  participant’s  trust  in  management,  and  six  to  assess  trust  in  co‐ workers. 

3. Results 3.1 Safety concerns and voicing at exit  The  first  question  addressed  was  whether  safety  concerns  had  prompted  participants  to  resign  (exit)  their  previous  job.  A  mean  response  of  1.58  (SD  =  2.0)  was  obtained  for  the  question  regarding  to  what  extent  safety concerns prompted the participant to leave the organization. Given the importance of this question, the  distribution  of  responses  was  examined:  0  (Not  at  all)  =  50.5%,  1=  8.9%,  2=  10.9%,  3  =  10.9%,  4=5.0%,  5=  10.9%, 6 = 0%, 7 (Very Much) = 3.0%. The response distribution translates into 51 participants who indicated  that no concerns about safety had influenced their exit decision, while the remaining 50 participants did have  such  safety  concerns.  This  split  in  the  sample  was  used  to  form  two  groups  which  were  labelled  no  safety  concerns and safety concerns. Significant differences between these two groups were found for job risk scores,  where the group with no safety concerns had a lower job risk mean (2.8, SD = .69) than those in the safety  concerns group (mean = 3.3, SD = .63; F[1,99] = 17.647, P <.01), and for responses to the general need to voice  question:  those  in  the  no  safety  concerns  group  had  a  lower  mean  (1.3,  SD  =  1.7)  than  those  in  the  safety  concerns group (mean = 2.8, SD = 2.1; F[1,99] = 13.062, P <.01). 

3.2 Feasibility of a safety‐specific exit survey process  In  order  to  examine  the  general  feasibility  of  a  safety‐specific  exit  survey  process,  the  responses  of  the  participants  (n=38)  in  the  safety  concerns  group,  who  gave  a  rating  greater  than  0  to  the  general  voicing  question (i.e. At the time you left your previous job did you feel there were safety issues/concerns which you  wanted  to  tell  someone  about  before  you  left?),  to  the  two  questions  on  willingness  to  voice  their  safety  concerns after exit to specific targets were examined. The first question pertained to willingness to voice to  management.  Four  participants  (10.5%)  responded  0  =  not  willing  at  all,  and  the  mean  response  for  the  remaining 34 participants was 3.82 (SD = 2.05, range 2 to 7). The second question pertained to willingness to  voice to co‐workers. Four participants (10.5%) responded 0 = not willing at all, and the mean response for the  remaining 34 participants was 4.29 (SD = 1.96, range = 1 to 7). Responses to the latter two questions indicate  that 68 percent of the participants that had safety concerns at the time they exited were willing to voice their  safety  concerns  if  given  an  opportunity  now.  These  results  may  attest  to  the  importance  of  the  safety  concerns, and to the feasibility of using a safety‐specific exit survey process.  

3.3 Predictors of safety voicing and need to voice at exit  Hypotheses  1  and  2  predicted  that  the  measures  of  management  and  co‐worker  safety  support  and  trust  would  be  positively  correlated  with  actually  voicing  safety  issues,  and  negatively  correlated  with  wanting  to  voice  at  exit.  Table  1  shows  the  correlations  addressing  these  hypotheses.  As  predicted,  safety  support  and  trust  were  positively  correlated  with  actual  safety  voicing.  Perhaps  more  importantly,  the  participants  that  rated safety support and trust as low in their previous job tended to indicate they wished to talk about more  safety issues at exit.  Table 1: Correlations between management and co‐worker support and trust measures, and voicing measures   

Scale Alpha 

Actual voicing  Percentage  N=34 

Management Support  Management Trust  Co‐worker Support  Co‐worker Trust  Actual voicing  Wanted to voice to co‐workers 

.87  .84  .81  .79     

.48**  .30#  .29  .42*     

** = P >.01, * = P >.05, # P = .08 

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Want to voice to  management  Percentage  N=34    ‐.40*  ‐.28  ‐.23  ‐.36*  ‐.87**  .37* 

Want to voice to  co‐workers  Percentage  N=34    ‐.16  .02  ‐.27  ‐.14  ‐.46**   


Christopher Burt et al.  To  further  examine  hypothesis  2,  the  participants  were  divided  into  2  groups.  The  51  participants  in  the  no  safety  concerns  group  (as  defined  above)  formed  one  group,  and  the  34  participants  in  the  safety  concerns  group that indicated they wanted to voice to management and co‐workers at exit formed the ‘wanted to voice  group’. Table 2 shows the means and standard deviations for these two groups for the safety support and trust  measures. Comparison of the means indicate significant differences for both management safety support and  trust. Inspection of the means indicate that the ‘wanted to voice group’ perceived that management support  for safety and trust were lower in their previous job compared to the no safety concerns group.  Table  2:  Means  and  standard  deviations  for  comparisons  of  management  and  co‐worker  support  and  trust  measures   

No Safety Concerns at Exit  N=51 

Management Support 

3.79  .88  3.52  .79  3.52  .87  3.95  .64 

Management Trust  Co‐worker Support  Co‐worker Trust 

Safety Concerns and  Wanted to Voice at Exit  N=34    3.17  1.30  2.98  1.02  3.39  .95  3.78  .71 

ANOVA Comparison  F(1,84) =    6.858*  7.539**  .298  1.340 

** = P >.01, * = P >.05 

4. Discussion The  results  clearly  suggest  that  there  is  an  association  between  workplace  safety  and  employees’  voluntary  turnover  decisions.  This  finding  is  consistent  with  previous  research  (e.g.,  Bell  &  Grushecky,  2006;  Cree  &  Kelloway, 1997). The results also support hypothesis 1, showing that perceived support from management and  co‐workers, and trust in management and co‐workers were positively associated with voicing safety concerns  while  in  the  job.  These  results  are  also  consistent  with  previous  research  findings  (e.g.,  Elizabeth  &  Phelps,  1999; Tucker, et al., 2008). Of particular importance to this paper are the negative associations found between  the support and trust measures, and willing to voice to management after exit. Clearly, employees who had  left  a  job  where  support  and  trust  were  perceived  as  low  had  issues  they  wished  to  voice,  and  this  sample  showed  some  willingness  to  voice  these  concerns  in  a  safety‐specific  exit  survey.  This  suggests  that  the  suppressing influence which a lack of safety support and trust might have on voicing within the job may not  necessarily extend to the exit context.    Overall, the results suggest that once workplace constraints that stem from a lack of support and trust around  safety, such as fear of blame or retaliation for voicing, have been removed because the individual has left their  job,  employees  may  be  willing  to  voice  in  a  safety‐specific  exit  survey  process.  Furthermore,  employees’  motivation to complete a safety‐specific exit survey process may stem from a desire to protect the co‐workers  that remain.     High scores on a safety exit survey (a lot of issues that exiting employees want to talk about) perhaps point to  issues with support and trust in the workplace. So while support and trust might not be measured in a safety‐ specific exit survey, the results may form a proxy measure, with extensive post employment voicing perhaps  indicating that there could be support and trust issues in the workplace. 

4.1 Practical implications: Issues in the use of a safety‐specific exit survey process  From an organization’s perspective it may be important that they do not consider a safety‐specific exit survey  as a process to find out why an employee is leaving their job. That is, the safety‐specific exit survey should not  be  thought  of  in  terms  of  a  classic  exit  interview/survey.  The  key  issue  is  that  traditional  exit  interviews/surveys conducted at the time the employee exits the job have been criticized for producing bias  information,  contaminated  by  impression  management,  and  a  desire  to  distort  or  hide  the  employees  true  reason  for  leaving  (Feinberg  &  Jeppeson,  2000;  Giacalone,  Knouse,  &  Montagliani,  1997;  Gordon,  2011).  Furthermore, as well as framing the safety‐specific exit survey as a safety initiative, the organization might gain 

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Christopher Burt et al.  more complex and valid information if the survey is administered sometime after the employee has exited the  job (Lefkowitz & Katz, 1969).    Separating  the  safety‐specific  exit  survey  from  the  actual  time  an  employee  leaves  the  job  may  also  have  another  benefit.  An  exiting  employee  has  to  make  a  decision  about  whether  to  voice  their  concerns  and  potentially  benefit  their  friends  and  colleagues  who  remain  with  the  organization,  versus  the  costs  to  themselves.  Costs  could  include  retaliation  against  the  exiting  employee  by  giving  them  a  negative  recommendation or reference to a future employer, and/or retaliation against friends and family who may still  be working for the organization (Feldman & Klaas, 1999). A simple way to remove these perceived costs would  be to allow anonymous completion of the safety‐specific exit survey. However, in practise ensuring complete  anonymity may be difficult in roles where the rate of employee turnover is low.     A key issue which the safety‐specific exit survey process must address is who conducts the process. That is how  can the safety‐specific exit survey process work if employees view management as un‐supportive and not to  be trusted? Here it is important to consider the question of whether all management are considered equal in  terms of safety support and trust. To address this issue it may be useful to draw the distinction between work  related  management,  such  as  a  supervisor,  foreman  or  line  managers,  for  whom  the  primary  focus  may  be  productivity (to ensure the assigned work is completed), and a safety manager who may have little direct daily  contact with employees, but whose role it is to ensure workplace safety. Ideally, it is the safety manager who  would be responsible for the safety‐specific exit survey process, as this manager may be seen as in a position  to actually respond in a positive way to voiced concerns, whereas the more immediate manager may in fact  have  already  been  told  of  the  concerns  and  not  responded  due  to  their  focus  on  productivity.  There  is,  however  some  research  evidence  which  suggests  that  attitudes  towards  both  immediate  supervisors  and  authority in general may affect willingness to discuss issues during exit processes (e.g., Knouse, Beard, Pollard  & Giacalone, 1996).     Each organization needs to consider what safety issues they could, or should, include in their safety‐specific  exit  survey.  Ideally  the  survey  items  would  be  developed  to  suit  the  specific  workplace  or  type  of  work.  Arguably, the more idiosyncratic the survey items to a specific organization and the type of work undertaken,  the more informative the data it generates will be for safety development.    In  addition  to  modifying  the  safety  issues  listed  in  a  safety‐specific  exit  survey,  organizations  could  adopt  different  response  formats.  The  current  focus  was  on  identifying  safety  issues  which  employees  wished  to  discuss, what might be termed negative safety issues. By varying the response format, the exit survey could  also  measure  positive  safety  issues.  One  alternative  or  additional  response  option  could  be  to  ask  exiting  employees  to  rate  how  well  the  organization  and  their  work  unit  have  been  managing  each  safety  issue.  Adding this response option might help identify both well managed and poorly managed safety aspects.    Finally, the study has both strengths and limitations. As a strength, the study advances the use of a knowledge  acquisition  tool  which  appears  to  have  previously  received  no  research  attention  in  relation  to  safety  management. Limiting the research is the use of self‐report methodology. However, the variables of interest in  the present study would be very difficult to assess with any other method. 

5. Conclusion If  there  is  no  formal  safety‐specific  exit  survey  process,  the  functional  use  of  any  safety  related  knowledge  which  exiting  employees  hold  cannot  occur.  In  such  circumstances,  neither,  workplace  safety,  or  the  costs  associated  with  employee  turnover  (assuming  the  replacement  employee  may  also  reach  similar  safety  concerns and subsequently leave), are being addressed. While the relationship between safety and employee  turnover identified in the present study suggests that some employees are very likely to have safety issues to  voice in a safety‐specific exit survey, such a survey might be usefully applied to all exiting employees from high  risk  work.  Even  employees  who  are  not  exiting  due  to  specific  safety  issues  may  have  some  useful  safety  knowledge  to contribute  to  the  organization  they  are  leaving.  Safety  gains  from  a  safety‐specific  exit  survey  process  could  be  considerable,  and  allow  an  organization  to  consistently  monitor  and  improve  its  safety  performance. 

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Knowledge Management in Defence Barry Byrne and Frank Bannister Irish Defence Forces and Trinity College Dublin barry.byrne@tcd.ie frank.bannister@tcd.ie

Abstract: Knowledge management in the military has traditionally been carried out by the incorporation of knowledge gained over many years, even centuries, into training and doctrine. Nonetheless, a great deal of knowledge is still learned and transferred in the field, often in quite informal ways, and specialised expertise and insights are frequently lost when experienced personnel leave or are killed in action. This paper examines the emerging trends for knowledge exchange, and explores ways in which technology can be used to facilitate knowledge capture and knowledge transfer in this environment. Emerging technologies have resulted in military forces facing an ever increasing challenge in the race to achieve information and decision superiority. The contemporary operating environments in which peacekeeping forces find themselves require military leaders to process continually increasing amounts of information fed to them by a myriad of sensors in the field. With this vastly increased availability of information comes a corresponding increased risk of information overload and degradation in the ability of commanders to convert information into usable knowledge. While information overload can have serious consequences in the world of business, the implications are even more critical on the battlefield where the quality of decisions can have life and death consequences. Command and control in peacekeeping operations is taking on new dimensions and the role of military personnel is steadily evolving into that of knowledge worker. While intelligence has always been a critical part of military operations, the transition from soldier to knowledge worker may seem an improbable one. However, awareness of the role and importance of knowledge management even at the level of the private soldier and the 'strategic corporal' has grown steadily in recent decades. In the words of a 2010 NATO publication; "knowledge is the new ammunition". This research investigates the potential for Information and Communications Technology (ICT) to aid information and knowledge management in the military in general and on peacekeeping in particular. As part of this research 159 defence personnel from over 15 countries were surveyed to ascertain their opinions and the international trends in this field. Follow up interviews were then conducted with a wide variety of defence experts, civilian and military, across several countries. The findings identify the sharing of information and knowledge as a key enabler in the quest to achieve information and decision superiority both on the battlefield and in the increasingly complex civil-military peacekeeping environment that represents the majority of operations that take place in the world today. A number of recommendations are made to improve the implementation of ICT enabled information and knowledge management initiatives in defence. Keywords: Knowledge management, defence, peacekeeping, decision making

1. Introduction The concept of a transition in the military from traditional soldier to ‘knowledge worker’ is well underway. Information and Knowledge are a military member’s primary resource, regardless of rank. A US Marine Corps General introduced the idea of the ‘strategic corporal’ in 1999, and since then the concept has gained widespread academic and military recognition (Krulack 1999). Militaries have always valued information, but they are increasingly recognising that information, and more specifically, knowledge, is indeed power. (Mace & Thomason 2008). The capture of knowledge, both explicit and tacit, is a challenge for most organisations, but even more so for the military and defence sector. As Goh and Hooper (2009) suggest, that there exists an inherent conflict between allowing information and knowledge to flow freely within the organisation, and the need to keep certain information secure; this is particularly acute in the armed forces where the correct dissemination methods in a closed information environment need careful design. A balance must be found between ease of use and a high level of security and information assurance. Over the last ten years the Irish Defence Forces have embraced the need for continuing change as part of its culture. They have gone through a major evolution and today are a highly professional, modernised, lean organisation with an establishment of 10,000 personnel serving at home and abroad. Ireland has a long and proud tradition of peacekeeping having contributed to 19 international missions in recent years. These engagements have resulted in a large body of knowledge about how to conduct peace keeping operations in what are often extremely volatile and sometimes hostile environments. It is this need to retain corporate knowledge that motivated this research. This research therefore set out to address the question of how Information and Communications Technology (ICT) can support information and knowledge management in defence. The objectives included understanding the current status of information and knowledge management in the Irish Defence Forces, the particular barriers to information and knowledge sharing and the possibilities for using information systems in facilitating the capture and dissemination of information and knowledge. The remainder of this paper is structured as

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Barry Byrne and Frank Bannister follows; first there is a brief literature review on knowledge management (KM) in the military. Next, the research approach is described. In section four the findings and analysis are presented. Section five discusses these findings and section six presents a brief conclusion.

2. Literature review Although some authors use data, information and knowledge interchangeably (Toffler and Butz 1990), it is generally accepted that in any accurate study of the discipline it is important to differentiate between them. This is easy to do with data and information. Knowledge is much more difficult to distinguish and a discussion of this will not be undertaken here as it is assumed that readers will be familiar with this debate. The management of knowledge is also a widely debated topic; protagonists believe it to be the about the management of Drucker’s (1993) “only meaningful resource today”; sceptics describe it as nothing more than the latest management fad (Wilson 2002). Sveiby (1990) was one of the first to write about the measurement of 'intangible assets' and other aspects of 'intellectual capital', but even then the strong ties with information management were evident. Maier (2007) describes knowledge management as a function and states that it is responsible for the resultant selection, implementation and evaluation of goal-orientated knowledge strategies. Rumizen (2002) a KM specialist who has worked with the U.S. Army and National Security Agency, treats knowledge management more as a systematic process and states that it is by this process that knowledge needed for an organisation to succeed is created, captured, shared and leveraged. The US Army states that “knowledge management is a discipline that promotes an integrated approach to identifying, retrieving, evaluating, and sharing an enterprise’s tacit and explicit knowledge assets to meet mission objectives.” (US Army 2010, p2). There is some debate as to whether ’management’ is the correct term to be used in relation to knowledge. Many authors prefer to talk about ’knowledge focus’ or ’knowledge creation’. While NATO has a definition of knowledge management in the Bi-Strategic Command Directive 25-1 that states “NATO knowledge management is a multi-disciplined approach to achieving organisational objectives by making the best use of information, expertise, insights and best practises” it tries to avoid the term ‘management’ and instead refers to the “knowledge centric organization” and “knowledge development” (NATO 2008). Even more dramatically it goes on to state that “Knowledge is the new ammunition. It is a commodity we are constantly collecting, integrating, exploiting and sharing. Regardless of whether you are an operator, staff officer, Subject Matter Expert or General, we are all knowledge managers in the business of transforming information to best serve our needs.” (NATO 2010, p19). Simply put; knowledge management deals with how best to leverage knowledge internally and externally (Liebowitz and Megbolugbe 2003), but perhaps what is needed in the modern environment is recognition that one can never fully manage knowledge, one can only transfer it. The focus should therefore be on managing knowledge transfer frameworks and facilities. In this context there is much debate about the tacit/explicit division and the SECI model which, again for reasons of space, will not be discussed here. Contributors to this debate include not only Nonaka and Takeuchi (1995), but Davenport, (1997) Gourlay (2006a), Stacey, (2001; Tsoukas (2003), Schultze and Stabell (2004), Gourlay and Klien (2008), Niedderer and Imani (2009), Hedlund (1994) and Day 2005). This debate has not deterred many people from pressing ahead with knowledge management models based on SECI and a large body of literature has emerged on each of its components. Liebowitz and Megbolugbe present a useful breakdown of some knowledge management methodologies shown in table 2.1 below. There are many examples of these knowledge management approaches proving highly successful, not only in the introductory phase, but also over extended periods of time. (Rumizen 2002), (Davenport, De Long et al. 1999). The importance of information and knowledge in the modern military environment is well described by McIntyre et al (2003). The exponential growth in the number of sensors and inputs on the battlefield or humanitarian relief environment means that filtering through this Clausewitzian (1976) ‘fog’ of information, to satisfy the Commander’s critical information requirements (CCIR) is fast becoming an almost impossible task. The difficulty lies not in getting the information to the decision-maker, but first in ensuring compatibility and then in the processing of that information, transforming it from data to information and from information to actionable knowledge.

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Barry Byrne and Frank Bannister Table 2.1 – Sample Knowledge Management solutions (Liebowitz and Megbolugbe 2003) IKM Solution

Complexity of Use

Difficulty of Development

Frequent get-togethers to exchange tacit knowledge (i.e. knowledge fairs, brown bag lunches, inter-department seminars)

Low – trying to maximise tacit-tacit knowledge exchanges

Low

Chat rooms, bulletin boards, list servs, online communities, communities of practise, communities of interest, tech clubs, etc. – on the organisation’s intranet Corporate portal for accessing expertise locator systems and used as entry to the organisation’s web site Codifying knowledge and information into knowledge repositories, best practises/lessons learned databases, etc Capturing knowledge and decision making processes via expert systems, intelligent agents, video streaming technologies, etc. Applying data and text mining techniques to look for patterns and inductively create knowledge Using intelligent agents to actively build user profiles and push appropriate lessons learned and material to the respective user

Low – maximising tacit knowledge exchanges in a virtual context

Low

Low

Low to medium

Low to medium

Medium

Low to Medium

Medium to high

Medium

High

Medium

Medium to high

It is important to understand how this information transformed within the military. One means is by staff officers adding their own knowledge, wisdom and insight during the Military Decision Making Process (MDMP) before it reaches the commander (Blodgett 2010). McIntyre, Gauvin et al describe how Choo’s (2002) model of the ‘knowing cycle’ when combined with the Nonaka and Takeuchi model of knowledge creation is reminiscent of the military command and control OODA loop (Observe, Orient, Decide, and Act) in which information and then knowledge are transformed into action. The US Army’s Centre for Army Lessons Learned (CALL) is often cited as one of the pioneering institutions in relation to knowledge management; the NATO Joint Analysis and Lessons Learned Centre (JALLC) is another such institution. Yet despite this head-start on the business world, what in business terms might be called a ‘first mover advantage’, a divide still exists between the effectiveness of civilian KM initiatives and military KM initiatives or programmes. In order to be successful organizations must have robust information and knowledge management strategies, processes, and protocols (Nonaka & Takeuchi, 1995; Davenport & Prusak, 1998; Desouza & Hensgen, 2005), but the challenge arises in reconciling the conflict between encouraging an open, information sharing environment, and maintaining the appropriate security protocols (Desouza and Vanapalli 2005). The problem for Defence organisations as others, is barriers to knowledge sharing. One barrier to adoption is the perception that knowledge is power, and that an individual or sub group that holds onto that knowledge for itself will retain the power associated with it. Another barrier identified by Swan and Scarbrough (1999) and later by Goh and Hooper (2009) is the absence of trust. Hexmoor et al. (2006) recognise the particular need for security, both for the individual and the organisation, but some debate exists over the best ways of overcoming these barriers. Desouza and Vanapilli advocate a strict, controlled approach to information security systems and information assurance while Goh and Hooper recommend a more open, holistic approach to information mechanisms and procedures, leading by example, embracing technical systems and compulsory training. Whichever approach is taken, it is clear that this issue must be addressed as there is a growing interest in applying these technical systems towards the knowledge management of sense-making, threat analysis and decision-making. (McIntyre, Gauvin et al. 2003). This holistic approach, while still leveraging technology to the fullest, ties in closely with the policies of the US Army. In constructing their ‘12 principles of Knowledge Management’ the Army included policies ranging from compulsory training to the “encouraged embedding of knowledge in media such as podcasts, videos and simulations” in the implementation of their knowledge management information system; ‘Army Knowledge Online’. (US Army 2010)

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2.1 Responsibility to Share Balanced with Need to Know The dominance of the traditional concept of “need to know” may in the past have held some military and defence organisations back from exchanging information effectively in recent years. This concept is evolving, and NATO’s new Information Management Policy takes cognisance of this; one of the principles of this document is information sharing. Here NATO states that “Information shall be managed with an emphasis on the ‘responsibility-to-share’ balanced by the security principle of ‘need-to-know’, and managed to facilitate access, optimise information sharing and re-use, and reduce duplication, all in accordance with security, legal and privacy obligations.” (NATO 2007, p3). This is a major paradigm shift in the approach to information exchange within a defence environment. NATO today recognises that the benefits of timely and accurate information exchange far outweigh the risks.

3. Methodology In this study, a mutimethodological approach was taken combining a quantitative survey with structured interviews. This study was conducted on quasi-randomly selected personnel from the Irish Defence Forces representing all ranks, units, corps, arms and brigades. Permission was also sought to interview and survey a wide selection of international militaries. Quantitative and qualitative research was conducted in Little Creek Naval Base, Virgina, NATO headquarters in Brussels, the Swedish Command and Control Training Regiment in Enkoping, and in a number of Irish locations. The large number of international responses obtained made it possible to compare and contrast the opinions of foreign military personnel to those of serving Irish Defence Forces personnel. The survey questionnaire was constructed using mostly closed-ended questions and a (5 point) Likert scale. A literature search for comparable studies revealed one such study conducted on a smaller scale within the New Zealand Defence Forces (Goh and Hooper 2009). Although the latter focused on the barriers to information sharing, some guidance on the construction of suitable questions relating to the potential for information systems to aid information and knowledge management was obtained. Pre-testing was conducted on the questionnaire on a sample group of 30 Irish military personnel. Once these findings had been incorporated into the instrument design, the full survey was undertaken. Due largely to the personal approach taken in the delivery of the surveys and possibly the regimented nature of military organisations, there was a 98% response rate. The data collected from the surveys were analysed using SPSS software. In total 159 surveys were completed, with semi-structured interviews conducted in the USA, Sweden, Ireland and Belgium. Due to the nature of the industry, no identities of personnel interviewed may be disclosed, but the interviewees represented a wide range of nationalities from civilian defence agencies, militaries and military bodies. A senior representative from the CIMIC Fusion Centre based in Norfolk Virginia was also interviewed, giving valuable insight into the difficulties of information sharing in a Civil – Military context. In total 15 interviews were conducted.

4. Findings and analysis The results of the questionnaire and semi-structured interviews showed that all ranks from junior private to senior officer, regardless of their nationality, recognised that there was a definite need for improved information and knowledge management in defence. A considerable amount of analysis was undertaken and there is insufficient space in this paper to report more than a modest faction of the output. The analysis included comparisons between Irish military and international personnel and between difference branches of the Irish military. The following are some of the salient findings. Many military personnel feel they have too little information available to them in their daily work (figure 4.1). Some 61.3% of Irish Defence Forces personnel and 48.8% of international personnel agreeing or strongly agreeing with this statement. The majority of respondents felt that the information that was available to them was inconsistent though almost all respondents regarded information received though information systems as accurate. There is broad agreement that the current information systems are facilitating knowledge and information sharing within defence. While respondents felt that ICT does facilitate information sharing, they also felt they received insufficient training on these systems to fully leverage the possibilities they offer. Information hoarding is regarded as a serious problem (figure 4.1). The threat of possible punitive action for the mistaken sharing of inappropriate or ‘over classified’ information creates a powerful disincentive and prevents some knowledge exchanges existing on any significant level (see next finding).

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Figure 4.1 â&#x20AC;&#x201C; Information hoarding exists between units/formations Information hoarding is also influenced by concerns about confidentiality as can be seen in figure 4.2. During the course of this study confidentiality and the inaccurate of over-classification of documents has frequently been cited as a key inhibitor to information and knowledge exchange in defence. It is clear from Figure 4.2 that regardless of rank, branch or indeed nationality, all respondents felt this was a major inhibitor of information exchange. Confidentiality concerns deter people from sharing information (figure 4.2). This is a major problem and has several dimensions not the least of which is confusion and uncertainty about the requirements for confidentiality in certain types of information and in who is entitled to see what.

Figure 4.2 â&#x20AC;&#x201C; Confidentiality concerns deter people from sharing information

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Barry Byrne and Frank Bannister One international interviewee noted that the situation had become so difficult that even the processing of routine paperwork had been inhibited â&#x20AC;&#x153;I could not even share information with myself...routine unclassified documents that I had created on one PC on my desk were automatically deemed too secure to move to the PC beside itâ&#x20AC;? Absence of motivation to engage in KM related activities is a further contributory factor. (figure 4.3). Staff felt that there were no incentives to engage in sharing of knowledge.

Figure 4.3 â&#x20AC;&#x201C; A suitable reward system exists for positive contribution to knowledge capital As noted by Stevens (2000), though rewards are not essential, they often act as a catalyst to improve sharing (Goh and Hooper 2009). However, the findings of this study show that there are almost no such rewards in place. This runs counter to the advice of Bartol and Srivastava (2002) who emphasized the importance of rewarding knowledge sharing. There is a strong belief that a key factors in information and knowledge hoarding is the belief that information and knowledge are power (figure 4.4). This suggests that there is a degree of cynicism in the military, but if this perception is close to reality, it suggests that operations may be put at risk by individual or group playing territorial games (Bannister 2005).

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Figure 4.4 â&#x20AC;&#x201C; Personnel hoard information because they believe information is power

4.1 Enhancing knowledge management Several ways of enhancing KM in the military were explored in the study. There was agreement on most of the approaches examined, particularly on the need for improved knowledge and information flow between units (figure 4.5)

Figure 4.5 â&#x20AC;&#x201C; Information and Knowledge flow well between units/formations This survey suggests that in general the Irish military is not as advanced in its use of KM as its international counterparts. It must be stressed that, given the small size of the sample, this is only an indicative finding, but it is strongly supported by respondentsâ&#x20AC;&#x2122; comments and observations in the interviews. Table 4.3 is one of

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Barry Byrne and Frank Bannister several examples where international respondents suggested that they were happier with their information and knowledge management than their Irish peers. Table 4.1 - I currently have enough access to information and corporate knowledge I currently have enough access to the information and corporate knowledge of the Defence Forces Stron gly Strong ly Agree Neutral Disagree Disagre e Ag ree Irish Forces

Defence 1.7%

25.6%

2 2.2%

39.3%

11.1%

8.1%

37.8%

2 9.7%

21.6%

2.7%

International

International responses also presented numerous different approaches to addressing information and knowledge management initiatives. The use of portals was a common method, however some used different combinations of functionality within the portal, for example one interviewee commented “We have a wiki for knowledge management and a document management system for information management” The use of awareness campaigns for information management has been particularly effective in Canada where even the most simple of mechanisms was noted to be effective at getting the message across to a large number of personnel. Mouse mats, cups and pens were made up with messages on the importance of data security and information management. What was also apparent from the international responses was that while information management is steadily gaining acceptance as an essential element of any military organisation’s business practises, knowledge management is still a slightly more ‘fuzzy’ concept. Where the responsibility for the direction and leadership of this knowledge management lies is at present not fully understood. This problem was put by one informant thus “The problem is information and knowledge management is being treated as a G2 (intelligence) issue, when really it should be a staff or headquarters issue.” Current information systems do not seem to be providing the level of collaboration facilities required by defence workers. In the current cost-conscious economic climate where defence budgets are being continuously scrutinised for possible savings this situation is less than desirable (table 4.2). Table 4.2 – Information systems encourage collaboration

Irish Defence Forces International Total

Current DF Information Systems encourage collaboration on projects Strongly Strongly Agree Agree Neutral Disagree Disagree .9% 20.9% 34.8% 35.7% 7.8% 5.3% 28.9% 26.3% 34.2% 5.3% 2.0% 22.9% 32.7% 35.3% 7.2%

It is well established in the information systems literature that for systems to be effective and successful, they should, inter alia, be well designed, be built in close consultation with users and have support from top management. However several interviewees were quite critical of the quality of information and knowledge management systems design. The degree of frustration can be seen in figure 4.6.

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Figure 4.6 – Contributing knowledge and information through DF information systems is easy. Finding expertise is a common problem (figure 4.7). In the survey, there was strong disagreement expressed with the statement “I can always locate an individual with a specific skill set”. This was particularly evident in international responses where ‘disagree’ and ‘strongly disagree’ accounted for a large percentage of the responses.

Figure 4.7 – I can always locate an individual with a specific skill set This was one area where the international experience was worse than the Irish one, but this may largely be a matter of scale. It may also be due to the increased emphasis ‘joint’ operations at an international/strategic level in the military world today. This working environment does not lend itself well to the traditional model

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Barry Byrne and Frank Bannister of subject matter experts becoming known to an organisation through socialisation and other informal, contact based means. On a positive note, there is widespread belief that access to information has improved in recent years. The interesting observation here is that despite the majority of international respondents agreeing with this statement, a sizable percentage disagreed completely; again pointing to the complex international operational environment of modern day crisis relief and peacemaking operations coupled the growth in the type and number of information systems trying to address this, not always in a cohesive and structured way.

5. Conclusions and future work Information and knowledge are the most valuable resources to any military while paradoxically also becoming the new ‘fog’ of modern war. The modern operating environments that peacemaking and peacekeeping forces find themselves in require military leaders to process exponentially increasing amounts of information fed to them by a myriad of sensors in the field. Identifying the relevant information and knowledge to enable faster, better informed decisions is a challenge. Despite an apparent ‘first mover advantage’ represented by the early recognition of Lessons Learned dating from Napoleonic times, to the US Army’s Centre for Army Lessons Learned (CALL), through to NATO’s more recent Joint Analysis and Lessons Learned Centre, there still exists a divide between civilian KM adoption and military adoption. This stems from security concerns hindering interoperability, the lack of understanding by military personnel in the appropriate security marking of documents and finally a lack of awareness of the principle of ‘responsibility to share’. One of they key findings of this research noted above, and one which little is currently written about, is the tendency of military personnel to deliberately overclassify documents they are working on so as to err on the side of caution, and for poorly designed information systems to perpetuate this problem. Militaries must ensure that they stay abreast of relevant interoperability considerations and standards when designing/implementing any system. Relevant use of standards such as STANAG (standardisation agreement) and interoperability platforms such as MIP (multilateral interoperability programme) should be leveraged to the fullest. Where possible, use one platform and control access rights accordingly. Another key finding is that there are currently insufficient reward systems in place to motivate personnel to contribute to the knowledge capital of the organisation. This problem is aggravated by the perceived advantages of doing the converse, i.e. hoarding knowledge. In addition to the usual recommendations (more training, top level support for new initiatives, etc.) this research suggests that systems that reward contributions to KM and penalise unnecessary hoarding are important. Greater clarity about confidentiality is also important. At present, military personnel will assume the most restrictive rules apply unless they know otherwise, particularly in a multinational operating environment. Good policies are essential. Fostering communities of practice will enhance cooperation and sharing. In the military these may have different nuances from the civilian sphere, but the basic principles remain the same. New challenges continue to emerge. In any situation information overload is a problem. In a military context, it can literally be fatal. This study suggests an increased awareness and investment in information and knowledge management in defence. With the correct balance of human and technological interaction, information and knowledge transfer frameworks and mechanisms can be facilitated and managed to supply the correct information at the right time, in the right format to the right person to satisfy the military decision maker’s informational needs and objectives. But the effort required is considerable and must be planned and executed with the support of all ranks.

References Bannister, F. (2005) E-government and administrative power: the one-stop-shop meets the turf war, Electronic Government, an International Journal, 2(2), 160-176. Bartol, K. M. and A. Srivastava (2002). Encouraging knowledge sharing: The role of organizational reward systems. Journal of Leadership & Organizational Studies, Summer. Blodgett, C. (2010). December NIMAG Conference 2010. NATO Information and Management Advisory Group, Brussels. Choo, C. W. (1996). The knowing organization: How organizations use information to construct meaning, create knowledge and make decisions* 1. International Journal of Information Management 16(5): 329-340. Choo, C. W. (2002). Information management for the intelligent organization : the art of scanning the environment. Medford, NJ, Information Today. Clausewitz, C., M. E. Howard, et al. (1976). On war, Princeton University Press, Princeton, NJ. Davenport, T. and L. Prusak (1997). Information ecology: Mastering the information and knowledge environment, Oxford University Press, USA.

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Barry Byrne and Frank Bannister Davenport, T. and L. Prusak (1998). Working knowledge: How organizations manage what they know, Harvard Business Press. Davenport, T. H., D. W. De Long, et al. (1999). Successful knowledge management projects. The Knowledge Management Yearbook 1999-2000: 89–107. Desouza, K. (2009). Information and Knowledge Management in Public Sector Networks: The Case of the US Intelligence Community. International Journal of Public Administration 32(14): 1219-1267. Desouza, K. and G. Vanapalli (2005). Securing knowledge in organizations: lessons from the defense and intelligence sectors. International Journal of Information Management 25(1): 85-98. Drucker, P. (1993). Management: Tasks, responsibilities, practices, Harper Paperbacks. Drucker, P. and J. Campanella (1993). Managing for the Future. Oxford, England, Butterworth-Heinemann Goh, C. and V. Hooper (2009). Knowledge and information sharing in a closed information environment. Journal of Knowledge Management 13(2): 21-34. Gourlay, S. (2004). 'Tacit knowledge': the variety of meanings in empirical research. Hexmoor, H., S. Wilson, et al. (2006). A theoretical inter-organizational trust-based security model. The Knowledge Engineering Review 21(02): 127-161. Irish Defence Forces, (2011). www.military.ie. Retrieved 02 Feb 2011, 2011. Krulack, C., Gen USMC (1999). Strategic Corporal: Leadership in the Three Block War. Marine Corp Gazette: pp 18 - 22 Liebowitz, J. (1999). Knowledge management handbook, CRC. Liebowitz, J. (2003). Keynote paper: measuring the value of online communities, leading to innovation and learning. International Journal of Innovation and Learning 1(1): 1-8. Liebowitz, J. and I. Megbolugbe (2003). A set of frameworks to aid the project manager in conceptualizing and implementing knowledge management initiatives. International Journal of Project Management 21(3): 189-198. Likert, R. (1932). A technique for the measurement of attitudes. Mace, B. and G. Thomason (2008). Knowledge Management Is Combat Power. Marine Corps Gazette 92(6): 37. Maier, R. (2007). Knowledge management systems: Information and communication technologies for knowledge management, Springer Verlag. McIntyre, S., M. Gauvin, et al. (2003). Knowledge management in the military context. Canadian Military Journal 4(1): 3540. NATO (2007). The NATO Information Management Policy. N. A. COUNCIL. C-M(2007)0118. NATO (2008a). The Primary Directive on Information Management. N. A. COUNCIL. C-M(2008)0113 (INV): 4. NATO (2008b). Bi-SC Information and Knowledge Management (IKM) DIRECTIVE. B.-S. C. (Bi-SC). 25-1: 1-11. NATO (2010). A lessons learned enabler for NATO transformation. The Three Swords. Stravanger, Norway. 17: 18-22. US NAVY (2005). Navy Knowledge Management Strategy communication U. NAVY. Niedderer, K. and Y. Imani (2009). Developing a framework for managing tacit knowledge in research using knowledge management models. Nonaka, I. and H. Takeuchi (1995). The knowledge-creating company: How Japanese companies create the dynamics of innovation, Oxford University Press, USA. Priest, D. a. W. T. A. (2010). The Secrets Next Door (from the series Top Secret America). The Washington Post. Washington. Rumizen, M. (2002). The complete idiot's guide to knowledge management, Alpha Books. Schultze, U. and C. Stabell (2004). Knowing what you don’t know? Discourses and contradictions in knowledge management research. Journal of Management Studies 41(4): 549-573. Stacey, R. D. (2001). Complex responsive processes in organizations: Learning and knowledge creation, Psychology Press. Stevens, L. (2000). Incentives for sharing. Knowledge Management 3(10): 54-60. Sveiby, K. (2001). A knowledge-based theory of the firm to guide in strategy formulation. Journal of Intellectual Capital 2(4): 344-358. Swan, J., H. Scarbrough, et al. (1999). Knowledge management–the next fad to forget people. Toffler, A. and B. Butz (1990). Powershift: Knowledge, wealth, and violence at the edge of the 21st century. New York, Bantam Books. Wilson, T. (2002). The nonsense of knowledge management. Information Research 8(1): 8-1.

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A Framework for Improving an Organizational Memory Information  System’s Deployment Architecture  Osvaldo Cairo and Oscar Ojeda Galicia  Instituto Autónomo de México, México D.F., México  cairo@itam.mx  oscar.ojeda3@gmail.com    Abstract:  The  demand  on  Knowledge  Management  in  the  organizations,  which  are  out‐performing  their  peers  by  above  average  growth  in  intellectual  capital  and  wealth  creation  has  lead  to  a  growing  community  of  IT  people,  who  have  adopted the idea of building Corporate or Organizational Memory Information Systems (OMIS). This system acknowledges  the  dynamics  of  the  organizational  environments,  wherein  the  traditional  design  of  information  systems  does  not  cope  adequately with these organizational aspects. The successful development of such a system requires a careful analysis of  essential for providing a cost‐effective solution which will be accepted by the employees/users and can be evolved in the  future. This paper proposes a nine‐layered framework for improving OMIS’ implementation plan in order to support the  effort  to  captures,  shares  and  preserves  the  Organizational  Memory  (OM).  The  purpose  of  this  framework  is  to  gain  a  better understanding of how some factors are critical for the successful application of OMIS in order to face how to design  suitable OMIS to turn the scattered, diverse knowledge of their people into well‐documented knowledge assets ready for  deposit and reuse to benefit the whole organization.    Keywords: corporate or organizational memory, information systems, knowledge management 

1. Introduction Currently, in most companies, employees' knowledge related to problem solving generally is not documented,  and if it is, it is captured in manuals, memos, text files, etc. On the other hand, the transfer of their experiences  is traditionally done in work meetings, training courses and by reading manuals, and in a few companies, in  electronic form by means of telephone, emails, videoconferences and electronic meeting systems. If a person  had  a  memory  like  the  average  company,  you  would  think  that  this  person  suffered  from  a  neurological  disorder, as companies often forget what they have done in the past and the reasons for what they did.    The knowledge of an organization is part of a new capital for businesses and taking advantage of it has become  a powerful arm to maximize their potential for adding value and increasing their competitive advantage.    The use of the Corporate Memory is a first step in making knowledge part of the corporate culture, due to the  fact that it extends and expands knowledge through the capture, organization, dissemination and reuse of the  knowledge generated by its employees. The Corporate Memory covers several aspects of the dynamics of an  organization; therefore it is necessary to use the information systems to support these kinds of initiatives or  projects.  The  use  of  the  correct  resources  clearly  influences  the  success  of  the  development  and  implementation of Corporate Memory Information Systems. This class of systems requires a careful analysis in  order to provide a cost effective solution that is accepted by the employees, that meets their objectives, and  has the potential to grow in the medium and long term. 

2. Theoretical framework  Stein and Zwass (1995) define a Corporate Memory or Organizational Information System (OMIS) as "a system  that functions to provide a means by which knowledge from the past is brought to bear on present activities,  thus resulting in increased levels of effectiveness for the organization." Lehner (1998) defines an OMIS as "a  system  that  integrates  the  elements  that  form  the  basis  of  knowledge  of  the  organization  with  the  help  of  information  and  communications  technologies,  and/or  integrates  and  supports  tasks,  functions  and  procedures that are connected to the use of the organization's base of knowledge".    An  OMIS  has  the  advantage  of  storing  knowledge  electronically;  its  applications  are  valuable  and  useful  (if  adopted willingly) and favor the achievement of organizational goals at relatively low costs. Among the most  important disadvantages of these systems are their difficulty in classifying or indexing the information, costs in  the recovery and interpretation of the information, which in some cases depend on the particular type of data,  limited by the Information Technologies (TIC) used.   

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Osvaldo Cairo and Oscar Ojeda Galicia  Stein and Zwass (1995) developed a framework for an OMIS that consists of two layers (see Figure 1). The first  layer  incorporates  four  subsystems  that  are  derived  from  four  functions  of  effectiveness:  integration,  adaptation, achievement of goals and pattern maintenance.     Integration  is  the  coordination  and  management  of  information  across  the  organization,  while  adaptation  is  the  ability  of  the  organization  to  adapt  to  the  changes  in  its  environment.  The  third  subsystem  is  the  attainment of objectives that depend on the ability of the organization to establish goals and assess the degree  of  compliance.  Lastly,  the  reproduction of a  social  system  through  time  (Pattern  Maintenance)  refers  to  the  ability of the organization to maintain the cohesion and morale of the work force.    The  second  layer  consists  of  mnemonic  functions,  including  the  acquisition  of  knowledge,  conservation,  maintenance, search and retrieval of information. These two layers may or may not be based on Information  Technologies (TIC). 

Figure 1: Framework for an OMIS (adapted by Stein and Zwass, 1995)  Stein  and  Zwass  (1995)  argue  that  certain  situations  could  limit  the  deployment  and  use  of  an  OMIS.  They  point out that although an OMIS can demonstrate its effectiveness in an organization, the project to develop it  may not actually start. Even if the project is initiated, it may not be concluded. If the project is completed, the  system may not be used. If the system is used, it may not be used properly. And even, if it is used correctly, it  may not reach its full potential.    A model of success for an OMIS should allow the assessment of the extent to which the implementation of an  OMIS will reach its full potential in relation to the improvement in the effectiveness of the organization. 

2.1 Success model for an OMIS  Jennex, Olfman, Pituma and Tong‐Tae Park (1998) created a successful model adapted to the context of the  OMIS  based  on  the  model  of  DeLone  and  McLean's  (1992)  known  as  I/S  Success  Model  (see  Figure  2).  The  model consists of five recursive blocks. This model has different, independent blocks in relation to the quality  of the system and quality of the information. 

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Figure 2: Model of success for an OMIS  The  model  can  justify  the  factors  for  success  in  the  implementation  of  an  OMIS  within  an  organization.  It  begins with the quality system block to determine the terms of its operative characteristics. Subsequently, the  information  quality  is  measured  in  terms  of  the  results  or  generated  outputs.  The  third  block  measures  the  components  of  the  OMIS  in  terms  of  use.  The  individual  impact  consists  in  identifying  the  change  in  staff  performance  associated  with  productivity.  Finally,  the  organizational  impact  is  associated  with  the  effectiveness  throughout  the  company,  which  is  measured  in  relationship  to  the  internal  organizational  performance  (costs,  work  environment,  trained  personnel,  quality  of  products  and  services,  etc.)  and  the  external organizational performance (level of customer satisfaction, sales, market position, value added, social  responsibility, perception of consumers and investors, etc.). 

3. Methodology A proposal  for  the  architecture  of  the  elements  that  must  be  included  in  the  Organizational  Memory  Information System (OMIS) is presented in this section. It is different from other already existing architectures  that integrate the planning phase and measuring of results. To elaborate it, elements from various projects of  OMIS  ‐‐  of  the  architecture  proposed  by  Stein  and  Zwass  (1995),  the  model  by  Jennex,  Olfman,  Pituma  and  Tong‐Tae  Park  (1998),  among  other  research  about  the  Corporate  Memory  ‐‐  were  taken  into  account.  The  functional elements of this architecture are looking for the collection, preservation, recovery and distribution  of  the  knowledge  of  the  employees  of  an  organization.  The  objective  is  to  propose  an  architecture  of  nine  layers  (see  Figure  3)  to  improve  the  implementation  plan  in  order  to  support  the  Corporate  Memory  to  increase its chances of success. 

Figure 3: Structure for an organizational memory information system  Each of the layers that make up the architecture works as a service, so that the architecture is scalable, flexible  and robust. In this way, each organization can adapt the architecture according to its needs, including having 

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Osvaldo Cairo and Oscar Ojeda Galicia  the possibility of omitting certain elements of the layers (always when it accepts the risks or the reduction in  the quality of the results delivered to the upper layers), in order to achieve the objectives established for this  type of project. The main objectives of each of the layers are:  ƒ

Layer of  culture  of  knowledge.  The  goal  is  to  establish  an  environment  that  promotes  the  sharing  of  knowledge  among  the  members  of  an  organization.  It  lays  down  the  foundations  for  the  support,  collaboration and participation, with the purpose of registering the knowledge of the employees and using  it  for  the  benefit  of  the  organization.  It  is  not  necessary  to  have  a  mature  or  deeply  rooted  culture  of  knowledge in order to establish these systems. However, the employees need a culture that will enable  them to be facilitators for the construction and operation of an OMIS. 

ƒ

Layer of  planning.  It  establishes  the  levels  of  the  Corporative  Memory,  with  the  intention  of  having  a  clearer picture of the objectives and activities to carry out. In addition, it serves to identify the areas of  opportunity  of  the  project  and  to  determine  if  the  organization  is  ready  to  continue  with  the  following  stages of the project. This layer has seven modules, which are: a) align the objectives of the OMIS with the  objectives of the organization; b) prepare for the change; c) create a work team for the project; d) audit  the current situation; e) define the important functions; f) relationship with the employees and g) analysis  of the return on investment (ROI). 

ƒ

Layer of knowledge. This layer establishes a methodology on how the knowledge of the people is going to  be sorted, stored and used. It has a strong impact on the way in which knowledge will be processed and  consists  of  four  modules:  a)  select  the  elements  of  knowledge  that  will  be  stored  in  the  OMIS;  b)  contextualize the knowledge stored in the OMIS; c) agents monitor the life cycle of the knowledge stored  and d) quality of knowledge. 

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Storage Layer.  It  provides  for  the  physical  means  of  storage,  establishes  the  location  of  the  storage  systems, the dimensioning of the storage space, design of the database or metadata, and categories for  grouping the information (databases, metadata, documents, etc.). 

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Layer of Elements and Quality of the System. The system handles a wide variety of functions and supports  certain activities. Therefore, this layer establishes the elements that support the system in the effective  and  efficient  management  of  the  employees'  knowledge.  The  main  elements  are:  the  business  process  model  (BPM), the  organizational  model,  roles,  profiles  and  ontologies  (tasks,  domains and  information).  Ludger  van  Elst,  Andreas  Abecker  and  Heiko  Maus  (2001)  developed  a  model  that  represents  the  interaction  of  these  elements.  In  addition,  it  is  necessary  to  have  agents  who  know  how  to  handle  or  manage the different scenarios that may be present in the system. 

In relation  to  the  quality  of  the  system,  the  objective  of  this  module  is  to  define  its  quality  in  terms  of  its  operative characteristics, i.e., it describes how good the system is. The quality is divided into three groups: a)  technical quality; 2) quality in the use of the system; and c) quality in the information provided.  ƒ

Security Layer.  It  establishes  the  processes,  mechanisms  and  strategies  to  protect  the  information  contained in the system. The knowledge contained in the system is a valuable asset to the organization,  and  therefore  it  is  recommended  that  the  best  safety  practices  be  applied.  Some  basics  that  should  be  considered  when  applying  security  in  these  systems  are:  to  facilitate  the  supply  of  the  OMIS,  and  to  improve the recovery processes of knowledge and automatic privacy mechanisms.  

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Communication Layer. Within the organization, the aim of the communication of knowledge is to take the  isolated knowledge (tacit and explicit) that the members of the organization have and transmit it to all of  the employees at the moment they need it. It sets out the strategies and mechanisms for communicating  knowledge  registered  in  the  system,  as  well  as  that  which  doesn't  exist,  but  that  can  be  found  through  directories of experts or though other means.  

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User Interface Layer. It allows the identification of points to consider in designing a user interface in order  that the one‐to‐one interaction with the system is pleasant, thus increasing the chances of acceptance of  the system. In the case of an OMIS, it establishes an interface similar to a virtual desktop in which work  and  knowledge  can  be  merged,  increasing  the  possibilities  of  use.  In  the  design  of  the  user  interface,  usability  should  be  considered.  Jakob  Nielsen  (1993)  establishes  10  basic  heuristic  usabilities:  a)  simple  and  natural  dialogues;  b)  speak  the  user's  language;  c)  minimize  the  memory  usage;  d)  consistency;  e)  feedback; f) clearly marked exits; g) shortcuts for the experts; h) good error messages; i) prevent errors;  and j) in case all else fails, there must be assistance and documentation.  

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Layer of measurement and evaluation. It establishes the planning of measurement indicators that reflect  the reality of the Corporate Memory in order to fully know the benefits of the OMIS, and identify areas of  opportunities in a precise manner. On some occasions, it is difficult to measure when the expectations are  not easily quantifiable (economic, productivity, comparison in relation to its competitors, etc.). However,  certain indicators are proposed that can help measure the impact that an OMIS has (at both the individual  and  organizational  level),  which  are:  learn  and  improve,  effectiveness  and  efficiency,  usability,  socialization, preservation and reuse of knowledge, generate new knowledge (tacit and explicit), quality,  ease in managing knowledge, return on investment (ROI), security of knowledge, increase of knowledge  without human intervention, and innovation and achievement of objectives. 

There is a tenth layer that could be applied as part of a process of continual improvement of the system and  only  under  certain  circumstances.  These  are:  a)  having  an  OMIS  working  at  its  maximum  potential;  b)  the  system offers tangible benefits and fulfills its objectives; c) investment for its deployment and d) consolidation  of the culture of knowledge.   ƒ

Extract, Transform  and  Load  (ETL).  The  purpose  of  this  layer  is  to  automatically  enrich  the  recorded  knowledge  in  the  system  to  see  information  from  external  sources.  To  the  extent  possible,  it  seeks  to  eliminate  human  intervention  in  the  search  and  selection  of  information  from  different  sources  (customers, providers, internal/external systems, competitors, news, statements of results, etc.) This layer  requires  a  rigorous  analysis  to  select  and/or  design  a  solution  that  allows  it  to  choose  the  correct  information to supplement the knowledge within the proper context. 

4. Benefits A study by Gartner Group estimates that more than half of the companies that are classified in the Fortune  1000 will depend on KM and KMS by the year 2003 (Johne, 2001) to extend the gap between them and their  competitors. Drucker points out that knowledge is productive only if it is applied to establish a difference.  He  suggests that this productivity should be the determining factor of any company or industry – apply knowledge  to products and /or services.    The life cycle of products and services can accelerate in an unprecedented manner, through knowledge. Some  examples of this is the market value (values to March 25, 2011) of some companies, such as Apple, Microsoft,  IBM, Google and Pfizer. Even conventional retailers like Walmart consider its competence in the management  of logistics a knowledge‐intensive activity, in order to turn it into its primary driver in business successes.    In addition, the ability of companies to exploit their intangible assets has become a more decisive factor than  their  ability  to  manage  and  invest  in  their  physical  assets.  When  the  markets  change,  uncertainty  prevails,  technologies  proliferate  and  competitors  multiply,  and  the  products  and  /or  services  can  quickly  become  obsolete. In order to be successful, companies should focus on obtaining the following skills:  ƒ

Generate new knowledge. 

ƒ

Distribute it rapidly. 

ƒ

Incorporate it into their products and / or services. 

An organization that learns sees the differences that exist between its actual and expected results, and tries to  correct  the  errors  that  have  caused  these  differences.  This  type  of  company  seeks  to  improve  its  actions  through the acquisition of knowledge and understanding. It does not only capture the knowledge, but it uses  its ability to respond and adapt to changes in the organizational environment (Hashim and Othman, 2003).  

5. Conclusions This  article  discussed  the  proposal  of  a  new  architecture  that  allows  for  the  improvement  in  the  implementation of the Corporate Memory Information System, and which consists of nine layers. These layers  are designed to establish the levels of the system and knowledge as well as the layout of the elements that  must  integrate  an  information  system.  They  ultimately  define  the  indicators  that  measure  the  reality  of  the  Corporate Memory in order to know how it achieves organizational efficiency and the competitive advantage.    The  contribution  of  this  proposal  is  to  have  an  architecture  that  integrates  both  aspects  of  information  systems, such as aspects that are not associated with Information Technologies (IT), with the intent that the  architecture  can  be  applied  to  any  Corporate  Memory  project  without  limiting  its  scope.  The  architecture  is 

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Osvaldo Cairo and Oscar Ojeda Galicia  designed in layers that function as services and that are independent of each other, with the purpose of easy  and flexible implementation, and additionally provides modularity, adaptation to the changes and scalability.    Finally, the implementation of an OMIS covers a variety of factors (tangible and intangible) that can influence  the achievement of the goals for which it was conceived. Having an architecture or framework that serves as a  guide to learn about the elements that influence the success of those projects facilitates its implementation  and its future growth.  The Information Technologies (IT) can contribute as a central component of knowledge  management and subsequently toward organizational learning. 

Acknowledgements   This work has been founded by Asociación Mexicana de Cultura A.C. 

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The KAMET II Methodology: A Real Process for Knowledge  Generation  Osvaldo Cairó and Silvia Guardati  Department of Computer Science, ITAM, México DF, México, Río Hondo 1, Mexico  cairo@itam.mx  guardati@itam.mx    Abstract:  Knowledge  acquisition  (KA)  is  considered  today  a  cognitive  process  that  involves  both  dynamic  modeling  and  knowledge generation activities. We understand KA should be seen as a spiral of epistemological and ontological content  that  grows  upward  by  transforming  tacit  knowledge  into  explicit  knowledge,  which  in  turn  becomes  the  basis  for a new  spiral  of  knowledge  generation.  This  paper  presents  some  of  our  attempts  to  develop  a  knowledge  acquisition  methodology  that  mainly  build  a  bridge  between  two  important  fields:  knowledge  acquisition  and  knowledge  management.  KAMET  II  (Cairó  and  Guardati,  2012),  the  evolution  of  KAMET,  represents  a  modern  approach  to  creating  diagnosis‐specialized knowledge models and knowledge‐based systems (KBS) that are more efficient.     Keywords: knowledge acquisition, knowledge management, knowledge modeling, knowledge generation 

1. Introduction Although  technologies  have  been  improved  and  in  general,  much  work  has  been  done  in  recent  years,  knowledge acquisition remains the main factor that hampers a well‐controlled KBS life cycle. The problem still  exists. Because the acquisition of knowledge involves predominantly a social process and a cognitive process,  we think that efforts to acquire and model the know‐how, know‐why and the care‐why of an expert (or group  of experts) must undoubtedly involve knowledge and ideas from different areas, such as psychology, sociology,  philosophy and computer science.    Knowledge  undoubtedly  represents  the  main  competitive  advantage  of  an  organization  ‐‐  we  assumed  the  ability  of  the  firm  to  recognize  and  assess  the  value  of  knowledge.  The  competitive  advantage  derives  from  difficult‐to‐imitate capabilities that lives in the mind of individuals, tacit knowledge, and that are embedded in  dyadic and network relationships (Yli‐renko et al., 2001; Dyer and Singh, 1998). It is the knowledge, the ability  to  create,  to  use,  and  to  transfer    it,  which  may  allow  the  creation  or  improvement  of  new  products  or  services.  But  knowledge  is  often  tacit.  Therefore,  it  is  difficult  to  transfer  knowledge  to  another  person  by  means of the written word or verbal expression. This is precisely one the main obstacles.    This paper addresses this important problem. We conceive the process of knowledge acquisition as a cognitive  process  that  involves  both  dynamic  modeling  and  knowledge  generation  activities.  These  processes  are  integrated  in  a  spiral  of  epistemological  and  ontological  content  that  grows  upward  by  transforming  tacit  knowledge into explicit knowledge, which becomes the basis for a new spiral of knowledge generation. KAMET  II  is  a  methodology  based  on  models  designed  to  manage  knowledge  acquisition  from  multiple  knowledge  sources  (KS).  The  method  provides  a  strong  mechanism  to  achieve  KA  in  an  incremental  fashion,  in  a  cooperative  environment,  and  in  a  shared  context  for  knowledge  generation.  It  must  be  said  that  KAMET  II  seeks to be general, although it is primarily aimed at solving diagnosis problems.  

2. KAMET II: The life‐cycle model as a knowledge generation process    The KAMET II life‐cycle model (LCM) provides a graphical framework for managing the knowledge acquisition  process.  Besides  providing  structure  to  set  up  and  facilitate  ways  to  organize  knowledge  acquired  from  multiple knowledge sources, to share knowledge, monitor project progress, and check quality control, much of  the  motivation  behind  utilizing  a  LCM  as  a  knowledge  generation  process  is  based  on  the  search  for  the  efficient transformation of tacit knowledge into explicit knowledge. Knowledge lives in the minds of individuals  and  we  are  trying  to  make  it  explicit.  We  are  much  more  interested  in  the  dynamic  process  of  knowledge  generation than the stockpiling of knowledge. This is one of the main differences with the previous version of  the methodology (Cairó, 1998).     The  KAMET  II  life  cycle  consists  of  four  stages:  the  strategic  planning  of  the  project,  initial  model  building,  feedback model building, and final model building. Each stage involves a process of knowledge transformation. 

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Osvaldo Cairó and Silvia Guardati  This was inspired by the concept of Ba. For those unfamiliar with the concept, ba can be thought of as a shared  space for emerging relationships, a shared space that serves as a foundation for knowledge creation (Nonaka  et al., 2000). The following sections briefly describe each stage.  

2.1 The strategic planning of the project  This is the socialization stage in which ideas, views, emotion, feelings, experiences and knowledge should be  shared through face‐to‐face interactions. It involves the sharing of tacit knowledge between individuals. This is  where  the  knowledge‐creation  process  begins.  This  process  is  necessarily  context‐specific  in  terms  of  who  participates and how they participate. Social, cultural and historical contexts are important for human beings  (Vygotsky, 1986), as such contexts provide the basis for interpreting information to create meaning (Nonaka et  al.,  2000).  The  strategic  planning  of  the  project  is  essential  to  the  development  of  the  project.  The  Project  Manager (PM) and the four groups involved in the project ‐‐Knowledge Engineers (KE), Human Experts (HE),  representatives of potential users (PU), and fund sponsors (FS)‐‐ must interact and be in total agreement with  the definition of the project to ensure its success. In this process, teamwork is definitely the fundamental key.    The steps comprised in the first stage (Cairó, 1998) are: a) define project goals, b) identify potential users, c)  specify  potential  benefits,  d)  divide  the  knowledge  domain  into  sub‐domains,  e)    identify  the  knowledge  sources that will be involved in the project, f) define mechanisms of model verification and validation, g) build  the  project’s  dictionary,  h)  specify  other  necessary  resources  to  obtain  KA,  i)  define  techniques  to  attain  knowledge acquisition, j) estimate time to complete the knowledge acquisition stage, k) estimate project costs,  and l) specify project documentation.  

2.2 Initial model building   The externalization process takes place in the second stage. It is the time for transforming tacit knowledge into  comprehensible forms that can be understood for others. When tacit knowledge is made explicit, knowledge is  crystallized. This means that now knowledge can be shared by others, and therefore, become the basis for a  new process of knowledge generation. The externalization process is also essential because it transcends the  limits  of  what  we  are  accustomed  to.  It  is  what  allows  us  to  move  from  the  invisible,  tacit,  to  the  visible,  explicit. This is the model ultimately that will allow us to interact with other agents and the environment for  the knowledge generation cycle to take place.    In the second stage, Knowledge Engineers elicit knowledge from different knowledge sources and proceed to  build the initial model, which is constituted by one or more models, as we will explain later. This stage involves  the largest number of risks, which mainly arise because interviews involve introspection and verbal expression  of  knowledge,  resulting  in  a  difficult  task  for  humans,  and  especially  for  experts.  The  success  of  the  initial  model  is  also  heavily  dependent  on  the  skills  of  knowledge  engineers  to  socialize  with  the  experts  and  to  formalize tacit knowledge.    The steps comprised in the second stage are: a) attain knowledge elicitation from multiple knowledge sources,  b) reassess  project time, c)  develop a library of cases, d) develop the initial model, e) verify and validate the  initial model, and f) revise and document the initial model.  

2.3 Feedback model building  It  is  the  time  for  combination  ‐‐  the  process  of  converting  explicit  knowledge  into  more  complex  and  systematic  sets  of  explicit  knowledge  (Nonaka  et  al.,  2000).  The  KE  distributes  the  initial  model  among  the  different knowledge sources to be analyzed. Ideas, experiences or perspectives are exchanged in relation to  the model. Because individuals typically have different views, training, ideas, knowledge and experience, it is  logical that differences are common and inevitable at this time. This should not be a cause for concern. The  synthesis  of  these  differences  should  be  used  to  generate  new  knowledge  and  bring  forth  diverse  views  in  reference to the created artifacts.     Finally,  the  PM  and  KE,  together  with  the  experts,  review  and  analyze  the  changes  introduced  in  the  initial  model and construct the feedback model. This involves collecting externalized knowledge and then combining  such knowledge. At the end of this stage, fewer inaccuracies will be found in the model because now it has 

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Osvaldo Cairó and Silvia Guardati  been enriched and reflects the knowledge and experience of several specialists in the knowledge domain of  the application. It must be remembered that the feedback model is only a refined and better initial model.     The steps that constitute the third stage are: a) distribute the initial model among experts who then analyze it  and generate feedback, b) develop the feedback model incorporating the different views of experts, c) verify  and validate the feedback model, and d) revise and document the feedback model.  

2.4 Final model building   In the last stage, the multiple knowledge sources participate in a series of meetings, under the coordination of  the  PM,  to  develop  the  final  model.  The  stage  is  considered  to  be  complete  when  the  model  satisfies  the  proposed  objectives  with  a  high  degree  of  plausibility  and/or  there  are  no  experts  capable  of  further  transforming  it.  Inaccuracy  at  the  end  of  the  stage  must  be  minimal,  since  the  model  now  expresses  the  knowledge  acquired  from  multiple  knowledge  sources,  which  collaborated  in  different  degrees  and  ways  to  solve the problem. The final model shows that explicit knowledge can be re‐distributed among team members  and converted into tacit knowledge again.      The steps to be followed in the fourth stage are: a) re‐distribute the feedback model among experts who then  analyze it, c) develop the final model incorporating new and more specific opinions from the experts, d) verify  and validate the final model, and e) revise and document the final model.  

3. The KAMET II conceptual modeling language (CML)  We must always keep in mind that we are looking for a dynamic process in which tacit and explicit knowledge  are exchanged and transformed. 

3.1 The KAMET II CML assumptions  The  KAMET  II  CML  has  three  levels  of  abstraction.  The  first  one  corresponds  to  structural  constructors  and  structural  components.  The  structural  constructors  are  used  mainly  to  highlight  the  problem  itself.  We  distinguish between problem, classification and subdivision (Figure 1). 

Figure 1: Structural constructors  The structural components (Figure 2), on the other hand, are used to establish the characteristics and possible  solutions  to  the  problem.  We  distinguish  among  symptoms,  antecedents,  time,  value,  inaccuracies,  process,  formula, solution and examination.     The  second  level  of  abstraction  corresponds  to nodes  (N)  and  composition  rules (CR).    Nodes  are  built  using  structural  constructors  and  structural  components.  We distinguish between three different types of nodes: initial, intermediate and terminal. Composition rules (Figure 3), for their part, are the ones that permit  the appropriate combination of nodes.     The  third  level  of  abstraction  corresponds  to  the  global  model.  It  consists  of  at  least  one  initial  node,  any  number  of  intermediate  nodes,  and  one  or  more  terminal  nodes.  A  global  model  should  represent  the  knowledge acquired from multiple knowledge sources in a specific knowledge domain.   

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Figure 2: Structural components 

Subdivision: Shows a subdivision.

Implication: It represents a connection from a source to a complication.

Action: Expresses that something must be completed: a formula, an examination, etc.

Union: The line shows a a connection between subdividions.

Figure 3: Composition rules 

3.2 The KAMET II CML formalization  The formalization of KAMET II CML (Cairó and Guardati, 2012) is based more on a metalanguage, than on a  strict group of theorems and mathematical proofs. The characterization of the method through diagrammatic  conventions and postulates can be summarized as follows.  3.2.1 Diagrammatic conventions   A  diagrammatic  convention  is  mainly  a  chart,  graph,  drawing  or  outline  designed  to  demonstrate  or  explain  how  something  works  or  to  clarify  the  relationship  between  the  parts  of  a  whole.  Following  are  the  diagrammatic conventions:   ƒ

DG1. The structural constructors and structural components can be named using a numerical or linguistic label. The use of names accelerates and facilitates the construction of models.

ƒ

DG2. The indicator is used to set up the number of elements that must be present in either a structural component or group. It is represented with a square and is located in the upper right‐hand corner of the group or the structural component. An indicator is named in three different ways: an n is used to express the  exact  number  of  elements  that  must  be  present,  an  n+  is  used  to  indicate  that  at  least  n  elements must be present, and an n,m is used to show the minimum and maximum number of elements that must be present, where n and m are integer values, and m>n.

ƒ

DG3. A  chain  is  defined  as  the  link  of  two  or  more  symptoms,  antecedents,  and/or  groups  (DG4).  The order of the link is irrelevant.

ƒ

DG4. A group is defined as a special chain. The linked elements have times and/or values in common, or are related among each other through an indicator. The group concept is recursive.

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Osvaldo Cairó and Silvia Guardati  ƒ

DG5. Assignment is defined as the process of labeling a node. The objective of the assignment is to be able  to  reuse  the  node  in  any  other  part  of  the  model  without  having  to  redefine  it.  It  allows  reusing  a  complete  node  not  only  in  form  but  also  in  content.  Reusing  is  a  universal  principle  of  coping  with  complexity  and  to  avoid  redesigning  or  redeveloping  parts  of  a  product,  which  already  exist.  The  assignment provides greater flexibility in modeling.  

3.2.2 Postulates   The  postulate  or  axiom  is  a  proposition  in  logic  that  is  not  proved  or  demonstrated  but  is  considered  to  be  either self‐evident or assumed to be true as a basis for reasoning. Its truth is taken for granted, and serves as a  starting point for deducing and inferring other propositions. Following are the postulates of the method:  ƒ

P1. The structural component time should always be placed to the right of a group, problem, subdivision,  antecedent, symptom, etc.  

ƒ

P2. The structural component value is always placed above a symptom, antecedent or group. The value component can make use of an indicator.  

ƒ

P3. The solution component is only related to structural constructors.  

ƒ

P4. There are three types of nodes: initial (I), intermediate (M) and terminal (T).  

ƒ

P5. The  nodes  are  related  using  composition  rules.  The  following  relationships  are  possible: initial  with  terminal, initial with intermediate, intermediate with intermediate, and intermediate with terminal.  

ƒ

P6. An initial node represents a symptom, antecedent, group, or chain. It is used to describe a part of the  problem. It does not have input flow and can have more than one output flow.  

ƒ

P7. The intermediate node is used to describe an intermediate part of the problem. It may have one or  more further inflows and one or more output flows.  

ƒ

P8. A terminal node represents a structural constructor. It has one or more input flows. The output flow is  only used to show possible solutions.  

ƒ

P9. The  initial  and  intermediate  nodes  can  be  grouped  together,  without  losing  their  properties  or  functions, into molecular nodes. These nodes, in turn, will act as a node in their own right. The molecular  nodes are formed through conjunctions or disjunctions.  

ƒ

P10. The composition rules are used mainly to relate the different nodes and the structural components  with the solution component.  

3.2.3 A simple example of modeling   In this section, we will provide a simple example of modeling in order to illustrate the method sketched in the  previous section. The example involves diagnosing faults in electricity (Figure 4).  

Figure 4: Simple electrical diagnosis   The model shows that problem P1 can occur as a result of two different situations. In the first one, the model  shows  that  if  symptoms  1  and  5  are  known  to  be  true  then  we  can  deduce  problem  P1  is  true  with  a  probability of 0.6. In the second one, the model shows that if symptoms 1 and 2 are observed then we can  conclude that the problem is P1 with a probability of 0.70. On the other hand, we can deduce that the problem  is P3 with a probability of 0.40 if symptoms 3 and 4 are known to be true. Finally, we can reach a conclusion  that the problem is P2 with a probability of 0.90 if problems P1 and P3 and symptom 7 are observed.  

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Osvaldo Cairó and Silvia Guardati  Finally, we add a real example of retinal migraine (Figure 5). The examples were extracted from the knowledge  models  of  a  knowledge‐based  system  for  the  diagnosis  of  headache  disorders,  cranial  neuralgia,  and  facial  pain.  

Figure 5: Retinal migraine 

4. KAMET II: A typical four component architecture   The  conceptual  framework  is  a  typical  four  component  architecture  (Fensel,  2000)  that  defines  different  elements  to  solve  diagnosis  problems:  a  task  that  defines  the  problem  that  should  be  solved  by  the  knowledge‐based  systems,  a  problem‐solving  method  that  defines  the  reasoning  process  of  the  knowledge‐ based systems, and a domain model that describes the domain knowledge of the KBS. Each of these elements  is  described  independently  to  enable  the  reuse  of  each  of  them.  Additionally,  a  fourth  element,  known  as  adapter, is introduced to adjust the three other independent and reusable parts. 

5. KAMET II methodology: Applications and results   The KAMET II Methodology (Cairó and Guardati, 2012) has been successfully used in different applications and  knowledge domains.  We have developed tens of KBSs applying KAMET mainly in medicine – cranial neuralgia  and  uveitis  ‐,  telecommunications,  recruiting,  concrete  design,  scheduling,  human  resources  management  system, and customer services, among others. A great deal of literature has also appeared on KAMET in recent  years (Hwang et al, 2011; Tseng and Lin, 2009; Lin et al., 2008; Calvo‐Manzano et al., 2008; Chu and Kwang,  2008; Elfadil, 2008; Beydoun et al., 2006; Hwang et al., 2006; Abdullah, 2006; Wagner and Subey, 2005; Chen  et al., 2005).     We think KAMET II, which involves a new dynamic modeling process and a revolutionary and fresh knowledge  generation process, provides the necessary elements so that KE can continue building KBSs. The methodology  also focuses naturally on risk‐reduction, which is a fundamental part in software and knowledge engineering.  

6. Conclusions   In  this  paper,  we  presented  a  renewed  and  fresh  knowledge  acquisition  methodology  from  multiple  knowledge  sources.  There  are  two  main  goals  in  developing  KAMET  II.  The  first  is  to  improve  the  phase  of  knowledge acquisition by making it more efficient. The second, and more important, is to introduce knowledge  acquisition as a cognitive process, as a spiral of epistemological and ontological content that grows upward by  transforming tacit knowledge into explicit knowledge, which becomes the basis for a new spiral of knowledge  generation.  This  is  one  of  the  first  attempts  at  incorporating  both  a  dynamic  modeling  process  and  a  knowledge generation process in a knowledge acquisition methodology.  

Acknowledgements   This work has been founded by Asociación Mexicana de Cultura A.C. 

References   Cairó, O., and Guardati, S. (2012) “The KAMET II methodology: Knowledge acquisition, knowledge modeling and knowledge  generation”, Expert Systems with Applications, Vol 39, No. 9, pp 8108‐8114.   Cairó, O. (1998) “KAMET: A Comprehensive Methodology for Knowledge Acquisition from Multiple Knowledge Sources”,  Expert Systems with Applications, Vol 14, pp 1‐16.   Chu, H., and Hwang, G. (2008) “A Delphi‐based approach to developing expert systems with the cooperation of multiple  experts”, Expert System with Applications, Vol 34, No. 4, pp 2826‐2840.   

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Osvaldo Cairó and Silvia Guardati  Dyer, J., and Singh, H. (1998) “The relational view: cooperative strategy and sources of interorganizational competitive  advantage”, Academic of Management Review, Vol 23, pp 660‐679.   Fensel, D. (2000) Problem‐Solving Methods: Understanding, Description, Development, and Reuse, Lecture Notes in  Artificial Intelligence, Vol 1791, Springer‐Verlag Berlin, Heidelberg.   Hwang, G., Chen, C., Tsai, P., and Tsai, C. (2011) “An Expert System for Improving Web‐based Problem‐Solving Ability of  Students”, Expert System with Applications (Article in Press).   Nonaka, I., Toyama, R., and Konno, N. (2000) “SECI, Ba and Leadership: a Unified Model of Dynamic Knowledge Creation”,  Long Range Planning, 33, pp 5‐34.   Tseng, S., and Lin, S. (2009) “VODKA: Variant objects discovering knowledge acquisition”, Expert System with Applications,  Vol 36, No. 2, pp 2433‐2450.   Wagner, P., and Zubey, M. (2005) “Knowledge acquisition for marketing expert systems based upon marketing problem  domain characteristics”, Marketing Intelligence & Planning, Vol 23, No. 4, pp 403‐416.   Yli‐renko, H., Autio, E., and Sapienza, H. (2001) “Social Capital, Knowledge Acquisition, and Knowledge Explotation in Young  Technologies‐Based firms”, Strategic Management Journal, Vol 22, pp 587‐613.  

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Knowledge management capabilities in family firms Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez Department of Management and Finance, University of Murcia antonioc@um.es danieljj@um.es

Abstract: Family firms face increasing global competition, changing customer demands and rapid technical change. In this context, the profitability of firms and even their survival depend on their ability of responds rapidly and flexibly. That is the main reason why innovation is frequently considered a key element for achieving a competitive advantage. Numerous studies have suggested that knowledge management capabilities, such as organizational memory and absorptive capacity are important in generating innovations. Furthermore, family involvement in the firm distinguishes the family firms from others. Several studies have focused on the capacity of the family to generate innovations and knowledge management in family firms. The results of an investigation with 249 Spanish firms show that both absorptive capacity and organizational memory have a positive relationship with innovation, as well as with family involvement in the management, where the second and subsequent generations are involved. Also, we found evidence that family involvement in management over generations fosters knowledge management capabilities (absorptive capacity and organizational memory). The relationship between family ownership and innovation was indirect. In general, the results show that family firms promote innovation through knowledge management strategies. Keywords: Absorptive capacity, organizational memory, innovation and family firms

1. Introduction The importance of knowledge as a determinant of innovation has received much theoretical attention over the last few years. The Resource-Based View (RBV) emphasizes the role of knowledge management in growth, generation, maintenance and development of innovation. In this work, two important knowledge management capabilities are analyzed. First, absorptive capacity, or the firm’s ability to identify, assimilate and exploit knowledge from the environment (Cohen and Levinthal, 1990). Second, organizational memory (OM) or the accumulated body of data, information and knowledge created during the organization’s course of action (Jackson, 2012). OM reflects the sum of know-how acquired through the company’s life, and plays an important role in future decisions (Walsh and Ungson, 1991). Numerous studies have suggested that there is a link between OM, absorptive capacity and a firm’s ability to generate innovations. In recent decades, there is an increasing interest in studying family firms because they are the prevailing form of enterprise worldwide (Littunen and Hyrsky, 2000) and because they are an important engine of economic growth and job creation in European economies, and the product innovations generated by family firms are a key source of growth. Sirmon and Hitt (2003) use the Resource-Based View (RBV) of firms to argue that family businesses assess, select, discard and revitalize their resources differently from non-family businesses. Family involvement in the firm distinguishes family firms from others (Chrisman et al., 2003). This paper suggests that these resources introduced to the family business by the family create capabilities that foster innovation. However, empirical research is scarce, not only regarding this proposition, but also with regard to innovation and knowledge management in family firms.

2. Literature framework 2.1 Innovation According to the RBV, resources are at the heart of competitive advantage and, therefore, business success. The RBV remains one of the most prominent theoretical foundations of management research (Newbert, 2007). The RBV describes how resources can contribute to the competitive advantage of organizations. In general, the literature considers innovation to be critical for firm success. The rationale behind this idea is that innovation often serves to deal with the turbulence of the external environment. In this context, companies with the capacity to innovate will be able to respond to challenges faster and to exploit new products and market opportunities better than non-innovative companies (Brown and Eisenhard 1995). From

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Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez this perspective, innovation allows the development of valuable and scarce resources in the company. Moreover, the capacity to innovate is difficult to imitate. Innovation has been conceptualized in a variety of ways. The definition given by Damanpour et al. (1989) broaches these different issues. They understand innovation as “the adoption of an idea or behavior, whether a system, policy, program, device, process, product or service, that is new to the adopting organization”.

2.2 Family firms Scholars have also applied the RBV to the field of family firms (Zellweger et al., 2010). Through this theoretical lens, Habbershon and Williams (1999) first introduced the term “familiness”, describing it as the idiosyncratic bundle of resources and capabilities resulting from the interaction of the family and business systems. In order to understand the family's role in supporting the competitiveness of the family firm, it is important to understand different family-based attributes of family firms that can create familiness.Within familiness there are three dimensions that distinguish the influence of the family in the business (Astrachan et al., 2002): power or family involvement in ownership and management; experience of the generation in control; and, finally, culture. This paper focuses on the influence of family in ownership and management, and experience of the generation in control. A family firm is defined as one in which there is majority family ownership. Family businesses tend to be disadvantaged in the development of innovation capabilities, and family firms are ill-equipped to build these capabilities; financial resources are more limited, and/or the family is concerned with the preservation of wealth, as the majority of its assets are invested in the business, and so they limit their investment and risk (Carney, 2005). Creating innovative capabilities requires a large investment in R&D and technological diversification, and usually forces the family to establish associations, or lease property to third parties outside the company, such as venture capital or institutional investors. Establishing external partnerships requires control mechanisms to review the actions of the non-family owners, reducing the opportunities associated with innovation. The concern of the family that owns the business to control partner opportunism reduces the company's ability to respond effectively to environmental changes or to take advantage of market opportunities that arise (Zahra et al., 2004).The tendency not to adopt innovative capacity increases with the extent that family presence increases in the ownership structures of the company, since it increases the interest to preserve family wealth, and reduces risk in the firm. It is therefore expected that: H1A. There is a negative relationship between the percentage of family ownership and innovation. The competitive advantages of family businesses improve when owner-managers involve other family members in the business (Eddleston and Kellermanns 2007). When only one person is in charge of decisions about innovation, other family members may not understand the decisions taken in the company and not participate (Kellermanns et al., 2012). However, when family members are included in the decision making process, they are more likely to critically evaluate the benefits of innovative behavior from many points of view, improving the quality of decisions and risk management in the business (March and Shapira 1987). High levels of family involvement in management may benefit innovative behavior (Kellermanns et al., 2012).Therefore, we expect: H1B. There is a positive relationship between family involvement in management and innovation. The family experience, understood as the information knowledge, judgment and intuition that comes through successive generations, affects the company's innovative capacity (Beck et al., 2011). Family firms in different generational stages differ in their innovation-oriented culture. The empirical study of Zahra (2005) emphasizes that family firms have a more innovation-oriented culture when later generations are involved in the management of the firm. An innovation oriented culture has an emphasis on creativity (Hurley and Hult, 1998), and creativity facilitates innovation (Amabile et al., 1996, Prajogo and Ahmed, 2006). This consequently has a positive influence on the family firm’s innovation. Therefore, we propose the following hypothesis: H1C. Innovation is higher among second- and subsequent- generation family firms than in firstgeneration family firms.

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Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez

2.3 Absorptive capacity and organizational memory Absorptive capacity is the ability of a firm to recognize the value of new, external information, assimilate it and apply it to commercial ends (Cohen and Levinthal, 1990). The contribution of Zahra and George (2002) was an ongoing attempt to analyze the dimensions of this construct. Following Cohen and Levinthal (1990), they claim that absorptive capacity is a bi-dimensional dynamic capability and its dimensions can be developed distinctly. Potential absorptive capacity (PAC) reflects the capability to acquire and assimilate external knowledge, while transformation and exploitation of the acquired knowledge constitutes absorptive capacity (RAC). As a result, PAC enhances receptiveness to knowledge of a company, while RAC represents a set of organizational routines related to transformation and use of the acquired awareness. Thus, PAC fosters RAC and the latter promotes the exploitation of this knowledge through the development of innovations. In consequence: H2A. There is a positive relationship between the potential absorptive capacity and the realized absorptive capacity. H2B. There is a positive relationship between the realized absorptive capacity and innovation. The work of Walsh and Ungson (1991) offers a deeper insight into how former experiences of a company can affect its present in terms of decision making. Being on the cutting edge is usually a result of consistent learning throughout the company’s history. Moreover, experience and success co-evolve; retrieving and manipulating past experiences is important, not only for avoiding new mistakes, but also to exploit old and valuable knowledge. Their viewpoint coincides with the idea of path dependency, which explains the continual use of products or services based on prior commitment and reference points of the company. In other words, a firm’s history influences its subsequent behavior (Teece et al., 1997). This indicates the importance of the firm’s old knowledge in the creation of new knowledge. Thus, PAC will increase the OM, since a company acquires new knowledge that could be stored in organizational databases or in the employees’ minds. Also, companies will exploit the acquired knowledge. However, the exploitation of this knowledge for innovations, i.e. RAC, will depend not only of the PAC but also on the current knowledge that is stored in the company. Thus, H2C. Organizational memory mediates the relationship between potential absorptive capacity and realized absorptive capacity. Based on the arguments above, and given the positive relationship suggested between innovation, OM and absorptive capacity, it seems reasonable that the scenarios that favor innovation in family business also favor the development of OM and absorptive capacity. So we expect that: H2D1. There is a negative relationship between the percentage of family ownership and potential absorptive capacity and organizational memory. H2D2. There is a positive relationship between the family involvement and potential absorptive capacity and organizational memory. H2D3. Potential absorptive capacity and organizational memory is higher among second- and subsequent-generation family businesses.

3. Methodology 3.1 Data collection and sample The present study investigates 475 Spanish manufacturing firms with more than 40 employees. A pre-test was conducted with five CEOs to check the intelligibility of the questionnaire used. Based on their feedback, a number of items were reworded. This pre-test also involved five academics from different universities and improved the clarity of the questionnaire and ensured effective, accurate and unambiguous communication with the respondents. The data was collected using a structured questionnaire via a webpage designed specifically for this purpose. The process was managed by a specialized market research company. First, we contacted the CEO or innovation executive of each organization. We explained the purpose of the survey, provided a username and password and gave the webpage address, following the practice used in similar studies in the field (Li and Atuahene-Gima, 2001; Atuahene-Gima et al., 2006). The market research company then tracked completion of the questionnaire and helped organizations to complete it. All the processes were supervised and the quality

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Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez of this activity was tested by contacting a randomly selected sample of firms that had answered the questionnaire. The questionnaire was designed based on the review of the literature described above. Finally, a total of 249 usable questionnaires were received (a response rate of 52.42%). These responding companies belong to different sectors of the economy, which ensures a good representation of companies in general. The food and beverage industry, the furniture industry and metal production have the highest representation in the sample. There are no significant differences in the mean responses on any construct across firms from different industries. In addition, Chi-square distribution analysis revealed no significant differences between the sample and the population, in terms of industry distribution, number of employees and sales volume. The rate of investment in R&D was measured. We found that 34.1% of the companies do not spend anything on R&D and that 53% of the companies dedicate less than 10% of their budgets to R&D. 22.9% of the firms spend more than 10% of their budgets on R&D activities. The percentage of income from sales of new products to total sales was also measured, and it was found that 31.7% of the companies did not generate any income from their product innovations in the previous year, 36.2% of the companies generated less than 10% from new product sales, and 22.1% of the companies generated more than 10% of their income from new product sales.

3.2 Measures and measurement properties Organizational innovation measure includes four items, each referring to one of the four types of innovation SRE (OCDE, 2005): innovations in products, processes, commercialization and management (ρc =0,95, AVE ρc =0,81). Organizational Memory: In the present context, OM refers to the old know-how and experience acquired by the company with regard to a category of products or services. In other words it is the old knowledge that a company has already acquired about a given product category. In this contribution, we adopt the scale offered by Chang and Cho (2008). This scale considers OM to be measured by the degree of knowledge, experience, SRE AVE familiarity and R&D investment in a specific kind of production (ρc =0,94, ρc =0,81). Absorptive Capacity: In this study we adopt and adapt the two-subcomponents of absorptive capacity offered by Zahra and George (2002). Thus, PAC and RAC were measured using the scale developed by Jansen el al. SRE AVE SRE AVE (2005) (PAC: ρc =0,96, ρc =0,85; RAC: ρc =0,98, ρc =0,92).. Family involvement: This is measured by the percentage of family managers and by the percentage of family ownership as in other works (Chrisman et al., 2005). Family generation. To distinguish between consolidated firms and second generation firms, for family firms, we set the age limit at 30 years. This decision is congruent with other works, e.g. Fernández and Nieto (2002). To assess the unidimensionality of each construct, a confirmatory factor analysis of the four constructs was conducted (Anderson and Gerbing, 1988). The measurement model provides a reasonable fit to the data 2 [χ (98)=206.37 (p=0.00), NFI=0.96, TLI=0,97, CFI=0,98, IFI=0,98, RMSEA=0,06]. The traditionally reported fit indexes are within the acceptable range. Reliability of those measures was calculated with Bagozzi and Yi’s (1998) composite reliability index and with Fornell and Larcker’s (1981) average variance extracted index. For all the measures both indices are higher than the evaluation criteria of 0.6 for the composite reliability and 0.5 for the average variance extracted (Bagozzi and Yi, 1998). Furthermore, discriminant validity is indicated since the average for every construct is higher than the square estimated correlation parameter between each two constructs (Fornell and Larcker, 1981). Table 1: provides an overview of construct means, standard deviations and correlations among the variables measured to test our hypotheses.

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Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez Table 1: Construct correlation matrix Construct

Mean

Correlation Matrix

Standard deviation

1

2

3

4

5

6

1 Family generation

0,21

0,41

1

2 % Family ownership

62,57

38,94

0,46**

1

3 % Family managers

28,84

22,05

0,24**

0,39**

1

4 Potential Absorptive Capacity (PAC)

3,47

1,05

0,15*

-0,03

0,14*

1

5 Organizational Memory (OM)

2,45

0,8

0,19**

0,10

0,29**

0,60**

1

6 Realized Absorptive Capacity (RAC)

3,7

1,53

0,06

0,01

0,11

0,82**

0,68**

1

7 Innovation

3,34

1,12

0,23**

0,11

0,24**

0,75**

0,62**

0,7 6* *

*** p<0,01; ** p<0,05; * p<0,1

4. Analysis and results A structural equation modeling (SEM) methodology was employed to test the hypotheses. The proposed structural model is shown in Figure 1. Conventional maximum likelihood estimation techniques were used to 2 test the model (Jöreskog and Sörbom 1996). The fit of the model is satisfactory [χ (139)=293.93 (p=0.00), NFI=0.95, TLI=0,97, CFI=0,98, IFI=0,98, RMSEA=0,06] (see Table 2), thereby suggesting that the nomological network of relationships fits our data.

Figure 1: A model of the relationship between family involvement, family generation, PAC, RAC, OM and innovation. Table 2: Construct structural model Hypotheses Linkages in the model

Standardized parameter estimates

Number

Sign

Parameter

Estimate

t-value

% Family Ownership -> Innovation

H1A

-

γ14

-0.03

0.73

% Family Managers -> Innovation

H1B

+

γ24

0.13

3.07***

Direct Effects

Family generation -> Innovation

H1C

+

γ34

0.15

3.42***

PAC -> RAC

H2A

+

β31

0.68

13,65***

RAC -> Innovation

H2B

+

β43

0.77

16.77***

OM -> RAC

H2C

+

β32

0.28

6.12***

PAC -> OM

H2C

+

β21

0.59

9.92***

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Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez

% Family Ownership -> PAC

H2D1

-

γ11

-0.17

2.21**

% Family Managers -> PAC

H2D2

+

γ21

0.15

2.17**

Family generation -> PAC

H2D3

+

γ31

0.18

2.47**

% Family Ownership -> OM

H2D1

-

γ12

0.04

0.62

% Family Managers -> OM

H2D2

+

γ22

0.19

3.34***

Family generation -> OM

H2D3

+

γ32

0.04

0.60

PAC -> Innovation

κ14

0.65

12.97***

OM -> Innovation

κ24

0.21

5.82***

% Family Ownership -> Innovation

κ41

-0.10

1.98**

% Family Managers -> Innovation

κ42

0.14

2.91***

Family generation -> Innovation

κ43

0.12

2.54**

PAC -> RAC

κ13

0.16

5.51***

% Family Ownership -> RAC

κ31

-0.13

2.00**

% Family Managers -> RAC

κ32

0.18

2.95***

Family generation -> RAC

κ33

0.16

2.57***

% Family Ownership -> OM

κ21

-0.10

2.17**

% Family Managers -> OM

κ22

0.09

9.92**

Family generation -> OM * p<0,1; **p<0,05; ***p<0,01; Fit statistics for measurement model: 2 χ (139)=293,93 (p=0.000), NFI=0.95, TLI=0,96, CFI=0,97, IFI=0,97, SRMR=0,04, RMSEA=0,06

κ23

0.11

2.41**

Indirect effects

In term of our hypotheses (Table 2), the findings for H1B (% Family managers -> Innovation;γ24 = 0.13, p<0.01) and H1C (Family generation -> Innovation;γ34 = 0.15, p<0.01) suggest that, as predicted, innovation is positively associated with family involvement in management and family firms in the second generation or more. We accept, therefore, Hypotheses H1B and H1C. Family ownership does not have a direct effect on innovation, even if it produces an indirect effect as can be seen in Table 2 (% Family ownership -> Innovation; κ41=-0.10, p<0,05). We reject Hypothesis 1A because the effects on innovation are caused indirectly rather than directly. The family-run and family generation to run the business also have indirect positive effects on innovation (% Family managers -> Innovation, κ42=0.14, p<0.01; Family generation -> Innovation, κ43=0.12, p<0,05). This finding support the thesis argued in the literature that familiness can be a source of competitive advantage. So, in spite of the risks and costs of innovation, companies which have a more family commitment to the business will have more innovative behavior. Companies with higher PAC increase the OM (PAC ->OM, β 21=0.59, p<0.01) and RAC (PAC ->RAC, β 21=0.59, p<0.01). We found that companies with higher level of PAC (PAC ->RAC, β31=0.68, p<0.01) and OM (OM ->RAC, β32=0.28, p<0.01) will be more innovative, since RAC affects innovation (RAC -> Innovation; β43=0.77, p<0.01). Thus, OM mediates the relationship between PAC and RAC. We accept, therefore, Hypotheses H2A, H2B and H2C. On the other hand, we find that companies with greater family involvement in the management of the family business, and family businesses in the second generation onward, have a greater PAC (%Family managers -> PAC, γ21=0.15, p<0.05; Family generation -> PAC, γ31=0.18, p<0.05). There is less PAC in the most family-owned businesses (%Family ownership -> PAC, γ11=-0.17, p<0.05). Contrary to our prediction, we did not find any direct relationship between family ownership and OM, although for firms that were in their second generation or later there was a direct impact on increasing OM, suggesting there are indirect relationships between family ownership, family generation and OM (%Family ownership -> OM, κ21=-0.10, p<0.05; Family generation -> OM, κ23=0.11, p<0.05). Last, we find in companies with a greater family involvement in management a greater OM (%Family managers -> OM, γ22=0.19, p<0.01).

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Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez We reject Hypotheses H2D1 and H2D3 as there are no direct effects between family ownership, family generation and OM, and we accept Hypothesis H2D2 that proposes a positive relationship between family involvement and PAC and OM. These results suggest that PAC and OM plays an intermediate role in the link between family involvement, family generation and innovation.

5. Conclusions Family involvement in ownership and management sets the minimum threshold for considering a firm a family firm and to enable the family to exercise its influence over the company (Zellwegeret al., 2010). But the most interesting characteristic is that these companies try to survive and transmit their business to their own family descendants. This requires that the company should adapt to organizational changes and consequently innovate. In family firms, innovation is important since it enables them to be passed on to later generations (Beck et al., 2011). A review of the literature shows that innovation requires a learning process that allows companies to generate new knowledge and provide fresh ideas for generating innovations. However, this process requires the participation of internal stakeholders (employees, family owners-managers) and external stakeholders (customers, suppliers, other organizations). Since, individual learning, though valuable, is not enough to guarantee success throughout the process of new product development, the company must share and manage knowledge resources to develop innovation. Our results show, on the one hand, how the knowledge-based (Wernerfelt, 1984) and dynamic capabilities approaches (Teece et al., 1997) emphasize the role of knowledge in growth, generation, maintenance and development of innovations. Specifically, we have examined two knowledge management capabilities and we have found a positive influence between organizational memory, absorptive capacity and product innovations. This relationship is further enhanced as OM increases, since OM mediates the relationship between PAC and RAC, since there is a positive relationship between the PAC and the RAC, and between the RAC and innovation. This evidence is similar to other studies (Lavie and Rosenkopf, 2006) and demonstrates that these capabilities are determinants of the development of successful innovations. On the other hand, we have analyzed the influence of the family on the relationships between knowledge capabilities and innovation. We have found evidence that family involvement in management fosters knowledge management capabilities (absorptive capacity and OM), and also that as the business passes to the next generation it promotes the absorption of knowledge. There is a positive direct relationship between family involvement in management and generation and innovation. However, we did not find a negative direct relationship, but only an indirect one, between family involvement in ownership and innovation. This result is similar to other studies that have failed to find a relationship between family ownership and innovations (Wu, 2008, Gudmundson et al., 2003). Furthermore, the analysis of the mediator effects of family involvement in ownership and management and the family generation on the relationship between knowledge management capabilities and innovation reveals that family support can foster this relationship. A possible explanation for this result is that the avoidance of risk-taking behavior in first-generation family firms leads to them having a high concentration of ownership in one or a few people involved in managing the business (Kellermanns et al., 2008). In addition, because of the changed environmental conditions during the internal orientation and riskaverse behavior of the first-generation family firms, later-generation family firms need to reinvent themselves and go beyond the legacy they know. In subsequent generations the property is spread over a larger number of family owners who participate and engage in management of the business. The results suggest that there are benefits of incorporating the family in the management of the business as a means to develop knowledge and promote innovation. However, this study has some limitations. First, the survey used single informants as the source of information. Although the use of single informant remains the primary research design in most studies in this area, multiple informants would enhance the validity of the research findings. In order to get round this limitation, analyses have tested for the absence of potential common method variance caused by collecting data from a single informant in each firm. The tests showed that there is no single factor with eigenvalue greater than one (Jöreskog and Sörbom 1996). A second limitation is the cross-sectional design of this research. Thus, researchers should interpret with caution the causality between the constructs (Jöreskog and Sörbom 1996).

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Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez Future research should use longitudinal studies and the inclusion of others individual characteristics of the family business founders. Acknowledgements We acknowledge the funding received from the Spanish Ministry of Science and Innovation (Research Project CSO2010-17761) to undertake this research. References Amabile, T., Conti, R., Coon, H., J, L. and Heron, M. (1996) Assessing the work environment for creativity. Academy of Management Journal, 39, 1154-1184. Anderson, J. C. and Gerbing, D. W. (1988) Structural equation modelling in practice: A review and recommended two-step approach. Psychological Bulletin, 103, 411-423. Astrachan, J. H., Klein, S. B. and Smyrnios, K. X. (2002) The F-PEC Scale of Family Influence: A Proposal for Solving the Family Business Definition Problem1. Family Business Review, 15, 45-58. Atuahene-Gima, K., Li, H. and De Luca, L. M. (2006) The contingent value of marketing strategy innovativeness for product development performance in Chinese new technology ventures. Industrial Marketing Management, 35, 359-372. Bagozzi, R. P. and Yi, Y. (1998) On the evaluation of structural equation model. Journal of the Academy of Marketing Science, 16, 74-94. Beck, L., Janssens, W., Debruyne, M. and Lommelen, T. (2011) A study of the relationships between generation, market orientation, and innovation in family firms. Family Business Review, 24, 193-196. Brown S.L. andEisenhard KM. (1995) Product development: past research, present findings, and future directions. Academy of Management Review, 20(2), 343–78. Carney, M. (2005) Corporate governance and competitive advantage in family-controlled firms. Entrepreneurship Theory and Practice, 29(3), 249–266. Chang, D. R. and Cho, H. (2008) Organizational memory influences new product success. Journal of Business Research, 61 13-23. Chrisman, J. J., Chua, J. H., and Zahra, S. A. (2003) Creating wealth in family firms through managing resources: Comments and extensions. Entrepreneurship Theory and Practice, 27, 359–365. Chrisman, J. J., McMullan, E., and Hall, J. (2005) The influence of guided preparation on the long-term performance of new ventures. Journal of Business Venturing, 20, 769–791. Cohen, W. M. and Levinthal, D. A. (1990) Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35, 128-154. Damanpour, F., Szabat, K. A. and Evan, W. M. (1989) The relationship between types of innovation and organizational performance. Journal of Management Studies, 26, 587-601. Eddleston, K. andKellermanns, F. W. (2007) Destructive and productive family relationships: A stewardship theory perspective. Journal of Business Venturing, 22(4), 545–565. Fernandez, Z. and Nieto, M.J. (2005) Internationalization Strategy of Small and Medium-Sized Family Businesses: Some Influential Factors. Family Business Review, 18, 77-89. Fornell, C. and Larcker, D. F. (1981) Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, XXVII, 39-50. Gudmundson, D., Tower, C. and Hartman, E. 2003. Innovation In Small Businesses: Culture And Ownership Structure Do Matter. Journal Of Developmental Entrepreneurship, 8, 1-18. Habbershon, T. G. and Williams, M. (1999) A resource-based framework for assessing the strategic advantage of family firms.Family Business Review, 12, 1–25. Hurley, R. E. and Hult, G. T. M. (1998) Innovation, market orientation and organizational learning: An integration and empirical examination. Journal of Marketing, 62, 42-54. Jackson, P. (2012) Transactive directories of organizational memory: Towards a working data model. Information and Management, 49, 118–125 Jöreskog, K.G. andSörbom, D. (1996) LISREL 8 user's reference guide. Chicago: Scientific Software International. Kellermanns, F. W., Eddleston, K. A., Barnett, T. and Pearson, A. 2008. An Exploratory Study Of Family Member Characteristics And Involvement: Effects On Entrepreneurial Behavior In The Family Firm. Family Business Review, 21, 1-14. Kellermanns, F., Eddleston, K.A., Sarathy, R., and Murphy, F. (2012) Innovativeness in family firms: a family influence perspective. Small Business Economic, 38, 85–101 Li, H. and Atuahene-Gima, K. (2001) Product innovation strategy and performance of new technology ventures in China. Academy of Management Journal, 44, 1123−1134. Littunen, H. and Hyrsky, K. (2000) The early entrepreneurial stage in Finnish family and nonfamily firms. Family Business Review, XIII, 41-54. March, J. G. andShapira, Z. (1987) Managerial perspectives on risk and risk taking.Management Science, 33(11), 1404– 1418. Newbert, S. L. (2007) Empirical research on the resource-based view of the firm: An assessment and suggestions for future research. Strategic Management Journal, 28, 121–146.

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Antonio Carrasco-Hernández and Daniel Jiménez-Jiménez OCDE (2005) Oslo Manual, The measurement of scientific and technological activities. Proposed guidelines for collecting and interpreting technological innovation data, European Commission. Retrieved August, 2005, from World Wide Web: http://www.oecd.org. Prajogo, D. I. and Ahmed, P. K. (2006) Relationships between innovation stimulus, innovation capacity, and innovation performance. RandD Management, 36, 499-515. Sirmon, D. G. andHitt, M. A. (2003) Managing resources: Linking unique resources, management and wealth creation in family firms. Entrepreneurship Theory and Practice, 27, 339–358. Teece, D. J., Pisano, G. and Shuen, A. (1997) Dynamic capabilities and strategic management. Strategic Management Journal, 18, 509-533. Walsh, J. P. and Ungson, G. R. (1991) Organizational memory. Academy of Management Review, 16, 57-91. Wu, H. 2008. When Does Internal Governance Make Firms Innovative? Journal Of Business Research, 61, 141-153. Zahra, S. A. and George, G. (2002) Absorptive capacity: A review, reconceptualization, and extension. Academy of Management Review, 27, 158-203. Zahra, S. A. and Sharma, P. (2004) Family business research: A strategic reflection. Family Business Review, 17(4), 331–346. Zahra, S. A. (2005) Entrepreneurial risk taking in family firms. Family Business Review, 18, 23-40. Zellweger, T.M., Eddleston, K.A. andKellermanns, F.W. (2010) Exploring the concept of familiness: Introducing family firm identity.Journal of Family Business Strategy, 1, 54–63.

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Relationship Between Perceived Organizational Support, Self‐ Efficacy, Subjective Norms and Knowledge Sharing  Delio Ignacio Castaneda and Manuel Fernández Ríos  Pontificia Universidad Javeriana, Colombia, Universidad Autónoma de Madrid, Spain  delio.castaneda@javeriana.edu.co  mf.rios@uam.es    Abstract: Despite the growing interest in knowledge sharing, there are few studies that contribute to its explanation. The  research was framed on the behavioral perspective of knowledge management, interested in the identification and study  of the human factors associated to knowledge management. In this direction, the paper presents the results of a research  in which it was studied the relationship between perceived organizational support, self‐efficacy and subjective norms on  the  knowledge  sharing  intention  and  behavior.  The  research  was  conducted  with  188  knowledge  workers  of  a  public  organization  at  the  national  level  in  Colombia.  According  to  results,  there  is  a  positive  relationship  between  perceived  organizational  support,  subjective  norms,  self‐efficacy  and  knowledge  sharing  intention  with  the  knowledge  sharing  behavior. At the same time, a positive relationship was found between subjective norms and knowledge sharing intention.  There was not found relationship between perceived organizational support and the knowledge sharing intention. Results  are  consistent  with  the  conceptual  framework.  A  model  of  the  relationship  between  variables  was  validated  using  chi‐ square.  There are some lessons to practitioners about the role of psychosocial variables in the facilitation of knowledge  sharing.    Keywords: perceived organizational support, self‐efficacy, subjective norms, knowledge sharing 

1. Introduction Knowledge  management  is  an  organizational  field  related  to  creation,  organization,  distribution  and  use  of  knowledge (Ju, Lin, Lin & Kuo, 2006). A behavior to make it possible is knowledge sharing. Storey and Barnett  (2002)  emphasized  the  need  to  understand  human  factors  which  are  related  to  the  knowledge  sharing  behavior, as a way of contributing to the development of knowledge management. The paper presents results  of  a  research  in  which  it  was  evaluated  the  relationship  between  three  psychosocial  variables:  perceived  organizational support, self‐efficacy and subjective norms, and the knowledge sharing intention and behavior.  Additionally, a model of the studied variables is presented using Structural Equation Modeling (SEM).      There  is  a  growing  interest  in  studying  knowledge  sharing  in  organizations.  As  it  was  expressed  by  Kogut  &  Zander (1995), firm´s survival depends in part of having and sharing knowledge; this behavior is also associated  to  organizational  competitiveness.  Despite  the  awareness  of  the  relevance  of  knowledge  sharing,  there  are  few studies that contribute to its explanation (Steward, 2008). This is confirmed by Wang & Noe (2010) who  based on a review concluded that the issue is still incipient.     Helmstadter  (2003)  defined  knowledge  sharing  as  voluntary  interactions  between  human  actors  where  raw  material  is  knowledge.  Knowledge  sharing  is  not  an  automatic  action,  but  a  behavior  highly  dependent  on  human will (Dougherty, 1999; Scarbrough & Carter, 2000). Knowledge sharing requires motivation to act (Wah,  Menkhoff, Low & Evers, 2005). What an individual share is: know‐what, know‐how, know why, know‐what for,  experiences, contextual information, values, ideas, believes and insights.    There are different frameworks for the explanation of human behavior. One of the most powerful theories is  the social cognitive theory formulated by Bandura (1986, 1999), who stated that people are not autonomous  agents acting without influence of context, or entities who respond mechanically to environmental conditions.  In  this  theory,  personal  factors,  environment  and  behavior  operate  as  determinants  of  reciprocal  influence  (Bandura, 1989). Therefore, human behavior is partly self‐generated and partly determined by environmental  conditions. For social cognitive theory, people are agents, self‐evaluators of their motivations and actions, who  are in constant interaction with environment (Bandura, 2001). A central concept in Bandura´s social cognitive  theory  is  self‐efficacy,  which  states  that  individual  beliefs  about  his/her  capacity  to  achieve  a  particular  behavior influence performance (1977). Self‐efficacy is not associated to the number of skills a person has, but  to beliefs the individual has about his/her capacity to act in a variety of circumstances (Cisneros & Munduate,  2000). Self‐efficacy contributes to predict whether or not a person faces a task. In this sense a person with high  self‐efficacy to share knowledge is expected to share it. 

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Delio Ignacio Castaneda and Manuel Fernández Ríos  There  is  some  research  linking  self‐efficacy  and  knowledge  sharing  behavior  (Endres,  Endres,  Chowdhury  &  Alam,  2007;  Lu  &  Leung,  2004;  Lu,  Leung  &  Koch,  2006).  Bock  &  Kim  (2002)  found  a  positive  relationship  between these two variables; however, self‐efficacy was understood as expectations of contributions, which  moves away from the original concept of Bandura (1977). Cabrera, Collins & Salgado (2006), in an exploratory  study  in  a  multinational  company  found  relationship  between  breadth  role  self‐efficacy  and  knowledge  sharing.  Hsu,  Ju,  Yen  &  Chang  (2007)  found  that  knowledge  sharing  has  direct  and  indirect  effects  on  knowledge sharing behavior. Some authors have also found a positive relationship between self‐efficacy and  knowledge  sharing  behavior  in  virtual  communities  (Chen,  Chuang  &  Chen,  2012;  Tseng,  2007).  From  above  the following hypothesis is formulated:  H1. Knowledge sharing self‐efficacy influences the knowledge sharing behavior.   Another variable associated to the explanation of a behavior is perceived organizational support (POS), which  is defined as the global interpretation of a worker about how much the organization values his contributions  and takes care of his welfare (Eisenberger, Huntington, Hutchinson & Sowa, 1986). POS generates a feeling of  reciprocity  in  the  person  to  contribute  to organizational  objectives (Eisenberger, Armeli,  Rexwinkel, Lynch  &  Rhoades, 2001). This concept correlates to organizational commitment, better performance and less rotation  (Rhoades  &  Eisenberger,  2002;  Uchenna  &  Tolupe,  2013).  Allen  &  Shanock  (2013)  stated  that  POS  is  a  relational mechanism that binds employees to the organization. If POS produces a feeling of reciprocity, then it  is expected, that a worker shares his knowledge.    There are few studies on the relationship between POS and knowledge sharing. King & Marks (2008) found a  positive  correlation  between  POS  and  the  effort  individuals  do  to  share  knowledge.  Bartol,  Liu,  Zeng  &  Wu  (2009) found that the correlation between POS and knowledge sharing was strong only to workers with a high  perception  of  work  security.  Lu,  Leung  &  Koch  (2006)  did  not  find  relation  between  POS  and  knowledge  sharing.  Hsin,  Shian  &  Sung  (2011)  found  that  POS  mediated  the  relationship  between  high  commitment  to  human resources management and knowledge sharing behavior.      In the present investigation, unlike King & Mark (2008), it was not measured the effort to share knowledge,  but the intention to share it and the knowledge sharing behavior. Additionally, unlike the study of Lu, Leung &  Koch  (2006),  it  was  used  the  POS  instrument  designed  by  the  authors  of  the  construct  (Eisenberger,  Huntington, Hutchinson & Sowa, 1986). The following hypotheses are formulated:  H2: Perceived organizational support influences the intention to share knowledge.  H3: Perceived organizational support influences the knowledge sharing behavior.  In this research it was also investigated the relationship between self‐efficacy and POS. Stadkovic & Luthans  (1998) stated that self‐efficacy changes when the person obtains new information and experience performing  a  task.  Having  feedback  on  performance  or  watching  a  model  doing  an  action  increases  self‐efficacy  (Saks,  1995).  Maurer,  Pierce  &  Shore  (2002)  held  that  POS  increases  self‐efficacy.  Meanwhile,  Lu,  Leung  &  Koch  (2006) did not found relationship between the two variables. However, in that study POS was measure by a  scale  developed  by  the  authors  and  not  by  the  instrument  designed  by  the  owners  of  the  construct  (Eisenberger, Huntington, Hutchinson & Sowa, 1986). In this research the relationship between POS and self‐ efficacy was studied using the original POS scale. The following hypothesis is formulated:  H4. Perceived organizational support influences self‐efficacy to share knowledge.   Subjective norms is the person`s perception that people who are important to him/her think he/she should or  should not perform the behavior in question (Carpi & Breva, 2001; Fishbein & Ajzen, 1975). Subjective norm is  the perceived social pressure to do or not an action. A normative belief is related to the approval or not of a  behavior by who are important referents to the individual (Ajzen, 1991). If subjective norm is high, so is the  intention. Unlike POS, subjective norm is not a perception of support but an individual`s belief about what is  expected to do in a context, and the motivation to act. In organizational contexts, if an employee believes his  boss considers he should share knowledge and the person is motivated to do what his boss wants, this is called  a subjective norm to share knowledge. Unlike POS, subjective norm is not an overall perception of backing, but  a belief about what it is expected to do in a context and the motivation for action. In the absence of strong  social  norms  people  tend  to  share  knowledge  based  on  personal  benefits  and  costs  (Constant,  Kiesler  &  Sproull, 1994).   

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Delio Ignacio Castaneda and Manuel Fernández Ríos  There are some studies about the influence of subjective norms on the knowledge sharing intention (Bock &  Kim,  2002;  Bock,  Zmud,  Kim  &  Lee,  2005;  Castaneda  &  Fernández,  2010;  Lin  &  Lee,  2004;  Ryu,  Ho  &  Han,  2003), and some on the influence of subjective norms on knowledge sharing (Bock & Kim, 2002; Castaneda &  Fernández, 2010; Lin & Lee, 2004; Müller, Spiliopoulou & Lenz, 2005). There is also evidence of the importance  of perceived social pressure from bosses on knowledge sharing behavior (Chatzoglou & Vraimaki, 2009). Based  on these studies the following two hypotheses are stated:  H5. Subjective norms influence the intention to share knowledge  H6. Subjective norms influence the knowledge sharing behavior.  Finally, according to the reasoned action theory (Fishbein & Ajzen, 1975), the closest determinant of behavior  is  the  intention.  Intention  is  the  cognitive  representation  of  the  disposition  of  an  individual  to  perform  a  behavior  (Ajzen,  1991).  Intention  is  the  degree  in  which  a  person  has  a  conscious  plan  to  do  a  behavior  (Warshaw & Davis, 1985). According to a prospective study, intention has explained between the 19% and 38%  of  the  variance  of  behavior  (Sheeran,  Trafimow  &  Armitage,  2003).  Therefore,  the  following  hypothesis  is  stated:  H7.  Knowledge  sharing  intention  influences  knowledge  sharing  behavior.  Figure  1  shows  the  research model.  Self-efficacy H4   H1

H1 Perceived Organizational Support

H2

Knowledge Sharing

H1

I

i

H7

H3 H4

H5

H4

H1

H1

Subjective Norms

H4   H4

H1

Knowledge Sharing Behavior H6

H4

Figure 1: Research model 

2. Research methodology  This is a correlational study that utilized self‐report responses using an online survey within an organization.  There is large evidence of the relevance of the constructs: perceived organizational support, self‐efficacy and  subjective norms in relation to some behaviors, but few studies in relation to knowledge sharing. This is the  reason why it is stated a correlational study, but with some explanatory scope. To validate the research model  it is used Structural Equation Modeling (SEM), a statistical technique to evaluate how the proposed model is  fitted to data.  

2.1 Participants and procedure  A  survey  was  conducted  with  188  knowledge  workers  of  a  public  organization  at  the  national  level  in  Colombia.  114  of  respondents  were  women  and  74  men.  With  the  support  of  the  human  resources  and  organizational  development  offices  of  the  public  organization,  392  workers  who  occupied  jobs  at  the  professional, advisory and management levels were invited to answer the online questionnaire. 48% of them  answered the request. An email was sent to the workers who fulfilled the research requirements. The email  provided a link that conducted the participants to a web page that contained a short description of the survey  as well as a confidentially statement. 

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2.2 Instruments Perceived  Organizational  Support  (POS):  It  was  used  the  8  items  version  of  the  instrument  developed  by  Eisenberger, Huntington, Hutchinson & Sowa (1986). The tool was translated into Spanish using the procedure  translation back translation. The questionnaire uses a likert scale of 7 levels of answer.     For  the  variables:  subjective  norms,  self‐efficacy,  intention  to  share  knowledge  and  the  knowledge  sharing  behavior  it  was  used  the  instrument  validated  by  Castaneda  &  Fernandez  (2010).  Each  variable  includes  4  items with the exception of subjective norms which utilizes 8 items. The variables use a likert scale of 7 levels  of answer. The reliability of the instrument was of 93% using alpha of Crombach. 

3. Data analysis and results  In this study some psychosocial variables which have showed theoretical consistency were tested in relation to  the knowledge sharing intention and behavior. In order to test the hypotheses, the correlations between the  variables were calculated and their degree of significance. Figure 1 shows the research model and table 1 the  correlations between the variables.    Five  of  seven  hypotheses  found  support  from  data.  There  was  not  found  significant  correlation  between  perceived organizational support and knowledge intention and between perceived organizational support and  self‐efficacy. Next step was to assess the validity of the model.    H1  examines  the  link  between  knowledge  sharing  self‐efficacy  and  the  knowledge  sharing  behavior.  The  correlation was 0,435, significant at the 0,01 level. The results are in the expected direction according to the  self‐efficacy theory (Bandura, 1977). In this sense, as it was found with other behaviors, there is a relationship  between self‐efficacy and the knowledge sharing behavior. This is, individual`s beliefs of his or her capacity to  share  knowledge  is  directly  related  to  his  or  her  knowledge  sharing  behavior.  The  results  contribute  to  document  the  importance  of  this  construct  in  relation  to  knowledge  sharing.  Although  there  are  some  previous studies that investigated the relationship between these two variables, one of them conceptualized  self‐efficacy  as  expectations  of  contribution  (Bock  &  Kim,  2002),  far  from  the  original  concept  created  by  Bandura  (1977)  and  the  other  focused  the  attention  on  the  role  breadth  self‐efficacy  (Cabrera,  Collins  &  Salgado). Further studies may investigate the relationship between self‐efficacy and different types and levels  of knowledge sharing.  Table 1: Pearson Correlations between the variables of the hypotheses  Correlation

Hypothesis

Self- Efficacy

Variables Knowledge Sharing

0,435 **

H1

Perceived Organizational Support

Knowledge Intention

0,026

H2

Perceived Organizational Support

Knowledge Sharing

0,213**

H3

Perceived Organizational Support

Self- Efficacy

0,7

H4

Subjective Norms

Knowledge Intention

0,476**

H5

Subjective Norms

Knowledge Sharing

0,729**

H6

Knowledge Intention

Knowledge Sharing

0,510**

H7

** correlation is significant at 0,01 level

H2  and  H3  inquired  on  the  association  between  POS  and  Knowledge  sharing  intention  and  behavior  respectively.  It  was  not  found  a  significant  correlation  between  POS  and  Knowledge  sharing  intention.  Although there are no studies published linking POS and knowledge sharing intention, there is a related study  in which it was found a liaison between POS and the effort to share knowledge (King & Mark, 2008). In our  research it was stated that if POS generates a feeling of reciprocity (Eisenberger, Armeli, Rexwinkel, Lynch &  Rhoades, 2001), then there was a connection between POS and knowledge sharing intention. The results do  not support this hypothesis.     In our study, the correlation between POS and knowledge sharing behavior was 0,213, significant at the 0,01  level.  There  are  some  contradictory  findings  in  the  literature.  White  Lu,  Leung  &  Koch  (2006)  did  not  find 

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Delio Ignacio Castaneda and Manuel Fernández Ríos  relation between POS and Knowledge sharing; Bartol, Liu, Zeng & Wu (2009) reported relationship only with  workers  with  a  high  perception  of  work  security.  According  to  the  conceptual  framework,  POS  generates  a  feeling of reciprocity in workers, which is expected to be manifested in behaviors such as sharing knowledge. It  is suggested additional research to understand when POS has a direct association to knowledge sharing and  when it does not.     H4 evaluated the linkage between POS and self‐efficacy. It was not found support from data to this hypothesis.  This  fact  contradicts  the  assertion  of  Maurer,  Pierce  &  Shore  (2002)  and  support  the  finding  of  Lu,  Leung  &  Kock  (2006)  of  no  connection  between  these  two  variables.  Additional  research  is  suggested  in  the  topic,  particularly  because  according  to  Stadkovic  &  Luthans  (1998)  self‐efficacy  changes  when  the  person  obtains  information from performance. Receiving information from the organization may impact self‐efficacy.    H5  and  H6  declared  that  subjective  norms  are  related  to  knowledge  sharing  intention  and  behavior.  The  correlation between subjective norms and knowledge sharing intention was 0,476, significant at the 0,01 level.  According to the reasoned action theory the two closest determinants of intention are: subjective norms and  attitude (Fishbein & Ajzen, 1975). As expected from this theory and the results from previous studies (Bock &  Kim,  2002;  Bock,  Zmud,  Kim  &  Lee,  2005;  Castaneda  &  Fernández,  2010;  Lin  &  Lee,  2004;  Ryu,  Ho  &  Han,  2003), the perception that an individual has from referents in an organization about knowledge sharing impact  his intention to perform this behavior. In the same direction, it was found a correlation of 0,729, significant at  the  0,01  level,  between  subjective  norms  and  knowledge  sharing  behavior.  The  results  contribute  to  add  empirical evidence on the relation of these two concepts. Workers in organizations need to know from their  leaders that sharing their knowledge is desirable. When it happens, this behavior has social pressure to occur  in the organization and the probability that it takes place increases.    H7  asserted  that  knowledge  sharing  intention  influences  knowledge  sharing  behavior.  According  to  results  there was found a positive correlation between the two variables, 0,510, significant at 0,01. Findings support  the reasoned action theory which asserts that the closest determinant of behavior is the intention. This theory  has  been  taken  as  a  framework  in  few  knowledge  sharing  studies  and  it  was  found  a  positive  relationship  between the knowledge sharing intention and the knowledge sharing behavior (Bock & Kim, 2002; Castaneda  & Fernández, 2010; Reychav & Weisberg, 2010). The closest predictor of knowledge sharing is its intention.    To validate the research model it was used Structural Equation Modeling (SEM). To evaluate the fitness of the  model  it  was  used  the chi  square  value, which  represents  the differences  between the  observed covariance  matrix  and  the  predicted  covariance  matrix.  According  to  data,  chi  square  was  87,739,  with  2  degrees  of  freedom  and  a  probability  level  of  0,000,  which  let  us  affirm  that  the  considered  variables  in  this  research  model are good predictors of knowledge sharing intention and behavior. Figure 2 shows the model.     A  purpose  of  proposing  a  model  is  to  identify  few  variables  that  explain  largely  a  behavior.  In  this  research  some constructs that have been strong explaining human behavior, but incipient explaining knowledge sharing  were studied together. From this research, if an organization focuses its attention in facilitating in employees  perceptions  of  support,  clear  messages  from  leaders  on  the  importance  of  knowledge  sharing,  and  positive  beliefs about their capacities to share knowledge, then the intention to share knowledge and the knowledge  sharing behavior may occur.    The research focused on psychosocial variables associated to knowledge sharing. There were not considered  organizational conditions which also impact knowledge sharing, for example, the availability of resources and a  knowledge  oriented  culture.  Further  studies  are  suggested  to  research  psychosocial  variables  and  organizational conditions together.    In  addition,  there  are  few  publications  that  present  results  on  the  relationship  between  perceived  organizational  support  and  subjective  norms.  Phattanacheewapul  &  Ussahawanitchakit  (2009)  in  Thailand  found  that  perceived  organizational  support  mediates  the  link  between  subjective  norms  and  task  perseverance.  In  the  future  may  be  investigated  the  role  of  perceived  organizational  support  as  a  mediator  variable between subjective norms and knowledge sharing behavior.   

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Delio Ignacio Castaneda and Manuel Fernández Ríos  0.76

E3

H4

H4

H1

1 0.62

Self-efficacy

H4

E1

H4

H1

0.7

0.80

1

-0.20

H4

H1

H4

Perceived Organizational Support

H1

-

Knowledge Sharing Intention

H1

0.14 H4

H4

0.47

H1

H1

H4

-

H4   H4

0.88

H4

H1

1

H1

Subjective Norms

Knowledge Sharing Behavior 1.00 H4

1

H4

H1

E2

0.78 H4

Figure 2: SEM analysis research model 

4. Conclusions The purpose of this research was to contribute to the understanding of the role of some psychosocial variables  in  the  explanation  of  the  knowledge  sharing  behavior.  All  the  studied  variables  have  strong  theoretical  frameworks:  Self‐efficacy  from  the  social  cognitive  theory,  subjective  norms  from  the  theory  of  reasoned  action,  and  POS  is  a  widely  studied  construct  in  organizations.  Although  these  variables  have  been  highly  studied in psychology, they have been used recently in the understanding of the knowledge sharing behavior.  In  our  research,  it  was  found  empirical  support  on  the  relationship  between  POS,  self‐efficacy,  subjective  norms, intention to share knowledge and the knowledge sharing behavior.     There  are  some  implications  from  findings  to  practitioners  in  knowledge  management.  First,  to  strengthen  human resources practices that may increase the perception of organizational support as a form to facilitate  the knowledge sharing behavior. Second, the design of organizational interventions oriented to increase the  knowledge  sharing  self‐efficacy  in  workers.  Sometimes  low  performance  in  sharing  knowledge  may  be  explained not because of a lack of competence to share knowledge but due to low self‐efficacy associated to  knowledge sharing. Third, leaders have a strong role orienting workers to specific actions. They must send the  message of knowledge sharing as a must. If workers assume knowledge sharing as a subjective norm, they may  be more willing to share knowledge and do so in practice.    There are some limitations in the research. The first is that participants were knowledge workers of a public  organization, then, it is not possible to generalize these results to public organizations in general or to private  companies. However, results  went in the direction of other studies. Second, POS was not unidimensional as  expected  from  the  theory  (Eisenberger,  Huntington,  Hutchinson  &  Sowa,  1986).  When  it  was  run  a  factorial  analysis of data, some items of the POS scale shared factorial loads in the intention to share knowledge scale.  Additional research it is suggested on the communalities between POS and the intention to share knowledge. 

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The Value of Extended Framework of TAM in the Electronic  Government Services1  Juan‐Gabriel Cegarra‐Navarro1, Stephen Eldridge2, Eva Martinez‐Caro1 and Maria Teresa  Sanchez Polo 1  1 Universidad Politécnica de Cartagena, Spain   2 Lancaster University Management School, UK   juan.cegarra@upct.es  s.eldridge@lancaster.ac.uk  meugenia.sanchez@upct.es  juan.cegarra@upct.es    Abstract: Spanish City Halls are making a great effort to develop citizen‐targeted online services in an attempt to enhance  their  effectiveness  and  reduce  expenses.  Hence,  citizens’  engagement  is  essential  for  the  adoption  of  e‐Government  services.  In  this  research,  an  extended  Technology  Acceptance  Model  (TAM)  is  developed  to  test  citizen  engagement  towards online e‐Government services from a sample of 307 citizens who used the benefits adviser tool within a Spanish  City Hall. To achieve this goal, a structuring equation model is developed and tested to confirm the explanatory power of  citizen  satisfaction  on  citizen  engagement.  The  results  obtained  suggest  that  the  core  constructs  of  TAM  (perceived  usefulness,  ease  of  use  and  attitude)  significantly  affect  users’  citizen  engagement.  This  study  also  reveals  a  general  support for citizen satisfaction as a determinant of citizen engagement in e‐Government services. The implications of the  findings are discussed and useful insights are provided on what policy to follow to establish the appropriate conditions to  build citizens’ engagement intent.    Keywords: citizen engagement, satisfaction, technology acceptance model, end users 

1. Introduction In  general  terms,  local  government  institutions  can  be  considered  repositories  of  knowledge  in  the  form  of  laws,  regulations  or  specific  cases.  These  institutions  provide  and  deliver  public  services  that  are  of  key  importance to citizens and business. In countries like Spain, the factors that influence the nature and structure  of the Spanish Public Administration (e.g. demand, costs, regulations, organisation, etc) are undergoing rapid  change.  Recent  reforms  have  regionalised  the  Spanish  Public  Administration  in  order  to  improve  response  times and increase the participation of communities in the development and management of electronic online  services at regional and local levels (Cohen & Nijkamp, 2004). According to a report recently released by the  Press  Office  of  the  Spanish  Ministry  for  Public  Administrations  (MAP  in  Spanish,  2011),  in  September  2011  Spain found itself among the ten most advanced countries in this area and ranked fifth in Europe in terms of  both  availability  and  sophistication  of  on‐line  public  services  (SIPA,  2011).  The  progress  of  e‐Government  in  Spain has undoubtedly been favoured not only by the greater awareness and predisposition to engagement  shown by potential service users but also by the planning and legislative efforts made by Spain’s public sector  in the last few years (MAP in Spanish, 2011).    In  Spain,  most  if  not  all  municipalities  (called  “municipios”  in  Spain)  are  engaged  in  the  development  and  delivery of efficient services to the public. Heichlinger (2004) defines e‐Government simply as a set of activities  supported  by  information  systems  with  the  aim  of  improving  the  relationships  between  government  institutions and citizens. These include collecting and paying money according to the laws and bylaws of Spain  as well as resolutions of city councils. A key component of local services is that of official town websites (OTW).  These are highly visible manifestations of city developments and are used for service delivery and information.  They enable local governments to provide citizens, business and other organisations with convenient access to  local services and opportunities to collaborate via information communication technologies (ICT) (Lean et al.,  2009).     Despite the fact that the majority of municipal governments have their own ICT and websites to provide public  information  to  citizens  (Moon  &  Norris,  2005),  there  has  been  no  emphasis  on  offering  online  financial  and                                                                    1

The dates of this research were taken from a research program supported by the Spanish Ministry of Education (REF: ECO2011‐28641‐ C02‐02), the  R&D  Project for Excellence. Andalusian Ministry of Education (REF:  SEJ‐6081), and the  research program supported by the  Agencia de Ciencia y Tecnología Región de Murcia (f SéNeCa 18709/EE/12). 

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Juan‐Gabriel Cegarra‐Navarro et al.  service  transactions  nor  on  providing  opportunities  for  electronic  and  interactive  political  and  policy  participation (Criado & Ramilo, 2003; Norris & Moon, 2005). As Criado and Ramilo noted in a previous study of  Spanish local government websites (2003), a low level of two‐way interaction between local governments and  citizens  could  be  characteristic.  To  address  this,  the  Law  on  Citizens'  Electronic  Access  to  Public  Services  published  in  June  2007 2   in  Spain  sought  to  strengthen  the  commitment  towards  e‐Government  implementation  and  use  by  autonomous  communities  and  local  authorities  through  the  improvement  of  coordination  mechanisms  between  various  levels  of  government  in  providing  e‐Government  services  (eServices) to citizens.     The  initial  stages  of  the  implementation  of  ICT‐based  services  in  the  local  government  environment  can  be  difficult, but considering that most technical obstacles are gradually being overcome, the question that arises  is  whether  people  are  willing  to  use  these  new  technological  advancements  (Suki  &  Ramayah,  2011).  Acceptance of information technology by users is deemed a necessary condition for its success (Davis, 1989).  Regarding  this,  while  customer  engagement  has  been  widely  studied  in  the  information  technology  area,  research has largely concentrated on customer responses to online retailers (e.g. Reichheld & Schefter, 2000),  few, if any, studies have considered the ways in which the use of municipal‐portals can be accepted through a  municipal’s ICT infrastructure (operationalised in this paper as citizen engagement).    There is a considerable volume of work related to technology acceptance. What we employ in this paper is an  application  of  the  Technology  Acceptance  Model  (TAM)  (Davis  1989).  Despite  the  amount  of  academic  research  dedicated  to  examining  the  determinants  of  information  technology  acceptance,  and  to  TAM  in  particular,  very  little  research  has  been  conducted  on  City  Halls  to  help  identify  how  technologies  may  be  accepted by citizens. Hence, the primary aim of this research is to use the core concepts of TAM to test the  citizen’s  engagement  towards  e‐Government  services  offered  by  City  Halls.  To  achieve  this  goal,  a  modified  TAM is developed and tested by using the Structural Equation Modelling (SEM) approach. These relationships  are  examined through an  empirical  investigation of 307 citizens  who  used  the  benefits  adviser  tool  within  a  Spanish City Hall. The concept of citizen engagement is discussed in detail in the following section. Section 3  investigates  the  development  of  hypotheses  as  to  how  the  TAM  contributes  to  citizen’s  engagement  in  e‐ Government. Details of the survey which was used to collect appropriate data to test the models is presented  in  section  4,  whilst  the  results  of  testing  the  models  are  presented  in  section  5,  followed  by  a  discussion  in  section 6. 

2. Conceptual framework  Abramson and Means, (2001) define e‐Government as digital governmental information or a way of engaging  in digital transactions with the public (citizens and businesses) and employees. Fraga (2002) suggests that e‐ Government  is  the  transformation  of  internal  and  external  relationships  in  the  public  sector  through  net‐ enabled  operations.  Durrant  (2002)  defines  e‐Government  as  “a  permanent  commitment  by  government  to  improve the relationship between the private citizen and the public sector through enhanced, cost‐effective  and  efficient  delivery  of  services,  information  and  knowledge”.  For  Jaeger  and  Fleischmann  (2013),  e‐ Government is about developing a citizen‐centred government environment which serves citizens (customers)  at any time, regardless of their physical location.    The above definitions suggest a variety of processes and services that can be supported by the use of ICT in  government affairs, as well as the diversity of perspectives that can be adopted to assess their impacts in both  governments and citizens (). These perspectives also provide us with an illustration that e‐Government is a way  for  public  administration  to  become  more  open  and  transparent,  to  enable  democratic  participation,  to  become more service‐oriented, providing personalised and inclusive services to each citizen, to become more  productive and to deliver maximum value for taxpayers' money as well as for any ICT investment. Researchers  agree  that  e‐Government  has  considerable  potential  to  contribute  to  learning  efficiency,  gains  and  cost  reductions for local government (e.g. Criado & Ramilo, 2003; Carter & Belanger, 2005; Badri & Alshare, 2008;  Lean  et  al.,  2009).  The  opportunity  to  access  new  knowledge,  learn  about  government  and  conduct  online  transactions can reduce red tape and simplify regulatory processes, therefore helping citizens to engage more  in issues that are important to local communities (e.g. public transport or street design issues).                                                                      2

http://www.boe.es/boe/dias/2007/06/23/pdfs/A27150‐27166.pdf 

 

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Juan‐Gabriel Cegarra‐Navarro et al.  Just  recently,  in  countries  like  the  USA  a  number  of  e‐Government  projects  have  been  developed  to  help  communities address their local problems with the use of websites (Bertot et al., 2011). In this way, a form of  civic engagement is promoted which focuses on public concerns and which includes both political involvement  in political institutions as well as community involvement in associational or voluntary activities or institutions  (Putnam 2000; Jennings & Zeitner 2003; Bennett 2008). Despite these trends and premises, there are only a  few cities around the world that continuously engage with citizens in policy dialogues or work with community  organisations to strengthen citizen engagement and participation at the neighbourhood level (Ho, 2002). What  seems  to  be  dominating  research  in  the  use  of  e‐Government  websites  is  the  study  of  the  dynamics  of  networks of communication that emerge in political campaigns, most of which are dominated by incumbent  groups (Hindman, 2009: Araya et al., 2010).     Civic engagement in general may be defined as individual and collective courses of action that are designed to  identify  and  address  matters  of  public  concern  (Hays,  2007).  Another  way  of  describing  this  concept  is  the  sense of personal responsibility individuals should feel to uphold their obligations as part of any community  (Putnam, 2000). This means that civic engagement can take many forms, from organisational involvement to  electoral  participation,  individual  volunteerism  or  engagement  with  new  activities  of  the  government.  This  paper is particularly concerned with the latter. That is, it focuses on those aspects of civic engagement that are  mediated through local government websites, rather than formal political institutions or voluntary activities. It  should be noted here that in this paper the civic engagement that we refer to is “citizen engagement”. More  specifically, it is concerned with citizen engagement facilitated by local governments to deal with local affairs  concerning  pollution  issues,  school  affairs  and  street  design  issues  (Zukin  et  al.  2006;  Lim,  2007).  From  this  perspective, citizen engagement includes efforts to directly address an issue, work with others in a community  to solve a problem or interact with the local institutions.    Nowadays,  e‐Government  in  Spain  encompasses  any  type  of  mutual  communication  or  interaction  between  citizens, business and public organisations and because of this, e‐Government is perceived as the use of ICT for  controlling  electronically  public  administration’s  processes  from  both  internal  and  external  perspectives  3 (Criado & Ramilo, 2003; Claver et al., 2008). Although initiatives like the Avanza2  and Avanza Local Plans give  testimony  of  how  local  and  regional  governments  in  Spain  have  been  continuous  adopters  of  ICT  in  recent  years (Torres et al., 2005; De‐Miguel‐Molina, 2010; SIPA, 2011), the digital informative transparency of Spanish  city  councils  is  very  poor  (De‐Miguel‐Molina,  2010).  As  Gandía  and  Archidona  (2008)  noted,  Spanish  city  councils often use their web sites to diffuse information of a general nature and with promotional or political  purposes that do not contribute directly to relevant informative content. Neither do they allow users to take  advantage  of  the  relational  and  interactive  capacity  of  the  internet.  A  possible  explanation  for  the  low  disclosure levels among Spanish city council web sites may relate to the website strategy and implementation  adopted  by  Spanish  city  councils,  and  how  such  strategies  have  been  associated  with  low  (or  non  existent)  citizen engagement (Gandía & Archidona, 2008).  

3. Hypotheses As  noted  above,  there  are  different  definitions  of  citizen  engagement  but  common  elements  include  knowledge of and discussion of public affairs (Rose & Grant, 2010; Jennings & Zeitner 2003; Mossberger et al.,  2008). E‐Government may provide new venues for information, enhancing citizen knowledge of government  policies, processes, programs, and performance, as well as community issues (Norris 2001). This knowledge, in  turn, may also encourage discussion or participation in community issues, including joining a group online and  face‐to‐face interaction with neighbours (Norris, 2001). Information about community affairs available on local  government websites might promote discussion and mobilization around these issues with neighbours, both  online and offline (Norris, 2001), this points to the information capacity of e‐Government as being a potential  resource for acquiring knowledge for citizen engagement (Norris 2001; Jennings & Zeitner 2003; Mossberger  et al., 2008).     However,  the  knowledge  learned  through  a  public  service  website  is  likely  to  be  dependent  on  the  gratifications  individuals  seek  from  media  and  their  resultant  media  choices.  Uses  and  gratification  theory  predicts that people use the Internet or other media in a variety of ways for a range of ends to satisfy different  goals (Althaus & Tewksbury, 2000). Put it another way, the achievement of user satisfaction with public service  websites  requires  attention  to  several  earlier  levels  of  user  interaction.  In  this  study,  the  Technology                                                                    3

http://www.planavanza.es/avanzalocal/Paginas/Index.aspx 

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Juan‐Gabriel Cegarra‐Navarro et al.  Acceptance  Model  (TAM)  was  used  to  analyze  the  processes  of  creating  satisfaction  with  public  service  websites.    The  Technology  Acceptance  Model  (TAM),  first  introduced  by  Davis  (1989),  is  one  of  the  most  frequently  employed models for research into new information technology acceptance. This model applies Fishbein and  Ajzen’s Theory of Reasoned Action (TRA) to explain the pattern of voluntary information system usage at an  individual level (Kim & Chang, 2007). TAM has been the subject of a lot of research in the area of information  systems over nearly two decades and has been supported by a number of studies. TAM suggests that when  users are presented with a new technology, their decision about how and when they will use it is determined  by  assessing  their  beliefs,  attitudes  and  intentions  (Davis,  1989).  There  is  a  considerable  volume  of  work  relating  to  technology  acceptance.  What  we  employ  in  this  paper  is  an  application  of  the  Technology  Acceptance Model (TAM) (Davis, 1989).     Attitude toward using a technology (A) was defined by Davis (1989) as “the degree of evaluative affect that an  individual associates with using a system in his or her job”. Attitude is determined by a function of two beliefs:  Perceived Usefulness (PU) and Perceived Ease of Use (PEOU). PU was defined as “the degree to which a person  believes  that  using  a  particular  system  would  enhance  his  or  her  job  performance”.  PEOU  is  “the  degree  to  which a person believes that using a particular system would be free from effort” (Davis 1989). PU and PEOU  create  belief  among  potential  users  and  subsequently  form  their  attitude.  A  user  that  believes  the  new  technology will be useful and relatively easier to implement may be expected to have a more positive attitude  towards that particular technology.    On the other hand, perceived ease of use has a direct effect on perceived usefulness. Between two systems  that  perform  an  identical  set  of  functions,  users  find  the  one  that  is  easier  to  use  more  useful.  However,  perceived usefulness has no impact on perceived ease of use. As Davis (1993) explained, perceived usefulness  concerns the expected overall impact of system use on job performance, whereas ease of use pertains only to  those performance impacts related to the process of using the systems per se. Moreover, TAM postulates that  Behavioural Intention (BI) is viewed as being jointly determined by the person’s attitude towards using system  (AT) and PU (Davis et al., 2009). Finally, actual system use is determined by BI.     The  technology  acceptance  model  specifies  the  causal  relationships  between  perceived  ease  of  use  (PEOU),  perceived  usefulness  (PU)  and  attitude  toward  using  (A).  Overall,  the  TAM  provides  an  informative  representation of the mechanisms by which design choices influence user acceptance, and should therefore be  helpful  in applied  contexts  for  forecasting and  evaluating  user  acceptance  of  ICT.  Therefore,  based  on  Davis  (1989), traditional TAM hypotheses were tested as part of their work, and we propose:  H1: Perceived ease of use is positively associated with perceived usefulness   H2: Perceived usefulness is positively associated with attitude   H3: Perceived ease of use is positively associated with attitude   Although, the research model built was based on TAM, several modifications were made to improve use of e‐ Government services such as satisfaction and citizen engagement.     On  the  one  hand,  satisfaction  construct  was  introduced  in  the  model.  Although  user  satisfaction  and  technology  acceptance  have  evolved  largely  as  parallel  research  streams,  the  two  approaches  can  be  integrated. Such integration can help build a conceptual bridge from design and implementation decisions to  system characteristics to the prediction of usage. Ultimately, this would improve the predictive value of user  satisfaction and augment the practical utility of technology acceptance (Wixom & Todd, 2005). According to  Bitner et al. (2002), effective and successful self‐service technologies are those that have been designed and  implemented especially to ensure customer satisfaction and to keep customers’ motivations and expectations  in mind. Satisfaction in a given situation is a person‘s feelings or attitudes toward a variety of factors affecting  that situation (Wixom & Todd, 2005). From an ICT point of view, satisfaction construct represents the degree  to which a user’s perceived personal needs and the need to perform specific tasks satisfactorily are met by an  information system (Goodhue & Straub 1991). Within the literature on user satisfaction, satisfaction is typically  viewed  as  the  attitude  that  a  user  has  toward  an  information  system.  Therefore,  user  satisfaction  is  conceptualized as affective reactions of individuals and it can be defined as an attitudinal construct. Several  authors (e.g. Guimaraes & Igbaria, 1997; Chris et al., 2006; Eastman et al., 2011), point out that users with a 

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Juan‐Gabriel Cegarra‐Navarro et al.  more  positive  attitude  towards  a  technology  are  likely  to  be  more  satisfied  with  it.  Hence,  attitude  was  considered here as an antecedent of satisfaction and the hypothesis we propose under this framework is:  H4: A positive attitude towards a technology is positively associated with satisfaction     The above considerations also lead us to argue that satisfaction achieved through local government websites,  could be expected to facilitate citizen engagement as well. If citizen engagement includes knowledge, interest,  discussion, and participation, then satisfaction with public service websites is one of the resources supporting  these different aspects of engagement (Norris, 2001). Regarding this, some prior research shows that online  news is a better predictor of citizen engagement than use of traditional media (Mossberger et al., 2008), and  e‐Government also has many features that lower the costs of information acquisition. Thus, satisfaction with  public service websites has a positive influence on citizen engagement, likelihood of recommending, word of  mouth and reuse/loyalty intentions (Van Riel et al., 2001; Taylor & Hunter, 2002; Yoon, 2002). User satisfaction  associated  with  ICT  usage  can  influence  subsequent  use  of  information  (Yen  &  Gwinner,  2003;  Yang  &  Peterson,  2004).  Regarding  this,  user  satisfaction  involves  making  the  citizen  aware  of  the  e‐Government  services and generating some positive feelings through the local government website. If online services meet  citizen’s  expectation,  satisfaction  occurs.  In  addition,  satisfaction  can  result  in  successive  use  of  the  online  services,  which  in  turn  facilitates  citizen  engagement.  Here  satisfaction  is  created  first  leading  to  citizen  engagement. Therefore, we propose:  H5: Satisfaction is positively associated to citizen’s engagement in e‐Government 

4. Method Using the records of the Cartagena City Council, we considered 1995 users, who were contacted and asked by  the City Council to participate in the study. Of these users, only 307 agreed. Then, on April and May 2012 we  conducted 307 telephone interviews with users, using a simple structured questionnaire. Therefore, the data  analysis was based on 307 valid responses (a response rate of 15.38%) with a factor of error of 5.15% for  p=q=50% and a reliability level of 95% percent. The great majority of respondents were male (73 percent) and  had university studious (37 percent). Additionally, this study conducts two statistical analyses to ensure the  absence of non‐response bias (Armstrong & Overton, 1977). Firstly, this study compares the responding and  non‐responding users in terms of level of education (1= secondary school; 2 = Bachelor’s Degree; and 3 =  Master’s Degree). In this regard, the independent sample t‐test revealed no significant difference between the  two groups (p= .93). Secondly, the respondents are then divided into two groups based on telephone interview  dates (i.e. 1 = April; and 2 = May). Comparison of the two groups in terms of e‐Government use again revealed  no significant differences based on the independent sample t‐test (p = .71). Therefore, non‐response bias  should not be a problem in this study. 

4.1 Measures In order to assure the research can be generalized, it is important to add control variables to the regression  model  in  order  to  assure  that  the  effects  of  technology  on  our  population  sample  achievement  are  independent  of  the  user’s  focus  on  their  achievement.  With  respect  to  this  issue,  the  findings  of  traditional  sociological studies point to more positive attitudes towards computer technology among males (e.g. Arch &  Cummins,  1989).  Specifically,  some  empirical  evidence  suggests  perceived  usefulness  more  salient  for  men  than for women (e.g. Venkatesh & Morris, 2000) while other researchers find that technologies are perceived  as  more  useful  by  women  than  by  men  (e.g.  Gefen  &  Straub,  1997).  Thus,  the  responder’s  gender  may  be  related to the Perceived Usefulness. In this paper, the variable “gender” has been treated as a control variable  and was measured with a single variable classified into two categories (1=male and 2= female).    Before  undertaking  the  survey,  a  series  of  telephone  interviews  with  five  users  of  a  pilot  sample  was  undertaken  to  learn  about  their  understanding  about  the  benefit  adviser  tools.  As  shown  in  Figure  1,  these  users stated that the benefit adviser tool basically allows them to apply for a census certificate and pays local  taxes such as the motor vehicle tax and the property tax. They also stated that the benefit adviser tool helped  them  to  see  how  payment  is  being  processed,  and  is  also  useful  for  generating  more  variations  of  existing  scenarios by providing scenario generation hints for each comparison feature.     A  questionnaire  was  developed  to  be  the  instrument  for  data  collection.  All  items  were  measured  using  a  seven‐point Likert‐type scale with anchors from “Strongly disagree” to “Strongly agree”. We combined scales 

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Juan‐Gabriel Cegarra‐Navarro et al.  from several other relevant empirical studies with new items to make an initial list of 15 items (3 measuring  the  range  of  PEOU;  3  measuring  the  existence  of  PU,  3  measuring  attitude,  3  measuring  satisfaction  and  3  relating  to  citizen  engagement).  Several  items  were  modified  through  interviews  with  colleagues.  Table  1  provides an overview of the final 15 questions used in the questionnaire. From an examination of the results  shown in Table 1, we can state that all of the constructs are reliable. 

Figure 1: The benefit adviser tools  Table 1: Construct summary: Confirmatory factor analysis and scale reliability  y

Items Services enhance effectiveness in doing things. Services make it easier to do things. Services enable me to accomplish thongs more quickly. In my opinion, it is desirable to use the city council’s website. I think it is good for me to use the city council’s website. Overall, my attitude toward the city council’s website is favourable. These services have met my expectations. I am pleased with the experience of using these services. My decision to use these services was a wise one. Public meeting in which there is a discussion of town affairs. Public meeting in which there is a discussion of school affairs. Citizen consensus conferences on critical street design issues Interacting with the city council’s website does not require a lot of my mental effort. I find the city council’s website to be easy to use. I find it easy to get the services to do what I want to do.

y

Standardized loading .76 .84 .81 .82 .78 .80 .73 .80 .77 .81 .75 .70 .73 .88 .77

y

T-value 13.81 14.12

y Reliability (SCRa., AVEb) SCR= .84 AVE=.63

14.39 14.96

SCR=.84

12.42

AVE=.64

13.96 13.21

SCR= .85

14.88

AVE=.65

12.88 13.41

SCR= .85

13.64

AVE=.66

10.85 16.63

SCR=.84

20.87

AVE=.64

16.59

Notes: The fit statistics for the measurement model were: Satorra-Bentler χ2(79)=176.40; χ2/d.f= 2.23; GFI=.90; CFI=.93; IFI=.94; RMSEA= .063; a SCR= Scale Composite Reliability (SCR) of pc= (Σλi)2 var (ξ) / [(Σλi)2 var (ξ) +Σ θii] b Average variance extracted (AVE) of pc= (∑λi2 var (ξ))/[∑λi2 var (ξ) + ∑θii] The asymptotic covariance matrices were generated to obtain the scaled chi-square (Satorra and Bentler, 1988) and robus estimation of standard errors.

Discriminant validity was determined by comparing the square root of the AVE (i.e., the diagonals in Table 2)  with  the  correlations  among  constructs  (i.e.  the  lower  triangle  of  the  matrix  in  Table  2).  On  average,  each  construct related more strongly to its own measures than to others (Fornell & Larcker, 1981).       

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Juan‐Gabriel Cegarra‐Navarro et al.  Table 2: Construct correlation matrix 

1. Perceived usefulness (range 1–7) 2. Attitude (range 1–7) 3. Satisfaction (range 1–7) 4. Citizen engagement (range 1–7) 5. Perceived ease of use (range 1–7) 6. Gender (range 1–2)

Mean 5.03 5.32 4.77 5.26 4.72 1.27

S.D 1.09 1.14 1.04 1.10 1.22 0.44

CA .84 .84 .81 .80 .83 n.a

1 .79 .71*** .66*** .52*** .46*** -.04

Correlation matrix 2 3 .80 .66*** .62*** .56*** -.06

.83 .67*** .54*** -.02

4

.81 .34*** .02

5

.80 -.07

6

n.a

Notes: *** <.01; n.a. = not applicable Mean = the average score for all of the items included in this measure; S.D. = Standard Deviation; CA = Cronbach’s Alpha; Intercorrelations are presented in the lower and shady triangle of the matrix. The bold numbers on the diagonal are the square root of the Average Variance Extracted.

5. Results Following the recommendations of Anderson and Gerbing (1988), we tested our theoretical model (TM), with  ‘satisfaction’  as  intermediate  variables  between  ‘attitude’  and  ‘citizen  engagement’,  against  an  alternative  model (AL), considering that ‘satisfaction’ does not need to be done first. Figure 1 provides a synopsis of these  models.  While  in  the  first  model  (Theoretical  Model)  the  impacts  of  ‘attitude’  on  ‘citizen  engagement’  is  potentially  mitigated  by  the  extent  to  which  satisfaction  exists,  in  the  case  of  the  Alternative  Model,  the  impact  of  the  ‘attitude’  is  not  mediated  through  the  extent  to  which  satisfaction  exists.  The  goodness  of  fit  indices show that the theoretical model has more adequate fit indices: RMSEA, CFI, IFI and PNFI (see Figure 1),  than  the  alternative  model.  It  is  interesting  to  note  that  the  difference  of  PNFI  between  the  two  models  is  above  0.01,  a  critical  value  recommended  by  Hair  et  al.  (1998)  as  indicating  that  one  model  represents  a  significant gain of parsimony over another.     In the Alternative Model we have also found an insignificant effect of ‘attitude’ on ‘citizen engagement’, with a  standardized  coefficient  of  0.09.  Furthermore,  the  theoretical  model  explains  more  variance  in  citizen  engagement than the alternative model. Therefore, the data we obtained provides support for the theoretical  model where the extent to which satisfaction exists is considered as a mediating variable between ‘attitude’  and ‘citizen engagement’. Together, these results provide full support for H1, H2, H3, H4 and H5. In addition,  responder  sex  was  insignificant  with  a  standardized  coefficient  of  (β 21=0.08)  and  therefore  gender  does  not  affect the Perceived Usefulness (see Figure 1). Therefore, our results did not indicate any significant effects of  gender on Perceived Usefulness and although there was a positive correlation in Figure 1 it was not significant.  It would appear that neither females nor males favour or appreciate the benefits of technology.  Gender

.08ns

.53***

R2= .28 Perceived usefulness

.28***

Perceived ease of  use

R2= .74 Satisfaction

.71***

.86***

.86*** R2= .74

R2 =.81 Attitude

Citizen engagement

Theoretical Model (TM): χ2/d.f= 2.09; CFI=.93; IFI=.93; PNPI= .79; and RMSEA=.060

Gender

.09ns

.53*** Perceived ease of  use

R2 =.28 Perceived usefulness

.28***

R2 =.73 Satisfaction

.71*** R2 =.81 Attitude

.85***

0.76*** .09ns

Alternative Model (AM): χ2/d.f= 2.47; CFI=.92; IFI=.92; PNPI=.78; and RMSEA=.069 Notes: *** p < 0.01 ns=not significant

Figure 2: Structural models 

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R2=.72 Citizen engagement


Juan‐Gabriel Cegarra‐Navarro et al. 

6. Discussion Relevant  e‐Government  literature  has  emphasised  the  fact  that  citizens  who  use  e‐Government  will  benefit  from the services and consequently be encouraged to adopt e‐Government as a regular method of accessing  and interacting with public services. Therefore, the first contribution of this research is to question the existing  models  which  relate  to  technology  and  citizen  engagement  in  online  e‐Government  services.  This  paper  supports  or  goes  in  the  same  direction  of  previous  studies  in  identifying  the  value  of  TAM  in  the  implementation of e‐Government services (e.g. Davis, 1989; Kim & Chang, 2007; Suki & Ramayah, 2011). The  data indicates that TAM (perceived usefulness, ease of use and attitude) significantly affect user behavioural  intention,  in  our  study  operationalised  as  citizen  engagement,  which  implies  that  the  main  aspects  of  TAM  apply to this context as well. In addition, perceived usefulness was found to be the most significant effect on  attitude, which suggests that a citizen’s belief in usefulness is a decisive antecedent of affective variables (i.e.  attitude and satisfaction), and consequently, of citizen engagement. This is consistent with previous research  which found that perceived usefulness plays a more significant and stronger role than perceived ease of use on  the affective variables (Roca et al., 2006).    The  second  contribution  is  to  extend  the  basic  TAM  towards  the  postcedents  by  adding  the  variables  satisfaction  and  citizen  engagement.  While  many  researchers  have  extended  the  basic  TAM  by  introducing  additional  variables  as  antecedents,  surprisingly  there  are  few  studies  that  deal  with  the  post‐acceptance  process beyond the TAM framework (Kim & Chang, 2007). In this regard, modelling local government websites  acceptance is very useful to local institutions but understanding why citizens build citizen engagement towards  them is crucial. The research model tested provides deeper insights into the process of citizens’ engagement  build‐up.  Satisfaction  was  included  in  the  model  acting  as  a  link  between  TAM  variables  and  citizen  engagement  and  results  indicate  that  a  positive  attitude  towards  e‐Government  services  leads  to  users’  satisfaction.  Hence,  it  is  very  important  to  work  to  get  the  highest  positive  attitude  in  users  by  enhancing  easiness of use and, mainly, perceives usefulness.     The  results  also  support  the  position  that  through  satisfaction  of  citizens,  City  Halls  will  enlarge  citizen  engagement. Thus, City Halls must continuously work at obtain satisfied users to encourage their continuing  using the local government websites. This insight corroborates the notions of Suki and Ramayah (2011), that  the  acceptance  of  e‐Government  services  can  be  explained  in  terms  of  attitude  towards  e‐Government  services. What this means for e‐Government is that when vaguely formed beliefs and attitudes concerning the  system to be implemented have already been developed, these vaguely formed attitudes should be taken into  account if a local government wishes to give a new system fair consideration (Hartwick & Barki, 1994). These  findings support the view of Carter and Belanger (2005), that perceived usefulness has positive and significant  effects on citizens’ continual usage intentions towards e‐Government services. If the utility of e‐Government  websites is understood, then mechanisms can be developed for allowing electronic transactions to occur in a  controlled and constructive way.    The third contribution of this research is to test the TAM in a citizen context. Previous research on the TAM has  mainly been conducted in workplace settings and, in particular, within regional and national contexts (Criado &  Ramilo, 2003; Carter & Belanger, 2005; Badri & Alshare, 2008; Lean et al., 2009). In this type of environment,  people’s  attitudes,  intentions,  and  behaviours,  as  well  as  their  interrelationships  are  likely  to  be  shaped  by  formal authority and directives (Lanseng & Andreassen 2007). This research has empirically supported the core  concepts  of  TAM  in  a  citizen  context,  where  respondents  are  free  to  form  their  own  beliefs,  attitudes,  and  intentions,  as  the  theoretical  foundation  of  the  TAM  assumes.  Thus,  the  results  contribute  to  the  general  validity of the model. We think that this is an important finding, as potential for any City Hall to implement e‐ Government  services  will  depend  substantially  on  its  ability  to  support  these  dimensions,  thus,  public  administrators may be over‐investing in the implementation of e‐Government services, and under‐investing in  (or underestimating) mechanisms and aspects to coordinate them. Put another way, since the population has  different levels of technology readiness, reliable, user‐friendly services, with good user interface consistency,  should be designed. In addition, services should be pre‐tested thoroughly and sufficiently across a wide range  of users to see if they actually have been designed to be easy to use by the average user. By failing to do so,  implementation may prove unsuccessful and more resources may be spent than saved (Lanseng & Andreassen,  2007).   

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Juan‐Gabriel Cegarra‐Navarro et al.  This study has some limitations. Firstly, although the constructs have been defined as precisely as possible by  reference to the literature and validated by practitioners, they can realistically only be regarded as proxies for  an  underlying  phenomena  that  in  themselves  not  fully  measurable.  Secondly,  only  a  single  research  methodology was employed and further research through interviews and observational case studies could be  undertaken for triangulation. Thirdly, any extrapolation of the conclusions might not be generalisable beyond  the  sample frame,  which  could  be  addressed  by cross‐sector  and  cross‐cultural  studies.  Finally,  we assumed  that use of e‐Government was similar for different actors and participants, and that therefore their assessment  could be done in the same way as evaluating electronic online services. In other words we do not include the  possibility  of  actors  and  participants  being  able  to  consider  alternative  uses  of  services  available  to  them.  Therefore, this assumption should be reviewed and explored further and might involve actors and participants  whose concerns and interests might differ from ours.     Taking  into  account  this  limitation,  it  would  also  be  interesting  to  extend  the  survey  to  different  actors  and  participants, since they might have a different level of knowledge concerning computers and technology tools,  and finally, despite most City Halls in Spain having internet access, there is a lack of awareness of the existence  and/or value of e‐Government services to citizens’ engagement, and this provides an opportunity for further  research.  In  order  to  ensure  that  future  research  is  more  accurate  and  reliable,  studies  should  be  based  on  more  than  the  four  variables  used  here  as  citizen  engagement  is  affected  by  many  factors.  This  is  because  these four variables cannot fully explain the factors influencing citizens’ acceptance of e‐Government services.  Consequently, future findings might be inconclusive. E‐Government will continue to be an important topic to  monitor, as it will dramatically affect the life of the individual citizen and their governments on a global scale. 

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A Context‐Aware Architecture for the Management of Laundry  Business Processes  Ufuk Celikkan and Kaan Kurtel  Department of Software Engineering, Izmir University of Economics, Izmir, Turkey  ufuk.celikkan@ieu.edu.tr  kaan.kurtel@ieu.edu.tr    Abstract: Business processes capture the experiences, insights and the knowledge of how a company conducts its business.  Because this knowledge is embodied in business processes, it is important that this knowledge is managed effectively and  efficiently  by  the  business  to  reach  its  goals.  While,  business  processes  are  essential  in  understanding  how  businesses  operate, they also play a major role in how information technology is used in the implementation of information systems.  Therefore, Business Process Management Systems have been developed to identify, understand, manage and coordinate  business  processes.  The  need  for  management  software  have  had  an  effect  on  the  role  of  software  architects,  who  are  becoming more involved in developing business process, in addition to their traditional role of describing the software. In  this  paper,  the  authors  propose  a  conceptual  Laundry  Management  System  solution  and  architectural  framework  to  monitor and autonomously manage the laundry process. The washing of laundry on an industrial scale has become highly  automated, carried out by machines using sensors generating very detailed data. Data from these sensors allow the precise  control  of  the  laundry  operation,  often  remotely.  The  combination  of  new  machines  with  information  technology  has  created a more efficient and cost effective process which requires software based on extensible architecture. Our proposal  for such a system incorporates the features of a context aware architecture since the operations of a laundry exhibit the  properties of a typical context‐aware system. The laundry context data is classified and categorized as being primary and  secondary.  Primary  context  types  are  further  categorized  as  location  (where),  identity  (who),  time  (when)  and  activity  (what).  The  context  modeling  is  based  on  ontology,  as  this  is  the  most  expressive  model.  The  system  defines  clear  boundaries among data acquisition, data management and the business logic which are encapsulated in their respective  layers. The system employs an inference and a workflow engine which conveys the overall status of the system to the user  through  a  convenient  user  interface.  The  proposed  architecture  is  based  on  Service  Oriented  Architecture.  The  business  oriented functionality and business rules are captured as a service for to be used by the system components internally and  by  the  customers  externally.  Moreover,  the  use  of  web  services  eliminates  the  tight  coupling  between  subsystem  components. Weak coupling supports flexibility and reusability. Using service‐oriented architectures to integrate and unify  various  departments  within  a  laundry  business  is  also  very  straightforward.  For  instance,  the  logistics  department  can  easily discover whether an item is ready to be shipped or the finance department can have very detailed report on the cost  of the resources used to clean a particular garment.    Keywords: business process management, context‐aware systems, laundry management system, service oriented  architecture, web services 

1. Introduction Information  technology  is  becoming  an  integral  part  of  every  business.  As  a  result,  software  architects  no  longer only describe what the software does, but also all the processes connected with the business (Weske,  2007). Business processes and rules together describe the business and they continuously change to adapt the  business  to  meet  the  demands  of  today’s  challenges.  Business  Process  Management  (BPM)  identifies  understands  and  manages  the  business  processes  and  aligns  customer  needs  with  the  business  goals  while  business  rules  formally  specifies  ways  of  connecting policies  and  constraints  of  an  enterprise  to  information  systems  (Debevoise,  2007).  Linkage  of  business  processes  to  business  rules  is  instrumental  in  implementing  business  intentions  in  business  processes  and  information  systems  (Fedlkamp  et  al.,  2007).  The  IT  that  supports a  business  must  work  seamlessly  with  the  business  objectives  and,  therefore  must  be  cognizant  of  the changes happening in the environment, and deal appropriately with changes in the processes and rules. A  context aware architecture applied to Business Process Management provides the agility needed.    The  operation  of  a  laundry  service  is  similar  to  any  other  business  in  the  sense  that  it  consists  of  many  different processes. The management of these processes is crucial to the efficient and effective operation of a  business.  A  Laundry  Management  System  (LMS)  has  the  primary  task  of  monitoring  and  optimizing  laundry  processes in order to increase customer satisfaction and business productivity, and to ensure that operational,  tactical  and  strategic  management  decisions  are  accurate,  consistent  and  timely  at  every  level.  Information  Technology  plays  an  important  role  in  achieving  this  goal.  A  laundry  business  that  aligns  its  processes 

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Ufuk Celikkan and Kaan Kurtel  seamlessly  using  information  technology  can  implement  a  sustainable  profit  model,  ensure  customer  satisfaction, and create and maintain its competitive advantage.    This paper presents a conceptual software solution and proposes an architectural framework for the features  and services of an industrial laundry service, based on the notion of context‐awareness. Unlike the traditional  application areas of context aware computing such as human computer interaction and mobile computing, the  methodology  used  in  this  study  will  be  a  process  oriented  approach  applied  to  the  domain  of  laundry.  One  objective of the system is to manage context according to the relationships among processes (Rosemann and  Receker, 2006), in this case laundry processes, instead of managing context according to the individual user or  system. The context aware system will oversee the progress of the whole transaction as it moves through each  process. The system is based on the features suggested by Dey and Abowd (2000) and can be summarized as  such:  information  and  services  are  presented  to  a  user,  a  service  is  executed  and  context  is  linked  to  information  for  later  retrieval.  Therefore,  another  objective  of  the  proposed  context  aware  system  is  to  provide  services  taking  into  account  the  needs  of  users  or  other  entities  in  the  system  by  exploiting  information  provided  in  the  context.  This  objective  can  be  most  effectively  provided  by  a  Service  Oriented  Architecture  based  on  web  services  augmented  with  context  awareness.  This  combines  the  advantages  of  flexibility and robustness of web services and context aware systems (Gu et al., 2004).    The rest of the paper is organized as follows. Section 2 includes an overview of the systems based on context‐ aware features and other Laundry Management System. In Section 3, the authors describe laundry operations  from  a  process  point  of  view.  Section  4  presents  the  technical  architecture  and  our  design  of  a  proposed  laundry management system based on context‐aware service‐oriented architecture. The authors also suggest  in  this  section  some  open  source  tools  that  could  potentially  be  used  in  the  implementation  of  the  system.  Finally, Section 5 draws some conclusions about the proposed system. 

2. Literature review  Context‐aware systems are highly adaptive systems that react to the ever‐changing context by adjusting their  operations without needing an explicit intervention from the user. Several architectures and design principles  are  proposed  for  the  implementation  of  context‐aware  applications.  One  common  underlying  principle  that  governs  a  good  context‐aware  architecture  is  the  separation  of  context  acquisition  and  context  use.  This  is  mostly achieved by employing a layered approach that uses encapsulation to hide the details of lower layers  from higher layers. With this layered approach, it is possible to separate the functions of business logic from  user  interface  and  data  acquisition.  Rehman  et  al.  (2007)  has  proposed  a  system  based  on  Model‐View‐ Controller  paradigm  while  the  conceptual  architecture  for  context‐aware  systems  proposed  by  Ailisto  et  al.  (2002)  and  shared  by  others  consisted  of  five  different  layers:  physical,  data  acquisition,  inference,  storage/management  and  application.  Even  though  such  architecture  is  robust  enough,  it  must  be  complemented by a flexible and extensible context model for representing and storing context data so as to  facilitate  the  processing  and  exchange  of  the  widest  possible  spectrum  of  context  by  intra  and  inter  applications.  Therefore,  choosing  the  right  context  model  is  paramount  to  the  effective  development  and  maintenance of the context‐aware application. Several context modeling approaches have been proposed and  discussed  in  (Strang  and  Linnhoff‐Popien,  2004)  and  (Perttunen  et  al.,  2009).  Among  these,  ontology  based  models are the most expressive in terms of simplicity, flexibility, and extensibility, while being generic.    Context‐aware Architectures (CA) have a wide area of application domains. There have been implementations  using  CA  in  a  diverse  range  of  other  domains.  The  majority  of  these  are  in  the  mobile  computing  segment  which involves mobile computing agents, in particular, handheld devices. Baldauf et al. (2007) and Hong et al.  (2009)  reviewed  of  context‐aware  systems  literature  in  detail.  These  studies  pointed  out  many  types  of  context‐aware  applications,  including  the  creation  of  smart  environments  such  as  home,  hospital  (Munõz  et  al., 2003), class room and tourism (Abowd et al., 1997). The Hong et al. (2009) study also lists context‐aware  applications in the areas of information systems, decision support systems, communication systems and web  service. Truong and Dustdar (2009) surveyed several systems from the web services arena and Miraoui et al.  (2008) surveyed context aware architectures in pervasive computing environments. As far as the authors are  aware,  there  are  no  laundry  management  system  implementation  proposals  based  on  the  principles  of  context‐aware architectures in the literature. The existing laundry system implementations do not address the  entire process in a complete way but focus on specific aspects. Lu and Yu (2010) and Lu et al. (2010) proposed  software  design  that  uses  Radio  Frequency  Identification  (RFID)  technology  to  track  to‐be‐cleaned  items 

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Ufuk Celikkan and Kaan Kurtel  between the laundry shop and the factory but does not account for the processes that take place within the  factory itself. Tajima et al. (2011) and Van et al. (2012) proposed tracking laundry items using clothes hangers.  The  study  by  Noor  et  al.,  (2012)  proposed  a  “smart  basket”  system  as  an  alternative  solution  in  order  to  optimize the management of electrical and water consumption in domestic laundry activities. 

3. Laundry processes   This section describes the operations of a laundry from a business processes perspective in order to reveal the  fundamental business functions and services. Business processes are supported by technical operations which  are  carried  out  by  the  technical  architectural  framework  based  on  information  technology.  The  Laundry  Management System technical architecture is presented in Section 4.    The core laundry business processes typically contains four major activities and shown in Figure 1:  ƒ

Collection and Transportation 

ƒ

Administration/Back Office operations 

ƒ

Scheduling

ƒ

Cleaning

Figure 1: The workflow of laundry management system (authors’ work, 2013)  Collection and Transportation: This sequence includes the collection of laundry to be washed, transportation  to factory and returned to customer to an agreed schedule. Collection requires some attention as certain items  need to be treated separately due to having different conditions (i.e. soil type). It is important that linens and  bedding used in surgical operations are processed separately from other laundry at every stage.    Administrative: Administrative process mostly involves managerial and administrative activities pertaining to  taking  orders,  controlling  cost,  packaging,  billing  and  other  kinds  of  customer  services.  Controlling  costs  therefore increasing profits is the primary goal of a company’s financial affairs. Correct pricing of the laundry  services,  minimizing  personnel  and  material  costs  is  vital  to  maintaining  a  healthy  financial  position.  An  effective cost control is achieved when cooperation among the aforementioned four processes is enhanced.  For example, the amount and type of detergent used in the cleaning process and delivery routes used during  transportation process both directly affect the costs.    Scheduling: Scheduling operations include the scheduling of collection, delivery, and cleaning.    Cleaning: The cleaning process stands at the core of a laundry business; therefore, it needs a high degree of  control and monitoring. An efficient cleaning process is a highly complex operation, with different rules and  parameters  used  depending  on  the  industry.  For  instance,  for  the  health  industry  the  World  Health 

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Ufuk Celikkan and Kaan Kurtel  Organization  strictly  defines  in  their  web  site  (2013)  laundry  disinfection  rules  for  severe  acute  respiratory  syndrome  (SARS)  since  contamination  by  blood,  body  fluids,  secretions  and  excretions  are  primarily  responsible for its spread. Another complicating factor is the use of different commercial laundry equipment  and  industrial  machines  in  this  process.  Activities  in  the  cleaning  process  are  carried  out  either  by  these  sophisticated  machines  or  by  humans,  or  in  some  cases,  a  combination  of  both.  The  overall  success  of  operation  depends  on  accurate  and  timely  functioning  of  the  whole  operation,  which  can  be  enhanced  by  innovative  and  well  designed  information  technology  services  such  as  RFID  and  rule‐based  workflow  management. 

4. Technical architecture  A layered architectural model is used in the realization of the Laundry Management System. One of the key  advantages  of  a  layered  architecture  is  that  it  partitions  the  system  into  functionally  disjoint  layers,  each  of  which provides a set of cohesive services through a public interface. Our layered model is shown in Figure 2  and explained below. Physical layer consists of virtual and physical sensors which generate aggregate data that  is  more  accurate  and  relevant  than  information  obtained  from  a  single  source.  Physical  sensors  capture  the  state  of  the  cleaning  process  and  report  machine  status  in  the  form  of  raw  data  via  some  communication  mechanism (PLC, IP‐based). Virtual sensors (the external data sources) use Application Programming Interfaces  or  web  services  to  obtain  data  such  as  GPS  position  or  real‐time  camera  stream.  The  next  layer‐  data  acquisition  layer  is  responsible  for  storing  application  and  context  data,  user  profile  and  the  rules  in  a  database. The application data represent business oriented operational data. This layer retrieves context data  from external sources using web services, combines data from different atomic data sources into higher level  information  and  stores  it  in  the  database.  Context  data  is  represented  in  Resource  Description  Framework  (RDF)  (RDF,  2013)  and  processed  using  Jena  (Apache  Jena,  2013).  The  inference  layer  provides  the  central  coordination of the processes through its workflow engine and makes deductions and inferences via its rule  engine  using  the  information  stored  in  the  database.  The  open  source  jBoss  technologies,  Drools  (Drools,  2013)  and  jBoss  business  process  management  workflow  engine,  jBPM  (JBPM,  2013)  are  two  promising  candidates in the implementation due to their availability at no cost, their programming support and editorial  tools  for  non‐technical  users.  The  top  layer  ‐  presentation  layer‐  represents  the  user  interface  and  the  navigational elements of the system. The users interact with the system using services of this layer. 

Figure 2: Context‐aware architecture for the laundry management system (authors’ work, 2013) 

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4.1 Context model  Based  on  the  definition  by  Dey  (2001),  the  content  included  in  the  context  can  vary.  In  the  case  of  laundry  domain, context could include information such as collection time, identification tags, the location and weight  of the items, washer temperature, the type and amount of detergent used, the wash duration, and the cost.  The  accurate  specification  of  the  contents  of  the  laundry  domain  context  requires  a  flexible,  extensible,  generic and rich enough model that allows the easy definition and manipulation of context data. The authors  shall  follow  the  two‐tier  taxonomy  introduced by  Dey  et  al.  (2000)  in our  context classification.  The  context  types  will  be  classified  as  primary  or  secondary.  The  primary  context  types,  those  that  are  marked  as  being  more  important,  are  location  (where),  identity  (who),  time  (when)  and  activity  (what).The  other  piece  of  context  information,  i.e.  secondary  type,  are  attributes  of  the  primary  types,  and  therefore  each  secondary  type  can  be  indexed  to  a  primary  type.  Table  1  provides  a  list  of  attributes  that  are  included  in  context  information for a washing machine and the sources of these attribute values. Ontology will be used to model  contextual data of LMS. Ontology based context models possess several desired properties such as formality  and  extensibility  (Strang  and  Linnhoff‐Popien,  2004),  (Perttunen  et  al.,  2009),  (Gruber,  1993),  (Studer  et  al.,  1998).  The  formality  of  ontology  based  modeling  makes  it  suitable  for  formal  reasoning  techniques  and  extensibility is of particular importance for a domain such as the Laundry Management System, because the  addition  of  new  context  elements  must  be  simple.  Although  designed  for  the  semantic  web,  Web  Ontology  Language (OWL) can be used to represent information which cannot be retrieved from the web, so has been  chosen to represent our context (2013). Web Ontology Language is intended to be used when information is  processed by the applications rather than presented to the humans.  Table 1: Laundry context data and types  Primary  Context  Types  Identity  Identity 

Secondary Context Type  (Attributes)  Type of laundry  Material 

Identity Activity  Activity 

Color Temperature  pH value 

Activity

Water Hardness 

Location Identity 

Location Number of times  washed  Time 

Time

Description

Data source 

Medical, hospitality, community  Represents the type of the laundry’s material, such  as fiber, cotton, and silk  Color of the article. i.e. white/non‐white  Water temperature  Monitoring pH value that withstands the acids and  caustic solutions  Amount of Calcium and Magnesium cations (Ca2+  and Mg2+)  Represents the location of garments  Total number of times an article was washed 

Manuel, Barcode, RFID  Manual 

The amount of time spent on the different phases  of the cleaning process 

Clock

Color Sensor  Thermometer  pH Sensor  Hardness Sensor  RFID & Barcode  RFID 

4.2 Service based context interpretation and inference  A laundry management system is composed of several processes which can be categorized as information and  business  processes.  Business  processes  are  driven  by  business  rules  which  create  a  set  of  guidelines  for  the  business  process  and  are  expressed  in  some  formal  or  informal  notation.  On  the  other  hand  information  processes  manage  the  information  flow.  Both  information  and  business  processes  are  driven  by  a  workflow  engine,  which  oversees  the  progress  of  a  complete  laundry  transaction  as  it  progress  from  one  process  to  another.  The  business  rules  are  interpreted  by  a  rules  engine  which  in  turn  guides  the  workflow  engine.  All  these components exchange information using web services. The rules engine which itself a web service, uses  the  data  obtained  from  context  sources  through  web  services  and  while  the  workflow  engine  is  able  to  accesses services of the rules engine through a web service. The context data is represented in RDF which can  easily  be  processed  by  applications.  The  use  of  web  services  decouples  the  laundry  business  logic  from  information and business processes. As business rules are loosely connected to the architecture through web  services,  it  is  possible  to  completely  change  the  business  rules  and  the  rules  engine  without  affecting  the  business processes. In the web service model, the rule engine acts like web service server, with the business  process as the client. The business process will interact with the rules engine using solicit‐response port type.  Figure 3 shows the interaction between the business process and the rule engine.    

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Figure 3: Web service interaction (authors’ work, 2013)  The business rule engine consumes the data and performs the computations, comparisons and controls, and  finally returns a value. The advantage of using such a model is that it allows the modification of the computer  program,  the  port  and  the  operation  calls  without  requiring  any  changes  to  the  client‐business  process.  Workflow  will  invoke  a  rule  on  the  rules  engine  using  a  web  service  and  change  the  flow  based  on  the  response. When a business rule changes or an addition is needed, only the rule engine and web service needs  to be modified. In addition, the workflow engine can invoke a web service to request a piece of context data  such as the pH value of the water in order to choose the most appropriate path in the flow. Workflow engine  orchestrates the processes of the LMS by creating tasks and dividing them into subtasks. The workflow engine  then  sequences,  schedules  routes  and  monitors  these  tasks.  The  data  acquired  from  context  sources  asynchronously  generates  events  which  are  processed  by  the  workflow  engine.  The  workflow  engine  could  also trigger data collection synchronously, for example by requesting the location of a garment or pH value of  the  water  using  a  web  service.  The  workflow  specifies  how  the  available  tasks  are  utilized  in  response  to  events. The graphical user interface interacts with the workflow engine to query the state of a process, and if  necessary,  to  alter  the  flow.  In  order  to  change  path  in  its  flow,  to  start  or  terminate  a  task,  the  workflow  engine relies on the rules engine, which creates a deductive connection between the business rules and the  workflow engine. Figure 4 demonstrates how the workflow and rules engine act as a controller coordinating  various subsystems using web services. 

Figure 4: System‐wide process view of the laundry management system (authors’ work, 2013) 

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5. Discussion   The proposal in this paper concentrates more on the relationships and interactions among processes. Laundry  management  system  can  be  partitioned  into  two  major  processes:  business  and  information  processes.  The  former  are  driven  by  the  business  rules  and  the  latter  are  driven  by  the  information  technology.  These  are  further  decomposed  into  sub  processes.  Web  services  allow  two  aspects  to  be  decoupled,  first  business  processes using workflows from business rules, and secondly, context data providers from the rules engine. A  context‐aware laundry system can monitor and alter the cleaning process using the context information and  the use of service‐oriented architecture makes the integration and unification of various departments within a  laundry  business  very  straightforward.  In  order  to  illustrate  the  functioning  and  practical  benefits  of  the  system,  we  present  a  context‐aware  scenario  below.  This  scenario  demonstrates  how  the  proposed  system  would be beneficial to a preferred hotel customer, who wants his laundry done at the hotel.  “Mr. Jones is a very special, cost conscious customer with some allergic reactions to pathogens in  fabric. A five star hotel does not want to lose the business of Mr. Jones. Therefore, the hotel does  everything  within  their  capacity  to  fulfill  the  laundry  requirement  to  his  satisfaction.  When  the  hotel picks up Mr. Jones’ laundry or when they replace the bedding and towels in his room, they  ensure that the laundry process is based on strict guidelines. Moreover, they want to make sure  that his laundry is delivered to him exactly on time and within the agreed cost requirements.”  This  scenario  shows  the  kind  of  context  information  that  must  be  taken  into  account  by  the  Laundry  Management System. The context information in the scenario is given in italics below. The system attaches an  RFID tag to Mr. Jones’ laundry items to inform LMS that items in the laundry process belong to Mr. Jones, and  sets the parameters for the cleaning process. The system uses a special kind of cleaning agent that requires a  particular  temperature  range.  The  drying  process  is  done  using  outside  air  instead  of  the  dryer.  When  the  process is finished the items are specially sealed and delivered to Mr. Jones at the exact time requested. As a  special customer, he is charged a special discounted price. A context‐aware laundry system can monitor and  alter the cleaning process using the context information for Mr. Jones, which, in this scenario consists of item  ids (RFID tag), detergent type, temperature, drying conditions (circulating air at room temperature), time, and  cost. The flexibility of the system allows other context information to be added. For instance, if Mr. Jones does  not want to use bedding and towels that are washed more than three times, this requirement can easily be  incorporated  by  adding  another  piece  of  attribute  into  the  context,  namely  the  number  of  times  an  item  washed.  Using  a  service‐oriented  architecture  based  on  web  services,  the  operator  can  constantly  and  remotely  monitor  the  process,  obtain  the  status  of  items  associated  with  Mr.  Jones  and  intervene  to  the  process if necessary. The proposed layered architecture is modular, extensible, and cohesive. The use of web  services provide the highest degree of decoupling of system components and the agility needed in the current  IT environment. 

6. Conclusion   This research paper is a conceptual paper that proposes a laundry management system solution based on the  principles  of  context‐aware  and  service‐oriented  architectures  in  which  context  acquisition  is  done  through  web services and context modeling is ontology‐based, as this is the most expressive model. The advantage of  using a service‐oriented context‐aware architecture is that the integration of the Laundry Management System  with  the  partners  is  seamless.  The  proposed  system  allows  the  convenient  integration  of  information  technology  infrastructure  of  hotels,  hospitals  or  other  businesses  using  cleaning  services  with  an  industrial  cleaning  system.  Using  service‐oriented  architectures  to  integrate  and  unify  various  departments  within  a  laundry  business  is  also  very  straightforward.  The  logistics  department,  for  instance,  can  easily  discover  whether an item is ready to be shipped or the finance department can have very detailed report on the cost of  the resources used to clean a particular garment. Controlling costs therefore increasing profits is the primary  goal of a company’s financial affairs. Correct pricing of the laundry services, minimizing personnel and material  costs  is  vital  to  maintaining  a  healthy  financial  position.  As  a  further  stage,  the  authors  are  planning  to  implement this infrastructure using open source software and deploy it in a real environment. 

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Modeling Organizational Intelligence Based on Knowledge Management in the Technical and Vocational Training Organization of Tehran Hossein Chenari, Fattah Nazem and Mahmood Safari Department of Education, Roudehen Branch, Islamic Azad University, Roudehen, Iran hossein_chenari@yahoo.com safari@damavand.riau.ac.ir

Abstract: The dire necessity of organizational intelligence is undeniable with regard to the importance of organizational intelligence in the Technical and Vocational Training Organization. In the other hand the effective factor leading to the organizations’ success does not only include capital, human force and raw material, whereas, it critically depends on the organization’s potential in producing the knowledge among the staff (Tanghoo, 2008). The research purpose is to construct a structural model to assess the organizational intelligence in the Technical and Vocational Training Organization of Tehran based on knowledge management. The population comprised all the employees of the Technical and Vocational Training Organization, out of which a sample of 226 employees was randomly chosen. The research instruments were two questionnaires which were administered in the Technical and Vocational Training Organization: Albrecht (2003) organizational intelligence questionnaire which consisted of 49 items with three underlying constructs of srategic vision, shared fate, appetite for change, heart, alignment and congruence, knowledge deployment and performance pressure with Cronbach’s Alpha of 0.88, and Sallis & Jones’ (2002) knowledge management questionnaire which consisted of 42 items with ten underlying constructs of vsion and mission, strategy, organizational culture, intellectual capital, learning organization, leadership and management, teamwork and learning communities, sharing knowledge, knowledge creation and digital sophistication for the organization with Cronbach’s Alpha of 0.83. The results of path analysis using LISREL software indicated that dimensions of knowledge management had a direct effect on organizational intelligence with the indices of 0.93. The model also showed that the factor of intellectual capital, leadership and management in knowledge management had the highest direct effect on organizational intelligence. It was also concluded that the proposed model appeared to be fully workable. Keywords: Knowledge management, organizational intelligence, Technical and Vocational Training Organization

1. Introduction One of roles of present era for the management and employees in an organization is intelligence. Also, the management and employees try to apply human capital and organizational capital for developed efficiency and effectiveness in their organization. Therefore, these goals will not be available unless all of them in the organization use intellectual capital as optimum. Most chief executive officers feel that knowledge is the most critical asset of their organization. In today’s movement, towards knowledge management, organizations try to leverage their knowledge internally in the organization and externally to their customers and shareholders. They try to capitalize on their organizational intelligence to maintain in the edge (Liebowitz, 1999). As a fascinating concept and intriguing research area, “intelligence” finds strong appeal in many disciplines outside of individuals and cognitive psychology (Sternberg & Kaufman, 1998). One of the disciplines that provoked increased interest in the importance of intelligence is the management and organization development literature (Glynn, 1996; March, 1999; Stalinski, 2004). Even if we disregard the entire literature in which organizational intelligence was supposedly aggregated (Kurzman & Owens, 2002), the term is still ambiguous in the context of organizational development scholarship. This is true because there is a lack of a unified theory of intelligence in organizational settings as noted by the numerous and fragmented perspectives and ideas of researchers in the field (Glynn, 1996). Albrecht (2003) designed a modal that Includes Seven Key dimensions of organizational intelligence (OI): 

Strategic Vision: strategic vision refers to the capacity to create evolve, and express the purpose of the enterprise and not to any particular vision, strategy, or mission concept in and of itself .

Shared Fate: a sense as “We're all in the same boat” creates a powerful sense of community and esprit de corps. Without a sense of shared fate, the psychological tone of the culture degenerates into a "Look out for number one" spirit.

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Appetite for Change: Some organizational cultures, usually led by their executive teams, have become so firmly set in their ways of operating, thinking, and reacting to the environment that change represents a form of psychological discomfort or even distress.

Heart: Separate from the element of shared fate, the element of heart involves the willingness to give more than the standard.

Alignment and Congruence: In the intelligent organization the system, broadly defined, all come together to enable the people to achieve the mission .

Knowledge Deployment: Knowledge deployment deals with the capacity of the culture to make use of its valuable intellectual and informational resources.

Performance Pressure: It's not enough for executives and managers to be preoccupied with the performance of the enterprise, i.e. its achievement of identified strategic objectives and tactical outcomes. In the intelligent organization, everyone owns the performance proposition, i.e. the sense of what has to be achieved and the belief in the validity of its aims (Albrecht, 2003).

Having an efficient and thriving educational organization triggering appropriate opportunity to develop and flourish students is an important issue which occupied the mind of planners and scholars (Mac Gilchrist, 2004). Notably, nowadays organizations encounter rapid and astonishing changes and their survival depends on the ability to adapt to changes. Flexibility, ability to adapt, and enjoyment of individuals and organizational ability to utilize the experiences are most important in strategies of organizations. As changes are rapidly occurring, survival and function of an organization depends on accelerating learning and developing knowledge management (Stonehouse & Pemberton, 1999). Although efficient application of the knowledge leads to formation of intelligent organizations, it rests on creative application of knowledge. Thus, educational organizations should simultaneously instruct knowledge, efficiency, and utilizing knowledge to the students to strengthen their potential talents. Organizational intelligence, therefore, is the most important ability to realize it. The necessity of organizational intelligence is undeniable with regard to the importance of organizational intelligence in the Technical and Vocational Training Organization. Hence, knowledge management takes on a pivotal role as an important resource in creating the competitive advantage. The effective factor leading to the organizations’ success does not only include capital, human force and raw material, whereas, it critically depends on the organization’s potential in producing the knowledge among the staff (Tsang ho, 2008). Organizations are bound to create an environment in which requiring, transferring and advancing the knowledge is facilitated among the staff members through enhancing the pattern of meaningful interactions (Nonaka, &Takeuchi, 1995). Sallis & Jones (2002) offer a useful knowledge management self-assessment checklist with scoring elements such as: 

Vision and mission: It refers to having vision as a knowledge-based organization and sharing it with the stakeholders and the mission as the knowledge creator and translating it into practical strategies.

Strategy: It refers to developing modeled scenarios and applying them in the management.

Organizational culture: It refers to the different dimensions of culture including the creating, centralizing, sharing, and recognizing organizational culture as a key competence.

Intellectual capital: It includes recognizing the value of intellectual assets and codifying its tacit knowledge.

Learning organization: Under learning organization, organization should create continuous learning, define skills to create new knowledge, recognize EQ and its influences encourage creative thinking, and promote action learning both for individuals and teams.

Leadership and management: In leadership and management, organizations are required to have seniormanagement support, have knowledge leaders and managers with appropriate leadership styles, and develop strategies for promoting middle-managers.

Teamwork and learning communities: Under teamwork and learning communities, organization should encourage learning communities and knowledge teams, establish trust, and recognize the need for intellectual autonomy.

Sharing knowledge: It signifies that organizations ought to collect, record major organization events, and share new information, and understand competitors’ knowledge management system.

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Knowledge creation: It requires the organizations to recognize new knowledge, those known as experts, and turn it into service.

Digital sophistication for the organization: In terms of digital sophistication, organizations are to develop technologies among its employees by clear technological architecture, enhancing its knowledge, and devising virtual collaborative systems and/or communities. (p.125-129 )

Aliei and Bahrololoum (2011), in a research entitled “Analysis of Knowledge Management and Organizational Intelligence Relationships in Science and Technology Parks” show that organizational intelligence involves emotional, behavioral, and cognitive dimensions. The results suggest that it is not necessary for organizations to focus on the all dimensions, but the main concern should be based on the importance and performance of the knowledge management factors. Therefore, considering the efficiency of information systems and the senior manager’s commitment to the principles of knowledge management, achievement is provided in the short run for organizations. Competitive advantage has been shown increasingly to rely on the effective management of knowledge (Bukowitz & Petrash, 1997; Stewart, 1997). This is particularly relevant for multinational firms, which may adapt not only the organizational structure of the subsidiary to the host country, but also its knowledge management practices in expanding abroad. Indeed, Drucker et al. (1997) have identified ‘‘harnessing the intelligence and spirit of people at all levels of an organization to continually build and share knowledge’’ as a top priority for firms wishing to succeed in today’s competitive environment (Chow et al., 2000). A prevailing perspective of knowledge management is the knowledge management value-chain common to many knowledge management descriptions (Shin et al., 2001; Dalkir, 2005; Chen & Chen, 2006). The four stages of knowledge acquisition, storage/sharing, diffusion, and application, although not necessarily sequential, are required to achieve the efficiency function of knowledge management within the organization (Alavi & Leidner, 1999; Drucker, 2001). As such, the two goals of knowledge management are productivity gains through efficient decision making and problem solving, and innovation by way of bringing a new idea to market (Hollsopple & Joshi, 2000). A previous thorough literature review of the history of knowledge management evolution from 1995 to 2004 (Chen & Chen, 2006) has showed that indeed the knowledge management process is similar to that of a value-chain. According to Chen and Chen (2006), ‘‘the basic underlying assumption is that knowledge may be viewed from a unified perspective as it circulates in the organization creating knowledge assets and influences the performance of the organization’’ (p. 18). Organizational intelligence is a new and important topic in organizational behavior and development scholarship. However, researchers should also investigate organizational intelligence empirically. The multidimensional and multifaceted nature of organizational intelligence can be tested by operationalizing information-processing capabilities, emotional capabilities and adaptive capabilities (Keskin et al, 2006). Mendolson et al, (2007), in their study, showed that organizational intelligence has a strong impact on the financial performance of organizations. Organizations with high organizational intelligence have gained more profit and progress. And also, they have captured external information, and ensured that the right decisions are made in these organizations. Mendolson (1999) mentions that “Organizational intelligence has a strong effect on a company’s performance.” The study of Sattari Ghahfarrokhi (2008) is consistent with the present research, demonstrating that there are positive and significant relationship between knowledge management and organizational intelligence. The results of the research demonstrate how the types of customer knowledge available to an organization can be categorized by the perceived quality and the perceived accessibility of the knowledge. These findings contribute to the field of knowledge management by moving towards a theory of how customer knowledge is used by an organization, and how internal and external factors affect this utilization. Furthermore, this study raises awareness of the importance of a KMS in managing customer knowledge, including key aspects of its design and implementation (Paquette, 2008).

2. Purpose of the study The duty of the Technical and Vocational Training Organization of Tehran is to provide the technical workers with necessary training they need in order to work in industrial factories . Because these training centers cover many areas in the whole country, the results of the present study can yield fruitful outcomes.

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Hossein Chenari, Fattah Nazem and Mahmood Safari The purpose of the research is to construct a structural model to assess organizational intelligence in the Technical and Vocational Training Organization of Tehran based on the knowledge management. Regarding the purpose of the research, the researcher tries to answer the following questions:

3. Research questions 

What is the structural model of organizational intelligence based on the knowledge management in the Technical and Vocational Training Organization?

Which variable has the highest effectiveness on organizational intelligence?

How is organizational intelligence knowledge management effective on promoting organizational intelligence?

How much is the goodness of fit in this study?

4. Method of the study The research methods of the study are: library research to access the theoretical framework and the related literature; and the survey method to collect, classify, describe, and analyze the data. The population under investigation in this study consist of official staff working in 12 administrative districts of the Technical and Vocational Training Organization in Tehran. Regarding the minimum research sample required for the staff’s group, 226 individuals were randomly selected, using simple random sampling method, and the same number of questionnaires were distributed among them. The research instruments were as follows: organizational intelligence which was designed and developed based on the theory of Albrecht (2003). The organizational intelligence questionnaire consisted of 49 items with seven underlying constructs of strategic vsion, shared fate, appetite for change, heart, alignment and congruence, knowledge deployment and performance pressure with Cronbach’s Alpha of 0.88, and Sallis & Jones (2002) knowledge management questionnaire which consisted of 42 items with ten underlying constructs of vision and mission, strategy, organizational culture, intellectual capital, learning organization, leadership and management, teamwork and learning communities, sharing knowledge, knowledge creation and digital sophistication for the organization with Cronbach’s Alpha of 0.83.The results of the study were obtained through applying path analysis using LISREL software (See Fig. 1 for more details).

5. Findings of the study The data collected from the administration of the instruments were analyzed. These data included the different indexes of central tendency, variability and the distribution of staff’s groups, the staff members’ scores obtained from knowledge management and organizational intelligence questionnaires and their related components. The distribution of the staff members’ scores in the given variables had tendency toward normality. As shown in Figure 1, the Lambda rate of external latent variable of knowledge management components was 0.38 for leadership and management, 0.23 for teamwork, 0.12 for sharing knowledge, 0.23 for knowledge creation, 0.29 for digital sophistication, 0.11 for vision and mission, and 0.01 for strategy, 0.08 for organizational culture, 0.39 for intellectual capital, and 0.17 for learning organization whose accumulation form the knowledge management variable with the effectiveness rate of 0.93. It means that 93% of the variation in the dependant variable of intellectual capital, Leadership and management is explained by a collection of these indexes. The variable of collective action indicates the highest amount of internal consistency in the external latent variable. The Lambda rate of internal latent variable of organizational intelligence components was 0.35 for strategic vision, 0.04 for shared fate, 0.27 for appetite for change, 0.41 for heart, 0.22 for alignment and congruence, 0.54 for knowledge deployment , and - 0.03 for Performance Pressure. Their accumulation form the organizational intelligence variable. The validity of variable indicates the highest amount of internal consistency in the internal latent variable. Since the model’s goodness of fit index is 0.92, it can be stated that it has an acceptable fit. The calculated index indicates the direct effect of knowledge management components on employees' organizational intelligence. Moreover, the model shows that the highest direct effect is related to intellectual capital, and Leadership and management. Table1 presents the indexes related to the model’s fit:

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Figure 1: Path analysis model for components of knowledge management and organizational intelligence Table 1: Model’s fit indexes Index Lewis-Tucker (Non-normed fit index) Bentler-Bonett’s (Normed fit index) Hoelter Root Mean Square Error (RMSEA) GFI

Rate 0.92 0.91 0.73 0.042 0.92

Interpretation High fit (more than 0.90) High fit (more than 0.90) High fit (more than 0.70) High fit (equal to or less than 0.05) High fit (more than 0.90)

The goodness of five fit indexes presented model’s fit and empirical data. Therefore, desirability adaptation is provided for the designed model and empirical data and can approve it as an appropriate model for the organizational intelligence. On the whole, it can be proposed that this proposed model has full fit since LewisTucker’s non-normed fit index (0.92) and Bentler-Bonett’s normed fit index (0.91) were both higher than 0.90. Besides, Hoelter’s index (0.73) was higher than 0.70 and shows high fit. The root mean square error (RMSE) (0.042) was lower than 0.05 and goodness of fit (GFI )( 0.92) was higher than 0.90 and indicate the new model’s fit.

6. Discussion and conclusions The results of path analysis method revealed that dimensions of knowledge management have positive impact on organizational intelligence. The findings of the present study, furthermore, indicated the influential role of knowledge management on organizational intelligence. The results of this study are in line with the studies done by (Ordones de Pablos, 2002; Keskin et al., 2006; Choi & Jong, 2010; Yaghoubi et al., 2010). Aliei & Bahrololoum (2011) show that knowledge management involves social, emotional, behavioral, and cognitive dimensions which invest on the two factors contributing to the efficiency of information systems, and the senior manager’s commitment can earn the most achievements in the short run for organizations. An important work of organizations should be to invest on intelligent personnel, so that the organizational operations become more efficient and effective than before. In general, it is inferred that intelligence is an undeniable factor for organization's intellectual capital, because the first condition to each organization to be successful is having intelligence (Yaghoubi et al., 2010). A common thrend in this body of work is that knowledge management processes are positively related to performance. These results have been shown to hold for many performance variables including long term measures such as firm market value (Choi & Jong,

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Hossein Chenari, Fattah Nazem and Mahmood Safari 2010), and other non-financial indicators of performance such as new product launch success and increasing rate of sales (Ordones de Pablos, 2002). As it was mentioned earlier, the unique outcomes of the present study indicate the direct effect of knowledge management components on organizational intelligence in the Technical and Vocational Training Organization of Tehran . Moreover, the model shows that the highest direct effect is related to intellectual capital, and Leadership and management. Moreover, through offering, guaranteeing and expanding the most efficient and superior services to Technical and Vocational Training Organization located in Tehran, and also identifying and fulfilling their needs, their satisfaction can be fulfilled and their loyalty can be engendered. Furthermore, considering the fact that intellectual capital exerts the most principal effect on the organizational intelligence, it can be suggested that in the Technical and Vocational Training Organization: 

Intellectual capitals should be appreciated and used appropriately by organizations;

Organizations should seek tacit knowledge (individual’s aggregate behaviors, experiences, aspirations, values, and feelings);

Existing challenges to the practice of knowledge management should be resolved by people in charge;

Leaders of organizations had better be knowledge leaders who choose appropriate leadership styles to apply, and distribute knowledge;

Some employees of the Technical and Vocational Training Organization should be trained to develop knowledge creation process.

In conclusion, the newly-proposed results in this research that show the direct effect of knowledge management components on organizational intelligence, can be effectively employed to enhance the organizational intelligence in similar organizations. It can be done through strengthening the knowledge management indexes, that is, vsion and mission, strategy, organizational culture, intellectual capital, learning organization, leadership and management, teamwork and learning communities, sharing knowledge, knowledge creation and digital sophistication.

Acknowledgements The researchers want to extend a heart-felt thanks to the members of Technical and Vocational Training Organization for their commitment and efficient research assistance. They are truly appreciated as their partnership was absolutely vital to carry out this research.

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An Introduction to STRIKE: STRuctured Interpretation of the  Knowledge Environment   Sally Eaves and John Walton  Faculty of Arts, Computing, Engineering, and Sciences (ACES), Sheffield Hallam University,  UK  research@sallyeaves.co.uk  J.R.Walton@shu.ac.uk      Abstract: Knowledge forms a critical part of the income generation of the system and the complex environment in which  actors  participate  in  the  creation  of  knowledge  assets  merits  robust,  eclectic  consideration.  STRIKE  ‐  STRuctured  Interpretation  of  the  Knowledge  Environment  affords  an  unobtrusive  and  systematic  framework  to  observe,  record,  evaluate  and  articulate  concrete  and  abstract  elements  of  a  setting,  across  internal  and  external  dimensions.  Inter‐ relationships between actor and environment are preserved. STRIKE is supported by underlying techniques to enrich data  and  enhance  the  authenticity  of  its  representation.  Adoption  of  photography  and  videography tools  provides  illustrative  and  interpretive  benefits  and  facilitates  researcher  reflexivity.  This  structured  approach  to  data  analysis  and  evaluation  mitigates criticisms of methodological rigour in observational research and affords standardisation potential, germane for  application in a verification or longitudinal capacity. Advancing exploratory validation studies, the method is employed to  evaluate the knowledge environments of two enterprises in the UK creative sector. These occupy a critical role in fostering  entrepreneurial  innovation  alongside  participant  self‐efficacy.  Access  Space  in  Sheffield  and  the  Bristol  Hackspace  are  committed to open software, open knowledge and open participation; sharing peer learning, creativity and socio‐technical  aims to address broadly similar community needs. Drawing on Wittgenstein’s Picture Theory of Meaning, the knowledge  management perspective is abstracted from the STRIKE assessment. It is argued that the tiered analytical approach which  considers  a  breadth  of  dimensions  enhances  representation  and  interpretation  of  the  knowledge  environment  and  presents  a  diagnostic  and  prescriptive  capability  to  actualise  change.  The  paper  concludes  by  evaluating  framework  effectiveness, findings application and future direction.     Keywords: knowledge environment; knowledge management; observational framework; workplace design; innovation 

1. Introduction: Knowledge management in praxis  Knowledge  management  is  diverse  in  nature,  difficult  to  demarcate  and  subject  to  multiple  attempts  at  definition. It is broadly considered as formal and informal exploratory, evaluative and synthesising knowledge  interventions (Wiig 1993), undertaken at the level of individual and collective intellectual assets. Approaches  centre on harnessing the organisational knowledge base to support optimal performance through innovation,  reutilisation  and  learning  (Du  Plessis  2007).  Drawing  on  Freitas,  Morais  and  Lopes’  (2012)  literature  analysis  presented  at  ECKM  2012,  knowledge  management  practices  cover  nine  core  areas  ranging  from  innovation  management  to  lessons‐learned,  supported  by  technological  tools.  Mechanisms  to  facilitate  these  practices  are equally broad, spanning fifteen dimensions from learning‐by‐doing to mentoring. Additionally, workplace  design  is  increasingly  recognised  as  a  “strategic  instrument”  (Bakke  2007,  p6)  that  can  support  knowledge  management, particularly collaborative norms and creativity (Walter 2012).      Monitoring  and  evaluating  a  diversity  of  knowledge  management  components  presents  a  critical  challenge  (Hulsebosch,  Turpin  and  Wagenaar  2009).  An  array  of  macro  and  micro  techniques  to  appraise  value  are  available (Perkmann 2002) but can be difficult to align with organisational realities, especially in highly original  settings.  The  rapidly  evolving  and  cross‐disciplinary  creative  sector  is  representative  of  this  problem.  It  lies  incongruent  with  the  information‐processing  or  object‐centred  perspective  associated  with  quantitative  measurement approaches and further, would benefit from new qualitative means to elucidate and appraise its  socio‐technical and place‐centric dimensions. The development of an innovative, flexible and lightweight tool  to  surface,  monitor  and  evaluate  the  knowledge  environment  from  a  holistic  perspective,  illuminating  the  learning and sharing behaviours therein, is therefore considered timely and germane.  

1.1 The creative sector  The definition of a creative industry is nebulous but in this study it reflects the intersection of manufacturing  and  digital  technologies  with  The  Arts,  underpinned  by  a  socially  meaningful  purpose.  The  growth  of  open‐ access workshops, hacklabs, hackerspaces and makerspaces embody this approach, benefiting from the pool  of knowledge afforded by an open source production model. Although terms are often used interchangeably, 

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Sally Eaves and John Walton  different  groups  afford  their  own  specialisation,  ideology  and  historical  roots  (Maxigas  2012).  All  provide  opportunities  for  idea  incubation  and  contagion,  technical  and  social  engagement,  collaboration  and  skill  support.     This  presents  an  underexplored  context  within  knowledge  management  research  despite  increasing  recognition  between  the  provision  of  such  environments  and  advances  in  entrepreneurial  local  and  global  innovation  (Mota  2013).  Certain  groups  afford  social  action  outcomes:  nurturing  individual  empowerment,  self‐efficacy and the development of intellectual and social capital through practical learning which can foster  wider population benefits (Walton 2010). Reflecting on The Medici Effect, this fusion of cross‐disciplinary skills  and  shared  purpose  has  the  potent  to  create  an  inter‐sectional  space  for  “remarkable,  surprising  and  groundbreaking ideas” (Johansson 2004, p6) to flourish.  

2. Explication of STRIKE technique   Observation  can  be  employed  to  describe  or  represent  a  setting  and  is  frequently  unstructured  in  nature.  STROBE – STRuctured OBservation of the Business Environment (Kendall and Kendall 1984) was conceived from  film  theory  to  provide  a  reliability  and  validity  assessed  framework  to  aid  system  analysts  unobtrusively  observe, classify and interpret the physical business environment of decision‐makers and their interaction with  it.  This  can  advance  understanding  of  human  information  requirements  and  the  alignment  between  technology solutions and end‐user needs.     The authors opine a capacity and underlying need to develop the system and business requirement analysis  focus of STROBE to one affording a knowledge perspective, capable of application across multiple domains. A  level  of  granularity  is  required  to  provide  insight  into  increasingly  complex  and  dynamic  post‐industrial  contexts and the environment in which organisational actors participate in the creation of knowledge assets  (Boisot  1998).  This  can  illuminate  the  nuances  of  cultural  norms  which  form  the  core  driving  dynamics  for  knowledge transfer to be supported (Ipe 2003).     STRIKE  affords  originality  in  terms  of  scope,  breadth  and  flexibility  of  design,  and  the  qualitative  data  acquisition and evaluation methods incorporated. The framework systematically evaluates dimensions across  the  internal  and  external  knowledge  environment  and  supports  identification  of  any  dissonance  between  them.  Internal  observations  comprise  Design/Layout;  Aesthetics:  Placement  and  Decoration  of  Workspaces;  Knowledge Sources and Branding whilst external evaluation considers both Physical and Digital Presentation.  This  approach  is  congruent  with  the  multiple,  influential  roles  afforded  by  workspace  design  (Elsbach  and  Bechky 2007) and the need to enhance understanding of its relationship with creativity (Walter 2012). Place‐ centric creative enterprises therefore present a novel, rich and emergent context for STRIKE evaluation.  

2.1 Technique validation, development and theoretical lens  Drawing  on  the  Design  Science  Research  Method  (Heje,  Baskerville  and  Venable  2012),  STRIKE  has  been  subject  to  descriptive  ex‐ante  evaluation  by  iteration  in  a  naturalistic  setting.  Face  validity  analysis  was  undertaken  by  Dr  Gordon  Rugg  from  Keele  University,  a  knowledge  elicitation  expert.  Successful  ex‐post  evaluation within two verification studies in hi‐technology private sector environments (Eaves 2013; Eaves and  Walton 2013) has demonstrated a particular capacity to allow the semantic layer to become more transparent.  This  study  explores  and  develops  tool utilisation  in  a different contextual  setting  and is  proposed  to  surface  novel,  interpretative  insight  into  knowledge  transfer,  its  management  and  any  boundaries  that  hinder  optimisation.     STRIKE aligns with the increasingly acknowledged yet underexplored perspective of sociomateriality (Leonardi,  Nardi  and  Kallinikos  2012).  This  recognises  organisations,  individual  actors  and  technologies  as  continually  linked and re‐linked with meanings, properties and respective boundaries entangled, temporal and subject to  constant reproduction (Orlikowski and Scott 2008). It is also congruent with the material‐semiotic perspective  of Actor Network Theory (Latour 2005). 

2.2 Supporting techniques  Photography  and  videography  were  utilised  to  support  researcher  observation.  Ethical  concerns  and  image  confidentiality were duly considered. 

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Sally Eaves and John Walton  Photography  offers  both  an  illustrative  capability  that  reflects  its  “quasi‐representational”  nature  (Warren  2005,  p861)  and  an  interpretive  capacity  to  develop  a  multi‐layered  narrative,  providing  a  highly  accessible  frame of reference for reflection. It is employed to enrich, complement and augment observation and support  researcher neutrality.     Video technology enables a multidimensional perspective on context and can facilitate focus on, and analysis  of, actor behaviours (Coiro 2009) and their interactions with the knowledge environment. Although usage and  analysis of videography lacks the comprehensive methodological guidance and case history of more traditional  methods, its introduction within STRIKE is based on the purposeful intent to bring something extra, building on  the  non‐digital  methods  employed  within  the  validation  studies.  A  time‐lapse  technique  was  used  to  record  workshop/exhibition sessions and create stills.  

3. Research methodology  A  dual  organisation  case‐study  approach  was  adopted  with  an  inductive  and  qualitative  perspective.  The  STRIKE  method  was  enacted  through  researcher  walk‐through  observation  sessions,  supplemented  by  photography and videography.  

3.1 Access Space   Access Space (2013) in Sheffield was established in 2000 by CEO James Wallbank and remains the UK’s longest  running open access media lab. In contrast to most hackerspaces, it operates under registered charity status  with  the  aim  to  advance  public  education  in  IT  and  visual  arts  alongside  supporting  unemployment  relief:  a  tripartite  focus  on  The  Arts,  Education  and  Urban  Regeneration.  It  therefore  bridges  the  creative  and  third  sectors. There are no preconditions or entry requirements ‐ anyone can take part. This is particularly important  in communities such as those served by the enterprise, where many individuals have traditionally felt “digitally  excluded”  (Walton  2010,  p11).  In  2012,  Access  Space  was  recognised  as  one  of  50  “New  Radicals”:  organisations making Britain a better place to live and work (Nesta 2012). Despite these achievements, funding  from Arts Council England was withdrawn in 2011 presenting a profound threat to its financial sustainability.     Within the physical space, there are two principal areas supported by a core of 6 staff. The media lab provides  free internet access and facilities to develop expertise in open source software, web development and a range  of audio and visual digital skills. The adjacent but separate Refab Lab was opened in 2009 and is based on the  FabLab  concept  developed  at  MIT.  This  space  houses  fabrication  equipment  such  as  a  3D  printer  and  laser  cutter, supports materials recycling, and is used by artists‐in‐residence to develop exhibition projects.  

3.2 Bristol Hackspace   The second creative context is Bristol Hackspace (2013), founded in November 2009 as a social enterprise with  the  goal  to  “open  up  technology  to  anybody  who  takes  an  interest  in  it”.  It  is  similarly  committed  to  the  principals  of  open  source  and  open  knowledge.  The  hackspace  is  based  in  the  Windmill  Hill  ward  which  experiences  deprivation  levels  above  average  for  the  city.  It  is  run  entirely  by  volunteers  at  BV  Studios,  an  artist‐led shared project and art space arranged into units within a warehouse of 30,000 square‐feet. Activities  are practical and hands‐on, ranging from projects in computing, robotics, electronics and metalwork to craft  based creative skills.     Open evenings are held each Thursday with a Hackkids session for under‐16’s taking place once per month.  Strong  links  are  maintained  with  local  technology  groups  and  across  the  wider  hackerspace  network.  A  minimum monthly subscription of £10 is requested from the 39 full members, with a small income obtained  through  public  workshops,  exhibitions  and  occasional  externally  funded  projects.  Membership  levels  are  increasing  with  discussions  ongoing  regarding  enterprise  future  direction  and  its  accommodation  within  the  physical space.  

4. STRIKE findings and integrated discussion  The environmental elements across each case setting are now fully elucidated. Images of workshop events are  stills created from video recordings.    

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4.1 STRIKE assessment of Access Space  Core  dimensions  from  the  STRIKE  evaluation  are  presented  in  Table  2,  supported  by  photography  to  enrich  observation, support transparency and enhance audience capacity to actualise place.   Table 2: STRIKE evaluation of Access Space  Environmental  Element 

Description and Supporting Photography 

Design/Layout

Open‐plan main media lab with circular seating to enable socialisation.  There is a separate Refab Space with secured access which houses heavy equipment alongside  materials for recycling. A dedicated area created and used principally by one staff member is  located above its floor plate.   

Aesthetics; Placement and  Decoration of  Workspaces     

    Dissonance is observed between cluttered areas and carpet in need of replacement in the open  main area and the highly organised, tidy Refab Space which affords more staff and artist‐in‐ residence privacy.   

      Further contrast identified between the personal, creative output of participants (not staff)  displayed in the media space and strong evidence of Industrial Art and personalisation  attributed primarily to one staff member found in Refab.  Across both zones, work is evolving, practical and amorphous in orientation.   

Knowledge Sources 

      Hands‐on practical peer learning leading to self‐experimentation.  Literature embracing community interests alongside technical themes is available to take away.  One revelatory example of explicit knowledge is observed, a sign which emphasises the tacit,  problem‐solving emphasis of the space:   'please help me with my problem but do not solve it for me'. 

 

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Sally Eaves and John Walton  Environmental  Element 

Description and Supporting Photography 

Branding

Distinct branding for Access Space and the Refab Space.  Local community focus exemplified by the urban fabric project exhibited. This uses rapid  prototyping equipment to promote dialogue on the “new” Sheffield.   

Physical External  Presentation 

Digital External  Presentation 

    Accessible city centre location within a IT/Creative Industries district.   Physical space lacks visibility and aesthetic evidence of the creativity within. 

  Facebook, Twitter and Vimeo (video) conduits preferred to Flickr (photo).  Distinction between Access Space (media lab focus) and the Refab space.   No significant evidence of online discussions regarding decision‐making.   

 

STRIKE evaluation  is  not  indicative  of  deep  knowledge  management  dysfunction  but  both  strengths  and  opportunities for enhancement are inferred. Reflecting on Gensler’s (2008) modes of working, the media lab is  particularly well suited to the elements of collaborate, learn and socialise, whilst the Refab area allows more  opportunities  for  individual  focus.  Access  Space  has  a  strong  creative  identity  but  this  is  not  reflected  in  its  physical  external  presentation  which  is  understated  –  you  could  easily  walk  past.  The  digital  presentation  is  more representative, supported by dual branding and a social network presence but still does not provide full  visibility of the rich diversity observed.     Recording of day‐to‐day behaviour is revelatory of the actual breadth of knowledge activities in praxis which  correspond  to  the  pragmatic  theory  of  truth.  These  demonstrate  practical  relevance  and  usefulness  to  an  individual  or  group,  with  a  strong  problem‐solving  emphasis.  This  is  verified  and  legitimised  by  prominent  display of knowledge artefacts which allow idea expression (Walter 2012) and support a positive psychology.  This aligns with symbolic functionality (Elsbach and Bechky 2007).    These  artefacts  demonstrate  the  individuality  of  participant  works:  their  interests,  creativity  and  priorities,  congruent with the do‐ocracy ethos described by Chen (2009, p55). It also illuminates a lack of personalised  décor or visibility in respect to staff projects. One exception is identified with reference to the Industrial Art  prominent in the Refab area which reflects the craftsmanship and discipline skills of an individual staff member  critical  in  its  construction.  It  is  noted  that  in  combination  with  the  additional  privacy  and  increased  order  observed  in  this  separate  zone,  this  physical  arrangement  has  the  potential  to  develop  into  dissonance  impacting  knowledge  boundaries,  even  within  a  collegiate‐style  setting.  Any  design  that  enables  significant  separation between actors, and allows differences in the features afforded (Walter 2012) can experience such  problems (Elsbach and Bechky 2007).    

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Sally Eaves and John Walton  Further,  it  is  argued  that  the  knowledge  artefacts  observed  afford  a  lens  into  organisational  identity,  the  potential  future  direction  of  Access  Space  and  its  evolving  superordinate  goal:  aspects  that  staff  had  found  difficult to elucidate during individual reviews (Walton 2013). By demonstrating the material structure of ideas  (Bieler 2001), STRIKE affords a means to demonstrate underlying interests and points of intersection expressed  in  artefacts.  This  can  support  the  understanding  of  intersubjective  meaning  in  action;  it  is  revelatory  of  the  knowledge  that  is  most  valued  as  a  collective.  This  perspective  is  supported  by  the work  of  Gramsci  (1971),  who asserts that a level of philosophy is implicit in all forms of practical action.     In terms of knowledge management evaluation, the hands‐on transfer, experiential development and dialogic  norms  identified  in  the  space  are  difficult  to  express  within  SMART  objectives:  outcomes  are  not  typically  amenable  to  standard  measurement  approaches.  Although  the  learning  processes  and  knowledge  sharing  behaviours  are  clearly  valued  by  beneficiaries  including  the  committed  staff,  these  are  not  easy  to  measure  and are difficult to plan against. This problem maps against the knowledge exploration‐exploitation dilemma  and  is  a critical  issue  for creative  enterprises  with  a  charitable  status, where  articulating knowledge  value  is  core to securing funding and sustainability.  

4.2 STRIKE assessment within Bristol Hackspace  The core elements emergent from the STRIKE evaluation are presented in Table 3.  Table 3: STRIKE evaluation of Bristol Hackspace  Environmental  Element  Design/Layout 

Aesthetics; Placement and  Decoration of  Workspaces   

Knowledge Sources 

Description

Supporting Photography 

Clearly identifiable work zones for different activities.   Connecting “corridors” allow flow between areas.  Informal seating supports socialisation.   

  Whitewashed walls, clean lines, tidy and organised equipment.  Provision of individual storage space. Limited evidence of personalised décor.   

    Emphasis on practical demonstration and self‐learning by experimentation.  External flow into space encouraged by attracting speakers.   The touchscreen table is a focal point for web access and dialogic discussion.   

  

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Sally Eaves and John Walton  Environmental  Element  Branding 

Description

Supporting Photography 

Supported by consistent use of social media (Twitter and Flickr in particular) and attendance  at Maker‐Faire events. Publicity material promotes activities, affording a distinctive logo and  providing a QR website code to create an integrated approach.   

    

Physical External  Presentation 

Digital External  Presentation 

External aesthetics are consistent with internal observations.   Accessible location near transport links, clearly signposted online.   

  Narrative emphasis on the association of hacking with creativity and building.  Website design including wiki and blog are congruent in design and branding.  A GoogleGroup account demonstrates strong collegiate style decision‐making.   

   

On evaluating and comparing the STRIKE data sets, the Bristol Hackspace displays greater symbiosis between  the  knowledge  environment  as  a  synchronous  physical  locale  and  as  an  asynchronous  digital  web  presence:  one  which  also  affords  increasingly  synchronous  communication  opportunities  through  Web  2.0  tools  that  enable immediacy of response. This can positively impact the intensity of experience perceived by members  (Mitchell  2003).  Social  media  channels  are  used  extensively  and  illuminate  the  projects  and  knowledge  activities undertaken. Within the physical space, there is less demonstration of artefacts or personalisation in  comparison to the exhibition of participant creativity within Access Space, reflecting differentiating nuances in  group goals.     The  physical  environment  is  particularly  suited  to  the  dimensions  of  collaborate,  learn  and  socialise  Gensler  (2008). There are some opportunities for focussed individual working but privacy to afford concentration can  be limited. The setting design presents a calm, consistent and pleasing aesthetic which can support a positive  sensory  experience  for  participants  (Elsbach  and  Bechky  2007).  This  is  particularly  utile  to  provide  an  appropriate  setting  for  the  under‐16’s  supervised  Hackkids  workshops.  Should  future  resources  permit,  attention to aesthetics within Access Space’s media lab would similarly enable development of a knowledge  environment that supports a younger audience.     Thematic  analysis  of  the  Bristol  Hackspace  GoogleGroup  (2013)  is  revelatory  of  knowledge  environment  tensions congruent with the lifecycle development of an expanding enterprise. There is a high level of virtual  organisation of ideas which was equally reflected within the zoned areas and order observed in the physical  space.  Underlying  discussion  concerns  how  to  balance  membership  growth,  collaborations  and  space  management, alongside securing funding and long‐term sustainability. In common with Access Space, identity  is a persistent theme but here this is more explicitly acknowledged with members articulating their respective 

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Sally Eaves and John Walton  and  sometimes  divergent  interests,  and  engaged  in  dialogic  discussion  regarding  how  best  to  accommodate  them.  Supported  by  a  strong  capacity  to  act,  this  collective  approach  may  aid  the  dissipation  of  potential  knowledge boundaries, particularly pragmatic forms (Carlile 2004).  

5. STRIKE evaluation  STRIKE  affords  a  systematic,  unobtrusive  framework  which  supports  consistency  of  approach  alongside  flexibility of application and high communicability of findings. The tool demonstrates capability to perform in a  variety  of  circumstances,  moving  from  the  hi‐technology  private  sector  organisations  considered  within  validation  studies,  to  the  highly  original  creative  sector  enterprises  appraised  in  this  research.  An  authentic,  panoptic  lens  to  connect  to  the  actor  lifeworld  is  made  available,  providing  structured  and  in  situ  capture,  expression and evaluation of their knowledge environment. The approach conforms to Wittgenstein’s (2001)  picture theory of meaning affording a pictorial, representational and logical level which aids interpretation and  articulation.    The  method  elucidates  the  importance  of  human  interaction  across  the  physical,  technological  and  social  environment  to  create  and  evolve  meaning  and  value.  The  socio‐technical  and  internal‐external  dimensions  benefit holistic appreciation of knowledge practices and mechanisms, affording identification of presentational  dissonance.  It  also  enhances  understanding  of  emergent  and  planned  space  design  in  creative  settings,  developing empirical support for the conceptual workspace creativity framework developed by Walter (2012).      It is opined that the multidimensional orientation of STRIKE provides a novel means to enable the verbalisation  of  tacit  knowledge  transfer  practices  (Seidler‐de  Alwis  and  Hartmann  2008)  which  is  difficult  to  achieve  through traditional interactive methods. It presents an unobtrusive language (Wittgenstein 2001) to express  meaning  and  surface  underlying  issues,  as  exemplified  by  the  materiality  of  ideas  achieved  through  their  physical  demonstration  and  evaluation.  This  may  be  described  as  the  reification  from  tacit  to  explicit  knowledge  which  affords  benefits  for  reviews  and  processes  of  organisational  translation  (Walton  2013)  ‐  aspects that impact both settings in distinct means, aligned to their respective lifecycle stages and goals.     STRIKE  supports  articulation  of  the  value  of  the  knowledge  activities  undertaken;  this  is  pertinent  to  Access  Space  where  it  can  aid  demonstration  of  the  “Reach  and  engagement”  funding  criteria  explicated  by  Arts  Council England (2011, p3). Its diagnostic‐prescriptive capability is also considered germane for utilisation by  practitioners  across  a  range  of  settings.  As  an  example,  implementation  of  a  high‐level  knowledge  management  initiative  would  equally  benefit  from  an  approach  that can  illuminate cultural nuances  such as  resistance  versus  acceptance  behaviours  and  additionally,  enable  a  form  of  transactional  analysis  of  actor  perspectives. Further, as the method provides a lens into a context at a particular juncture and across specific  dimensions, it affords standardisation benefits. It can be employed in a verification or longitudinal capacity to  validate  or  revisit  research  findings,  or  equally  to  evaluate  the  success  of  a  knowledge  management  intervention  over  time.  STRIKE  would  also  be  suitable  for  application  in  mixed  methods  research  to  support  data triangulation.    Enactment  of  this  framework  is  enhanced  by  visual  tools  which  enable  a  multiplicity  of  perspectives  and  reduce  reliance  on  direct  researcher  observation.  Whilst  a  single  image  can  present  “very  particular  information”,  a  cumulative  group  can  begin  to  afford  “signifiers”  revelatory  of  the  cultural  context  (Prosser  2012,  p1).  Videography  proved  effective  for  researcher  reflection  and  to  support  the  creation  of  additional  stills but its full dimensionality is inherently difficult to articulate within a textual piece. It does however offer  additional potent for presenting findings directly: as a familiar, rich, engaging and distinctive visual medium,  video  can  convey  a  deep  sense  of  “direct  experience  with  the  primary  phenomena”  (Pea  1999,  p353).  This  supports  the  call  to  incorporate  digital  methods  into  the  mainstream  (NCRM  2013).  In  future  studies,  the  application of social media evaluation tools such as Google Analytics will be considered to extend assessment  of the digital external environment.  

6. Knowledge environment conclusions   Access  Space  and  Bristol  Hackspace  are  exemplar  enterprises  which  support,  and  are  catalysts  for,  rapid  technological innovation. From different perspectives, they are also considered drivers in a critical new social‐ economic model in which social economic change is regarded the embodiment of innovation: supporting the  development  of  intellectual  and  social  capital  and  affording  the  potential  for  sustainable  entrepreneurship 

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Sally Eaves and John Walton  (Mota 2013). This is facilitated by an open knowledge production model which co‐exists with more traditional  forms, alongside an enabling, almost cosmopolitical (Latour 2004) knowledge environment that bridges socio‐ technical dimensions to support curiosity, self‐efficacy, idea incubation and artefact production. In congruence  with the nature of the sector, knowledge management practices may be described as emergent. It is argued  that  the  diagnostic‐prescriptive  tool  STRIKE  focuses  attention  to,  and  evaluation  of,  knowledge  in  action  to  benefit the overarching mechanisms that support them, including workspace design.     Technological  developments  and  production  model  changes  have  indeed  removed  many  of  the  barriers  of  time,  space  and  restricted  knowledge  that  have  previously  inhibited  wider  levels  of  collaboration  and  innovation.  This  study  elucidates  that  despite  this  evolution,  the  physical  environment  and  actor  interaction  with  it  plays  a  critical  role  in  supporting  the  practices  and  mechanisms  of  knowledge  management.  It  is  important that this is integrated with its digital presence.     Specifically,  the  Refab  environment  within  Access  Space  is  demonstrative  of  the  relationship  between  technology and architecture (Silver and McLean 2008): it affords a physical design solution that is creative as  well  as  functional,  fit  for  purpose  but  adaptable  to  future  needs,  elegant  but  also  practical.  In  the  Bristol  Hackspace, the organised activity zones and easy flow between them is notably supportive of task organisation  alongside exposure to multidisciplinary techniques and creative collaboration (Walter 2012).     The  effectiveness  of  Access  Space  and  the  Bristol  Hackspace  may  be  attributed  to  the  development  of  pragmatic,  eclectic  knowledge  communities  which  balance  individual  and  group  goals,  utilising  dynamic,  integrative and “participatory technology‐development techniques” (Grenier 1998, p.vii). Place, tools, research  and development, social structure and innovation are therefore increasingly merged and aligned. Drawing on  the  MOA  framework  (Gan,  Kosonen  and  Blomqvist  2012),  these  enterprises  exemplify  a  tripartite  of  staff/attendee motivation and developed abilities, alongside the opportunity afforded by place: providing both  cognitive and physical space to those who work, volunteer or participate within them.  

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Ipe Revisited: Validating a Multidimensional Model of Individual  Knowledge Sharing Influences  Sally Eaves  Faculty of Arts, Computing, Engineering, and Sciences (ACES), Sheffield Hallam University,  UK  research@sallyeaves.co.uk    Abstract: This paper elucidates the spectra of influences that impact the intra‐organisational tacit and explicit knowledge  sharing  behaviour  of  the  middle  line.  It  addresses  a  deficiency  in  research  that  affords  an  eclectic  approach  across  both  knowledge  types  simultaneously  and  at  an  individual  level  of  analysis.  Ipe  (2003)  develops  a  conceptual  model  of  knowledge  sharing  between  individuals,  opining  that  behaviour  is  influenced  by  Motivation  to  Share,  the  Nature  of  Knowledge, Opportunity to Share and most significantly, Culture. A critical analysis is presented to surface limitations and  concludes the framework to be overly reductionist. This provides the catalyst for revision: a pluralistic consideration of the  elements which impact volition and capacity to share. Adopting a multi‐disciplinary perspective, significant augmentations  to  the  original  factors  are  proposed  and  the  Nature  of  the  Individual  and  Organisational  Velocity  are  introduced  as  key  impacting elements on knowledge sharing, the latter in a moderating capacity. The Nature of the Individual embraces the  influence  of  human  characteristics  such  as  personality  traits  and  demographics.  Organisation  Velocity  is  an  original  conceptualisation  of  the  continual,  episodic  and  ambiguous  change  which  reflects  the  reality  of  many  post‐industrial  settings. It is expressed as the tension between centrifugal and centripetal forces acting on the five other influence factors.  Exploratory  validation  of  the  resultant  Multidimensional  Model  of  Individual  Knowledge  Sharing  Influences  is  achieved  through  a  robust,  empirical  study  elucidating  the  sharing  behaviour  of  middle  management  in  four  leading  UK  Communication  Sector  operators.  All  six  factors  are  shown  to  impact  individual  knowledge  sharing  practice,  with  Organisational Velocity acting in a moderating and primarily centrifugal capacity on Motivation to Share, Opportunities to  Share and the Nature of the Individual. It is demonstrated that a panoptic, interdisciplinary perspective combining human,  social,  technological  and  contextual  factors  must  be  considered  to  understand  behaviour  and  optimise  knowledge  management interventions. A particular element may not be evaluated in isolation.    Keywords: knowledge sharing, individual knowledge sharing influences model, nature of the individual, organisational  velocity, middle managers 

1. Introduction: Individual knowledge sharing behaviours and challenges  Knowledge exists across multiple organisational levels and may be transferred in different forms and directions  (Ipe 2003) but is typically controlled at the level of the individual (Gupta and Govindarajan 2000). Knowledge  sharing is considered the critical, determining factor in knowledge management success (Boisot and Cox 1999)  with  intra‐organisational  exchange  emergent  from  individual  motivations  (Bock  et  al.  2005)  and  consequent  actions  and  interactions  (Foss  2007).  The  capacity  to  leverage  knowledge  assets  is  therefore  dependent  on  human  capital:  the  individuals,  who  create,  use  and  critically,  can  elect  to  share  what  they  know.  Middle  management  affords  a  vital  influence  combining  boundary  spanning  position  (Lin  2007)  with  the  strategic  sense‐making  capacity  to  perform  analytic,  intuitive  and  pragmatic  roles  to  create,  integrate  and  share  knowledge (Janczak 2004).     Exchange remains a complex and often unnatural process with diverse challenges identified across individual,  organisational  and  technological  dimensions.  These  include  dynamic  contexts,  free‐riding,  conflicting  values,  lack  of  time  or  tools,  and  socio‐cultural  issues  (Riege  2005).  Transferability  problems  also  relate  to  its  very  nature with tacit knowledge difficult to express and share due to its sticky, experiential, intuitive and sense‐ making  properties  (Chon  2011).  There  remains  a  lack  of  holistic  understanding  of  the  factors  influencing  sharing behaviour with many studies wholly conceptual (Ipe 2003), focussed on one knowledge type (Lin 2007)  or on a limited number of influences (Bartol and Srivastava 2002). Drawing on Lincoln and Guba’s (1985, p226)  definition  of  the  characteristics  of  a  research  problem,  this  is  ‘‘a  state  of  affairs  that  begs  for  additional  understanding”.  

2. Ipe’s theoretical drivers of knowledge sharing behaviour  Ipe  (2003)  opines  that  individual  knowledge  sharing  is  influenced  by  Motivation  to  Share,  the  Nature  of  Knowledge, Opportunity to Share and Culture. Although soundly based on a significant literature review, it is  argued  that  the  relative  importance  and  interaction  of  these  factors  is  not  adequately  explored,  nor  the  underlying  constructs  fully  substantiated.  The  resultant  conceptual  model  does  not  consider  a  breadth  of 

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Sally Eaves  influencing factors and is perceived to be overly reductionist and insufficient to reflect the range of potential  contributory issues and a holistic treatment of individuals.     Specifically,  Ipe  assumes  that  individuals  are  homogenous.  The  author  asserts  that  this  view  negates  the  potential  for  differences  in  response  to  context  and  stimuli  to  be  appropriately  addressed.  It  is  argued  that  individuals are not homogeneous in respect to their motivations (McGregor and Cutcher‐Gershenfeld 2006) or  emotions (Pfister and Böhm (2008) but a dominant force may be determinative.  

2.1 A multidimensional model of individual knowledge sharing influences  Reflecting  on  the  critical  analysis  of  Ipe’s  framework,  an  expansive,  multidisciplinary  literature  review  was  undertaken drawing on the evaluation guidance of Boote and Beile (2005). Studies were selected the basis of  foci  (outcomes,  methodological  approach,  underlying  theory);  contribution  to  goals  (issue  identification,  criticism, integration/synthesis); and coverage (multi‐disciplinary, emergent nature, authority). The approach  may be described as a narrative but incorporating systematic review practices. Development was supported by  the  mixed  methods  case  study  findings  of  primary  research  (Eaves  2013),  alongside  peer  and  expert‐based  discussions  until  a  saturation  point  was  achieved.  Explication  of  all  factors  and  constructs  identified  for  the  new model is now provided.    2.1.1 Opportunities to share factor  In order to share knowledge, opportunities must be available for organisational actors to do so. These may be  formal  or  informal  in  nature  and  span  individual,  social,  organisational  and  technological  dimensions.  The  constructs aligned to this factor are elucidated in Table 1.   Table 1: Opportunities to share constructs  Constructs  Knowledge Sharing Tools/Techniques  Knowledge Management Team  Knowledge Management Strategy  (Individual/Organisational)  Social Network  Structure and Hierarchy  Perceived Behavioural Control  Managerial Role  HRM Practices  Time  ICT 

Primary Reference  Bartholomew (2005)  Bartholomew (2005)  Wei, Choy and Yew (2009)  Chow and Chan (2008)  Wei, Choy and Yew (2009)  Ajzen (2002)  Refaiy and Labib (2009)  Lepak and Snell (2002)  Kankanhalli, Tan and Wei (2005)  Teerajetgul, Chareonngam and Wethyavivorn (2009) 

2.1.2 Motivation to share factor  Motivation  facilitates  knowledge  sharing  behaviour  through  the  complex  processes  of  socialization,  externalization  and/or  combination.  It  comprises  internal,  intrinsic  aspects  that  impel  individual  action  alongside external aspects which may be action inducing. Bock et al. (2005) stress the importance of improving  understanding of individual‐level motivations. Aligned constructs are presented in Table 2.   Table 2: Motivation to share constructs  Construct (Intrinsic Motivators)  Intention to Share  Emotion  Eagerness to Share  Image  Sense of Self‐Worth  Commitment  Power  Knowledge Ownership  (Individual/Department/Organisation)  Construct (Extrinsic Motivators)  Willingness to Share 

Primary Reference  Bock et al. (2005)  Van den Hooff, Schouten and Simonovksi (2011)  De Vries, Van den Hooff and De Ridder (2006)  Kankanhalli, Tan and Wei (2005)  Bock et al. (2005)  De Vries, Van den Hooff and De Ridder (2006)  Kankanhalli, Tan and Wei (2005)  Constant, Kiesler and Sproull (1994) 

De Vries, Van den Hooff and De Ridder (2006) 

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Sally Eaves  Construct (Intrinsic Motivators)  Sharer‐Receiver Relationship  Trust  Distributive Justice  Procedural Justice  Pay Satisfaction 

Primary Reference  Lichtenstein and Hunter (2005)  Teerajetgul, Chareonngam and Wethyavivorn (2009)  Reychav and Weisberg (2009)  Moorman (1991) 

Sweeney and McFarlin (2005) 

2.1.3 Nature of knowledge factor  This  moves  beyond  the  consideration  of  a  tacit/explicit  distinction  to  reflect  knowledge  type  based  on  an  operational, procedural, process or product perspective. Task characteristics are explored via the dimensions  of equivocality, uniqueness and interdependence. Knowledge auditing is incorporated as its use can facilitate  understanding  of  how  well  internal  activities  are  meeting  organisational  goals,  whilst  identifying  potential  knowledge stores. Aligned constructs are detailed in Table 3.   Table 3: Nature of knowledge constructs  Construct  Knowledge Type  Task Equivocality 

Primary Reference  Huysman and de Wit (2010)  Van Den Hooff and Huysman (2009) 

Task Uniqueness  Task Interdependence  Knowledge Auditing 

Lepak and Snell (2002)  Jarvenpaa and Staples (2001)  Bartholomew (2005) 

2.1.4 Culture factor  Ipe (2003) presents culture as the primary factor in knowledge sharing behaviour, influencing all others. Every  actor possesses personal values, beliefs and experiences which influence their perceptions and actions. These  combine  with  the  norms,  practices,  values  and  history  which  intimate  organisational  culture,  creating  a  powerful dynamic. Culture is a distinct factor in this model.   2.1.5 Nature of the individual factor   This  original  factor  considers  the  direct  impact  of  specific  personality  traits  and  demography  on  individual  knowledge sharing behaviour, areas which are underexplored. These characteristics are typically either static  or evolve over an extended period of time. It is argued therefore that they should be considered as distinct  from  the  more  contextually  influenced  and  variable  aspects  aligned  with  (intrinsic)  Motivation  to  Share.  Constructs associated with this factor are elucidated in Table 4.   Table 4: Nature of the individual constructs   Construct    Allocentric Personality  Ideocentric Personality  Gender  Function  Education Level  Certification Type  Role Experience  Organisation Tenure  Sectoral Tenure 

Primary Reference  Matzler et al. (2008)  Matzler et al. (2008)  Harrison and Mason (2007)  Riege (2005)  Keyes (2008)  Eaves (2013)  Bakker et al. (2006)  Ojha (2005)  Eaves (2013) 

2.1.6 Organisational velocity  This  potential  moderating  influence  advances  the  environmental  velocity  and  knowledge  intensity  model  of  Jarzabkowski and Wilson (2006). It is opined that velocity can also be an organisational characteristic as within  an industry similar size market players are far from homogeneous in their internal environments. The following  definition is offered:    

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Sally Eaves  “Accelerated  rates  of  discontinuous  change:  complex,  dynamic,  multi‐dimensional  and  multi‐ faceted  in  nature,  these  can  puncture  the  organisational  equilibrium  and  are  considered  continually episodic”.   Adopting  a  pragmatic  perspective,  this  original  conceptualisation  builds  on  elements  of  existent  theories  of  change,  specifically  advancing  Weick  and  Quinn’s  (1999)  work  on  two  distinct  types.  Continuous  change  is  described as "constant, evolving, cumulative" (p366) whilst episodic change is “infrequent, discontinuous, and  intentional"  (p365).  It  is  argued  that  this  polarity,  although  considered  more  representative  than  the  static,  linear and rational orientation of authors such as Lewin (1951), still does not reflect the reality of increasingly  uncertain environments. In such cases, the tempo of change may almost be described as continually episodic.  It is constant yet not cumulative, with strategic direction ambiguous and moving; it is discontinuous in terms of  type  and  scale  but  not  in  frequency,  suggesting  that  effective  adaptation  is  not  attained  (Eaves  2013).  Synthesising the factor review, Figure 1 introduces the resultant conceptual framework.  

Figure 1: Conceptual multidimensional model of individual knowledge sharing influences  

3. Methodology 3.1 Research setting  The high‐technology UK communications sector is continually evolving and knowledge intensive with diverse  challenges including complex consumer behaviours, strong competition and converging data architecture. Four  leading  operators  by  market  share  are  considered  ‐  one  of  which  (Firm  A),  has  been  established  to  be  representative  of  high  Organisational  Velocity  (Eaves  2013).  This  affords  a  rich  opportunity  for  individual  knowledge  sharing  practice  to  be  compared  against  the  grouping  of  the  other  three  operators  which  demonstrate relatively stable conditions.  

3.2 Model validation strategy  A  quantitative  survey  was  developed  based  on  the  extensive  literature  review  and  the  findings  of  a  mixed‐ methods  case  study  which  facilitated  nuanced  understanding  within  a  specific  setting  (Eaves  2013).  This  method  enabled  model  testing  across  leading  organisations  in  the  same  sector  to  provide  an  exploratory  assessment and comparison of how the factors and aligned constructs apply. Additional case or ethnographic  research could be pursued at a later stage dependant on findings.     Construct  measurement  utilised  or  augmented  existing  scales  where  appropriate,  selected  on  the  basis  of  scope, relevance and demonstration of dimensionality, reliability and validity. The dependent variables of tacit  and  explicit  knowledge  sharing  were  measured  across  questions  employed  or  adapted  from  the  established  behaviour scales of Yi (2009) and Reychav and Weisberg (2009). Independent variables were aligned across the 

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Sally Eaves  five  core  influence  factors  in  the  model  as  previously  detailed.  A  five  point  Likert  scale  was  adopted  throughout for attitudinal measurement.      Dr Gordon Rugg from Keele University, a knowledge elicitation expert, conducted content validity analysis on  construct  design  and  survey  wording,  with  focus  directed  at  reducing  self‐reporting  bias.  A  pre‐test  was  performed  to  evaluate  specification,  framing,  ordering,  usability  and  phrasing  to  reduce  ambiguity  and  the  potential of non‐response.  Purposeful sampling was adopted to identify middle manager respondents (N=78)  with research undertaken in Q3 2012 via web‐based survey distribution.  

4. Findings and integrated discussion  The  data  set  comprised  a  majority  of  males  (N=60)  aged  50‐59  (N=30)  and  with  sectoral  experience  of  15+  years  (N=48),  aligning  with  the  employment  profile  of  this  industry  in  the  UK.  Reliability  analyses  were  conducted  in  order  to  determine  internal  consistency  reliability,  achieving  acceptable  Cronbach  Alpha  coefficients above .70 for all scales. A synopsis of correlation results is provided alongside full presentation of  regression findings for the four organisations as one group.  

4.1 Correlation and regression analysis: Demographics   Pearson or Spearman's rho correlations were performed as appropriate to data type. Two backward stepwise  linear regression analyses were conducted as detailed in Tables 5 and 6. Predictors having a probability level  above .15 were removed. Results are highlighted in respect to having probability levels lower than .05 (95%+  confidence), lower than .01 (99%+), and lower than .001 (99.9%+).  Table 5: Regression Analysis on Tacit Knowledge: Demographics    Scale                                                         B                 Std. Error         t  Education Level        ‐.088       .095    ‐.92  Function        .889***       .191    4.65  Certifications Held      ‐.131*       .049    ‐2.70  Sectoral Tenure       .063       .062    1.01  Organisation Tenure      ‐.494***      .068    ‐7.23  KM Team Presence     1.122***     .225     4.99  Knowledge Auditing       ‐.212       .165     ‐1.29  K Type: Operational      .263       .212    1.24  K Type: Procedural      .621**       .198    3.13  K Type: Process      .207       .214      .97  K Type: Product        .430*       .177    2.43  Constant        4.048***   .301              13.45  Notes: *p<.05, **p<.01, ***p<.001; N = 47; F(12, 34) = 10.20, p<.0001; R2 = .7826, Adj R2 = .7058.   

Based on  the  predictors  included,  70.58%  of  the  variance  in  tacit  sharing  is  explained.  Function,  Knowledge  Management  Team  Presence  and  Knowledge  Type  (Procedural,  Product)  are  positively  significant,  with  number of Certifications Held and Organisation Tenure negatively significant.  Table 6: Regression analysis on explicit knowledge: demographics   Scale                                                   B                Std. Error      t      Gender (Female)      ‐.487*       189             ‐2.57  Function        .232       .206              1.13  Role Experience         .073       .100                .73  Sectoral Tenure        ‐.054       .082               ‐.66  Organisation Tenure      ‐.230**       .082              ‐2.81  Knowledge Auditing      .326**       .120               2.72  K Type: Operational      ‐.788**       .233              ‐3.38  K Type: Procedural      ‐.016       .267                ‐.06  K Type: Process      ‐.483       .256              ‐1.89  K Type: Product        ‐.318       .226              ‐1.41  Constant        3.843***     .364             10.55  Notes: *p<.05, **p<.01, ***p<.001; N = 61; F(11, 49) = 4.58, p<.001; R2 = .5067, Adj R2 = .3960.   

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Sally Eaves  The  model  collectively  explains  39.60%  of  the  variation  in  explicit  knowledge  with  only  Knowledge  Auditing  found positively significant. Gender (Female), Knowledge Type (Operational) and congruent with tacit findings,  extended Organisation Tenure afford a negative, significant association.  

4.2 Correlation and regression analysis: Scales  Pearson correlations revealed a large number of scales demonstrated a strong positive or negative relationship  with  tacit  and/or  explicit  knowledge  sharing  behaviour.  A  negative  correlation  identified  between  the  Time  (Opportunities  to  Share)  and  Power  (Motivation  to  Share)  scales  and  both  types  of  knowledge  sharing  was  particularly significant. Based on question design, the inference that time availability is negatively associated  with  sharing  necessitates  additional  insight.  Table  7  presents  the  results  of  backward  stepwise  regression  analysis.  This  indicates  that  77.02%  of  the  variation  in  tacit  knowledge  is  explained  on  the  basis  of  the  predictors included.   Table 7: Scales regression analysis on tacit knowledge  Scale                                                   B          Std. Error          t                   r2  Ideocentric Personality       ‐.160  .057    ‐2.83**  .022  Allocentric Personality       ‐.419  .130    ‐3.23**  .247  Eagerness to Share     .136  .066     2.05*  .268  Sharer‐Receiver Relationship   .190  .059     3.20**  .475  Time          ‐.161  .051    ‐3.18**  .296  Structure and Hierarchy      ‐.091  .054    ‐1.67  .170  Power          ‐.128  .053    ‐2.40*  .108  Intention to Share      ‐.271  .074    ‐3.65**  .258  Emotion        .077  .052    1.48  .320  Perceived Behavioural Control    .121  .057    2.13*  .452  Social Network        .145  .056    2.59*  .257  Task Eqivocality      .184  .062    2.97**  .372  Task Uniqueness      .093  .041    2.25*  .062  Distributive Justice      .101  .050    2.02*  .154  Ownership: Department      .071  .036    1.99  .027  Ownership: Organisation    ‐.082  .049    ‐1.65  .052  Ownership: Individual      ‐.075  .048    ‐1.54  .001  Commitment        .128  .054    2.35*  .233  Constant        6.613  .560    11.81***   2 2 Notes: *p<.05, **p<.01, ***p<.001; N = 72; F(18, 53) = 14.22, p<.001; R  = .8285, Adj R  =  .7702.   

A positive and significant association was found between tacit knowledge sharing behaviour and the following  scales: Eagerness to Share, Sharer‐Receiver Relationship, Perceived Behavioural Control, Social Network, Task  Eqivocality, Task Uniqueness, Distributive Justice and Commitment.     A negative significant relationship was found with regard to the scales for: Ideocentric Personality, Allocentric  Personality, Time, Power and Intention to Share.     Table 8 summarises explicit knowledge findings, indicating 65.23% of the variation is explained.      Significant and positive associations with explicit knowledge were found for the following scales: Eagerness to  Share,  Knowledge  Ownership  (Department),  Sharer‐Receiver  Relationship,  Structure  and  Hierarchy,  Task  Uniqueness, Pay Satisfaction and Culture.     Additionally,  significant  negative  associations  were  identified  with  regard  to:  Knowledge  Ownership  (Individual),  Sense  of  Self‐Worth,  KM  Strategy  (Organisation),  KM  Strategy  (Individual),  Social  Network,  Procedural Justice and Image.    All factors are significantly involved in sharing practice, justifying the multidimensional approach. With respect  to  correlation,  where  a  significant  relationship  is  identified,  this  is  primarily  positive  and  impacts  tacit  and  explicit knowledge simultaneously. This is congruent with the dynamically‐linked emphasis opined by Polanyi  (1966) and the mutual facilitation discussed by Cook and Brown (1999). Only Sectoral Tenure has a significant 

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Sally Eaves  relationship with explicit knowledge in isolation. At regression, more negative relationships are identified and  there is greater differentiation on the significance and direction of relationships based on knowledge type. This  justifies the decision to split the knowledge sharing dependent variable by a tacit/explicit distinction. Results  such  as  the  negative  impact  of  Time  (availability),  Allocentric  Personality  and  Intention  to  Share  on  tacit  sharing require further exploration.    Table 8: Scales regression analysis on explicit knowledge  Scale                                                   B          Std. Error          t                   r2  Knowledge Tools Used      ‐.086  .059    ‐1.47  .004  Eagerness to Share     .262  .114     2.30*  .049  Ownership: Individual      ‐.171  .068    ‐2.53*  .006  Ownership: Department      .148  .057     2.61*  .007  Sharer‐Receiver Relationship   .271  .083     3.27**  .222  Structure and Hierarchy      .650  .098     6.60***  .218  Task Uniqueness      .255  .073     3.51**    Willingness to Share      .183  .100     1.82  .065  Sense of Self‐Worth      ‐.608  .130    ‐4.67***  .108  KM Strategy: Organisation    ‐.298  .094    ‐3.16**  .016  KM Strategy: Individual      ‐.307  .108    ‐2.86**  .016  Social Network        ‐.197  .087    ‐2.28*  .042  Pay Satisfaction        .410  .070     5.85***  .162  Procedural Justice      ‐.216  .077    ‐2.82**  .007  Image          ‐.218  .090    ‐2.42*  .032  Culture           .289  .118     2.45*  .178  Constant        5.058  .510     9.92***        Notes: *p<.05, **p<.01, ***p<.001; N = 72; F(16, 55) = 9.32, p<.001; R2 = .7306, Adj R2 = .6523.   

5. Assessing the impact of organisational velocity  With  origins  in  physics,  centrifugal  or  centripetal  forces  can  also  be  applied  to  conceptual  behaviours  to  represent an effect (LaLiberte 2009). Organisational Velocity as a centrifugal force moderates the significance  of a construct with the outcome of decreasing sharing behaviour, moving away from the knowledge sharing  core inter‐sectional point as illustrated in Figure 1. By contrast, Organisational Velocity as a centripetal force  moderates the significance of a construct increasing knowledge sharing behaviour, pulling towards the centre  of the model. To determine impact, data for Firm A with its established high Organisational Velocity context  was removed, analyses repeated and compared.    From a correlation perspective, Motivation to Share has a significant relationship with Organisational Velocity  in  terms  of  the  Power  construct  which  affects  tacit  and  explicit  knowledge  sharing  as  a  centrifugal  force.  A  significant relationship is also observed within Opportunities to Share, impacting the Time construct for both  knowledge  types  centrifugally.  The  same  factor  is  influenced  with  the  Social  Network  construct  for  tacit  knowledge sharing only and as a centripetal force.     At  regression,  the  Nature  of  Knowledge  and  Culture  reveal  no  significant  relationship.  Constructs  within  Motivation to Share and Opportunities to Share are primarily impacted centrifugally, alongside the centripetal  affect of Knowledge Ownership: Department (Motivation to Share) on explicit knowledge and Social Network  influence  on  tacit  knowledge  (Opportunities  to  Share).  The  Nature  of  the  Individual  is  only  impacted  centrifugally.  High  Organisational  Velocity  affords  a  greater  range  of  impact  by  factor  for  tacit  knowledge  sharing but a greater number of constructs are moderated for explicit sharing. The centrifugal affect is notably  strong  for  Allocentric  Personality,  Time  and  Intention  to  Share.  Synthesising  overall  findings,  the  conceptual  framework is revisited in Figure 2.    These  findings  surface  issues  of  knowledge  ownership  and  personal  versus  organisational  knowledge  management strategies. It is inferred that in uncertain and dynamic circumstances, dimensions which would  be  expected  to  benefit  knowledge  sharing  practice  are  militated  or  indeed,  reversed.  It  is  opined  that  actor  focus orientates towards knowledge protection rather than its transfer. Aligning with the “accelerated growth”  of  personal  knowledge  management  (Cheong  2011,  iii)  and  increasing  middle  line  influence  (Janczak  2004), 

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Sally Eaves  opportunities  such  as  time  availability  or  the  benefits  of  social  network  membership  may  be  utilised  for  individual rather than organisational gain.  

Figure 2: Revised multidimensional model of individual knowledge sharing influences  

6. Conclusions and benefits of study  The Multidimensional Model of Individual Knowledge Sharing Influences advances Ipe’s (2003) framework by  affording breadth and cross‐disciplinary coverage. A plethora of constructs related to Motivation to Share, the  Nature of Knowledge, Opportunity to Share, Culture and Nature of the Individual are significantly associated  with sharing behaviour across all operators. The model progresses from conceptual explication to exploratory  empirical  assessment  with  the  variance  explained  by  the  regression  models  notably  strong,  particularly  for  tacit  knowledge.  Differences  in  practice  are  identified  based  on  knowledge  type,  supporting  the  tacit  and  explicit distinction utilised.     Consideration  of  the  impact  of  context  is  afforded  through  development  and  exploratory  validation  of  the  original conceptualisation of Organisational Velocity. Differences in sharing norms were observed in the high  velocity  context  of  Firm  A  as  opposed  to  the  other  operators,  with  reduced  sharing  identified  through  constructs within the Motivation to Share, Opportunities to Share and the Nature of the Individual factors. This  demonstrates its moderating capability, primarily as a centrifugal force.     The study findings affirm its justification: knowledge sharing is too complex a process to be explained by one  or  a  few  factors  in  isolation  or  by  a  specific,  narrow  focus  on  tacit  or  explicit  knowledge.  Further,  continual  episodic change, central to the definition of Organisational Velocity, is interpreted to exert a notable impact at  the  individual  level  with  expansive  consequences  for  intra‐organisational  knowledge  sharing.  This  increased  understanding  of  the  driving  and  restricting  influences  affecting  individual  sharing  behaviour  can  support  provision of enabling conditions. It can also benefit the design and facilitation of knowledge management and  strategic change management interventions. 

7. Limitations and future direction  This  study  captures  the  individual  influences  impacting  knowledge  sharing  at  a  particular  point  of  time.  Repeating  the  research  process  at  staged  intervals  would  provide  an  opportunity  to  develop  longitudinal  enquiry,  fully  examining  the  orientation  and  strength  of  causal  relationships  and  changes  in  Organisational  Velocity  over  time.  Research  could  then  be  developed  to  operationalise  the  direction  and  magnitude  of  Organisational Velocity changes as vectors. Further, it would be utile to explore the impact of this dimension in  contexts of varying levels of knowledge intensity and to examine Functional and Role Velocity as potential sub‐ components. Case study and ethnography could be employed to support this process. The exploratory findings 

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Sally Eaves  from  this  work  therefore  provide  a  catalyst  for  the  direction  of  future  research  and  the  management  of  intense organisational conditions in praxis.  

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Simulation of Space Operation ‐ A Study on Learning in Control  Rooms  Anandasivakumar Ekambaram1, Brit‐Eli Danielsen2, Liz Helena Froes Coelho2 and Trine  Marie Stene2  1 SINTEF, Trondheim, Norway  2 NTNU Samfunnsforskning AS/CIRiS, Trondheim, Norway  siva@sintef.no  brit‐eli.danielsen@ciris.no  Liz.coelho@ciris.no  Trine.stene@ciris.no    Abstract: Simulation is one of the ways to promote learning in organizations. Learning constitutes several aspects, and one  such aspect is reflection. This paper looks at the role of reflection in and around the simulation process. In other words,  this  paper  looks  at  the  role  of  reflection  and  learning  in  simulation.  This  paper  is  based  on  a  study  that  is  a  part  of  a  research project called the N‐USOC project. The Norwegian User Support and Operations Centre (N‐USOC) is one of nine  European control centres for European Space Agency's (ESA's) payload and science operations on‐board the International  Space  Station  (ISS).  These  USOCs  (User  Support  and  Operations  Centres)  are  located  in  Belgium,  Denmark,  France,  Italy,  Germany,  Netherlands,  Norway,  Spain  and  Switzerland.  In  order  to  work  on  console  the  operator  has  to  go  through  a  certification  process.  Simulation  is  applied  as  an  important  part  of  the  training,  when  the  new  employees  are  to  be  certified.  Experienced  employees  also  participate  in  simulation  sessions  in  order  to  prepare  themselves  for  a  specific  experiment. ESA and NASA arrange the simulation sessions. One simulation is studied, where the major participants of the  simulation‐session are: (1) N‐USOC: User Support and Operations Centre in Norway (2) MUSC: This is an USOC in Germany  (3)  COL‐CC:  Columbus  Control  Centre  (Col‐CC)  is  ESA's  control  centre  that  has  responsibility  for  the  European  module  Columbus on ISS (4) POIC: Payload Operations Integration Centre (POIC) is NASAs control centre responsible for payload  operation on ISS. This paper uses qualitative and quantitative methods to study the simulation sessions with the focus on  the  topics  of  reflection  and  learning.  Reflection  ‐  when  it  is  considered  in  connection  with  a  professional  action  that  an  organizational  member  participates  ‐  can  be  viewed  as  reflection‐on‐action  and  reflection‐in‐action.  It  is  interesting  and  important to look at these two processes with respect to learning through simulation, because these two processes would  lead to understand more on how participants of simulation make sense of the learning process, and how they learn and  create knowledge. This understanding is useful in order to make possible improvement in the simulation sessions in the  future.     Keywords: learning, simulation, space operation, reflection, sense making 

1. Introduction Learning  is  considered  as  a  means  for  organisations  to  obtain  sustainable  competitive  advantage.  In  this  regard,  it  is  relevant  to  mention  learning  related  theories,  such  as  learning  organizations  (Senge,  1990)  and  resource‐based  theories  (Prahalad  &  Hamel,  1990).  Learning  can  manifest  in  various  forms,  for  example,  creating  new  knowledge  and  sharing  existing  good  practices.  Learning  can  happen  in  individual,  group  and  organizational levels (Crossan et al., 1999).    Different kinds of mechanisms are used to promote and facilitate learning in organizations. In this paper, we  shall  look  at  simulation  as  a  learning  mechanism:  How  a  group  of  people,  some  of  them  are  geographically  scattered  and  located  in  different  control  rooms,  learn  space  operations  through  simulation.  This  learning  process  constitutes  several  aspects.  We  shall  look  at  this  learning  process  primarily  from  the  stand  point  of  reflection.     The purpose is to study the participant’s reflection and learning with respect to a simulation session. In other  words, we study the role of reflection and learning in a simulated learning situation.  This paper has the following structure:  ƒ

The context: Contextual information connected to the study on which this paper is based. 

ƒ

Theoretical framework 

ƒ

Research methods 

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Results and discussion 

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Concluding remarks  

2. The context  2.1 Space operations  The International Space Station (ISS) is a habitable space station in low Earth orbit (between 330 and 435 km  above the Earth surface). The station has been continuously occupied by humans since November 2000.     The  ISS  programme  is  a  joint  project  among  five  participating  space  agencies:  the  American  National  Aeronautics  and  Space  Administration  (NASA),  the  Russian  Federal  Space  Agency  (Roscosmos),  the  Japan  Aerospace  Exploration  Agency  (JAXA),  the  European  Space  Agency  (ESA),  and  the  Canadian  Space  Agency  (CSA).  The  ownership  and  use  of  the  space  station  is  established  by  intergovernmental  treaties  and  agreements.    The ISS serves as a unique microgravity and space environment research laboratory in which crew members  conduct experiments in biology, human biology, physics, astronomy, meteorology and other fields. The station  is also suited for the testing of spacecraft systems and equipment required for missions to the Moon and Mars.  ESA’s laboratory on‐board the ISS is a module called Columbus.    ESA has chosen a decentralized Ground Segment for its payload and science operations on‐board the ISS, by  the use of User Support and Operations Centres (USOCs). Under the overall management of ESA, the European  User  Support  and  Operations  Centres  (USOCs)  act  as  the  link  between  the  scientific  user  communities  and  ESA's  Columbus  Control  Centre  (Col‐CC)  in  Oberpfaffenhofen,  Germany,  NASA's  Payload  Operations  Integration  Center  (POIC)  in  Huntsville,  Alabama,  and  the  Russian  Mission  Control  Centre  in  Moscow.  These  USOCs are located in Belgium, Denmark, France, Italy, Germany, Netherlands, Norway, Spain and Switzerland.  The Norwegian User Support and Operations Centre (N‐USOC) is one of these nine European control centres.  The  mission  of  N‐USOC  is  to  provide  qualified  support  to  the  ISS  microgravity  research  activities  in  general.  Specifically,  N‐USOC  is  responsible  for  two  payloads  in  the  Columbus  module;  the  European  Modular  Cultivation System (EMCS) and the Vessel ID System (VIS).    During operations N‐USOC personnel is on console to monitor and control the payloads and associated crew  operations 24/7. The operations require close cooperation with other control centres, as well as engineering  support  and  science  teams.  In  order  to  have  the  necessary  qualifications,  the  console  personnel  have  to  go  through specialized training and certification (Danielsen & Stene, 2013).  

2.2 Simulations in space operations  Simulation is an important part of the training and certification process of console operators that monitor and  control equipment on‐board the ISS. The simulations are “live”, which means the actual players use genuine  systems  in  a  real  environment  (Classification  of  simulations  as  it  is  used  by  the  American  Department  of  Defence Modelling and Simulation Coordination Office (M&S CO)).    For N‐USOC operators, “live” simulations imply that simulation sessions are performed in the N‐USOC control  centre, using the same tools and interacting with control centres internationally just as is done for real‐time  operations.  In  this  environment  the  trainees  will  spend  time  learning  valuable  lessons  in  a  "safe"  virtual  environment yet living a lifelike experience.     In addition to the mandatory training provided in the N‐USOC training program, the trainees are responsible  for their own preparation before the simulations. After the simulation there will be a debrief and an evaluation  of  the  trainees  performance  is  given.  Evaluation  gives  important  feedback  for  the  trainee  to  improve  performance, and is also the basis for the formal certification. 

2.3 A specific simulation of an experiment to be executed on‐board the International Space  Station (ISS)  The simulation being focused in this study is a Joint Multi‐Segment Training (JMST). The JMSTs are defined as  simulations  under  the  responsibility  of  NASA,  where  in  addition  to  the  NASA  Payload  Operation  and 

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Anandasivakumar Ekambaram et al.  Integration Center (POIC) all other relevant payload control centres and training facilities are involved. JMSTs  are  high‐fidelity,  flight‐specific  simulations  across  various  station  segments  to  practice  communications  and  coordination among the different centres, sometimes including the Mission Control Center in Houston (MCC‐ H) and crew (or surrogate).     The  simulation  was  held  on  February  21  2013,  and  in  addition  to  POIC,  ESA  and  JAXA  control  centres  participated.  For  this  study  we  focused  on  the  participants  from  the  control  centers  involved  in  the  future  execution of the ESA experiment Gravi2. The Gravi2 is a biology experiment that will use several facilities on  the ISS, and therefore will need the interaction of several centres responsible for the different facilities.    Figure  1  shows  the  control  centres  participating  in  the  simulation.  In  addition  to  the  crew,  the  following  centres were involved in Gravi2 operations during this JMST: NASA POIC (Payload Operation and Integration  Center), ESA Col‐CC (Columbus Control Centre), N‐USOC and MUSC (Microgravity User Support Centre).     N‐USOC  is  the  overall  responsible  for  the  Gravi2  operations,  being  responsible  for  the  science,  operations  planning and one of the facilities involved. The N‐USOC control centre are manned with two operators during  the experiment execution: one is responsible for the EMCS facility (EMCS Ops working towards POIC) and the  other is responsible for the science, planning and all operations outside the EMCS facility (N‐USOC Ops working  towards Col‐CC).    Before the actual simulation session, a chart with the responsibility sharing between the teams was distributed  to all centres involved to make sure they were all on the same page.  

Figure  1:  Gravi2  Joint  Multi‐Segment  Training  operations  interface.  The  boxes  represent  different  ground  operators. The black boxes represent the operators from the NASA POIC. The white boxes represent  the  operators from  the  ESA Col‐CC.  The  light  grey  boxes  represent  the operators  from  the  USOCs  involved (N‐USOC and MUSC). The astronaut assigned to this operation is represented by the grey  box on the top. The communication between the centres is outlined by the arrows 

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Anandasivakumar Ekambaram et al.  The trainees participating from N‐USOC were certified console personnel. The goal for the simulation session  was to prepare and train with all centres involved in the Gravi2 operations as well as generic training for the  operators.     The  preparation  for  the  simulation  started  with  classroom  lessons  about  the  Gravi2  science  and  operations.  The N‐USOC participants went through the timeline with the specific activities being simulated. In addition, the  following topics were covered: anomaly reports, lessons learned from past operations, and “What‐If” scenarios  for Gravi2.    Just  after  the  simulation,  debrief  with  all  the  participants  were  held  by  the  NASA  simulation  director.  The  participants got feedback about their performance and the major issues were discussed. The N‐USOC training  manager also performed an internal debrief the day after the simulation, where the focus was on the N‐USOC  performance, challenges and improvements.  

3. Theoretical framework  Theories related to learning in organizations have cognitive and behavioural dimensions (Fiol & Lyles, 1985).  When it comes to looking at learning in simulation or in simulation related mechanisms, such as serious games,  the focus has been primarily on individual learning: How the individual's cognitive framework changes in order  to carry out new pattern of behaviour that corresponds to the expected effect of the learning process. Though  the learning has both cognitive and behavioural aspects attached to it, we shall consider mainly the cognitive  aspect of learning. In this regard, it is important to look at the concept of reflection.     Boud et al. (1996) suggest that reflective skills are needed in order to turn an experience into learning. When  reflection is considered in connection with a professional action that an organizational member participates,  then it can be viewed as reflection‐on‐action and reflection‐in‐action (Schön, 1998). Reflection‐on‐action is a  process  in  which  the  individual  reflects  on  his  or  her  past  experience  or  on  a  future  act  deliberately  or  unintentionally.  Reflection‐in‐action  is  a  process  in  which  the  individual  reflects  on  what  he  or  she  is  experiencing  while  he  or  she  is  engaging  in  the  activity.  It  is  interesting  and  important  to  look  at  these  two  processes (reflection‐on‐action and reflection‐in‐action) with respect to learning through simulation – How do  the participants of simulation make sense of the learning process?     Argyris  and  Schön  discuss  about  learning  as  understanding  and  eliminating  the  gap  between  the  expected  result  and  the  actual  result  of  an  action  (Argyris  &  Schön,  1996).  When  an  unexpected  result  of  an  action  occurs,  it  will  create  surprise  for  the  person  who  has  taken  that  action.  In  a  learning  situation,  this  surprise  tends to create reflection on what has happened with respect to the expectation. This is a way of making sense  of  the  experience.  Hence,  the  person  thinks  retrospectively  and  finds  cues  to  make  sense  of  his  /  her  experience. This sense‐making can lead to actions that can eliminate the gap between the expected result and  the actual result.     Weick (1995, page 45) mentions that in order to understand sense‐making, one has to understand how people  cope with interruptions. He says: "The reality of flow becomes most apparent when that flow is interrupted. An  interruption  to  a  flow  typically  induces  an  emotional  response,  which  then  paves  the  way  for  emotion  to  influence  sensemaking.  It  is  precisely  because  ongoing  flows  are  subject  to  interruption  that  sensemaking  is  infu