ENoLL Research Day Conference Proceedings 2015

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Research Day Conference proceedings 2015 OpenLivingLab Days


The “Research Day – Conference proceedings 2015” reports findings presented during the OpenLivingLab Days 2015, annual summit of the Living Lab community held in Istanbul from the 25th to the 28th of August. Now in its third edition (first call for academic contributions was launched in 2013), this publication is the result of the Call for Papers launched in December 2014 and tackles some of the numerous Living Lab related challenges recently investigated by scholars and practitioners around the world.

ISBN (e-book): 9789082102741

© 2015 ENoLL - European Network of Living Labs All rights reserved


Table of Contents Living Lab theory and thematic domains (session I) “Enhancing Co-Creation with Privacy and Security-by-Design methodologies”, Francesco Alberti and Sauro Vicini…………………………………………………………………………………………..7 “Living Labs: a systematic literature review”, Dimitri Schuurman, Lieven De Marez and Pieter Ballon………………………………………………………………………………………………………….16 “Living labs as a mean to spur collaboration and innovation in a tourist destination”, Dominic Lapointe, David Guimont and Alain Sévigny……………………………………………………….……29 “Girls Making History Summary Report Communities and culture network funded research pilot”, Penny Evans and Roz Hall………………………………………………………………………….….41 “Smart City Living Lab – city as a place”, Maija Bergström…………………………………………..…47

Living Lab Theory and tools (session II) “The wearable Living Lab: how wearables could support Living Lab projects”, Tanguy Coenen, Lynn Coorevits & Bram Lievens……………………………………………………………………………….57 “Change Laboratory as a method of innovation management in an Urban Living Lab”, Virpi Lund and Soile Juujärvi……………………………………………………………………….…………………68 “Involvement of end-users in innovation process: towards a user-driven approach of innovation – A qualitative analysis of 20 Livings Labs”, Perrine VANMEERBEEK, Lara VIGNERON, Pierre DELVENNE, Benedikt ROSSKAMP, Mélanie ANTOINE…………………………………..…...…..79 “A hypothesis driven tool to structurally embed user and business model research within Living Lab innovation tracks”, Ruben D’Hauwers, Olivier Rits, Dimitri Schuurman, Pieter Ballon………………………………………………………………………………………………………………..…87 “Living Labs As Innovation Platforms: The Key Constructs”, Christ Habib, Westerlund and Leminen, S……………………………………………………………………………………………………………98 “Getting personal – Exploring the usage of persona in order to optimize the involvement of a living lab panel”, Sara Logghe………………………………………………………………………………………….115


Living Lab cases (session III) “Care Living Labs Flanders: Social and Open Innovation”, Mark Leys, Lukas Versteele and Lien Pots…………………………………………………………………………..………………………………….125 “Experimenting with location-based service applications: exploring a new methodology for Living Labs”, Uschi Buchinger, Heritiana Ranaivoson, Pieter Ballon and Karel Verbrugge............137 “Organisation of labour, quality of work, and relational coordination in Care Living Labs”, Leen De Kort, Ezra Dessers, Geert Van Hootegem…………..……………………………….……………….148 “Creating a Smart City Vision in a Living Lab – Case Study of Smart Kalasatama Vision-building Process”,Veera Mustonen……………………………………………………………………………………….156 “Use of Living Lab in Innovative Public Procurement: Case Keyless Home Care”, Lotta Haukipuro, Torvinen Hannu, Väinämö Satu, Mattila Pasi…………………………………………168 “Towards a sustainable panel-based living lab approach in older adult care innovation”, Juul Lemey, Charlotte Brys, Koen Vervoort, Patricia De Vriendt and An Jacobs..........................180


Review panel

Chair Pieter Ballon

Reviewers Ana Garcia Tuija Hirvikoski Marita Holst Piotr Krawczyk Seppo Leminen Artur Serra Anna Ståhlbröst James Stewart Shenja van der Graaf


Living Lab theory and thematic domains Session I

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Enhancing Co-Creation with Privacy and Security-by-Design methodologies Francesco Alberti a, Sauro Vicini a a

City of the Future Living Lab, Fondazione Centro San Raffaele, Milan, Italy {alberti.francesco, vicini.sauro}@hsr.it

Abstract The definition and the analysis of privacy and security requirements is a major challenge in the product/service/software lifecycle, given both the complexity of security and privacy concepts and their being process-dependent. In this paper we present a new requirement analysis process, SPACE, aiming at involving the end users in the privacy and security requirement analysis phases. Supported by practical tools arranged in a pipeline, our process allows tackling privacy and security requirements from the early beginning of the product/service/software lifecycle. To provide a clear evidence of the applicability and effectiveness of such methodology, this paper reports the outcome of the application of SPACE within our City of the Future Living Lab, in the context of developing systems for handling sensitive data. Keywords co-creation, living lab, privacy-by-design, security-by-design. 1 Introduction The participation of end users to the creative phases of technological innovation is of vital importance in order to deploy high-quality services meeting their needs (Vicini, Bellini, & Sanna, User-Driven Service Innovation in a Smarter City Living Lab, 2013). Their role is even more important when sensitive data come into play. Indeed, in this setting, in addition to the quality of the services provided, another dimension arises: the one of trust. It has been widely shown the ultimate importance to adopt Privacy- and Security-byDesign (PSbD) methodologies in order to achieve higher quality requirements leading to development of more robust products (see, e.g., (Shostack, 2014)). Unfortunately, however, in such methodologies the elicitation of security and privacy requirements is either intended mainly as an expert-only task or, in the best cases, it is not supported by any practical tool favoring the end-users co-design of the system. The outcome is that the final product might not meet the user requirements in terms of trust, not conveying the necessary confidence that is required in critical domains where sensitive data are handled.

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In this paper we present the SPACE process, where SPACE is an acronym for Security and PrivAcy CodEsign. SPACE is a new process that is becoming part of the Co-Creation process of the City of the Future Living Lab (Vicini, Bellini, & Sanna, The City of the Future Living Lab, 2012). In this paper we introduce the process and discuss the practical tools devised to apply it for the direct involvement of the end users in the elicitation of privacy and security requirements. The main strength of SPACE is its being supported by practical tools for the identification of feared events, based on which privacy and security requirements can be derived. The tools supporting SPACE have been devised with the goal of engaging the end-users in their usage during workshops, working groups or brainstorm sessions. The advantages brought by adopting SPACE in the development of a new software system are threefold. First, increasing the customers’ trust in the deployed product. Users’ trust in the system plays a central role in achieving confidence and success on the market. Estimating the needs of the users in terms of trust towards the final product is important for developing a product achieving high-level of satisfaction from the customers’ point of view, especially when the system under deployment will deal with sensitive data in untrusted environments (Pearson, 2009). Second, the analysis of the feared events and threats is one of the main ingredients of a PSbD methodology. In this process, undesired events such as theft or malicious/accidental modification of data, disclosure of data to untrusted third-parties, etc., are taken into account for a privacy and security initial assessment that will lead to the definition of privacy and security requirements (Notario, et al., 2014). Such process strongly benefits from the stakeholders’ inputs, providing new points of view on the possible undesired scenarios that might come true once the system will be deployed and running on the market. Third, privacy and security requirements will be analyzed very early in the product/service/software lifecycle. The definition and the analysis of privacy and security requirements is usually addressed after the definition of functional requirements, because it is generally perceived as a process-dependent task. The major drawback of addressing security and privacy after having defined the functionality of the system is that security and privacy requirements most likely influence the functional part of the system under development, requiring their re-definition. Iterative methodologies allow achieving high-level quality results, but at the same time might require several iterations to converge. Our procedure reduces significantly the number of iterations, and at the same time allows achieving fully satisfactory results in terms of requirements definition. As we show in this paper, privacy and security can be addressed in the early stages of the requirement analysis phase. This helps in setting-up a clear picture, in terms of security risks and privacy threats, where functional requirements will be developed in light of preserving security and privacy qualities, which are key needs for applications dealing with sensitive data and/or untrusted third parties, especially nowadays where distributed cloud architecture, generally perceived as untrusted environments, are offering an always more cost-effective environment for deploying end-users services. 2 The SPACE process The SPACE process can be viewed as part of the Co-Creation methodology of the City of the Future Living Lab (Vicini, Bellini, & Sanna, User-Driven Service Innovation in a Smarter City Living Lab, 2013). With SPACE we identified the concrete steps and participative tools supporting the Scenario Analysis part of the PRIPARE methodology (Notario, et al., 2014), one of the most advanced privacy-by-design methodology that has been developed so far. SPACE is structured in four phases: “Scenario Definition”, “Input Data Identification”, “Stakeholders’ Goals and Data of Interest Analysis” and “Threats and Feared Events Investigation”. Such phases are arranged as shown in following picture, 8

which highlights also the tools/tasks required, and will be described in more details in the following sections.

Scenario De+inition

Input Data Identi+ication

•  Co-­‐Design tools •  Interviews •  SOTA investigation

•  List of relevant data-­‐ types handled in the system

Stakeholders' Goals and Data of interests Analysis •  Stakeholders' Goals table (Table 1)

Threats and Feared Events Investigation •  Feared Events table (Table2)

2.1 Scenario definition This phase targets the definition of the application scenario. During this phase, stakeholders will be identified via an incremental process: as the scenario is generated and enriched of details, new stakeholders may appear. A practical tool widely adopted in the Co-Creation methodology to achieve this goal is the interview. As widely known, interviews do not follow strict templates and have to be adapted case by case (see, e.g., (Stickdorn & Schneider, 2012; Fox, 2009)). In this phase, the interviews have to target the elicitation of the so-called “needs and pain-points” of the users, i.e., highlight the missing services and those services which need a substantial re-design. Despite the interviews are very effective tools for eliciting the end-users requirements, other co-creation tools (like focus-groups, workshops, brainstorming sessions, etc.) can be exploited here, if needed, for having a better picture of the scenario. The analysis of the state-of-the-art (SOTA) is also required at this step and complements the aforementioned tools. The output of this phase is a textual description of the scenario. 2.2 Input data identification The definition of the scenario will naturally allows the identification of the set of input data of the system, i.e., the data that will be provided by the stakeholders. Notably, once the scenario with its stakeholders and data into play has been defined and the set of input data has been identified, a first privacy and security assessment investigation can be performed, e.g., by identifying which kind of data needs ad-hoc countermeasures because of their high sensitiveness which is protected by the law. At this stage, inputs from legal/ethics experts would be beneficial to identify important requirements arising from the handling of particular data. 2.3 Stakeholders’ goals and data of interest analysis The two previous phases generate the elements that are fed into the third phase of the SPACE process, devised for the analysis of stakeholder’s goals and their data of interest. The following table, Table 1, is the template for carrying out such analysis. It is a table clearly and precisely summarizing the list of stakeholders, their goals and the set of data they are interested in. Notably, new data-types may be defined here (for a practical example see the case study presented in Section 3). The importance of filling-in this table is that it will highlight the data of interest of each stakeholder according to their goals. The usage of this data without privacy and security countermeasures, however, may violate some privacy or security principle. It is therefore of vital importance characterize the highlevel goals of the stakeholders and identify the data they need to provide their service, in order to consider the circumstances in which privacy or security breaches might occur. 9



Data of interest

Table 1: The “Stakeholders’ Goals table” template, used for analyzing stakeholders’ goals and data of interests.

As a side effect, upon completion, this table offers a double-checking tool for identifying weaknesses of the two previous phases. That is, it allows to double check whether all the input data that have been defined will be of interest for at least one stakeholder and whether all the stakeholders will have a clearly defined goal. 2.4 Threats and Feared events investigation The table with the list of stakeholders, their goals and data of interest is fed into this phase. This phase is also parameterized by a set of threats that are pre-defined and can be tailored according the privacy and security facets of greater interest. In our application scenario, we exploited the privacy and security properties listed in the LINDDUN (Deng, Wuyts, Scandariato, Preneel, & Joosen, 2011) and STRIDE (Howard & Lipner, 2006) threats categories. The LINDDUN threats category, also exploited in the PRIPARE methodology, comprises seven threats, each associated to a privacy property. The LINDDUN privacy properties are: 1. Unlinkability: hiding the link between two or more actions, identities, and pieces of information. 2. Anonymity: hiding the link between an identity and an action or a piece of information. 3. Plausible deniability: ability to deny having performed an action that other parties can neither confirm nor contradict. 4. Undetectability: hiding the user’s actvities. 5. Confidentiality: hiding the data!content or controlled release of data content. 6. Content awareness: user’s consciousness regarding his own data. 7. Policy and consent compliance: data controller to inform the data subject about the system’s privacy policy, or allow the data subject to specify consents in compliance with legislation. Each privacy property is associated to a threat: Linkability, Identifiability, Nonrepudiation, Detectability, Disclosure of information, Unawareness, and Non-compliance. For security properties, we focused STRIDE threats category. The STRIDE privacy properties are the following: 1. Authentication: establishing the author of an action performed in the system. 2. Integrity: ensuring that data will not be (accidentally or maliciously) modified or deleted. 3. Non-repudiation: providing unforgeable evidence that a specific action occurred. 4. Confidentiality: avoiding the disclosure to unauthorized third parties of the information stored in the system or exchanged between two parties within the system. 5. Availability: the property of being accessible and useable upon demand by an authorized entity. 6. Authorization: regulating the permits of the system users.


The corresponding security threats are: Spoofing, Tampering, Repudiation, (Information) Disclosure, Denial of Service, and Elevation of Privilege. The investigation of threats and feared events consists in determining whether each stakeholder may violate a security or a privacy property by exploiting the associated threat on some data of their interest. In this phase, the active role of the stakeholders is strongly beneficial and of vital importance, as each stakeholder may identify possible undesired events that may become reality. Furthermore, in this table we add a new stakeholder that is the UIP, Untrusted Infrastructure Provider. The UIP represents an abstract stakeholder, and is required if the service will run in an untrusted environment, e.g., a cloud service: in this case, the infrastructure provider has to be considered untrusted to allow the identification of countermeasures to avoid any malicious behavior from its side. The outcome of this phase will be a table will fill a table, as the one displayed in Table 2. Stakeholder Threat

Data involved

Feared Event

Security/Privacy requirements

Table 2: The “Feared Events table” template used for investigating Threats and Feared events.

In this phase the contribution of end-users and the stakeholders plays a central role in defining the feared events and, by consequence, the security/privacy requirements. This table reports the security and privacy requirements, i.e., countermeasures that have to be taken in order to avoid the threats. 3 Case study: A Cloud-based Service for Genomic Data Handling We applied SPACE in an on-going projects within our City of the Future Living Lab, which goal is to provide a secure and privacy-preserving service for handling genomic data in untrusted environments, widely recognized nowadays as key assets in devising costeffective and scalable solutions. The entire requirement elicitation process took only two months. The compiled “Feared Events table” constitutes a solid basis for the development of the future system services. For space reasons we intentionally report here only a shortened version of the outcome produced with SPACE in this scenario. 3.1 Scenario definition Genomic data are always playing a more important role in health environments, and will most likely be one of the fundamental pillars of the future P4 medicine service, i.e., the Predictive, Preventive, Personalized and Participatory health system (Hood & Flores, 2012). In particular, the availability of patients’ genomic data allows achieving a high-quality Personalized health service to the public. Given the computational complexity of the algorithms exploited by researchers for advancing the state-of-the-art in their research fields and support better diagnoses procedures, the adoption of massively parallel frameworks, like the cloud ones, provides a strategic cost-effective solution to achieve their goals. Given the intrinsic sensitiveness of the data into play, however, solid security and privacy-related countermeasures have been taken to avoid (accidental or malicious) loss, deletion, tampering or theft of data. The series of interviews we conducted within our City of the Future Living Lab allowed us to have a clear description of the scenario. The stakeholders we will take into consideration in this section are the patients, the doctors and the researchers (mainly working in the bioinformatics field). As stated previously, a default stakeholder (the UIP, Untrusted 11

Infrastructure Provider) will be also considered for eliciting privacy and security requirements. While patients and doctors are widely known actors, we will not enter into details explaining their role in the scenario. More words about researchers, instead, are in order. Within a hospital environment, researchers play several roles, which can be overall summarized in two main categories: they offer support to the doctors for some clinical analyses and investigate new solutions to open problems in their research fields. In our scenario, we will consider only the first set of tasks, i.e., those related to supporting clinical diagnostic-oriented decisions. In the field of genomic analysis, researchers (mostly in bioinformatics) analyze some mutations of the patient’s DNA and inform the doctor on the likelihood of the patient of developing some disease or their response to some drugs. In order to do that, they run some state-of-the-art algorithms on the sequenced DNA and interpret the outcome accordingly. These algorithms are generally very expensive from a computational point of view, and therefore they would extremely benefit from parallel architectures like the one offered by cloud infrastructure. 3.2 Input data identification In our case, since we restricted our scenario to a service providing a secure handling of genomic data from a clinical point of view, the system will receive as input data the identification data of the patients (name, surname, date of birth, etc.) and their DNA1. Researchers will also provide some algorithms and code for the automatic analysis of DNA. This is the third input data we expect: the code. 3.3 Stakeholders’ goals and data of interest analysis The third task of SPACE requires to complete the “Stakeholders’ Goals table”. Table 3 reports the outcome of this process for our case study. Stakeholder Patients

Doctors Researchers UIP

Goals Take advantage of Genomicbased medical treatments; know “ludic” information about their DNA. Cure patients; Diagnose diseases. Support the hospital staff. Selling a new service. Administrating the (untrusted) infrastructure on which the analyses are carried out.

Data of interest DNA, Ludic metadata, metadata.


Identification data, Clinical metadata. DNA Resource statistics (disk usage, network traffic, CPU load); System logs.

Table 3: The “Stakeholders’ Goals table” for our case study.

Notably, new data has been defined: Ludic and Clinical metadata and Resource statistics. These are different data generated by the system itself. Metadata are retrieved by analyzing DNA either directly from the researchers or indirectly by the system, if it will embody some data-mining procedure working on genomic data. Clinical metadata can be, e.g., the probability of developing a disease that can be retrieved from the DNA. Ludic 1

An extension is to consider also more health-related kind of data, e.g., the patients; EHR (Eletronic Health Record). This can be a viable extension, but will not be taken into account in this paper. 12

metadata refers to non-clinical information (e.g., color of the eyes, etc.). In addition, UIP will need resource statistics and system logs for administrating the service. 3.4 Threats and Feared events investigation The forth step of SPACE targets the generation of privacy and security countermeasures. The outcome of this process is reported in the following table, Table 4. As we stated before, we are reporting only a small fragment of the actual table that has been compiled in our case study. Stakeholder Threat

Data involved DNA

Feared Event

Unauthorized code modification or fabrication (intentional or unintentional) with the purpose of revealing sensitive data.


Data tampering


(Software) Tampering





Hospital staff


Undesired addition or modification of the data.

Full disclosure of DNA, affecting his/her relatives’ privacy. Clinical Patient does metadata; not have the Identification control on who data accesses his/her data.

Security/Privacy countermeasure The system must provide a trusted access-control schema to control the accesses and a module able to ensure the authenticity and integrity of data. The system has to provide means for checking the authenticity of the programs running in the Untrusted Infrastructure before executing it, ensuring their integrity. The system must ask the signature of the informed consent to the patients’ relatives. The system must track logs of all the access and allow the user to know who is accessing and when they are accessing their data.


Researchers Unawareness


Unauthorized research activity.

Researchers must sign an agreement specifying that they cannot perform research activity, if the patient did not allowed third parties research activities. The system must provide access to the minimum amount of DNA that is sufficient for a specific task.




Researchers Linkability


Knowing more things about the patient than the things the patient expect the researcher to know. “Blood-link” The system must between avoid direct patients. access to multiple DNA data that can lead to the “blood-link” discovery.

Table 4: The “Feared Events table” for our case study.

During our project we observed that such table can be compiled quite easily during workshops and brainstorming sessions, and allows the real elicitation of the end-users and stakeholders requirements. 4 Conclusion We presented SPACE, a new process for the elicitation of security and privacy requirements. The strength of SPACE is that it allows defining security and privacy requirements in the very early phases of a software lifecycle, avoiding refinement cycles between functional requirements and privacy/security ones. An added value of SPACE is that it also specifies simple and practical tools for engaging the end-users of the system directly in the requirement elicitation process. Thanks to this intrinsic feature, SPACE is a valuable extension of the Co-Creation methodology. SPACE has been evaluated experimentally within the City of the Future Living Lab within a new project targeting the definition of a new service dealing with genomic data. Such service badly demands for strong security and privacy requirements given the highly sensitive nature of the handled data. The evaluation has also been extended, as a proof-ofconcept, to other lighter scenarios, always needing some security and privacy requirements. In all such setting, SPACE allowed saving time. Furthermore, the cocreative nature of the process allowed achieving requirements that will likely lead to a high satisfaction of the end-users.


5 Acknowledgement The work described in this document has been conducted within the project WITDOM, started in January 2015. This project has received funding from the European Union's Horizon 2020 research and innovation programme (H2020-ICT-2014-1) under grant agreement No. 64437. This work was supported in part by the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract No. 15.0098. The opinions expressed and arguments employed herein do not necessarily reflect the official views of the European Commission or the Swiss Government. 6 References Deng, M., Wuyts, K., Scandariato, R., Preneel, B., & Joosen, W. (2011). A privacy threat analysis framework: supporting the elicitation and fulfillment of privacy requirements. Requirements Engineering , 16 (1), 3-32. Fox, N. (2009). Using Interviews in a Research Project. Nottingham: The NIHR RDS for the East Midlands / Yorkshire & the Humber. Hood, L., & Flores, M. (2012). A personal view on systems medicine and the emergence of proactive P4 medicine: predictive, preventive, personalized and participatory. New Biotechnology , 613-624. Howard, M., & Lipner, S. (2006). The Security Development Lifecycle. Redmond, WA, USA: Microsoft Press. Notario, N., Crespo, A., Kung, A., Kroener, I., Le Métayer, Troncoso, C., et al. (2014). PRIPARE: A New Vision on Engineering Privacy and Security by Design. Cyber Security and Privacy - Third Cyber Security and Privacy EU Forum, CSP Forum 2014, Athens, Greece, May 21-22, 2014, Revised Selected Papers (p. 65-76). Athens, Greece: Springer. Pearson, S. (2009). Taking Account of Privacy when Designing Cloud Computing Services. Proceedings of the 2009 ICSE Workshop on Software Engineering Challenges of Cloud Computing (p. 44-52). Washington DC: IEEE Computer Society. Shostack, A. (2014). Threat Modeling: Designing for Security. Indianapolis, Indiana: John Wiley & Sons. Stickdorn, M., & Schneider, J. (2012). This is Service Design Thinking: Basics, Tools, Cases. Wiley. Vicini, S., Bellini, S., & Sanna, A. (2012). The City of the Future Living Lab. International Journal of Automation and Smart Technology , 2 (3). Vicini, S., Bellini, S., & Sanna, A. (2013). User-Driven Service Innovation in a Smarter City Living Lab. International Conference on Service Sciences (ICSS) (p. 254 - 259). Shenzhen: IEEE.


Living Labs: a systematic literature review Dimitri Schuurman a, Lieven De Marez a & Pieter Ballon a a

iMinds/ iLab.o, Belgium dimitri.schuurman@iminds.be

Abstract This paper presents a systematic literature review of the body of scientific Living Labs literature. Based on a general review of the Google Scholar and Web of Science databases, we can conclude that the Living Labs movement in terms of theory and research has taken off since 2006 in quantity of published papers. However, in terms of quality and impact, the academic field of Living Labs is still rather insignificant. An analysis of the 45 most cited papers reveals that the practice-based side is much further developed than the theoretical side, with only few references to more established innovation theories such as Open Innovation and User Innovation, despite the fact that concepts from both literature streams are present in all papers. Strikingly, 18 out of 45 papers refer to no framework at all, remaining merely descriptive. There is also a lack of empirical, more quantitative and comparative studies that focus on the added value of Living Labs. This paints the picture of Living Labs as a research domain in development which calls for a better anchoring within more established innovation theories in order to advance the field. Keywords Living Labs, Open Innovation, User Innovation, Literature review, Innovation 1 Introduction The official birth of the European Living Labs movement is often situated in 2006, the year the European Commission officially declared its support by stimulating projects to advance, coordinate and promote a common European innovation system based on Living Labs (Dutilleul et al., 2010), and also the year in which the European Network of Living labs (ENoLL), was established an organization aimed at connecting Living labs for knowledge exchange, networking purposes and the development of a shared innovation concept (European Commission, 2013b). Despite the fact that Living Labs have been around for nearly a decade, in terms of conceptualization, the current literature stream is still inconsistent and sometimes contradictory. Følstad (2008a) identified nine living lab characteristics, of which five were diverging, which indicates a large variety of approaches being labeled as living lab. Moreover, a second literature review two years later by Dutilleul et al. (2010) revealed five different meanings given to discern living labs in the papers they studied: 1. an innovation system consisting of organized and structured multidisciplinary networks fostering interaction and collaboration; 2. real-life or ‘in vivo’ monitoring of a social setting generally involving experimentation of a technology; 3. an 16

approach for involving users in the product development process; 4. organizations facilitating the network, maintaining and developing its technological infrastructure and offering relevant services; 5. the European movement itself. Most recently, Westerlund and Leminen (2014) even found eight different perspectives on Living Labs. However, to this date, a structural and systematic analysis of the Living Labs literature is missing. Within this paper we wish to fill this gap by using a clear methodology for selecting and analyzing the current body of Living Labs papers and articles. This allows to identify the main perspectives and viewpoints on Living Labs and how they have been embedded within the more established innovation theories. 2 Methodology In order to get an overview of the State-of-the-Art of academic and empirical research into Living Labs, we conducted an exploratory review of the available literature. Hereto we constructed a sample of the most cited Living Labs papers. We used the Google Scholar academic search engine2 and looked for articles by using the search string “Living Lab” (end of October 2014). This yielded more than 6.500 results. Subsequently, we narrowed the number of articles down by only including articles where “Living Lab” was mentioned in the title in order to weed out the articles where “Living Lab” appeared ‘accidentally’ or only occurred on a side note. This resulted in 563 articles. From this sample, we chose to include only journal or conference papers (excluding books, book chapters, theses or other citations) with a direct link to the abstract and only articles with a citation count of more than 10. This led to a total sample of 45 articles (see attachments for the full list). In order to get an overview of the number of Living Labs papers in top ranked journal, we did a similar exercise in the Web of Science database, looking for all articles that had “Living Lab” in the title. This led to 50 articles in total. In the following table we give an overview of the total number of articles from our three searches, organized per year. In terms of time intervals, we used 2006 as an anchoring point, as this year marked the establishment of the European Network of Living Labs and more formal support for Living Labs from the European Commission. The papers published before 2006 were merged into one category, while we give an overview of the rest of the sample per year. Publication year

Articles in sample Articles in total (Google Scholar + (Google scholar) 10 citations)

WoS articles

Until 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Total

4 3 5 7 6 9 5 4 2 0 45

3 0 3 3 8 8 6 7 8 4 50

18 9 15 52 69 74 65 95 92 74 563

Table 1: Sample overview per year (October, 2014) 2

http://scholar.google.be/ 17

100 90 80 70 60 50 40 30 20 10 0

Scholar total Scholar +10 cit WoS total

Un.l 2006 2007 2008 2009 2010 2011 2012 2013 2014 2005 Figure 1: Living Labs papers evolution

In terms of the total articles, we see a clear ‘explosion’ of research after the establishment of ENoLL, somewhat similar to the growth of ENoLL itself in the first years. The years 2009-2011 seemed to mark a stagnation in the number of published papers, whereas 2010 was the top year of new Living Labs entering the network. However, as the number of new Living Labs started to drop significantly from 2011 onwards, the number of papers started to increase again in 2012 and seems to have stabilized again. What looks more problematic, is the evolution of papers that effectively generate impact. In terms of papers with a citation count of more than 10, no year has yielded more than 10 papers, with a maximum of 9 papers in 2010 being cited more than 10 times. In terms of Web of Science-papers, we also get the image of a research field ‘in development’. When we select all articles in the Web of Science database that have “living lab” in the title, this results in only 50 papers that have been published in journals (21) or conferences (29) that are abstracted in this influential database. This is only a fraction of the almost 600 papers with Living Lab in the title from the Google Scholar-search. Moreover, when we look at the citation count of these papers, only 2 have more than 10 citations in other WoS-publications: Wolfert et al. (2010) with 24 citations and De Moor et al. (2010) with 11 citations. The majority of the WoS publications (33) even has no citations at all. Moreover, the overlap with our Google Scholar most cited sample is rather scant, with only 8 papers appearing in both list (cf. also the attachments): Budweg et al. (2011), De Moor et al. (2010), Hlauschek et al. (2009), Liedtke et al. (2012), Schuurman et al. (2011), Svensson et al. (2010), Wadhwa (2012), and Wolfert et al. (2010). Therefore, we decided to continue our analysis with the top-cited Google Scholar articles. For the 45 Google Scholar papers with a citation count higher than 10 the total citation count is 1943, which means an average of 43 citations per paper. Only 5 papers are cited more than 100 times: Abowd et al., 2002 – 135 cit.; Eriksson et al., 2005 – 176 cit.; Niitamo et al., 2006 – 142 cit.; Almirall & Wareham, 2008 – 124 cit. and Følstad, 2008 – 182 cit. Note that none of these papers is also on the WoS. For Open Innovation, West & Bogers (2013) conducted a similar literature overview which resulted in 287 papers in SSCI journals (Web of Science papers), with the first 10 papers being cited at least 500 times, with Chesbrough’s book (2003) even cited more than 8000 times, and Chesbrough being (co-) author of most of the top-cited papers. The same is true when looking for literature with the terms ‘User Innovation’ and ‘lead user’, with von


Hippel as a dominant figure and easily more than 10 articles with over 400 citations, although the Open Innovation literature is clearly dominant in terms of quantity. Based on these general statistics, we can conclude that the Living Labs movement in terms of theory and research has taken off since 2006, at least in quantity of published papers. However, in terms of quality and impact, the academic field of Living Labs is still rather insignificant. Regarding the authors, 39 papers were authored by European scholars, five by American scholars and one paper originated from Australia (Third et al., 2011). This is further proof that the Living Labs field is clearly dominated by Europeans. However, there is not a single author very ‘dominant’ as in the Open and User Innovation literature, with five authors (Almirall, Wareham, Ståhlbröst, Eriksson and Feurstein) (co-) authoring 3 papers. This is also a further indication of a scattered research field. We will continue the rest of our analysis with the 45 Google Scholar 10+ cited papers. We chose to use this sample as it has some clear advantages. The selection criteria are clear and unambiguous, which enables later reproduction (e.g. for future comparative studies). Moreover, the sample size allows to have a more in-depth knowledge of all the papers, while at the same time representing a fair share of the total amount of papers (8%). However, we also acknowledge some limitations that come with our selection methodology. Papers that do not have “living lab” in the title are excluded (e.g. Ballon et al., 2007), although based on our knowledge of the literature, this has only a minor impact. Perhaps more impact is generated by including the criterion of 10+ citations. This tends to limit the inclusion of the most recent Living Labs papers, as it takes some time to get cited by even newer publications. However, this would raise the issue on how to measure or assess the quality of these more recent publications. Therefore, we chose to keep our initial criteria and propose future research should adhere to these criteria to include more recent literature that by that time has reached a significant degree of impact. 3 Results & discussion When going through all the papers, two important issues arise. First, only a small minority of the papers reports on well-grounded empirical research on Living Labs. The majority of the papers are descriptive single or multiple case studies, or conceptual papers relying on desk research, without a rigid methodology being used or explained. In our sample, 18 out of 45 papers are merely project descriptions with only limited conceptual value (Abowd et al., 2002; Baida et al., 2007; Schwittay, 2008, Hlauschek et al., 2009; Krieg-Brückner et al., 2010; Hess & Ogonowski, 2010; Budweg et al., 2011, Schuurman et al., 2011; Liedtke, 2012; Wadhwa, 2012; Schwartz et al., 2013; Ogonowski et al., 2013) or they describe a single case study where a ‘Living Lab approach’ is used, but without Living Labs themselves being the subject of the research (Haymaker & Chachere, 2006; Scott et al., 2009; Wolfert et al., 2010; Bliek et al., 2010, Ryu, 2010; Third et al., 2011). Remarkably, all American papers and the single Australian paper are to be found in this category, which is another indication that Living Labs are largely a European phenomenon. Also, the Ryu (2010) paper is the only downright negative paper in the whole sample, as it describes the power relations a large company can exert in the process of ICT introduction in developing countries. All other 44 papers approach Living Labs in a neutral or overtly positive way, which is an indication of the absence of a critical attitude towards Living Labs as a concept. In the Open and User Innovation literature we also encountered mostly positive case studies, but in both fields some critical papers have also emerged. To this day, no real ‘critical’ Living Labs paper has been published, which is a further proof of the rather low impact of the field in other literature streams.


Paper type Descriptive papers State-of-the-Art papers Conceptual & methodological papers Empirical paper

Number of papers 18 4 16 7

Table 2: Living Labs paper type

Subsequently, we can discern a category of four papers that contain multiple Living Lab cases, but merely as high-level descriptions and illustrations. First, we have the oldest paper from our sample by Markopoulos and Rauterberg (2000) who give an overview of the American Living Labs that were blossoming at that time, with also examples from this kind of Living Labs in Europe3. Next, we have the widely cited papers by Eriksson et al. (2005) and Niitamo et al. (2006) who give an overview of the developing European Living Labs field, also including some of the American examples. As a fourth paper in this category, we have Schaffers et al. (2007) who discern the Living Labs for rural development, which represents a new type of Living Labs that popped up in practice. Besides these four ‘state-of-the-art’ papers, we have a rather large sample (16 or just over 1/3 of all papers) that deal with methodological and conceptual contributions to Living Labs, based on single case studies or purely conceptual papers. Pierson and Lievens (2005), Kusiak (2007), Følstad (2008b), Levén and Holmström (2008), Feurstein et al. (2008), Schuurman and De Marez (2009), Bergvall-Kareborn et al. (2009a&b), Santoro and Conte (2009), Pallot et al. (2010) deal with user contribution and project methodologies for Living Labs. Some papers base themselves on more research data, such as Schumacher and Feurstein (2007) who report on a Living Labs survey, albeit in a very descriptive way. Mulder et al. (2007 & 2008, basically two times the same paper) report on a brainstorming exercise of Living Lab practitioners and map different methods and tools on a ‘harmonization cube’, while Svensson et al. (2010) base themselves on user contribution in more than 100 user interaction instances in three Living Lab projects to inventarize different methods. Ponce de Leon et al. (2006) and De Moor et al. (2010) deal with testbeds in the context of Living Labs, and how to intergrate these, with De Moor et al. (2010) dealing specifically with Quality of Experience as methodology which can support Living Labs and vice versa. However, only seven papers dig deeper into the Living Labs phenomenon with a larger sample, a more rigid methodological approach or a more in-depth analysis of the cases studied. First, there are two papers containing literature reviews: the Følstad (2008a) and Dutilleul et al. (2010), which we both touched upon briefly in the introductory section. Although their methodology for selecting the papers is not very clear, both articles have been referred to rather often. 3.1 Theoretical frameworks We also assessed which theoretical frameworks were used in the papers. Therefore we examined the theoretical and introductory parts of the paper and looked which frameworks or paradigms were mentioned as foundations for Living Labs. Building further on Schuurman et al. (2013), we looked for indications of the Open Innovation and User Innovation frameworks, and because of the influence of the cooperative design movement for the early Living Labs (Ballon & Schuurman, 2015), we also looked for indications of these literature streams. In practice, we looked at the occurrence of the ‘Open Innovation’, ‘User Innovation’, ‘user-centered design’ (UCD) and ‘participatory design’ (PD) 3

Note that the authors were also European and connected to a Dutch Living Lab. 20

expressions, but also for citations of prominent authors associated to the fields such as Chesbrough or von Hippel. The table below gives the numbers of articles where the proposed frameworks are used, together with the number of articles where none of the theoretical foundations were used. Paradigm Open Innovation User Innovation UCD / Participatory design None

N 11 17 19 18

Table 3: Dominant framework

Surprisingly, Open Innovation is only explicitly referred to in 11 papers. This can be explained by the fact that in a lot of these papers, terms like open collaboration, PublicPrivate-People partnership, or even Open Innovation are used without any referral to literature from the Open Innovation domain. A lot of the Living Labs papers seem to take the use of Open Innovation for granted, without reflecting in terms of the Open Innovation literature base or without apparent knowledge of this literature stream. Papers like Schuurman and De Marez (2009), Svensson et al. (2010) and Pallot et al. (2010) equal Open Innovation with user involvement and open collaborative innovation, something which was also discussed in West & Bogers (2013). In 18 articles, none of these frameworks was referred to, whereas 17 papers referred to the User Innovation literature. The UCD/PD framework is the most cited with 19 papers, which is an indication that the ‘cooperative design’ predecessor still has a large influence on the current Living Labs movement. Moreover, the large amount of papers without reference to these frameworks is remarkable, but also congruent with the previous finding that 18 papers within our sample are for the largest part descriptive without much attempt at theory building. Among the earlier papers with a reference to design thinking, we find especially American authors with references to participatory design and requirements-driven innovation (Abowd et al., 2002; Haymaker & Chachere, 2006; Kusiak, 2007). In Europe, the Scandinavian authors have maintained a strong connection between Living Labs and design thinking (Følstad, 2008a&b; Levén & Holmström, 2008; Bergvall-Kåreborn et al., 2009a). 3.2 Living Labs and Open Innovation Referring back to the initial goal for the promotion of Living Labs within the wider European innovation system, which was to help solving the European Paradox, or the imbalance between knowledge exploration and exploitation, we would also expect Open Innovation to be more prominent as framework for conceptualizing Living Labs. In order to ‘solve’ the European Paradox, Living Labs should be able to facilitate the process of exploitation. Therefore, we looked at the Living Lab definitions, and more specifically the goals that were mentioned for the Living Lab activities that were described in the paper. We coded all papers for the three Open Innovation processes of exploration, exploitation and retention (Lichtenthaler & Lichtenthaler, 2009; van de Vrande et al., 2009): Exploration: innovation activities to capture and benefit from external sources of knowledge to enhance current technological developments Exploitation: innovation activities to leverage existing knowledge or technological capabilities outside the boundaries of the organization Retention: maintaining, storing and reusing knowledge over time outside of an organization’s organizational boundaries 21

Besides the word exploration itself, we considered words such as experimentation, study (of user behavior), testing,… as indicators of exploration goals. For exploitation, we regarded words and phrases like ‘creating initial demand’, adoption, technology transfer, implement, and business models to refer to an exploitation goal. For retention, indicators such as knowledge and information sharing, multi-stakeholder communication and rethinking were used. Process Exploration Exploitation Retention

N 45 15 7

Table 4: Open Innovation processes

All papers (45) define Living Labs and Living Lab activities as an exploration of new knowledge, whereas only one out of three (15) mentions exploitation as a motive for Living Labs. This is a clear mismatch with the original intentions described in the Helsinki Manifesto (2006) of Living Labs as facilitators of knowledge exploitation. The exploitation motive of Living Labs is the most common in the more thematic Living Labs (e.g. Baida et al., 2007; Hlauschek et al., 2009; Wadhwa, 2012) or Living Lab projects where an innovative infrastructure is rolled out amongst a population (e.g. Schwittay, 2008; Ryu, 2010; Third et al., 2011; Bliek et al., 2010; Schwartz et al., 2013). The fact that knowledge retention is the least common is not a real surprise, as this process is also the least studied within the Open Innovation literature. The seven instances where retention was an explicit goal, were in thematic Living Lab constellations where stakeholders from a certain sector intend to collaborate and exchange knowledge regarding future opportunities (Baida et al., 2007; Wolfert et al., 2010), two projects aimed at sustainable innovation with the creation of user awareness (Scott et al., 2009; Liedtke et al., 2009), the literature review of Dutilleul et al. (2010) who refer to the regional knowledge sharing opportunities of Living Labs, and the two papers by Mulder et al. (2007 & 2008) that incorporate the outcomes of a brainstorming session of Living Lab practitioners in an attempt to create shared tool and methodology set for Living Labs. This is an indication of the imbalance in the attention for the Open Innovation processes in the current Living Labs literature. Moreover, the fact that only 11 papers explicitly refer to Open Innovation as a defining paradigm, but that in all papers references to knowledge transfers between actors can be found, suggests that Living Labs are emanations of Open Innovation. This calls for a better conceptualizing of Living Labs that allows to frame them in terms of Open Innovation. 3.3 Living Labs and User Innovation We now turn over towards the appearance of User Innovation within our sample of Living Labs papers. As within the Living Lab definitions user involvement and user co-creation are essential characteristics, we looked in our sample for the degree of this user involvement. As key framework, we chose the categorization of Kaulio (1998), who discerns innovation/design for, with and by users. Design for denotes an innovation approach where user involvement is limited to passive user feedback, gathered through Voice of the Customer-methods or user behavior studies, as were conducted in the American Living Labs. Design with denotes an innovation approach based on co-creation, as users and manufacturers work together in an iterative manner, where the locus of innovation can be seen as shared between both involved actors. Design by refers to an innovation approach where users innovate themselves, which is in line with the Lead User-approach and the CAP, as the locus of innovation resides with the user. 22

Design… For users With users By users

N 11 34 0

Table 5: User involvement mode

We looked at all articles and assessed what the dominant mode of user involvement was for the Living Lab activities that were described in the paper, or in the case of conceptual papers how the user contribution was defined. Not surprisingly, design with users, or the co-creation stance, was dominant in the majority of the papers (34). None of the papers described activities where the ‘innovation by users’-mode was dominant, although it was described in some papers (cf. infra). However, it is remarkable that the majority of the papers refers to co-creation with end-users, but only 17 papers mention User Innovation as anchoring paradigm. Apparently, the current Living Labs do not support true User Innovation, or at least do not see this as the dominant form of user contribution. Design for users, where the user only plays a passive role in the innovation process, is the dominant mode in 11 papers, including the American Living Labs and the real-life testbeds with passive user observation or simple evaluation, and some papers that deal with Living Lab projects where technologies are rolled out amongst a group of users with technical testing in real-life as main goal. Regarding the rest of the papers that dealt with the User Innovation paradigm explicitly, we would expect that the roles and characteristics of end-users in Living Labs would be described and researched in greater detail because of the user-centric nature of Living Labs. However, when going through the literature, this was not really the case. Lead User methods are mentioned in the context of Living Labs when overviews of methods to be used are presented (e.g. Pallot et al., 2010; Kusiak, 2007), but how this should exactly be approached remains unclear. In the works of Almirall et al. (2012), the Lead User concept also pops up with no clear specification on how to implement this, except for ‘selection of relevant users’ (Almirall et al., 2012). The Lead User method is also displayed as separate from Living Labs, with a slight overlap. The same goes for Pallot et al. (2011), who consider the Lead User-method as one of the user involvement techniques that are being used in Living Labs. Interestingly, Almirall and Wareham (2008) consider Lead User entrepreneurs as an important stakeholder group in Living Labs, something which is also mentioned by Pallot et al. (2011). 4 Conclusion Out of this overview of the theoretical state-of-the-art of the field of Living Labs, we have gathered that the practice-based side is much further developed than the theoretical side. In terms of empirical research and academic publications, Living Labs have received some attention, but this attention is virtually absent in top ranked journals. There is also a lack of empirical, more quantitative and comparative studies that focus on the added value of Living Labs. In the Living Labs literature, neither Open nor User Innovation is the dominant paradigm. Referring back to the Living Labs predecessors, it is the User Centered Design that originated from the Participatory Design movement that is still dominant. Strikingly, 18 out of 45 papers refer to no framework at all, remaining merely descriptive. User Innovation occurs more frequently than Open Innovation, but it seems that in recent papers Open Innovation is more and more adopted within the Living Labs literature. This is in line with the trend we also discovered in the previous chapter on 23

Living Labs practice, where we noticed the emergence of a new type of Living Lab constellation, based on multi-stakeholder collaboration and knowledge sharing, rather than on user involvement. However, in the Living Labs papers that deal with Open Innovation, for the most part this is equaled to open collaborative innovation, as it is argued that Open Innovation stresses user involvement and that Open Innovation takes place in a process of co-creation with internal and external parties. This ignores Open Innovation processes such as licensing and buying, which do not involve any form of co-creation at all. For example, this is also apparent in Westerlund and Leminen (2011) who see Open Innovation as a driver for user involvement and mention open source and crowdsourcing as alternatives to conventional in-house development. Based on their research, we proposed five distinct stakeholder roles within Living Labs: users, utilizers, providers, enablers and researchers. Despite the fact that Open Innovation is far from the dominant reference framework in Living Labs literature, we could find references to knowledge transfers between actors in all of the papers. As we considered this as one of the key characteristics of Open Innovation, we can conclude that Open Innovation is implicitly present witin Living Labs. Referring to the ‘European Paradox’, or the apparent gap between knowledge exploration and exploitation, at least in the literature there is also an imbalance in Living Labs. All of the Living Labs papers refer to knowledge exploration processes, whereas only one out of three papers mention exploitation processes. At least in terms of the Living Labs theory, there seems to be an issue with overcoming the European Paradox as there is too much focus on exploration. Regarding User Innovation, 17 papers explicitly refer to this paradigm as theoretical foundation, but in all papers user involvement is a given which also shows that User Innovation is at least implicitly present in the Living Labs literature. Regarding the degree of user involvement, one of the key frameworks we identified in the User Innovation literature, ‘design with users’ is dominant in the majority of the papers, whereas ‘design for users’, or the classical ‘voice-of-the-customers’ techniques, is the main user involvement mode in 11 papers. However, based on the literature, there is no general methodology towards user involvement in Living Labs, and the literature from the User Innovation paradigm is rarely extensively mentioned or implemented in the context of Living Labs. The Lead User concept pops up from time to time, but no clear method on how to implement this is provided. The only main difference in user involvement approach between Living Labs was so-called open user involvement (self-selection) versus closed user involvement (selecting users with certain characteristics). The most clear definition sees Living Lab projects as a quasi-experimental approach with a ‘pre’ and a ‘post’ assessment of users with an intervention stage. This adheres to the three principles of Dell'Era and Landoni (2014), as this allows to capture the use context, the artifact can be seen as the intervention with the innovation or another stimulus (Proxy Technology Assessment, Prototype,…), and the user is actively involved in multiple stages (triangulization). Our main conclusion is that in terms of methodology and user characteristics, the Living Labs literature is rather silent and positions Living Labs too much as an ‘everything is possible’ concept that resembles an empty box, in the sense that you can put whatever methodology or research approach inside. It remains a given that users are involved in Living Labs, but although cocreation was said to be the central process in Living Labs (Levén & Holmström, 2012), 11 papers mentioned ‘innovation for users’ as the dominant interaction mode. For the 34 papers where ‘innovation with users’ is dominant, no clear co-creation methodology is put forward. Therefore, within the current Living Labs literature, it remains unclear whether Living Labs hold value in terms of structuring user involvement according to User Innovation theory. 24

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Living labs as a mean to spur collaboration and innovation in a tourist destination Dominic Lapointe a, David Guimont a & Alain Sévigny a a

Université du Québec, Montréal (Canada) Lapointe.dominic@uqam.ca

Abstract The fragmented nature of the tourism industry and the ease of copying tourism innovation limit destinations’ capacities and motivations to innovate. To counter this fragmentation, destinations rely on destination management organisations (DMOs). However, DMOs have had very little or no success in stimulating innovation, hence the importance of exploring other models, such as living labs (LLs), to boost the innovation capability of tourism stakeholders. This paper analyses the innovation capability of a group of tourism stakeholders and users (tourists and tourism providers) involved in action research through a LL aimed at co-creating an experience enhanced by technology. It argues that the co-creation processes at work in the LL have raised innovation capability by using a combination of technology-supported innovation processes and in situ innovation processes. In this context, collaborative innovation takes place iteratively over a two years projects. Keywords Living lab, open innovation, tourism, Quebec, e-tourism, innovation capability, barriers Acknowledgement This research is funded by receive its funding from the Ministère de l’Éducation, de l’Enseignement supérieur et de la Recherche et de la Science du Québec (Programme d’aide à la recherche et au transfert – Volet innovation sociale) In today’s increasingly technological world, the need to adapt and innovate has become a major imperative for many industries. Tourism is no stranger to that trend, and is undergoing a complete technological revolution that has upset the industry and its businesses and forced them to rethink their operations (Baggio et al. 2014;ii/Gretzel et al. 2006/Buhalis and Law 2008). While the industry is considered a pioneer in the use of information technology (IT) (Buhalis and Law 2008), innovation has not been widely discussed in tourism literature (Halkier et al. 2014). Furthermore, new innovation paradigms are emerging and transforming existing innovation processes. One such paradigm is open innovation, which proposes that 29

businesses use external knowledge and skills to accelerate the innovation process (Chesbrough 2006). Strong competition and the risks that innovation entails are driving many organisations to put the consumer or user at the heart of innovation efforts (Westerlund and Leminen 2011). However, the tourism industry appears to struggle to integrate those new approaches (Najda-Janoszka and Kopera 2014). Although research on tourism innovation is a relatively recent phenomenon, it is possible to identify drivers, barriers and innovation processes specific to the industry. We will focus more specifically on the role of destination management organisations (DMOs) in stimulating tourism innovation. We will look at how implementing a living lab (LL) can help DMOs to boost tourism innovation at the destination level. Then, we will introduce the LL concept and discuss the specific LL process implemented as part of our research, and its impact on innovation among project stakeholders. 1 Innovation in the tourism industry Innovation in tourism is a complex but relevant topic. The Internet has globalised the tourism offering (Buhalis and Law 2008), generating fiercer competition between businesses and destinations and driving many of them to try and innovate in order to remain competitive (Halkier et al. 2014). This very competitive environment, coupled with major technological change, has placed innovation at the heart of the tourism phenomenon. The Internet and mobile phones unleashed a wave of innovation that keeps transforming the ways of travelling and the tourist experience (Buhalis and Law 2008). Unsurprisingly, innovation has become a critical issue for many tourism organisations and businesses, which innovate primarily in an attempt to create value for themselves, for consumers or for both (Weiermair 2004). Innovation can take place at the offering level (products and services) or at the process level (Weiermair 2004/Najda-Janoszka and Kopera 2013). The key factors that drive tourism businesses to innovate include customers, competition, industry leadership (Weiermair 2004) and technology providers (NajdaJanoszka 2013). But the true catalyst for innovation is the tourists themselves, or customers (Weiermair 2004/Najda-Janoszka 2013). Constantly searching for satisfactory—even unforgettable—experiences, they are eager for novelty. Although tourists are looking for new experiences, the tourism industry in its current form is struggling to innovate (Weiermair 2004/Halkier 2014/Najda-Janoszka and Kopera 2014), faced with a number of barriers. Najda-Janoszka and Kopera (2014) identified the main barriers to tourism innovation and grouped them into categories: environmental (external), organisational (internal) and innovation process-related (Table 1). Environmental (external)

Organisational (internal)

Innovation related


Heterogeneity of businesses Size of businesses Volatility of businesses Demand fluctuations Low-trust culture Inadequate tourism policies Limited legal protection

Small size of businesses Lack of innovation management, knowledge management and change management culture High personnel turnover Insufficient IT skills and resources

Informal, ad hoc and poorly understood innovation process Inefficient knowledge management process Lack of interest from businesses

Table 1 - The barriers to innovation in tourism, adapted from Najda-Janoszka and Kopera (2014)


These authors argue that several barriers stem from specific features of the tourism industry: heterogeneity of businesses, large number of small businesses, volatility of businesses, and vulnerability to demand fluctuations. Low propensity to collaborate on innovation and inefficient knowledge transfer create a low-trust culture among partners (Hjalager 2010). Several authors also point out that public institutions, despite their key role in fostering innovation, are viewed as significant forces of inertia (Halkier 2014/NajdaJanoszka 2013/Weiermair 2004). Tourism policies and strategies are often inadequate, as they fail to respond to the current needs of businesses and the changing market environment (Halkier 2014/Najda-Janoszka and Kopera 2014). Internal or organisational barriers often arise from the very nature of the industry, which includes large numbers of small businesses that often lack the financial and human resources and the skills necessary to innovate. Lack of knowledge and skills in the areas of technology, innovation, and change and knowledge management (Najda-Janoszka and Kopera 2014), as well as high personnel turnover, shows that human resources pose a major challenge to innovation. In addition, stakeholders’ absorptive capacity—i.e., their capacity to acquire and retain the knowledge necessary to innovate (Cohen and Levinthal, 1990) —appears to be low. This situation is thought to stem from the prevalence of small and medium-sized enterprises (SMEs) in the tourism industry (Baggio and Cooper 2010). When it comes to innovation processes, lack of formal, clear and permanent processes hinders innovation in the tourism industry. Also worthy of note is the fact that businesses show little interest in the process due to their low innovation capability and to the difficulty of protecting tourism innovations (Najda-Janoszka and Kopera 2014). Adding to this situation is the low level of trust among tourism organisations (Rønningen 2010). Although the tourism industry claims to place consumers/tourists at the forefront, they are virtually never involved in innovation processes (Najda-Janoszka and Kopera 2013/Guimont and Lapointe 2015). Tourist involvement could be achieved by opening up the innovation process (Chesbrough 2005/Lapointe and Guimont 2014), notably through co-creation of the tourist experience (Neuhofer et al. 2012). With the rise of social media, it is becoming ever harder to keep viewing tourists merely as passive consumers (Gretzel et al. 2014). Today’s tourists expect the industry to cater to their complex and individual needs (Gretzel et al. 2014). Tourists must be considered fullfledged players involved in the market (Neuhofer et al. 2012/Gretzel et al. 2014), and potential co-creators of the products and services intended for them. Co-creation is primarily an approach that places the user, or tourist, at the heart of the destination’s processes and strategies. It offers a new perspective on the market, resources, tourists and technology, incorporating tourists’ ideas and creativity into the design of tourist products and services (Tussyadiah and Zach 2013). This integrated approach is thought to boost innovation. Co-creation means looking at the destination in a new light and developing tools, techniques and capacity for involving not only tourists (Tussyadiah and Zach 2013), but also other stakeholders in the tourism system—basically, working with tourists, not for tourists. Accordingly, co-creation involves opening up the innovation process to players outside the organisation. Open innovation can be understood as the opposite of the vertical, internal approach to innovation. It is a new paradigm based on the assumption that businesses must use both internal and external ideas in the innovation process (Chesbrough 2006). It views research and development as an open system: since the knowledge needed for innovation may be found outside the organisation, external sources of knowledge should be identified and incorporated into the innovation process (Chesbrough 2006). Open innovation, which relies in large part on the co-operation of various stakeholders, does entail a number of constraints. Several barriers to adopting that new approach to innovation stem from human resistance to change (Lapointe and Guimont 2014). Chief 31

barriers include fear of giving an edge to competitors (Veer et al. 2012), lack of human and financial resources, uncommitted managers, lack of time, and inappropriate innovation strategies (Chesbrough and Crowther 2006/Meer 2007). Moreover, public institutions fail to take on a leadership role in fostering collaboration and innovation (Najda-Janoszka and Kopera 2013). The low propensity of tourism businesses to collaborate on innovation (Najda-Janoszka and Kopera 2014/Hjalager 2002) highlights the need for an effective and efficient intermediary that can improve collaboration and stimulate innovation. Since DMOs play a key role in ensuring competitiveness and co-operation at the destination level, one might think that they would take on a leadership role in fostering collaboration on innovation. Tourism SMEs that struggle to implement the management systems required to spur innovation (Rønningen 2010) could turn to DMOs or other organisations for knowledge and information that would allow them to innovate. But the truth is that DMOs seem to have trouble adapting to the current technology revolution (Gretzel et al. 2006/Neuhofer et al. 2012) and therefore positioning themselves as innovation leaders. In fact, public institutions overseeing tourism are often said to hinder innovation (Weiermair 2004/Najda-Janoszka 2013). Their governance structure appears to prevent them from moving away from their traditional promotion-based approach and building their new strategies around innovation (Halkier 2014). They are also struggling to create an environment that promotes collaboration and innovation (Najda-Janoszka 2013). The difficulty in getting tourism stakeholders to collaborate is now a major hurdle to innovation in tourism (Halkier 2014/ Najda-Janoszka 2013) and forces tourism organisations to seek other innovation models. 2 Living labs as a mean to spur innovation The rise of the Internet and social media prompted a shift in approaches to the market, resources and individuals (Vargo and Lusch 2004/Prahalad and Ramaswamy 2004). As information technology develops and social media emerge, it is becoming harder to ignore individuals’ power and desire to get involved (Prahalad and Ramaswamy 2004). Value creation used to be considered the sole prerogative of businesses, but nowadays value is co-created by both individuals and businesses (Prahalad and Ramaswamy 2004). Cocreation—a new, individual-oriented way to look at how the market works—has driven organisations to design new ways of involving and collaborating with individuals (Kotler et al. 2010). Innovation, which was traditionally restricted to academics or research and development departments, now increasingly calls on users as co-creators. Methods are being modelled on innovation networks or ecosystems from the IT industry, including LLs. LLs fall within the open innovation paradigm and involve a user-centric approach. They provide “physical regions or virtual realities in which stakeholders form public-privatepeople partnerships (PPPP) of firms, public agencies, universities, institutes, and users all collaborating for creation, prototyping, validating, and testing of new technologies, services, products, and systems in real-life contexts” (Westerlund and Leminen 2012: 7). Stakeholders collaborate on common value-creation objectives by co-developing products and services focused on user needs (Šifrer et al. 2012). With the LL approach, users must be at the centre of research or innovation efforts. Instead of attempting to understand users or consumers through studies, some organisations now prefer to directly involve users in their actual innovation process (Westerlund and Leminen 2011). This co-creation approach stimulates innovation and delivers a number of benefits: better grasp on consumers’ latent needs, lower risk of failure in product and service design, shorter lead times for new products and services, and higher profits (Westerlund and Leminen 2011). The LL addresses simultaneous processes of 32

exploration and exploitation as suggested by Almirall and Wareham (2011), although it appears that living labs are particularly good for exploration purposes. However, living labs also hold a lot of potential in terms of retention of generated knowledge, especially when successive cases run on the same living lab infrastructures (Schuurman et al. 2013). We believe that the process holds promise for stimulating tourism innovation. Through LLs, “tourist service providers will obtain insight to what tourists actually want and will have an opportunity to improve and develop new services targeted to different customer segments” (Lenart et al. 2014). Such insight could not only enable identification of new markets, but also spur innovation, development and product improvement (Buhalis and Amaranggana 2014) through more frequent interactions among stakeholders in a partnership. Interactions between users (tourists) and providers of technology and tourist services being a key catalyst for innovation (Hjalager 2002), LLs could create increased collaboration opportunities through a common platform where stakeholders would share, discuss, assess and design various solutions (Lenart et al. 2014). In addition, LLs have the potential to become innovation facilitators (Schuurman et al. 2014/Lapointe and Guimont 2014) and thus create what DMOs are struggling to build: an environment that promotes co-operation among tourism industry stakeholders to enable innovation (Najda-Janoszka 2013). The tourism industry’s innovation challenges led us to implement a LL process to promote exploration and retention of information and observe how LL participants collectively and individually address the barriers to innovation that they face. 3 The living lab process implemented in Rivière-du-Loup Over the years, many regions around the globe have looked at tourism and made it the cornerstone of their development strategies. An explosion in the number of destinations ensued. While many of them are small, they still need to deal with the technology revolution that is transforming the tourism industry. Investigations into how a smaller destination manages to integrate new innovation practices are therefore extremely relevant. The essentially rural territory of the Rivière-du-Loup area makes it an interesting object of study, with unique dynamics compared to large urban centres. In the Quebec territorial context, the Rivière-du-Loup area is relatively far from large outbound markets (Montreal and Quebec City) and is not considered a hub for international tourism. It is a rural area with a favourable geographical setting, along the vast St. Lawrence estuary. Featuring interesting landscapes (forest, estuary and islands), the area is home to Rivière-du-Loup, a town of 19,400 people, and a dozen smaller municipalities that bring the total population to 27,700. The area’s DMO is a private association with a membership of some 230 tourism organisation and businesses. Members also include the municipalities, which provide nearly 50% of the operating budget through public funds. The association is very active, focusing on the traditional DMO roles: information and promotion. It fosters dialogue and supports development initiatives as far as its resources allow. Based on the above list of barriers (adapted from Najda-Janoszka and Kopera 2014), the area (its tourism businesses and its DMO) struggles with the following: • Limited IT skills and resources • Small businesses, often with high personnel turnover because of their seasonal nature, giving organisations limited absorptive capacity for technology and innovations • Businesses often lacking a strong knowledge and change management culture; some level of inertia among organisations; poor understanding of the value of innovation; risk aversion 33

Very basic levels of trust and collaboration, especially compared to open innovation standards • On the flip side, businesses and stakeholders are willing to innovate in spite of existing barriers These observations show the value and challenge of boosting innovation and stakeholder innovation capability, and provide the backdrop for our action research: Co-creation of a tourist experience enhanced by technology, in the context of a living lab. •

4 The project’s LL process and the stakeholders involved The DMO’s initial goal was to update its sightseeing routes (available on paper maps) and to record podcasts providing tourists with complementary information about the sights, and about rural attractions in particular. LLio, the region’s LL, approached the DMO and offered to co-lead a co-creation process involving stakeholders and tourists working together to develop a technology proposal for the sightseeing route update. The facilitated open innovation process would be funded through a Quebec government research program, and the DMO had to be comfortable with not knowing the outcome in advance. A private-sector partner was also approached to be involved not as a mere supplier, but as a full-fledged co-creator of a technology-enhanced tourist experience. Our action research in a LL context involves three stakeholder groups: the LLio, a LL associated with the local teaching institution, the DMO, and a local web developer. A steering committee made up of one representative from each group is in charge of project coordination. Here is the breakdown of stakeholder groups in a typical PPP partnership in a LL context (Almirall and Wareham 2008): • Population (beneficiary): The DMO and its members • Private sector : The web developer • Public (institutional/research) sector: LL with his researchers and students User groups involved in co-creation • Tourism stakeholders: 19 volunteers (DMO members) who commit for two years. Recruited from the pool of DMO members following a tourism industry discussion event, using personal invitations, and through a general call for participants. •

Tourists: 21 Volunteers. French-speaking tourists who use information and communications technology (ICT) and own a tablet or smartphone. Recruited from the DMO’s visitor centre, the DMO’s Facebook page and the living lab’s panel.

Tourism providers take part in co-creation workshops both in situ and on the online platform. Tourists participate online only. We use “in situ” to characterized the participation in local co-creation workshops (not to be confused with “in situ” as in the context that “refers to information from customers/users that originate from a real-life, value co-creation situation” (Edvardsson, 2012). We believe that The in-situ open innovation workshop could serve as an entry point in OI for private stakeholders (Lapointe and Guimont, 2014). Our action research in a living lab context relies on phases, cycles and activities adapted from the FormIT approach (Bergvall-Kåreborn et al. 2009). The first iteration of the fivephase process took place during Year 1 of the project. Here is a more detailed chronology (table 2), over 24 months:


1. Planning (6 months) >

2. Concept 3. Prototype 4. Innovation design design design (2 (2 (2 months) > months) months) > >

5. Implementati on / beta testing (3 > months)

Stakeholder integration Steering committee meetings Recruitment of tourism stakeholders Recruitment of tourists Initial meeting of stakeholders

Co-creation workshops with the stakeholders Three rounds of interactions with the tourists to capture their needs, expectations, ideas, suggestions, reactions and feedback

Co-creation workshops with the stakeholders. New round of interactions with the tourists focusing on the journey map, in order to test the prototype

Development of the beta application Tests with the stakeholders and tourists

Public launch of the beta version Real-life testing during the summer to assess the application’s userfriendliness and the overall tourist experience

1. Planning and 2. Concept review 3. Prototype adjustments and design (1 month) experimentation (2 months) with new options (2 months)

4. Innovation design – second beta version and/or complementar y modules (2 months)

5. Implementati on (2 months)

Second iteration (1–5) (9 months)

Table 2 - Adapted FormIT process

During Year 2, the co-creation process will be repeated. This second iteration will allow for adjustments to the collaborative working mechanisms and the application itself. The same steps and stakeholders will be used (although additional participants could be onboarded). In addition to recruiting and involving various stakeholders, and designing the co-creation phases, the project involved implementing an information gathering and sharing infrastructure—a collaborative infostructure, “a digital environment for networking” (Najda-Janoszka and Kopera 2014). The group of stakeholders uses the collaborative innovation lab at the teaching institution, the living lab’s collaborative web platform (WordPress website with posts and a forum) and a closed Facebook group for co-creation and for viewing information obtained from tourists. Tourists are surveyed primarily through online surveys, and they can access profiles and summaries on the collaborative platform. Shared online forms and documents are also used for specific interactions (e.g., co-creation of common representations based on commented texts). Examples of in situ and online asynchronous interactions between tourism providers and tourists : • Stakeholders (tourism providers) make hypothesis about tourists needs and preference, during co-creation workshops. • Then, by the mean of an online survey, the tourists express their preferences, needs and habits (about technology, travel and technology in travel). Open and narrative forms are preferred to let tourists express themselves. We use the same survey with the tourism providers to have a comparison point (and because they are tourists too). 35

• •

During a new workshop, tourism providers use the synthesis of the responses to better conceptualize the new technology enhanced experience. The tourists are then questioned again, building on the synthesis of their previous answers and the concept they are being presented.

This kind of asynchronous exchanges goes on at every phases. At each step, everyone gets a better view of the whole concept and everybody can see the impact of the suggestions of its group/community. The communities cumulate informations, knowledges and valuable insights about the tourism experience 2.0 : the way to co-create it and what are the real needs and aspirations of tourists. The role of the lead researcher in this process is to oversee the living lab process, prepare co-creation workshops, and facilitate co-creation both in situ and online. He leads the “experimentation” component. He also documents the process (planned versus completed tasks) as well as user participation and engagement to describe how innovation capability is growing, and the drivers and barriers at play. The collaborating researchers support the co-creation process, deliver specific workshops on technology and the tourist experience, and help to document and characterise the growth in innovation capability. 5 Stimulating innovation Now that Phase 1 of the project has been completed, we can observe changes in stakeholder innovation capability. The project is acting on both the barriers and the innovation process. Changes were observed in all three of the abovementioned barrier categories. Gaps in IT competency in the stakeholder population had been identified at the outset of the LL project. After Phase 1, we can see that the gaps have shrunk and that stakeholders’ IT skills have grown. First, upgrading efforts were made: stakeholders received training on co-creation and on technology’s role in tourism. The fact that participants actively contribute to the collaborative platform and share best tourism and IT practices on the project’s Facebook page provides further evidence of the shrinking gaps. Moreover, participants are embracing IT and tourism discourse and concepts during in situ meetings. We can also observe changes in the innovation management culture. Project stakeholders told the researchers that they have incorporated open innovation tools into their management practices. New behaviours include using innovation project management template and involving stakeholders in innovation efforts. The matrix used by the project researchers to characterise and describe innovation initiatives was adopted by other stakeholders, who now manage their own projects in a more participative and user-centric fashion. For the DMO, the project was a catalyst for change and made it aware of its role in driving members towards innovation. A rethinking of the DMO’s planning strategy ensued. The five-yearly tourism forum was organised using a participative and collective intelligence approach focused on members as users and on community dynamics. Furthermore, the DMO applied knowledge management strategies to identify best practices, but also in an effort to place tourists and their knowledge at the heart of planning activities. We can conclude that the project has shifted the focus to users—whether DMO members or tourists—as a potential source of innovation. The new focus on tourists as users was also observed among other project stakeholders. As the project advanced and the mobile application which is its core deliverable started to take form, stakeholders increasingly suggested recourse to the tourist panel, whereas such suggestions used to be made only by researchers. Stakeholders now spontaneously suggest that questions be put to tourists instead of looking for answers themselves, and researchers 36

have to adapt the surveys sent to the tourist panel accordingly. As a result, the innovation process is increasingly centred on the needs of tourists/users. The project has also lifted or reduced process-related barriers, formalising the innovation and solution-seeking process among stakeholders. The result has been integration of in situ open innovation practices (Lapointe and Guimont 2014) by project stakeholders in their own development activities. Two local development agents have incorporated such processes into their operations. Another example would be the tourism forum based on open innovation practices organised by the DMO in order to identify high-priority projects for strategic planning. Lastly, the technology provider involved in the project is a committed participant in the LL process: it finds the process inspiring and does not attempt to derail it and impose its regular technology development process instead. The provider has also expressed interest in using the LL process for future development efforts. As for external barriers, the project has fostered a climate of trust within the industry. Collaboration opportunities among stakeholders have flourished. In addition, stakeholder engagement has been maintained: since the very beginning, not one participant has left; in fact, new people were onboarded as the project advanced. In addition, information sharing among stakeholders has grown, whether in situ, on the collaborative platform or on the project’s Facebook page. Lastly, the related projects jointly initiated by project stakeholders testify to the climate of greater trust that now exists. Stakeholders have not only raised their innovation capability in the specific context of the project, but also developed new innovative projects of their own beyond the scope of the LL project that is the focus of our research. We regard such spin-offs as the main indicator that participation in a LL project has raised stakeholders’ innovation capability. Four spinoff projects are already under way, spurred by the acquisition of knowledge about the 2.0 tourist experience and the integration of co-creation skills. The projects are as follows: • New inspiration/search module better suited to visitors’ needs on the DMO’s website • Creation of a research and development unit, as part of the web developer training program, that works on developing a technology-enhanced experience (Estimote and iBeacon) for a local attraction • Launch of a joint geocaching/treasure hunting project by the town and county departments of cultural development • New action research project aimed at turning an island in the St. Lawrence into a tourist destination using LL-inspired collective intelligence processes The collaborative process yielded a concept more fitting than the DMO’s original goal (before getting involved in the project, the DMO wanted to develop podcasts). The mobile application concept will help visitors to plan, navigate and share their discovery experience. Users can find inspiration, select attractions, and edit, share or comment on preset routes. However, limitations and challenges were encountered. The objective was to recruit more than 25 tourists (up to 100). We currently have 21. Recruitment is challenging, notably because tourists do not form communities of technology users (unlike users of a given phone brand or fans of a specific video game, for instance). Recruiting and involving participants from a community that does not exist formally is a difficult task. Lack of community spirit also makes interaction more challenging. Our action research will help to document methods and tools for promoting more effective interaction and reinforcing the culture of co-creation in tourist communities. Lastly, as we document the co-creation process followed by tourism practitioners and stakeholders, we notice that individuals’ motivations and willingness to subscribe to a given goal depend on their respective fields of expertise. The living lab facilitator is very helpful in reconciling divergent views, 37

specifically reconciling the DMO’s natural tendency to focus mostly on promotion and staging, but less on technology and co-creation (level 1 of the Typology of technology-­‐‑ enhanced tourism experiences [Neuhofer et al., 2014; 346]) with the web developer’s natural tendency to propose a mobile tool offering maximum reliability but not necessarily suited to co-creation, which requires some degree of randomness and compromise in the programming. While the process expressly provides for ways to address such situations, constant adjustments are needed. It will be interesting in the future to document this challenge using the framework of the technology enhanced tourist experience (Neuhofer et al., 2014). 6 Conclusion In spite of the abovementioned limitations, our results lead us to conclude that tourism stakeholders involved in the project have raised their innovation capability. Initially, Rivière-du-Loup’s tourism community faced many of the typical barriers to innovation in the tourism industry. However, the first year of action research has shown us that the selected LL approach has indeed reduced several barriers to innovation at the destination level. The capacity of LLs to stimulate innovation, which has already been observed in more technology-intensive industries (Schuurman et al. 2014) but also in the tourism industry (Lenart et al. 2014/Šifrer et al. 2014), is confirmed in our case. Change can be seen in the way that stakeholders embraced the technological tools and the LL process, and in the emergence of a climate of greater trust that generated spin-offs. Accordingly, this research also confirms results from our past work on open innovation (Lapointe and Guimont 2014) and the potential of LLs as intermediaries to open up the innovation process, but also as a means to raise stakeholder innovation capability. The power of the LL to boost innovation capability stems from the co-creation process which, as part of this research, helps to establish an innovation management culture and a climate of trust among stakeholders. Researchers’ role in the process is threefold: they are sparks that move the LL forward, facilitators, and critics who reassess the process and its outcomes in collaboration with stakeholders. Based on our experience, we can say that while researchers can step away from the spark role, the other two roles tend to stick. This is evidenced by spin-offs from our project: although such spin-offs were not initiated by researchers, the stakeholders involved still turn to researchers for help in facilitating and critically assessing the process. In addition, the LL’s role as an intermediary and innovation facilitator enables innovation leadership in an industry whose very structure (prevalence of SMEs and fragmentation across sectors) makes it hard for a champion of innovation to arise. While the process implemented with the Rivière-du-Loup DMO has enabled tourism stakeholders to take part in a structured innovation process, the ultimate question remains whether it will stand the test of time and be widely adopted by the community. The LL originally set up for co-creating a technology-enhanced tourist experience would need to become a more permanent entity providing innovation support, as requested by tourism stakeholders. Spin-offs provide evidence that a new culture of innovation—more specifically open innovation—is emerging in the industry. Nevertheless, it is too early to say that innovation is now institutionalised. 7 References Almirall, E., & Wareham, J. (2008). Living Labs and open innovation: roles and applicability. The Electronic Journal for for Virtual Organizations and Networks, 10(3), 21–46.


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Najda-Janoszka, M. (2013). Innovative Activity of Small Tourist Enterprises–Cooperation with Local Institutional Partners. Journal of Entrepreneurship, Management and Innovation, vol.9, no.1, 17-32. Neuhofer, B., Buhalis, D., & Ladkin, A. (2013). A Typology of Technology-­‐‑Enhanced Tourism Experiences. International Journal of Tourism Research, 16(4), 340–350. Porter, I. (2013). Une cible, 1831 messagers. Retrieved from http://www.ledevoir.com/societe/actualites-en-societe/381429/une-cible-1831-messagers Prahalad, C. K., & Ramaswamy, V. (2004). Co-creation experiences: The next practice in value creation. Journal of Interactive Marketing, 18(3), 5–14. Pallot, M., Trousse, B., Senach, B., & Scapin, D. (2010). Living Lab Research Landscape  : From User Centred Design and User Experience towards User Cocreation. In In First European Summer School’Living Labs' (Vol. 0). Rønningen, M. (2010). Innovation in the Norwegian Rural Tourism Industry: Results from a Norwegian Survey. The Open Social Science Journal, 3(1), 15–29. Schumpeter J. (1934). The Theory of Economic Development. Boston, Harvard University Press. Schuurman, D. et al. (2013) “Open Innovation Processes in Living Lab Innovation Systems : Insights from the LeYLab” in Technology Innovation Management Review. November 2013 : 28-36. Sifrer, A., Pucihar, A., Borstnar, M. K., & Lenart, G. (2012, May). Development of the prototype solution for user involvement in the Living Lab approach. In MIPRO, 2012 Proceedings of the 35th International Convention (pp. 1705-1708). IEEE. Tussyadiah, I., & Zach, F. (2013). Social Media Strategy and Capacity for Consumer CoCreation among Destination Marketing Organizations. Information and Communication Technologies in Tourism 2013, 242. Vargo, S., & Lusch, R. (2004). Evolving to a new dominant logic for marketing. Journal of Marketing,1–17. Veer, T., Lorenz, A., & Blind, K. (2012). How Open is Too Open? The “Dark Side”of Openness Along the Innovation Value Chain. In 35th DRUID Celebration Conference 2013. Barcelona. Weiermair, K. (2004). Product improvement or innovation: what is the key to success in tourism. Innovations in Tourism UNWTO Conference. Westerlund, M. & Leminen, S. (2011). Managing the Challenges of Becoming an Open Innovation Company  : Experiences from Living Labs, (October), 19–25.


Girls Making History Summary Report Communities and culture network funded research pilot Penny Evans a, Roz Hall a a

Knowle West Media Centre (KWMC), University of Bristol pennyevans@kwmc.org.uk

Abstract Girls Making History (GMH) is a Bristol-based project designed and led in a co-productive partnership, by Knowle West Media Centre (KWMC) and a group of local young women aged 13-24. The project asks how, by harnessing the expertise of young women’s direct experience of violence and coercive control in their relationships, digital tools might raise awareness of the cultural normalisation of partner violence in teenage relationships and social networks. A six-month research phase ran from January to June 2014, which was an opportunity to critically reflect upon how involvement in this co-produced project might support these young women to transform their understanding of their own experience, develop new imagined futures and, on a wider scale, transmit new ways of understanding externally into ‘real’ and ‘virtual’ communities. During this pilot study the young women collaborated with engineers, digital experts and artists’ in the design of two digital platforms. In line with the principles of the project this research was co-produced with the young women, KWMC staff and researchers collaboratively developing and conducting all elements of the research programme. 1 Introduction Girls Making History (GMH) is a Bristol-based project designed and led in a co-productive partnership, by Knowle West Media Centre (KWMC) and a group of local young women aged 13-24. The project asks how, by harnessing the expertise of young women’s direct experience of violence and coercive control in their relationships, digital tools might raise awareness of the cultural normalisation of partner violence in teenage relationships and social networks. A six-month research phase ran from January to June 2014, which was an opportunity to critically reflect upon how involvement in this co-produced project might support these young women to transform their understanding of their own experience, develop new imagined futures and, on a wider scale, transmit new ways of understanding externally into ‘real’ and ‘virtual’ communities. During this pilot study the young women collaborated with engineers, digital experts and artists’ in the design of two digital platforms. In line with the principles of the project this research was co-produced with the young women, KWMC staff and researchers collaboratively developing and conducting all elements of the research programme. 41

2 Rationale Violence against women and girls remains a national crisis. In 2009 the NSPCC published a ground-breaking report, which, for the first time, documented teenage partner violence in the UK context4. The study reported significant numbers of both young men and women perpetrating violent behaviours in their intimate relationships. Young women were shown to be experiencing violence more frequently and conveyed a significantly higher degree of negative impacts on their wellbeing than their male counterparts, with three-quarters of young women reporting experiencing emotional violence, one third reporting sexual violence and one quarter reporting physical violence. 3 Pilot Project Aims • • • • •

To develop our understanding of ‘community’ as envisioned by teenage girls. To enable teenage girls to overcome barriers to discussing the normalisation of violence and to understand the value of dissent, through a programme of !upskilling, peer mentoring and co-creation in digital media. To build confidence in this group of young women to challenge such normalisation and enable them to support, through a wider campaign, other teenage girls at!risk of becoming involved in abusive / violent relationships. To develop our understanding of the potential use of digital tools as!supportive spaces for teenage girls experiencing intimate partner violence. To explore how these spaces can be employed as transformative arenas subverting the !normative nature of teenage intimate partner violence.

4 The process of co production The research design, responsive to the projects aims, was deliberately outlined in a loose and flexible manner, anticipating an iterative process that engaged with the emerging findings of the project. Four work strands were identified and this served as a guide map to aid the collaborative design of the six-month workshop series. Girls Making History was borne out of a commitment to collaborative research and creating partnerships that are meaningful in terms of research contribution, community development and enhancing ‘self-knowing’5 amongst all involved. By using co-production approaches that have been developed and refined over years of practice at KWMC, there was a desire to support academic partners to leap outside of their ‘comfort zones’ into an unknown and unpredictable territory, to draw on different sites and types of knowledge. Through the embracing of ‘uncertainty’ we hoped to open up new possibilities and contingencies6 for academic research, in particular, to situate young women in a place and space that recognised the expertise of their experience and could speak to their marginality as a site of resistance7. By widening and diversifying ‘participation in the 4

40% of teenagers are accepting aggressive behaviour from dating partners, 1 in 4 girls have experienced an abusive relationship, 1 in 3 girls have experienced sexual violence. (NSPCC (2009) Partner exploitation and violence in teenage intimate relationships, Barter, C et al) 5 Butler, J. (2005). Giving an account of oneself. Fordham Univ Press. 6 Pearce, J. (2008) ‘We make progress because we are lost’: Critical Reflections on Co Producing Knowledge as a Methodology for Researching Non-Governmental Public Action, NGPA Working Paper Series. LSE. 7 Hooks, Bell. 1990, “Choosing Margin as a Space of Radical Openness”, The Feminist Standpoint Theory Reader: Intellectual and Political Controversies, Ed. Sandra Harding, (2004), 153-160. Routledge, London. 42

production of knowledge, ideas and capacities’ we hoped to create a pathway in which the possibly ‘disruptive truths’ of young women’s experience could ‘acquire greater authority’8 and enable the ‘micro-local’ to reach out into wider power structures. Ultimately GMH sought to foster transformational outcomes 9 targeting ‘individual and collective empowerment for progressive social change’10, developing reflexively a collaborative experience of learning. 5 Relevance of the KWMC Approach GMH expressly situated the experiences and opinions of all those participating as equal, bringing together digital experts, campaigners, domestic violence ‘specialists’, academics and young women affected by teenage partner violence to experiment with what might be developed if multiple ‘experts’ could co-produce together. This approach has close affinity to models of action research11 and responded to the principle that ‘people are able to theorize about their lives and experiences and act in self-directed and consciously political ways to change their own communities’12. The Products Through this process two digital tools were developed: Digital Tool 1: The Emoti-Meter The diamond fits in the hand and the two halves rotate, allowing you to align the colours and play with colour combinations. The bottom half of the keyring features six coloured buttons. Each button has a small counter connected to it.

Attached to the chain is a ‘how to’ guide, which introduces the idea that colours relate to emotions and that you can privately assign an emotion to each colour. Every time you press for example, the green button, representing the nervous emotion, the counter clocks it up. So at the end of the day, or a week, you can reveal the counters and compare how many times you have felt nervous, scared, or excited. This monitoring of your emotions 8

Brigstocke, Julian. (2013) ‘Democracy and the Reinvention of Authority’. Problems of Participation: Reflections on Authority, Democracy, and the Struggle for Common Life. Ed. Noorani Tehseen, Claire Blencowe, and Julian Brigstocke. Authority Research Network; 7-12. Pg. 11. 9 Heron, J. & Reason, P. (2008). Extending epistemology within a cooperative inquiry. In P. Reason & H. Bradbury (Eds.) Handbook of action research: Participative inquiry and practice (2nd ed.) (pp. 366–380). London: Sage. 10 Banks, S. & Armstrong, A, et al. (2014). Using co-inquiry to study co-inquiry: community-university perspectives on research collaboration. Journal of Community Engagement and Scholarship 7(1). 11 Bradbury, H., & Reason, P. (2003). Action Research An Opportunity for Revitalizing Research Purpose and Practices. Qualitative Social Work, 2(2), 155-175. 12 Gatenby, B. & Humphries, M. (2000), February. Feminist participatory action research: Methodological and ethical issues. In Women's Studies International Forum (Vol. 23, No. 1, pp. 89-105). Pergamon.


over a self-organised duration of time gives the user chance to gather an overview of their own emotional wealth. Digital Tool 2 - The Game The “Knowing the Signs” game was developed with the Games Hub in Bristol. Three games designers came to a workshop to speak to the young women and get a sense of what the project was about. Unlike many of the projects that the game designers have worked on it was a challenge to create a ‘game’ with such serious content.

The girls told the game designers their stories and about the research that they had been doing. The most prevalent thing that came from the discussion was a need for young women to recognise what an unhealthy relationship actually is, hence the name, ‘Knowing the Signs’. The game puts the user in the third person, acting as if they are looking at an abusive relationship from the outside. This is a well-known strategy when discussing abusive relationships with young people, as they find it easier to reflect on other people’s situations than their own. The game gives the user a series of scenarios from which they have to choose an answer. Some of the decisions are not necessarily the correct answer, but the game is about building confidence and peace levels. For example; “He tells you not to wear a dress” the options would be: ‘wear it anyway’/ ‘tell him that he’s upset you but change anyway’/ ‘immediately change’. The first option would build your confidence levels but lessen your peace levels. The more confidence you build during the game, the easier it becomes to leave the relationship. 6 Challenges of working with this issue Two key issues became apparent throughout the developmental stages of the digital tools: - What if the abusive partner found it and used it as a means to create additional power, for example if it was a diary app to write about your experiences? - Often, when you’re in an abusive relationship you don’t realise it. Both the emoti-meter and the game address these issues. If the abusive partner was to find the emoti-meter it would be easily explainable, the user is just monitoring their emotions rather than it being directly about abuse. Therefore, it is about the emotional wellbeing of the girl and educating her to start thinking about the patterns of her emotions. For example, if she was counting up high numbers of anger then the website would suggest reasoning and help. The game addresses the issue about the realisation of being in an abusive relationship and understanding the complexities of what it is like to be in one.


7 Benefits and impact of the process Sharing stories was a central mechanism through which GMH engaged with the expertise of the young women involved in the project. Though GMH was expressly not attempting to create a therapeutic space, there was significant hope that the sharing of stories might operate as a form of ‘praxis’ through which the collective could begin to think transformatively about relationship violence in the context of their own lives as well as considering the wider societal issue. GMH recognised the potential of group work as a ‘tertiary prevention’ through which those who have lived with partner violence could reduce harm by overcoming and make sense of their experiences 13 using ‘skilled facilitation’ and mutual learning through sharing with other women of similar experience14. The space for individual stories to emerge was within the context of practical skills/learning orientated workshops, envisaged as a shared and dialogical experience. In terms of listening and being listened to, some of the young women reported a process of transformation through which being trusted as a listener imbued them with the confidence that they would be listened to in a non-judgemental manner, for example: ‘I kind of spoke a lot with confidence [at GMH] and like normally I don’t. And I don’t really speak out a lot like I have no confidence so I kind of hide away in the corner and stuff but in being there it kind of gave me a sort of voice that I wasn’t kind of scared to say what I felt and I was quite happy to be open and honest and like it kind of felt like – when you’re listening it felt like other people had like you had – other people had confidence in you to hear what they’ve gone through.’ What is indicated in this quote is how young women involved in GMH have experienced personal development; as their confidence has increased so has their sense of their own potential to make positive change within their own lives and the lives of others in their community. They have also developed greater understanding of relationships, criminology, the law and everyday sexism. Furthermore, they have developed an understanding of how these things relate to the media and so they have become increasingly aware of how they might utilise the very skills they have developed during GMH, in, for example, photography, in ways that are counter to the pervasive normalisation of domestic violence through everyday sexism. 8 Conclusions GMH was a unique and ambitious project that employed an experimental and challenging methodology to collaboratively develop understanding of the normalisation of teenage partner violence and the ways in which digital tools might intersect in such phenomena. KWMC continues to work collaboratively with the young women involved in the project and is currently exploring additional funding opportunities to further develop the digital tools designed during the project. The young women involved are keen that the project and their involvement is expanded upon, so that the two products can be produced, but also so that young men can also explore some of the societal pressures there are around masculinity, in order to address and counter those pressures that young men may feel encourage them to be perpetrators of domestic violence. Young women involved are also keen to co-productively work with 13

Mullender, A. and Hague, G. (2000) Reducing domestic violence ... What works? Women Survivors’ Views. Home Office Briefing Note, London: Home Office. 14 Hester, M. & Westmarland, N. (2005). Tackling domestic violence: effective interventions and approaches. Home Office Research, Development and Statistics Directorate.


other services and initiatives across the city, to make the most of and share the learning they have experienced to date. Copyright: Knowle West Media Centre/Law School, University of Bristol. Copyright images: Knowle West Media Centre! Visit: http://kwmc.org.uk/projects/girlsmakinghistory/

46 Â Â

Smart City Living Lab – City as a place Bergström, Maija a a

Forum Virium Helsinki maija.bergstrom@forumvirium.fi

Abstract Smart cities are often discussed in the context of technology development or virtual services. However, smart cities are still real places where people live, work and play. Livability – a target often discussed in smart city strategies – is also connected to the particular places where urban dwellers spend their every day lives. The aim of this paper is to show how both qualitative research and art projects can be used to offer information about the identity of the place. This information may be used as a starting point towards placemaking in a citizen-driven Smart City Living Lab. This is demonstrated by three cases. They showed the need for distinctiveness, re-occurring events and happenings to produce a feeling of a place, and a narrative that stems from the history of the place. Ideas on Smart City would develop better if there would be something concrete, something that could be experienced, touched, seen, heard; something that would represent the Smart City for the citizens. Keywords Smart city, Kalasatama, Placemaking 1 Introduction 1.1 Placemaking in a Smart City A smart city is a different kind of city than the one we consider “normal”: adaptive and sustainable, open and democratic, creative and well educated and directed by real-time information. Three factors can be found in definitions of a smart city: technology factors, institutional factors and human factors (Nam & Pardo, 2011). Nam & Pardo suggest that a rather technology-centered definition still prevails, but more emphasis on the human factors would be needed: a socio-technical view of a smart city. The active development of an area – the whole city or just a part of it – to a certain direction can be further elaborated in the terms of placemaking. The starting point for this 47

should be the understanding of the current state of the place, its sense of place which means how the place can be identified, how it stands out from it’s surroundings (Auburn & Barnes, 2006). The disctinctiveness means more than just the physical surroundings, including also the narratives and mythologies linked to a place (Wortham-Galvin, 2008). Smart cities are often discussed in the context of technology development or virtual services. ”Smartness” may reside in the cloud. However, smart cities are still real places where people live, work and play. Livability – a target often discussed in smart city strategies – is also connected to the particular places where urban dwellers spend their every day lives. Further, smart city development offers new possibilities to placemaking: e.g. new layers to the experience via augmented reality solutions or possibilities to add changing digital tags, sensors and data to selected locations. Thus, smart cities are interesting also in the context of placemaking and offer new possibilities to create interesting, multifunctional, shared spaces. When talking about the sense of place, or the identity of a place, we are referring to peoples shared ideas of this place. From a social psychological perspective these shared ideas can be understood as it’s social representations, a concept used for researching various phenomena, developed by Serge Moscovici (1961/2008). The place itself has no power on defining itself, but these definitions come from the outside, the people and the media. This idea of a place stems from it’s past (deAlba, 2011) and stretches towards the future. With the use of the word “identity”, the personality and uniqueness of the place is emphasised. As each person has their own, distinctive understanding of a place due to their personal history, values and attitudes, the challenge is to capture this diversity, but try to classify and arrange it in a meaningful and informative manner. Here, three cases on the place identity of Kalasatama are described and then discussed further in the context of placemaking in a smart city. The first case is an empirical research project (Bergström, 2015), the next ones are art projects of Eskus, the center for performing arts running a community arts project “Kalasataman taidetalkoot”15. The aim of this paper is to show how both qualitative research and art projects can be used to gain information about the identity of the place, and how this information may be used as a starting point towards placemaking in a citizen-driven Smart City Living Lab. 2 Smart Kalasatama project 2.1 Kalasatama as a place Kalasatama is a new, developing inner city district in Helsinki, Finland. The construction work in Kalasatama started after the old port moved away from the area in 2008, and the first inhabitants moved to the area in 2012. The work will continue until the 2030s. A total of 20,000 inhabitants will reside in the area and 8,000 jobs are expected. Kalasatama is a place undergoing a massive regeneration. It has an industrial and maritime history as a port, surrounded by wholesale markets and marketplace to sell the imported goods and a gas plant to produce energy – a protected, historical building of Suvilahti that was recently turned into a cultural center. After the plans emerged to build a new residential area in Kalasatama, and the old port moved away in 2008, the area came to be known from it’s opportunities for temporary uses. The city officials accepted festivals, graffiti fences and urban gardening to take place in Kalasatama and Suvilahti as a strategy for developing the place through culture (Krivý, 2013). In Kalasatama, the highest buildings in Helsinki insofar will be built. The topic awoke some controversy and the process was 15

In both of the art projects presented here, the author of this paper has been in collaboration with Kalasataman taidetalkoot -community art project of Center for Performing Arts (Esitystaiteen keskus). 48

delayed because of complaints to the court. Now the construction work has started and shopping center ”REDI” with its first two towers should be completed in 2018. 2.2 Smart Kalasatama The aim of Smart Kalasatama project is to co-develop Kalasatama as a smart city with the residents and other actors in the area. To drive this process forward, Kalasatama is used as a Living Lab where new smart services can be co-created and tested in the real environment. For this work to have a firm base, the residents are invited to participate in the process. A way to start the co-creation is to work together and define the local identity. Smart Kalasatama project grows from the collaboration between the City of Helsinki, companies and residents. The aim is to inspire residential participation and create new business and innovations. The Smart Kalasatama is a development environment that brings together the research, development and innovation activities of businesses, and the development of city services. Companies and the city bring their projects to the mix; the ideas then are being developed, tested and composed together with the inhabitants and those working in the area. Smart Kalasatama is a 6Aika spearhead project of the City of Helsinki, coordinated by Forum Virium Helsinki. It is part of the Six City Strategy – Open and smart services carried out by the largest cities in Finland (Helsinki, Espoo, Vantaa, Tampere, Oulu and Turku). In 2015–2017 Smart Kalasatama is funded by Six City Strategy (ERDF/HelsinkiUusimaa Regional Council), the City of Helsinki and the Finnish Ministry for Employment and the Economy. The budget for three years is approximately 900 000 euros. 2.3 Kalasatama as a living lab Kalasatama forms a geography based Living Lab for the Smart Kalasatama project. The area houses approximately 2000 residents in 2015. A collaborative working space will be opened in autumn 2015 to support different development activities such as workshops, hackathons and seminars. Kalasatama Developers Club will be launched to support the smart development of the area and further support connections between different actors on the area. Minor financial supports will be available for entrepreneurs to support product development and agile testing. Westerlund and Leminen (2011), following the view of Ballon et al. (2005) define living labs as ”physical regions or virtual realities where stakeholders form public-private-people partnerships (4Ps)”. 4P-model is an attempt to move from dual-partnership of public and private, towards a more democratic multi-stakeholder companionship where the resident and the customer are at the heart of development activities (Anttiroiko, 2010). This also supports well the beforementioned need to shape the definition of smart cities into a more human-centered one. Weeckman et al. (2013) have emphasized the need to establish ways for community interaction and stakeholder engagement in order to succed in implementing living lab projects and create user-centerd innovation. The role of the Smart Kalasatama project in the living lab could be defined as what Westerlund & Leminen (2011) call ”enabler”, or orchestrator, organizing the network meetings and enhancing collaboration as well as offering collaborative working space and methodological knowledge to support the living lab activities. The project also has to establish ways for effectively communicate and engage its networks: the users and other stakeholders. 3 Case studies


Case 1. Researching the shared ideas on Kalasatama Three different kind of data sets were collected and analysed in the study (Bergström, 2015): a) public documents on communication between the city and residents and other stakeholder b) hand drawn mental maps of Kalasatama by the citizens of Helsinki c) word association lists related to trigger words “Kalasatama”, “Suvilahti” and “High buildings in Helsinki” from the same citizens. The public documents were analysed according to methods suggested by discursive psychologists (e.g. Potter & Wetherell, 1987; Billig, 1996/1987; Juhila 1993). Especially, the controversies and the logic of argumentation were looked at closely. The mental maps were analysed for their spatial dimensions as well as for the symbols and contents in a similar manner as in Milgram and Jodelet (1976) study on psychological maps of Paris. Word associations were classified and analysed for their positive, negative or neutral quality, as indicated by the respondents. The results show that the way in which Kalasatama was represented in the ideas of citizens was not very diverse or specific, according to descriptions given by the respondents for the word associations (Bergström, 2015). The views of Kalasatama were very consistent, and were defined by proximity to the sea, the subway, and novelty. On the other hand, Suvilahti, the old industrial area near Kalasatama, now a cultural center, which is considered as a part of Kalasatama, triggered a more vivid set of descriptions: summer, parties, music, a certain style of living. This could be seen as a result of recurring events and happenings that have shaped the representation and formed an identity for the area. This was further indicated by the numerous amounts of names of places associated with Suvilahti. Even places (cafe, event arenas) that were situated further away and so could have been associated with broader Kalasatama area, were associated with Suvilahti. This seems to stem from the way the representation of Suvilahti is strongly anchored and likened to the category of culture. When the core of the representation has formed, it will guide further notions about the phenomena (Abric, 2001). The visual dimension of Suvilahti, with its gasholder, graffiti, and the skatepark, support the idea of modern urbanism, which draws on nostalgia for the industrial era and the freedom of action in urban space. Case 2. KA:LAB – installation and living room KA:LAB was a two-week-long temporary living room and art installation. Construction and development company NCC offered an empty office space for the project. During these two weeks, a collaboratively made installation grew in KA:LAB, shaped by visiting groups and individuals. In KA:LAB video material from interviews with the residents were shown, and in art workshops different groups created art to be shown at the installation. Local people brought baked goods to be served in the living rooms cafe, and the local communities held their meetings in KA:LAB during the two weeks. The installation was a collaborative process, and the use of the space was part of the artwork. By using a space that would otherwise be quiet and empty, the people of Kalasatama expressed their wish for a lively, active city.


Part of the installation, a map of Kalasatama built by visitors, is now in possession of Helsinki City museum and will be shown again on 2016. The map was one attempt to archive the fleeting and changing ideas of a place that is constantly and so dramatically changing. The installation differed from many previous temporary art projects in that it was held in the middle of the new residential area, not in Suvilahti cultural center or its surroundings. Case 3. Kalasatama map service -community art project During KA:LAB, the art project held its first workshop, where the working methods were tested, aiming at producing thematic routes. By walking these routes a newcomer could explore Kalasatama like a tourist, seeing local specialties and learning about the history of people who live or used to live there. The workshops were partially based on previous study (Bergström, 2015), but the data collection methods were modified so that it could be collected in different workshops. The following events were held during spring 2015: a workshop table at a flea market in Suvilahti, three workshops with teenagers at the Centre for Performing arts and two workshops with elderly people in a senior house. The selection of people for the workshops, were guided by the need to easily reach groups that would be interested in working with the project. At the flea market a very wide spectrum of people attended, the teenagers were attending as a part of school program and the seniors were attending as a part of recreational program in their senior house. Approximately 150-200 people altogether attended these events. The ”drive-in workshop” at the flea market was aimed at producing a large amount of material that could be further developed and worked with at the following events. The people were asked what words they associated with Kalasatama (see blue notes on a map in Picture 1.), and which places they think would be worth seeing in Kalasatama (yellow notes in Picture 1.). We also asked people to pick up one of the photos of Kalasatama that we have selected, and write the reason why they found it interesting on the other side of the photo. Most of the people that attended the workshop didn’t reside in Kalasatama, so this way we produced an outsider’s perspective to the area.


Figure 1. Map of Kalasatama produced in workshops. Photo: Anastasia Artemeva

Figure 2. The old gas plant of Suvilahti in Kalasatama. Photo: Wikimedia Commons, Leena Tarjamo

The gasholder and old industrial building of Suvilahti (in Picture 2.) awoke vivid images in the participants: “In my imagination, this has been the ‘abandoned amusement park’. When I’m walking past, I hear the wagons of the rollercoaster rattling.” 52

“Unusual building and its history.” “I’ve never known what this building is. Don’t know it yet… It makes me think of the ‘Wall of death’, the motordrome in a circus.” The map was used in a workshop for the teenagers as a means of understanding other people’s ideas on Kalasatama. After that they produced their own performances to the urban space. With the seniors of Kalasatama we worked the material further: asking them to find something that they agreed or disagreed with. We collected “truths” about Kalasatama and then found meaningful places from the area. At the workshops we produced mind maps of the history, present and the future of Kalasatama with the seniors. They connected Kalasatama’s history to it’s maritime past, the boats, the trade and sailors. They also made a connection to a nearby residential areas of Sörnäinen and Kallio, recently gentrified inner city areas, that are known from their notorious past: bars, violence and prostitution. The present state of Kalasatama is connected to urban culture, represented especially by Suvilahti area. The residential area is not very well known by the wider citizen community. The residents often face questions, if the area is only for the rich people, despite of the fact that most of the participants didn’t count themselves as being especially wealthy, but very ordinary citizens. The seniors saw a very optimistic vision of a metropolitan, urban future ahead, but some uncertainty prevailed of how to get there. In these workshops we found interesting notions on how Kalasatama is seen among the residents and the outsiders. There are two different perceptions to the area: a wider one, that includes also parts of the surrounding areas that are seen linked to Kalasatama. This view comes close to the results of Case 1. The narrower one, that includes mostly the new residential area, was more popular among the residents. This narrower conception might be further emphasised by the limited transportation opportunities and few walking routes that the residents must use every time they need to leave the new residential area. The residents also are aware of the “subareas” that altogether form the broader Kalasatama area. The names of subareas were quite seldom mentioned among the non-residents that attended the workshops. 4 Discussion 4.1 Place identity of Kalasatama The three cases demonstrate means to produce descriptions of the area. This could serve as a base for the placemaking. The first case, a research project (Bergström, 2015), consisted of an empirical analysis of different data sets: public documents, hand-drawn maps and word associations. The level of analysis was a collective one: in the discourses and the visual material, certain descriptions of the place were widely shared by the participants. Together the analysis of the data offered a rich description of Kalasatama, and supported the idea of a place shared by human geographers such as Tuan (1977/2007, 171-172) who emphasizes the meaning of distinctiveness, history and significant events, and Friedmann (2010) who suggests that small scale places that serve as arenas for recurring event and ritual produce the feeling and experience of a place. The two latter cases were art projects, although the ”Kalasatama map service” used partially similar methods for collecting material, as was used in the research of Bergström (2015). The art projects are not aimed to produce knowledge per se in a similar manner as empirical research does, but rather reflect the feelings and ideas of people together with 53

them. KA:LAB – installation and living room aimed at producing a shared space for citizens to use: making a place in an empty space. The installation was a joint production of the residents mediated by the artists. 4.2 Engaging citizens in placemaking The act of producing a vision of a place is a powerful one. A collective vision was produced in the latter art project too, the ”Kalasatama map service”. It worked the individual notions and experiences forward, by grouping the material thematically, pulling together typical or similar ideas together with the citizens. This is very similar to the analysis of qualitative data, where the researcher moves back and forth between the data and the theory (see e.g. Braun & Clarke, 2006). Here, the participants produced their own material and at the same time built on the previous interpretations of other participants. It could be said, that the interpretation here was done by the participants, where in the research project it was done by the researcher. Giving voice for the people, is one of the aims for research in social sciences. In the arts project, the aim was to help people give the voice for themselves. The understanding of a geographical place and the shared meanings that are given to it by the people living in the area and other citizens are part of the operational environment of the living lab. Veeckman et al. (2013) very relevantly emphasized the need to establish ways for community interaction and stakeholder engagement. These ways of gaining new indepth understanding of a place that also serves as a living lab, help to set a firm base to open, user-centered innovation. It helps to direct and focus the user-participation to areas of development that are most meaningful and most relevant to them. It also helps defining which notions should be given more attention when communicating the living lab activities for the users and residents in an interesting manner. In this paper I have suggested some possible methods for gaining this understanding. As Veeckman et al. (2013) have suggested, the interplay between the characteristics of the living lab environment, the living lab approach, and the innovation outcome could and should be analyzed in a more detailed way after these first steps towards a truely open, user-centered innovation platform. When developing projects like Smart Kalasatama as a truly open innovation platform, understanding the shared ideas and representations of the people should be followed by well-planned possibilities to take part in living lab activities. Living labs should be a step towards a more democratic multi-stakeholder 4P-model (on 4P-model see e.g. Anttiroiko, 2010). Hence, their true purpose will not be fulfilled if the participation stays only on the level of consulting and gaining understanding peoples ideas. 5 Conclusions Placemaking is an active, collaborative process. Linda Rutherford wrote on a blog post in Project for Public Spaces (May 13, 2014) about placemaking: “I like to think of it as crowdsourcing meets urban and community planning”. This comparison is a very good one. Placemaking could be understood as a goal-directed journey from the starting point towards a new vision, done together by the community; public authorities, charities, or an organised group of citizens, in collaboration with businesses and other organisations. Making a place means that there must be distinctiveness, re-occurring events and happenings and a narrative that stems from the history of the place. Ideas on Smart City would develop better if there would be something concrete, something that could be experienced, touched, seen, heard; something that would represent the Smart City for the citizens. As our next step in the Smart Kalasatama project we are opening a collaborative working space for the citizens. The understanding of the place that these cases offer, help 54

us to understand what might be the problems that should be addressed, and what are the strengths of the area. It also helps to produce a narrative, a story for Kalasatama as a smart, new and developing place. 6 References Abric, J.-C. (2001). A structural approach to social representations. Teoksessa K. Deaux & G. Philogène (Eds.), Representations of the social. Bridging theoretical traditions (s. 42-47). Oxford, UK: Blackwell. Auburn, T. and Barnes, R. (2006), Producing place: A neo-Schutzian perspective on the 'psychology of place' , Geographical Review, 26(1), 38-50. Bergström, Maija (2015). Kalasataman rakentaminen sanoista ja sementistä. Tutkimus uuden alueen konstruoimisesta ja sosiaalista representaatioista. Master’s thesis, University of Helsinki. Billig, M. (1996). Arguing and thinking. Cambridge: Press Syndicate of the University of Cambridge (originally published in 1987). Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77-101. De Alba, M. (2011) Social representations of urban spaces: a comment on mental maps of Paris. Papers on Social Representations, 20, 29.1-29.14. Friedmann, J. (2010). Place and Place-Making in Cities: A Global Perspective. Planning Theory & Practice, 11(2), 149-165. Juhila, K. (1993). Miten tarinasta tulee tosi? Faktuaalistamisstrategiat viranomaispuheessa. In Jokinen, A., Juhila, K. & Suoninen, E. (ed.) Diskurssianalyysin aakkoset. Tampere: Vastapaino. Krivý, M. (2013). Don't Plan! The Use of the Notion of 'Culture' in Transforming Obsolete Industrial Space. International Journal Of Urban & Regional Research, 37(5), 1724-1746. Milgram, Stanley & Jodelet, Denise (1976). Psychological maps of Paris. In Harold Proshansky, William Ittelson & Leanne Rivlin (ed.), Environmental psychology: People and their physical settings, 104-124. New York: Holt Rinehart and Winston. Nam, T. & Pardo, T. A. (2011) Conceptualizing Smart City with Dimensions of Technology, People, and Institutions. The Proceedings of the 12th Annual International Conference on Digital Government Research, 282-291. Available at: demo.ctg.albany.edu/publications/journals/dgo_2011_smartcity/dgo_2011_smartcity.pdf Potter, J. & Wetherell, M. (1987). Discourse and Social Psychology. Beyond Attitudes and Behaviour. London: Sage Publications. Rutherford, Linda (2014). Blog post, May 13, 2014: Project for Public Spaces. Why public places are the key to transforming our communities. Available at: http://www.pps.org/blog/why-public-places-are-the-key-to-transforming-ourcommunities/ Tuan, Y. (2007). Space and Place: The perspective of experience. Minneapolis, MN: University of Minnesota Press (originally published in 1977). Wortham-Galvin, B. D. (2008). Mythologies of Placemaking. Places, 20(1). 32-39.


Living Lab theory and tools Session II


The wearable Living Lab: how wearables could support Living Lab projects Tanguy Coenen a, Lynn Coorevits b & Bram Lievens a a

iLab.o, iMinds-SMIT, Vrije Universiteit Brussel b iMinds-MICT, Universiteit Gent tanguy.coenen@vub.ac.be

Abstract Part of the added value of living lab or other in-situ research resides in its capability to capture contextual and personal data of end-users in real life environments. In this paper, we present an architecture for the wearable living lab (WELLS), allowing the collection of user experience feedback in a more permanent and unobtrusive way. It enables mainly the user researcher to capture contextual and experience data during a Proxy technology assessment, a formative or a summative software evaluation. Keywords Wearables, living lab, evaluation 1 Introduction Wearables provide intrinsically different opportunities for the research process of several application domains ranging from health to consumer research. We perceive wearables as any computing device that can be worn on the body (from smart-textiles to smartbracelets, -jewelry and –watches). They enable the monitoring, tracking and controlling of several human activity types. A distinguishing feature is that, unlike other devices such as smartphones, wearables are often worn almost permanently and therefore allow the continued and longitudinal capturing of data. The market for wearables is looking promising and wearable computing devices are increasingly hitting the market, like smart and sport watches (e.g. Pebble, Apple Watch,...), fitness trackers (e.g. Fitbit, Jawbone UP3,...) or smart glasses (e.g. Google Glass). Consumer-grade wearables allow the measurement of different types of user data in a less obtrusive and often more objective way than current, mainstream living lab data collection methods , i.e. observation techniques or surveys. Also, software development is more and more taking place in the context of mobile devices, where the interactions that the user has with the system are mediated by the context in which the use takes place (at work, at home, in the car, in bed,...). The assessment of such systems requires an in-situ or “in the wild” evaluation. Current application developers and researchers try to evaluate the software product by logging the actions of the users. However, logging data on itself has its limitations as it cannot track all contextual elements nor the individual’s personal experiences related to the usage of the application. Therefore, (additional) experience sampling is used to capture 57

in the moment experiences of users. Both techniques allow to track users ‘in the wild’, but requires specific research methods that afford the continuous evaluation of the user’s response to the system. Katz (2001) concluded that there is an invisible side of emotions that cannot be induced from observations of user behavior alone. One way to measure emotional fluctuations is by researching their physiological changes via skin conductance in order to understand arousal. Due to the specific set-up and technology required, such measurements were only possible in a dedicated physical location. Because of the ongoing commercialization of wearables allowing measurement of behavior as well as psychological changes, wearables provide research opportunities in living lab environments. To allow this, the challenge which was already addressed in e.g. the work of Kocielnik et al (2013) or Sano & Picard (2013), to make such measurement work outside of controlled lab conditions, must be further taken up for application in living lab conditions. In other words, we must ask how these measurements can be made in the in-situ evaluation conditions that distinguish living lab projects from other design approaches. In this position paper, we discuss how wearables can be used in living lab projects (and by extension other types research with an in-situ component) to perform novel types of systems evaluation. To do this, we first discuss the process structure of living lab projects, which informs us on what living lab stages can benefit from unobtrusive systems evaluation. Then, we proceed to discuss how this can be done with the means that are currently or in the near future on the consumer market. We focus on consumer-grade devices, as it is important that the user of the device become as accustomed to it as possible, in order not to bias the data (Henandez et al 2014). Consumer-grade devices are designed to accomplish exactly such accustomedness. Another reason for focusing on consumer-grade wearables is that evaluations in living labs are often large-scale. This can only be achieved if the wearables to be used are already owned by the user, or because their cost of acquisition is low. In sum, this paper discusses how the need for in-situ evaluations that exist in living labs can be met by the opportunity of new wearables becoming available as consumer devices. 2 Prototype evaluation in Living Lab projects Living lab-research is a state-of-the-art methodology aiming at the involvement of endusers in the innovation process. Although there are several ways of integrating consumers in the innovation process, living labs are interesting because of the context for understanding customer co-creation. Living labs are experimental platforms where endusers can be studied in their everyday context (Eriksson et al. 2005). They confront (potential) users with (prototypes or demonstrators of) products and/or services in the innovation process (Schuurman & De Marez 2012). As a distinguishing factor of living labs is that the systems they produce are tested in non-laboratory conditions, but “in the wild” (Westerlund & Leminen 2011, Ballon 2015). By introducing this in a real life environment, experience based learning and discovery (facilitating serendipity) is made possible. Through real-time iterations the design and development actions are constantly being validated. This will help developers to make more informed decisions, thus increasing the likelihood of success (Trimi & Berbegal-Mirabent, 2012). Various types of process models for living labs have been proposed in literature (e.g. Pierson & Lievens 2005, Schaffers et al 2008, Tang & Hämäläinen 2012, Bergvall-Kåreborn et. al 2009). Recently, Coenen & Robijt (2015) proposed the Framework for Agile Living Labs (FALL) process model as a way to guide both researchers and practitioners in how to perform a living lab project. This process model was shown to be compatible with most of the existing process model literature. 58

In the FALL approach to a living lab project, there are 2 stages in which user feedback can be of use, i.e. the problem formulation and the so-called BIEL phase. In the problem formulation phase, users can be brought in contact with existing technologies that are configured to mimic the behaviour of the prototype that the project team has in mind. This is done through a Proxy Technology Assessment (PTA) (Pierson et al 2006). In the iterative build, intervene, evaluate and learn (BIEL) phase, two different types of evaluations can be performed to get user feedback on a prototype: formative or summative evaluation. In formative evaluation, the prototype is of a very provisional nature and the aim is to get feedback that allows the living lab team to create better prototypes after it. In summative evaluation, the objective is to evaluate a more stable prototype and find out how effective and efficient it is to be able to report this to some project stakeholder (client who commissioned the project, customers, societal actors,…). These three types of prototype evaluation are the domains where we see potential in living lab projects for the application of research methods that are supported by wearables. 3 WELLS or how wearables can be used to support prototype evaluation in living lab projects Based on our experiences in conducting real life evaluations of prototypes in living labs, as well as the literature on wearables, usability research and affective computing, we propose the architecture for a Wearable Living Lab Software Evaluation System (WELLS) depicted in Figure 2. Various roles are described as part of FALL, of which the user researcher is the role that is involved in carrying out the evaluation of prototypes. It is therefore the user researcher that will be the main consumer of the data generated by WELLS. Taking into account the opportunities of the wearable devices and the research needs for in-situ, contextual user-centered living lab research we focus on two main types of data-sets collected through wearables: bio-data and context data.

Figure 1: Architecture for a Wearable Living Lab Software Evaluation System (WELLS)


4 Bio-data In our choice of sensors for measuring bio-data to be included at the core of the WELLS system, we concentrate on sensors that can provide a measure of the arousal experienced by the user. Arousal is a general term describing an emotional response by the user. The valence of the response can be either positive or negative representing emotions such as excitement and frustration. We interpret arousal according to the two factor theory of Schachter Singer (1962), assuming that arousal is the product of physiological arousal and the cognitive processes that respond to a particular situation(=context and stimuli) provoking the emotion. The cognition of the user will determine whether the physiological arousal will be perceived as anger or happiness. As sensors can detect arousal but not the valence of the emotion, the WELLS model also adds contextual data in order to enrich and by so interpret the captured bio data better. Measuring arousal will detect positive or negative experiences and therefore identifying moments and actions where a prototype can be improved on. Various physiological measures can be used to indicate arousal, among which blood pressure, heart rate, heart rate variability (HRV), electrodermal activity (EDA), pupil diameter (Sano & Picard 2013) as well as facial expression (Albert & Tullis 2013). However, not all of these measures can be collected using unobtrusive devices. For example the measurement of pupil dilation requires the constant training of a camera on the subject’s pupil. By investigating current hardware offerings, we found that what can currently be measured in the least obtrusive way are electrodermal activity and heart rate. 4.1 Electrodermal activity “Electrodermal activity is a measure of sweat excreted by the eccrine glands, which are innervated by the sympathetic nervous system”. (Hedman et al 2012). Electrodermal activity has been used widely to measure the response of the sympathetic nervous system to events in our environment. In the past, devices that were used to do this were often cumbersome to the wearer, resulting in feelings of stress resulting from wearing the device itself. Recently, devices like Philips’ Discrete Tension Indications (DTI-2) or the Empatica E4 Wristband have become available that allow EDA measurement by wearing a relatively unobtrusive, watch-like device. The latest in wearable fitness trackers, like the Jawbone UP3 wristband allows to measure electrodermal activity through the use of a device type that is becoming more and more mainstream on the consumer market. These mainstream devices will reflect a natural setting for participants and will allow Living Lab researchers to maintain a real life research setting. 4.2 Heart rate Heart rate and heart-rate variability, or the fluctuations in beat-to-beat intervals, can be used to detect stress and arousal (Albert & Tullis 2013, Choi et al 2012). There are more devices that can measure heart rate than EDA, making it a pragmatically useful addition to the WELLS architecture. Indeed, heart rate can be measured by mainstream fitness wearables by wearing a sensor band on the torso. However, wearing such a band is obtrusive and few are the people who would want to wear it permanently, beyond their fitness workout. But as for EDA, new devices are becoming available that can be worn on the wrist and that also measure heart rate.


5 Context data 5.1 Video and audio Video can be used to capture the interactions of the user in a rich way and has been proven to be highly valuable to detect possible improvements of the user experience. Within usability research, video has been used in various way to capture and detect user interactions and experience. However, this has either been in a controlled lab environment or with very obtrusive equipment when performing this in-situ. For a pervasive game called “Playground”, we collected user data with smart glasses, as they are able to capture the users context when using the system in a rather easy and less obtrusive way. Players were asked to play the game on smartphone, while wearing these smart glasses and performing the think aloud protocol. The latter is a standard method in which participants thinking aloud as they are performing a specified amount of tasks. Because the data is recorded, developers can look back at the experiences and reactions of the users and interpret the data. As pervasive games are not only about the use of the game on a mobile device, but also about the experience of the player with the physical environment in which the game is set. By using smart glasses, both dimensions (use of device and interaction with physical context) could be captured in rich detail. Our experience within the Playground project indicated that the use of smart glasses is promising but still a number of issues need to be tackled. First, they are less unobtrusive than expected. For example, Google Glass constantly shows a display in one’s field of vision. It is therefore hard for the user to “forget” the presence of the recording device. In addition, battery life can be a hurdle in smart glasses. The battery life time of Google Glass is limited (one hour of video recording), making long experience sessions difficult. In addition, there were issues with the video framing. As the camera in the Google glass is located in the top-right corner of the glass frame, the recorded video did not always catch the interface on the smartphone. Finally, often the video was not focused on the interface, but on other objects in the field of view. This resulted in blurry recordings of the interface, making it hard to identify certain interface elements. An alternative to using smart glasses is devices that are used for “LifeLogging” or the longterm recording of video in daily life. One example is the Narrative clip 2, which allows up to 30 hours of video recording through a device that can be clipped on clothing and is around 10 by 10 cm large. However, many of these devices do not record audio. Our experience within Playground learned that audio is often essential as extra information layer to allow users to express their frustration and provide additional context on what it is that they are experiencing. 5.2 Experience sampling Experience sampling is a research methodology in which users are asked to self-report on various elements (such as experience, context,…) on specific moments (this could be timebased, event-based,…). Huang et al (2014) and Sano & Picard (2013) e.g. used experience sampling, via short questionnaires distributed through a smartphone app, to query the user on their emotional state of mind. In their research they demonstrated that gathering survey data can be of great use in identifying emotions such as stress related to a specific context. The captured data also linked with a whole batch of collected metrics like EDA, heart rate and others. However, in systems evaluations in living labs, taking place in reallife, naturalistic environments, the identification of stress needs to take place within a brief time interval from the event that caused the affective response. This needs to be done to be able to identify instants that caused an affective response, making aggregate experience 61

sampling per day ineffective as retrospective self-reporting will not reveal these specific moments. Therefore, more fine-grained approaches need to be included to measure affect. Two options are possible: (1) based upon real-time data of the wearables in which the reporting is triggered by certain data-points. But this would require a permanent online connection and could also results in too many interactions and request. (2) based upon predefined intervals in which the user is asked to evaluate her aggregate affect level in a previous time interval. Such an approach would not produce labels on the exact moments when stressful events took place, but being able to search down the search space would be useful in analysing the large amounts of data that will be produced by a large-scale evaluation using the WELLS infrastructure. 5.3 Location, event logs and time Keeping track of location is important to be able to gather context data. Such location data can come from geolocation based on GPS, wifi or bluetooth data as is often done in mobile, geolocative apps. A well-known drawback of such apps is the rate at which they drain a smartphone’s battery. Situations where location is less accurate but more energy efficient can be built based on iBeacon solutions. In such cases, the captured data only shows in what general area the user resides. An infrastructure cost is associated with such a solution, as the area in which the user interaction takes place needs to be fitted with iBeacons. Next to location, movement is also an important contextual element, which can easily be determined due to the accelerometers within smartphones and wearables. This data stream is also important, as it can determine if a user is moving or not. Keeping event log data is another important aspect of evaluating data during in the wild trials. Such log data can indicate bugs and can provide useful context information to be able to further make sense of the user’s behavior. Finally, keeping accurate time is essential for synchronizing data in the research interface when data is coming from multiple sensors (Banaee et al 2013). Therefore, having timestamps that are in sync for all measurements is critical. 6 Smartphone The smartphone plays an important central role. Firstly, most wearables need a smartphone to make connection to various (cloud-based) services. Therefore it can be used to bundle the incoming data and send it over to the data repository in an efficient way (stability, robustness…). In the future, wearables may become directly connected to internet, bypassing the need for smartphone. Secondly, the smartphone can help in keeping all sensor data sets synchronized. 7 Data repository The data repository should store the data coming from as many sources as required. It should be able to receive real-time or batch data from the smartphone. In addition, this data should be stored in such a way that privacy requirements are met. It is important to keep in mind that other metrics can be of use when measuring user affect. As more wearable sensors will become available, it will be important to make the architecture as extensible as possible, to be able to quickly add new sensors to the system. The data repository, and the way in which it is accessed, provides the main point in the architecture where such future compatibility needs to be realised. This will require flexible API’s that can accommodate data coming from a wide array of sensors as well as an efficient identification mechanism. 62

8 Research interface The purpose of the research interface is to allow user researchers to make sense of the data that is produced by the sensors and the smartphone. Especially relevant are moments in the user’s experience that have generated arousal while using the application being evaluated. In order to support sense making by user researchers, the WELLS data should be visualised, mined and made queryable.

Figure 3: Wearable Living Lab research interface mockup, adapted from Kocielnic et al (2013). Galvanic Skin Respons (GSR) is synonym to eletrodermal activity (EDA). Foto is a still from a Google Glass recording of a user session in Playground Kortrijk

8.1 Data mining The amount of data produced by sensors over a longer period of time can be very large. In order to make sense of such sensor data, which comes in the form of a time-series, analytical methods are necessary. Banaee et al (2013) provide a survey of the methods used in data mining and machine learning in the area of medical applications, that is relevant to the aims of this paper. In their literature review, they found support vector machines, decision trees, neural networks, hidden markov models, gaussian mixture models and rule-based models to be in use. It is important to distinguish EDA and HRV fluctuations resulting from movement from electrodermal activity resulting from emotional response. This can be achieved by applying rule-based filtering, one of the main data mining approaches discussed by Banaee et al (2013). The data from the 3-axis accelerometer is crucial in distinguishing both types of EDA and HRV response. Rules can be built that disregard EDA data from periods in which the user was moving along one of the 3 axis in a value that exceeds a certain threshold. The main objective in the analysis of data coming from user experience evaluation in living labs should be on finding instants that coincide with increased arousal from users. These instants can then be labeled as possible candidates for further analysis. By juxtaposing data that has been labeled in such a way from EDA or HRV with video, audio and location data, a rich picture will emerge of what features and contextual circumstances can be stressful or enjoyable to the user.

63 Â Â

8.2 Visualisation In order to be useful, the system needs to visualize the data in a way that facilitates sense making. The video and audio data will be the main way in which the user researcher will come to understand what exactly was going on at a particular point in time. However, the video and audio data of a certain evaluation can be extensive and if the trials are largescale, user researchers can not be expected to go over all the produced video and audio for each participant. Therefore, combining the video/audio feed with data mining techniques on data coming from other sources can be powerful to discover moments in the data where the user got frustrated with using the software. Kocielnic et al (2013, 2014) experimented with collecting work stress-related data using EDA over a prolonged period of time. A visualisation was created that combined sensor data from EDA and accelerometer with labels that were extracted by interfacing with online agendas. Not only did this approach deliver an instrument for the analysis of the data, it was also able to present the findings back to the user and in this way obtain better self-reporting. By combining a visualisation of EDA data with calendar data and questionnaire data, users were able to make sense of their experiences in terms of the relative stressfulness of different events in their day-to-day professional life. 8.3 Privacy issues Continuous tracking poses many privacy challenges that neither users nor stakeholders are ready to deal with. Wearables constantly collect, transmit and store data that is considered personal, private, sensitive and confidential by users. This brings many benefits to the researchers, as it can provide them with access to end-users’ latent experiences and fill the gap between the saying versus doing paradigms. Yet for users this constant surveillance and sousveillance can lead to privacy threats and risks. Sousveillance is the recording of an activity by a participant in the activity typically via small wearables or other small portable technologies (Mann, Nolan & Welmann, 2003). Users are currently less aware of these privacy concerns because wearables are a relatively new thing. In addition, wearables are often shaped as accessories that never posed any privacy threats to users such as glasses, watches, etc. Motti & Caine (2014) identified several privacy concerns from users about wearables related to the device and the application itself, the data being captured and the sensors. Especially their last two concerns are of importance to living lab research. Data specific privacy concerns are related to the issues of users that certain data, when combined, could have critical implications. Next to having the explicit consent of the users, it will also be necessary to inform the users on which type of data will be collected during the scope of the research, what will be done with that data as well as to foresee the ability to delete all data afterwards (in line with the EU policy on the right to forget). 9 Discussion We have described the general architecture of a wearable living lab and touched upon certain opportunities and challenges. However we are still in the phase of putting the integrated WELLS architecture into practice. The benefit of WELLS is that there are no aspects of the architecture that can not be implemented using today’s consumer-grade wearables technologies, web-based programming languages, database systems, machine learning and visualisation techniques. What remains to be investigated, however, is the accuracy of the different devices that are and will become available and the quality of the data. In addition, some other concerns exist in terms of battery power, data heterogeneity, form-factor, ruggedness and ease of use. 64

Battery power has been a constant issue in many recent technology developments. Certain applications, like geolocalisation, can drain a smartphone battery at a much increased rate compared to a normal smartphone application. The WELLS system will only remain operational for as long as all of its components remain active. How long we can expect this to be still remains unclear, but is an important unknown to figure out in order to allow long-term measurements of user experience. Data heterogeneity will result from different devices creating different data in a variety of formats. Handling this so that for example all data feeds can be combined and accurately synchronized is a hurdle which we still need to tackle. Form-factor is an important aspect, as it influences the obtrusiveness that is experienced by the user. For example the form factor of the Google Glass proved to be sub-optimal, as users would not feel comfortable with wearing the device. For devices in the wearable living lab to function well, they should be as invisible as possible, both for the user as its environment. Video-capturing devices are available that allow more discreet video-recording, but many of them also have their limitations, like lack of audio recording capability. Still, previous research on wearables shows that even for more common devices such as wristbands it takes a while for users to get accustomed to the device and start behaving naturally (Hedman, 2011). Therefore we will need to investigate how the use of a WELLS architecture impacts the natural use of the systems under investigation. Rugedness is important, as the wearables living lab needs to remain operational in various environmental condition. Especially continued active when it is raining seems essential. Finally, the WELLS architecture should be coordinated through an app that runs on a smartphone and that is able to handle all the interactions that are needed with the user. As with all applications, it will be necessary to make sure that the user experience design of this app, and the way in which it integrates with the wearables, is created in such a way that it is as easy to use as possible. The WELLS architecture can be of use in each of the three living lab phases discussed above: a PTA, a formative prototype evaluation or a summative prototype evaluation. WELLS will be most useful in situation in which mobile technologies are evaluated. Indeed, these are the technologies that are hard to evaluate in usability lab conditions, as many of the user’s reactions will result from the combination of the software and the context in which the user resides. Ballon (2015) found that, although there is heterogeneity in the existing living lab approaches, they share four characteristics: (1) the discovery of unexpected usage and new service opportunities, (2) the evaluation or validation of new digital technology solutions by users, (3) a familiar usage context, and (4) a medium or long term research angle. We believe it is clear that WELLS can add novel aspects to each of these characteristics but can not go into detail on how this is the case due to space restrictions. We plan to use this architecture in many of our ongoing research and development projects. One example is a pervasive city game in which players can use their smartphone to play games in the urban environment. Another is a project in which the aim is to provide resistive schyzophrenic patients with cognitive behavioral therapy over wearable devices. Both projects are examples that will need users to experience the system in a prologued way, underlining the need for a research approach that can collect, analyze and visualize in the wild and continuous data, originating from an extensible set of sensors. 10 Conclusion We have presented an architecture for the wearable living lab, a system to collect user experience feedback in living lab projects. The user researcher is the main consumer of the WELLS data and can use the system in a living lab project during a PTA, a formative or a summative software evaluation. Its relevance for Living Lab or other in-situ research 65  Â

resides in its capability to capture contextual and personal data of end-users in real life environments. The next steps are to build, gradually, a concrete instance of WELLS and to explore and evaluate the different elements addressed in this paper. This will entail creating a system that can support a living lab research approach (and in-situ research in general) that can collect, analyze and visualize in the wild and continuous data, originating from an extensible set of sensors. 11 References Albert, W., & Tullis, T. (2013). Measuring the user experience: collecting, analyzing, and presenting usability metrics. Newnes. Ballon, P. (2015). Living Labs. The International Encyclopedia of Digital Communication and Society. John Wiley & Sons Banaee, H., Ahmed, M. U., & Loutfi, A. (2013). Data mining for wearable sensors in health monitoring systems: a review of recent trends and challenges. Sensors, 13(12), 17472–17500. Bergvall-Kareborn, B., Hoist, M., & Stahlbrost, A. (2009). Concept design with a living lab approach. In System Sciences, 2009. HICSS’09. 42nd Hawaii International Conference on (pp. 1–10). IEEE. Choi, J., Ahmed, B., & Gutierrez-Osuna, R. (2012). Development and evaluation of an ambulatory stress monitor based on wearable sensors. Information Technology in Biomedicine, IEEE Transactions On, 16(2), 279–286. Eriksson, M., Niitamo, V. & Kulkki, S., 2005. State-of-the-art in utilizing Living Labs approach to user- centric ICT innovation - a European approach., Sweden. Hedman, E. "The Frustration of Learning Monopoly: The Emotional Tension of Entering a New Game Encounter," The Ethnographic Praxis in Industry Conference, Boulder. September 18-21 Hedman, E., Miller, L., Schoen, S., Nielsen, D., Goodwin, M., & Picard, R. W. (2012). Measuring autonomic arousal during therapy. In Proc. of Design and Emotion (pp. 11–14). Hernandez, J., Riobo, I., Rozga, A., Abowd, G. D., & Picard, R. W. (2014). Using electrodermal activity to recognize ease of engagement in children during social interactions. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 307–317). Huang, S. T.-Y., Kwan, C. M. Y., & Sano, A. (2014). The moment: a mobile tool for people with depression or bipolar disorder. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication (pp. 235–238). ACM. Katz, J. (2001). How Emotions Work. London: University of Chicago Press. Kocielnik, R., Sidorova, N., Maggi, F. M., Ouwerkerk, M., & Westerink, J. H. (2013). Smart technologies for long-term stress monitoring at work. In Computer-Based Medical Systems (CBMS), 2013 IEEE 26th International Symposium on (pp. 53–58). Kocielnik, R. D. (n.d.). LifelogExplorer: A Tool for Visual Exploration of Ambulatory Skin Conductance Measurements in Context. In Proceedings of Measuring Behavior 2014. Mann, S., Nolan, J. & Wellmann, B. (2003)., Surveillance & Society 1(3),331-355 Pierson, J., & Lievens, B. (2005). Configuring Living Labs For A “Thick” Understanding Of Innovation. Ethnographic Praxis in Industry Conference Proceedings, 2005(1), 114–127. Pierson, J., Jacobs, A., Dreessen, K., Lievens, B., Van den Broeck, I., & Van den Broeck, W. (2006). Walking the interface: uncovering practices through proxy technology assessment. EPIC 2006 Proceedings, 24–26. Sano, A., & Picard, R. W. (2013). Stress recognition using wearable sensors and mobile phones. In Affective Computing and Intelligent Interaction (ACII), 2013 Humaine Association Conference on (pp. 671–676). IEEE. 66

Schaffers, H., Garcia Guzman, J., & Merz, C. (2008). An Action Research Approach to Rural Living Labs Innovation. Proceedings of the Cunningham and M. Cunningham (Eds), Collaboration and the Knowledge Economy: Issues, Applications, Case Studies. IOS Press. Schachter, S., Singer, J. (1962). Cognitive, Social and Physiological Determinants of Emotional State, Psychological Review, 69, 379-399 Schuurman, D. & Marez, L. De, 2012. Structuring User Involvement in Panel-Based Living Labs. Technology Innovation Management Review, (September), pp.31–38. Tang, T., & Hämäläinen, M. (2012). Living lab methods and tools for fostering everyday life innovation. In Engineering, Technology and Innovation (ICE), 2012 18th International ICE Conference on (pp. 1–8). IEEE. Trimi, S. & Berbegal-Mirabent, J. (2012). Business model innovation in entrepreneurship. International Entrepreneurship and Management Journal, 8(4), 449–465. Westerlund, M., & Leminen, S. (2011). Managing the challenges of becoming an open innovation company: experiences from Living Labs. Technology Innovation Management Review, October 2011.


Change Laboratory as a method of innovation management in an Urban Living Lab Virpi Lund & Soile Juujärvi a a

Laurea University of Applied Sciences virpi.lund@laurea.fi

Abstract Urban living labs (ULL) challenge researchers and developers with bottom-up approach and diverse problems which require appropriate tools for innovation management. The Change Laboratory® (CL) is such a promising method which has widely been used in organizational development but not yet applied in living lab contexts. The present paper describes the application of the CL in the suburban area in Southern Finland. Residents, city planners, civil servants and non-governmental organizations (NGOs) were invited to join the workshop process aiming at enhancing collaboration and establishing shared goals for urban development. Problems were analyzed and reinterpreted with the CL tools revealing contradictions in current practices. The results suggest that mirror data and conceptual tools as intervention methods are powerful stimulus for problem-analysis and goal-setting in urban and community development. Keywords Change Laboratory, living labs, residents, stakeholder collaboration, urban development 1 Introduction Cities can be said to be self-organizing organisms, involving complex problems, such as excessive bureaucracy, social segregation, poor image, or economic differences (Baynes, 2009). Living laboratories provide a promising approach to handle those problems and innovate new solutions in urban areas, requiring bottom-up innovation process and collaboration among multiple stakeholders. One of the success factors for urban living labs is a composition of all actor roles: enablers, utilizers, providers and users (Leminen, Westerlund & Nyström, 2012). Enablers represent public-sector actors providing strategy, visions, and networks, and allocating financial resources; utilizers are enterprises, public sector actors, and NGOs willing to experiment services and products; providers represent research and development institutions offering innovative methods and taking care of systematic augmentation of knowledge. Finally, users are residents and other people habiting the area who give opinions, participate in co-creation and empower other residents in developmental initiatives (Juujärvi & Pesso, 2013). Urban Living Lab (ULL) has been defined as a forum for innovation that integrates residents and other stakeholders to develop and test new ideas, systems and solutions in complex and real contexts (JPI, 2013). ULLs capture many essential features identified in 68

the living lab literature (Westerlund & Leminen, 2014). First, they represent an ecosystem or networks involving multiple stakeholders which are motivated by different objectives but would benefit from collaboration. Prerequisites for successful collaboration are learning for interaction and handling power issues (Hakkarainen & Hyysalo, 2013). Second, ULLs provide tools for enhancing and implementing public and user involvement. Resident involvement has been regarded crucial for speeding up innovation process and enhancing participatory democratic practices; despite that recruiting residents is challenging and they need targeted support (Friedlich, Karsson & Federley, 2013; Veeckman & Graaf, 2015). Third, ULLs can be seen as an innovation management tool for building networks and user involvement in urban development (Edwardsson et al., 2012; Westerlund & Leminen, 2014). Notwithstanding all above-mentioned aspects are important, the present paper is focused on innovation management that has received little attention in past studies. The Change Laboratory® is a formative intervention method based on the theory of expansive learning (Engeström, 1987, 2007; Virkkunen & Newnham, 2013) which has been widely applied for promoting innovation and learning within organizations but not explicitly used in regional or urban development to date. The aim of this paper is to present the application of the CL with the emphasis on one of its distinguishing features: the analysis of contradictions. We argue that the CL provides a comprehensive conceptual framework for innovation management, and effective tools for analyzing and solving multidimensional urban problems through collaborative learning. Our challenge is to modify it to respond to the needs of ULL that gathers actors across variety of organizations and sectors lacking explicit shared goals, rather than from single organizations with officially defined objectives. The remainders of the paper are organized as follows. The target area of the ULL initiative, Espoo Centre, is next described, followed by the description of the CL and its recent application, Community Workshops. Then the application of the CL is exemplified by the case Community Space emerged in the workshops, focusing on the phase of problemanalysis (analysis of contradictions). In particular, we wish to illuminate one of the distinguished CL tools, using double stimulation, as means of enhancing problem-solving and collaboration. Last, the paper is finalized by conclusions. Our aim is to describe the implementation of the Change Laboratory method and its possibility to reveal the contradictions of everyday practice. 2 Espoo Centre as an ULL platform This study is a part of a three-year participatory action research (Kemmis &McTaggart, 2000) aiming at examining and enhancing residents’ participation and developing efficient means for residents and stakeholders’ collaboration in urban development. The focus area is a part of the municipal district in the city of Espoo, in southern Finland, consisting of the administrative centre of the city with a railway station and two shopping malls, surrounded by two neighbourhoods of 17 000 people altogether. The area is characterized by different historical layers in terms of construction and waves of migration, mainly refugees, from 1970’s onwards. Cultural and ethnic diversity in daily life is reflected in a high proportion of immigrants and over 70 of spoken languages. In the light of social and economic indicators, the area represents the least advantaged area in the City of Espoo, mainly due to the concentration of social housing (Residents’ welfare in Espoo, 2013). The area has also multiple strengths, such as good transportation and availability of services, surrounding nature with indoor activities, and historical buildings. The area has been a focus for dozens of research and development projects in last decades, including current renovation projects by the city.


The present research project is motivated by two main observations: low user involvement in previous development projects and a lack of systematic collaboration between various local stakeholders and developers. Recent interviews with stakeholders however revealed their strong will to develop collaboration and engage residents in development activities (Juujärvi, 2014, Juujärvi & Lund, forthcoming). It was concluded that the living lab approach could provide an appropriate innovation platform for a systematic collaboration initiative that would bring together local residents and other stakeholders with overlapping aims to share their interests and build collaboration. The CL was primarily selected as a suitable method, because its aims at expanding participants' understanding about the objects of development work that would furthermore lead to shared goals enabling purposeful collaboration. Second, the CL starts with the analysis of contradictions in current work practices that are historically molded and outdated to respond to urgent challenges in work. It seemed obvious that current practices in urban and community development were heterogeneous originating from various historical layers and developed to respond individually to emerging urban problems at different times. We therefore expected that the analysis of contradictions could be essential for creating sustainable new ways of collaboration. 3 Change Laboratory as an intervention method CL is a formative intervention method widely used in organizational development which has roots in cultural-historical activity theory (Vygotsky, 1978; Leontj’ev, 1978), and its Finnish application of developmental work research (Engeström, 2007; Engeström, Virkkunen, Helle, Pihlaja & Poikela, 1996; Virkkunen & Newnham, 2013). In the culturalhistorical theory, work can be conceptualized through the activity system with six components: the subject, the object, mediating artifacts, the rules of participation, community, and the division of labor. The activity system is usually depicted as a trianglemodel (see Figure 1) (Engeström, 1987, 2001). The activity system is a unit of analysis in the CL; it is used to describe the entity of activity with the changing object. A crucial part of the analysis is contradictions within and between the components which are seen as a driving force for a change (Il’enkov, 1977, 1982). Contradictions are systemic, structural obstacles that need to be broken away from new forms of activity to emerge. Each activity system has its own history against which contradictions and challenges can be understood. The analysis of the internal contradictions of the activity system helps CL participants to shape and renegotiate the shared object and work on other components as well.


Tools, Instruments

Object Outcome




Division of Labour

Figure 1. The structure of human activity (Adapted from Engeström, 1987, p.78)

Collaboration among participants in the CL is based on expansive learning which means new understanding in concrete situations with the elements (components) of the activity system. Expansive learning forms a cycle where questioning and analyzing contradictions necessitate changes in current practices, leading to innovating new models and ways of working. The cycle of expansive learning is interwoven in the phases of the CL process (see Figure 2). Usually the CL process has from five to ten successive sessions. In our case, we made a shortened version of five workshops for ULL purposes covering five phases with the experimentation period of two months. The main reason for shortening was that people participated on the voluntary basis and, therefore, it could be difficult to maintain their participation over long time. 6. Spreading and consolidati ng

5.Implementi ng the new model

1. Charting

the situation

2. Analyzing the situation

4. Concretizin g and 3. Creating testing a new model the new model Figure 2. The phases of Change Laboratory process (Virkkunen & Newnham, 2013, p. 17)

4 Community workshops The research project Välittävät Valittavat Verkostot (Caring and Sharing Networks in English) arranged the Community Workshops in winter-spring 2015. The procedure 71

involved five successive workshops with two-week intervals and the experimentation period of two months between the fourth and five workshops. The workshops were scheduled to start at 04.30 p.m. in a local city hall and took approximately two and half hours. Forty-seven invited people attended to the workshops, varying from 30 to 38 across the workshops. The participants involved residents and members of resident associations, managers of regeneration projects, city planners, public servants and experts in the city administration, representatives of non-governmental organizations and local parishes, and managers of shopping malls. The workshops were managed by a consultant qualified for practicing the CL method in collaboration with four researcher-interventionists who acted as group facilitators in four groups. For research purposes, all workshop activities were recorded and documents photographed. The analysis of the present paper is confined to the second workshop in which participants with similar interests grouped together and were instructed to analyze present troubles and contradictions in current practices. The authors listened to the recordings several times, reviewed prior observations by the group facilitators and analyzed the group documents. Finally, one of the groups was selected a case to illustrate the workshop process. 5 Double stimulation as an intervention method Collaboration and learning in the CL is based on the method of double stimulation (Vygotsky, 1978; Sannino & Engeström, 2015). Double stimulation enables human being to use volition and agency for transforming the contradictory circumstances with the help of the external artifacts providing meaningful tools (Sannino, 2015). There are two types of stimulus material: the mirror data as the first stimulus and conceptual tools as the socalled mediating second stimulus. The mirror data is ethnographic data collected in various ways such as observing events, interviewing actors, shadowing practices, or studying documents representing critical viewpoints, trouble and problems in current practices. The mirror data can be collected by participants or research interventionists. The purpose of the mirror data is to make distracting and deviating things in current practices visible; it has a crucial role in identifying contradictions in the current system of activity. It is presented to participants in order to challenge various interpretations and get them engaged in seeking new solutions. Tasks, models and questions given by researcherinterventionists serve as the second mediated stimulus that helps participants to analyze and interpret the mirror data. These two types of stimulus serve different purposes; the mirror data makes participants confront unpleasant facts of the current activity, whereas theoretical tools help them to distance themselves from the emotionally difficult situation. Movement between concrete observations and abstractions is important, because it fuels participants’ learning and real change (Virkkunen & Newnham, 2013). 6 Case Community Space The purpose of the second workshop was to analyze present troubles and contradictions in current practices and ways of working. The session was started with a speech of one researcher-interventionists that summarized the outcomes of the previous workshop and introduced the role of the mirror data in problem-definition and problem-solving. In addition, another researcher gave a short presentation about the history of the residential area and its distinctive characteristics. Participants then were divided in four groups of interest each focusing on a certain developmental challenge identified in the previous workshop. It was expected that every challenge would have an activity system of its own, reflecting a definite aspect of general development. 72

This paper is focused on a group dedicated to further process the theme Community Space that had emerged in needs-charting in the previous workshop. There had been a chronic lack of public non-commercial premises where residents and associations could meet and organize social activities. The group members represented various stakeholders who had a sort of premises on their agendas but who did not know interests of each other that well. There have been several individual attempts to find and establish such premises for citizens, but they had constantly failed due to the bureaucratic model of municipal governance and a lack of political will. The specific mirror data was built to illustrate this complicated situation based on earlier observations and interviews with stakeholders: people talked a lot about “the residents’ house”, however referring to various existing premises and different kind of concepts. This contradiction had been presented as a PowerPoint slide to participants in the beginning of the workshop and competing expressions by various stakeholders were further elaborated by one of the researcherinterventionists (Figure 3).

Occupying empty City Hall Low treshold social services

Old chapel

Dimensions of Residents' House Old railway station building

Community Centre

Culture Centre in a hotel Figure 3. Dimensions of “Residents’ House” (Salin, 2014)

The purpose of the mirror data is to stimulate discourse that would reveal one-sided perspectives and repeating myths in current practices and point out the need of change (Engeström, 1987, 2007). The participants were asked to pinpoint problems, interruptions and conflicts in present practices and identify tensions and contradictions against the mirror data. The following excerpt from the group conversation exemplifies how participants start to build the big picture of the problem by sharing their own presumptions. Amanda (a worker of the city planning department): I have heard so often that people want a community space, so I am curious, why this issue does not go any further. 73

Josh (a second -generation immigrant): I am interested in having an office for my association, we have tried to buy a place, but it fails constantly. But we keep on doing this again, and we do have an intention to purchase a place. Macy (a worker of an international encountering place): Taking into account how much we have space available here, it is a pity, that they are vacant and not utilized. Jill (a worker of the cultural department): We do have space and we can offer it to others, too. There are places available, but how can we utilize them? We have a happy problem; we can provide spaces. Macy: The problem is who is managing this? Someone said that the NGOs should be the ones who coordinate but they do not have money to finance activities. The money has to come from elsewhere; the associations do not have money! The problem is that there should be the municipality involved who would lead this, and then in collaboration, we can do things…. Tim (a leading staff member of social services): Coordination is lacking here. And the perspective; should social services be involved or should it be cultural activities, this has not been crystallized yet. Jane (a resident, a social worker): There are a plenty of organizations with money, if we only could have so-called “heart” which could be a prime mover for more networking, and when it bubbles over coordination starts to happen just by coincidence The groups could find each other, if they had a place. Mike (an architect of city planning): The aims are not yet defined. After that it would be easier to find a place. Keith (a director of a NGO): Do we have a vision? Mushrooms have its mycelium beneath the ground, but we need caps for the mushroom. That’s why we need the community space, to enable the mycelium functioning, we are the mycelium with the activities. Jane: We cannot go and use premises owned by the municipality, because then we will be involved with the housing department, and we will have rental payments, limitations and troubles. The aim is to enable residents’ activities in evenings and weekends too, it should function as free as possible to enable its flourishing Jill: It pops up more and more all the time, I can’t outline the big picture, there is so much happening all the time, isn’t there already enough of places and activities? Do we need more premises? Could it be so that residents’ premises are located in different places, do we need only one space? Amanda: Premises cost, who takes the responsibility? We do have places available, but no one dares to ask how they are utilized. Should someone just ask? Keith: The problem is connected to the place. As citizens, we can allow time, the organizations can allow other resources, but we need the place. Associations are financed according to their activities, not according to premises. Jane: Coordinating needs resources, running activities needs walls! I have been involved in many meetings and groups dealing with the future residents’ house, but they are all abolished. The discussions have been going on in many arenas. You are certainly confused about which place you are gonna to plan and draw for us? Mike: Well, there are a plenty of places, but I don’t know what kind of premises you want. Tim: These issues have been taken care of separately, in different ”boxes”. Keith: The municipality should be the core layer: (providing) the place and the coordinator. After that the civil society will arrive and produce other stuff: time, resources, activities, and then everything starts blooming. 74

Keith: The thing is that everyone starts to protect own resources, instead we should give resources to our shared target. The summary of the discourse was documented in a three-piece clipboard and its findings were explained to other groups (see Table 1). The phases of the clipboard was to show the present practice with the disturbances and tentative suggestions for the future. It was not necessary to invent yet complete ideas for the solutions of the problem; the thorough processing was more crucial. Disturbance/problem - A heart that collects stakeholders together, layers of the mushroom? -Who takes care of responsibilities, management and coordination? -Overall picture is missing, aims are unclear. -How to combine the resident house and its ideology to the architectural planning process?

Present Practice - everyone is working in”boxes” of their own

New Ideas -something common -coping an already existing concept of “the residents’ house” -occupying new space -assisting the ongoing planning process of “ the residents’ house”

Table 1. The analysis of the disturbances of the Community Space present practice

As explained above, analytical tools provide another component of the double stimulation method. In the CL sessions, the triangle model of the current activity system is usually used for this purpose. The triangle model illustrates the structure of the present practice and reveals tensions and contradictions embedded. It also helps participants to shape and advance a joint object in a visible way. This phase is strongly guided by researcherinterventionists’ questions: why there is a need to a change, who are involved, what are the tools needed, who belong to the community, according to what principles the work is divided, what are the rules, instructions and limitations? The participants are also instructed to mark the recognized contradictions within and between the components of the activity system by flashes. The triangle model constructed by the participants is shown in Figure 4.


Figure 4. The analysis of the structure and contradictions of the present practice

To summarize the outcomes of the group work, the analysis of the current practices revealed that there have been a number of actions and initiatives by single residents, small groups and larger communities to promote community spaces in the area. The main obstacles have been a lack of funding and suitable premises, as well as confusion about which stakeholders should take responsibility to advance and organize community spaces. All interested stakeholders had not even met each other before. Stakeholders have not been able to act alone which has caused frustration. The present discourse revealed that group members have a plenty of resources for creating a joint community space: time, activities, experienced practitioners, premises, and even a public initiative with a budget for the future residents’ house. Many of them were ready to take more responsibility for planning, organizing and implementing a joint community space or the residents’ house, but the shared vision with specific aims should be created at the first place. There were still competing views on the ideology and purpose of the potential joint community place. The group members recognized urgent needs for further coordination of collaboration. Political decision-makers should get involved in the planning process, and various options for financing should be sorted out. As a result of the workshop session, the participants succeeded to form a big picture and shape a joint goal for future activity. The intervention tools helped them to elaborate scattered and unfinished ideas and build new knowledge. The atmosphere was constructive and enthusiastic, enabling creating relations and mutual learning. The experiences from other groups not reported here were quite similar, showing that the presentation of various types of data (excerpts for residents’ interviews, a letter to a local newspaper) elicited emotional responses and got the participants engaged. The chosen analytical tools proved challenging but manageable within the time limits. Gained knowledge provided a basis for planning experiments in the following workshops. 7 Conclusions The findings highlighted the importance of the analysis of contradictions and conflicts in current practices in order to create shared understanding and appropriate goals for future development. The mirror data served as a powerful stimulus for shared reflection and learning, whereas the triangle-model of activity system as a conceptual tool made current contradictions visible to participants, enhancing understanding of the emerging shared object. Double stimulation boosted stakeholder collaboration that is critical in solving multidimensional urban problems. The participants started to take charge of the development process by exercising agency provoked by the mirror data and double stimulation. It is worth noting that the present ULL activity was driven by the researchers who had an opportunity for deriving the appropriate mirror data from the project’s multiple databases. Another option would have been to have participants gather the mirror data themselves. This however proved too challenging within the scheduled workshop programme. Successful mirror data is emotionally touching, and may provoke powerful and contradictory feelings that must be handled carefully by facilitators in order to maintain constructive atmosphere. As the final conclusion, the Community Workshops based on the CL provided an innovation platform and helped to build new practices in urban development through collaboration between various stakeholders. The sessions succeeded to build a creative encounter of multiple perspectives with complementary expertise and resources needed in problem-solving and creating new models of practice (Miettinen, 2014). The CL provides a structured procedure for managing innovation process, still allowing room for creativity of 76

individuals. The major challenge might be a relatively big number of participants that is typical for urban living lab networks. Therefore, the CL method needs to be modified to meet needs of heterogeneous groups and actors involved in urban development. 8 References Baynes, T. (2009). Complexity in urban development and management. Historical overview and opportunities. Journal of Industrial Ecology, 13(2), 214–227. Edwarsson, B., Kristensson, P., Magnusson, P. & Sundström, E. (2012). Customer integration within service development – A review of methods and an analysis of in-situ and ex-situ contributions. Technovation, 32, 419–429. Engeström, Y. (1987). Learning by Expanding: an Activity-theoretical Approach to Developmental Research. Helsinki; Orienta-Konsultit. Engeström, Y. (2007). Putting Vygotsky to work: The change laboratory as an application of double stimulation. In H. Daniels, M.Cole & J.V.Wertsch (Eds.), The Cambridge companion to Vygotsky (pp. 363-382). Cambridge, UK: Cambridge University Press. Engeström, Y., Virkkunen, J., Helle, M., Pihlaja, J. & Poikela, R. (1996). Change laboratory as a tool in transforming work. Lifeling learning in Europa, 1(2), 10–17. Friedrich, P., Karlsson, A. & Federley, M. (2013). Report 2.1. Boundary Conditions for successful Urban Living Labs, SubUrbanLab, http://jpi-urbaneurope.eu/wpcontent/uploads/2014/01/Report-Boundary-conditions-for-successful-Urban-LivingLabs.pdf, accessed April 2015 Hakkarainen, L. & Hyysalo, S.(2013). How do we keep the living laboratory alive? Learning and conflicts in living collaboration. Technology Innovation Management Review, December 2013, pp. 16–22. http://timreview.ca/article/749, accessed April 2015. Il’enkov, E.V. (1977). Dialectical logic. Essays in its history and theory. Moscow, Russia: Progress. Il’enkov, E.V. (1982). The dialectics of the abstract and the concrete in Marx’s capital. Moscow, Russia: Progress. JPI (2013). Urban Europe. Joint call for proposals 2013. http://www.ffg.at/sites/default/files/downloads/call/jpi_ue_pilot_call_2__call_text_final_2013-06-18.pdf, accessed April 2015 Juujärvi, S. (2014). Osallisuudesta toimijuuteen Espoon keskuksessa.[From participation towards agency in the Espoo centre] Eetvartti 3/2014. Espoo: The city of Espoo. Juujärvi, S. & Lund V. (forthcoming). Engaging residents: Insights from Participatory Action Research into Urban Living Labbing. In E. Amirall, S. Leminen & M.Westerlund (Eds.) Living Labs – Innovating by Co-Creating with Users in Real-Life Environments. Juujärvi, S.& Pesso, K. (2013). Actor roles in an urban living lab: What can we learn from Suurpelto, Finland? Technology Innovation Management Review, November 2013, http://timreview.ca/article/742, accessed April 2015. Kemmis, S. & McTaggart, R. (2000). Participatory action research. In N.Denzin & Y.Lincoln (Eds.) Handbook of Qualitative Research (pp. 567–605). Thousand Oaks: Sage. Leminen, S., Westerlund, M. & Nyström, A-G (2012). Living Labs as open-innovation networks. Technology Innovation Management Review, October 2012, 6–11, http://timreview.ca/article/602, accessed April 2015. Leont’ev, A.N. (1978). Activity, consciousness, and personality. Englewood Cliffs, NL: PrenticeHall. Miettinen, R.. (2014). Creative encounters, collaborative agency, and the extraordinary act of the meeting of a need and an object. In A. Sanninio & V. Ellis (Eds.), Learning and Collective Creativity: Activity-theoretical and Sociocultural Studies, (pp.158-173). New York: Rotledge. 77

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Involvement of end-users in innovation process: towards a user-driven approach of innovation A qualitative analysis of 20 Livings Labs Perrine VANMEERBEEK a, Lara VIGNERON b, Pierre DELVENNE , Benedikt ROSSKAMP b, Mélanie ANTOINE c b


CRIDS, UNamur University of Liège c SPIRAL, ULg perrine.vanmeerbeek@unamur.be b

Abstract Initially developed to bridge the gap between research and market, a Living Lab can be described as an open, innovative and collaborative process based on three core characteristics: user involvement in the innovation process, experimentation in real-life context and the gathering of stakeholders in public-private-people partnerships. The paper focuses on user involvement and provides an insight on how this principle is put in practice, through the qualitative analysis of interviews conducted with twenty Living Labs in Europe and Canada. Our results interestingly point out that practice of user-driven approach, unlike what is promoted in Living Lab theory, is rather limited. Indeed, many Living Labs do not involve users for the ideation phase at all, and those ones usually use a user-centered approach for the following steps. Besides, when observed, user-driven approach is often restricted to the ideation phase. We can though ask ourselves the question of what is, or should be, living in a Living Lab? Furthermore, our results suggest that a user-driven approach seems more suitable when a Living Lab aims to create social value than when its objective is to create economic value. Keywords Living Labs, open innovation, user involvement, qualitative study 1 Introduction Initially developed to bridge the gap between research and market, a Living Lab can be described as an open, innovation and collaborative process based on three core characteristics: user involvement in the innovation process, experimentation in real-life contexts and the gathering of stakeholders in public-private-people partnerships (Dubé et al., 2014). Because it is based on the diversity of actors to be engaged and on a strong focus on innovation’s users, the Living Lab methodology can be considered as a social innovation. Besides, by involving users in the long run, Living Labs aim to speed up the innovation process and to reduce the risks related to market failure or public backlash with regard to new products. Unlike traditional approaches, where innovation lies in the experience and the creativity of professionals, the Living Lab values users’ tacit knowledge to reach an 79

alignment between supply and demand. In this perspective, professionals are considered as experts in technology and users are considered as experts in usage. Living Labs are supposed to be valuable for every stakeholder of an innovation project. In theory, private and public sector as well as citizens are concerned. Dubé et al. (2014) refer to Santoro and Bifulco’s model of value creation – the “KBS Framework” (PRO-VE, 2005) – to talk about the value created in a Living Lab. Three dimensions are highlighted: “knowledge”, “social” and “business” (p. 18). “This value can be modelled by the compromise between the knowledge created by experimenting, the economic value produced, and the social benefits generated by a specific experimentation project. Each project will have a particular identity within this framework.” (p. 18, our translation) What does user involvement mean in practice? In order to assess user involvement in Living Lab projects, inspiration might be found in the New Product Development literature. Hoyer et al. (2010) outline and discuss a conceptual framework that focuses on the degree of consumer co-creation in new product development (NPD). According to their framework, the degree of co-creation activities in NPD is a function of both the scope of co-creation activities as well as the intensity of these activities. “The scope of co-creation refers to the propensity of firms to collaborate with consumers across all the stages of the NPD process which include ideation, product development, commercialization, and postlaunch activities. Thus, firms that are highest in their scope of co-creation look out for collaboration with consumers in all of these stages. Intensity of co-creation refers to the extent to which firms rely on co-creation to develop products within a particular stage of NPD. Thus, firms that are highest in their intensity of co-creation in a particular stage of product development rely exclusively on consumers for their development activities in that stage.” (Hoyer et al., p. 288) Considering the scope dimension, it may be argued that users in Living Labs take part in every step of the innovation process. “Involving users in the early development of a product or service enables to ensure that the product or service corresponds not only to users’ natural behaviours but also to users’ life context” (Dubé et al., 2014, p. 31, our translation). Similarly, Ballon, Pierson and Delaere (2005) studied different types of test and experimentation platforms for broadband innovation. They introduce the Living Lab concept as a type of test and experimentation platform and explain that the novel aspect is that it involves users in all stages of R&D and all stages of the product development lifecycle, “not just at the end phases as, for example, in more classical field trials or user testing of products” (Ballon, Pierson and Delaere, 2005, p. 9). Considering the intensity dimension, Living Labs may be presented as user-driven methodologies more than user-centered methodologies. To better grasp what is meant by “user-driven methodologies”, we can rely on the work of Almirall, Lee and Wareham (2012), who carried out four case studies of Living Labs and divided their methodologies in four different categories. (1) User centered: users are mostly passive subjects of study; (2) Design driven: designers take the lead; (3) Participatory: users are considered on equal ground with the rest of the partners in a co-creative process; (4) User-driven: where the user is the one who drives the innovation process. “On one end of the spectrum, users are regarded as subjects of observation, such as in human factors, ergonomics, or applied ethnography. On the other extreme, users are co-creators, such as in the case of lead users or open source communities. In the middle, we find the majority of methodologies, such as co-design, design thinking, and design-driven innovation.” (Almirall, Lee and Wareham, 2012, p. 17) The notion of empowerment might also be helpful to understand the extent to which users are involved. Bergvall-Kareborn and Stahlbröst (2009) analyse how two Living Labs involve citizens in the design of an e-service. They insist on the empowerment of users. “Inherent in being a partner, from an end-user perspective, is the power of choice. People 80

always can choose if, when and to what extent they want to participate” (BergvallKareborn and Stahlbröst, 2009, p. 367). According to the authors, the fact that user needs and ideas are traceable in the concepts, prototype and finished product is highly important. To sum up, the question we focus on is the following: to what extent users have the power to influence the process and the nature of innovations? Dubé et al. (2014) argue that Living Labs consider users on the same level as other stakeholders and enable the development of new products and services that are conform to their needs. In our point of view, this rather corresponds to the “participatory” level defined by Almirall, Lee and Wareham (2012). With user-driven methodologies, users are the ones who make decisions. Literature draws our attention on the fact that reality might be nuanced. Users’ tacit knowledge might be captured without giving them any power on what will be made of the knowledge. We might also observe Living Labs where users are given full power on the whole innovation process. 2 Methodology The paper is based on the intermediary results of a research project financed by the Walloon Region (Belgium) to assess the interest in and the conditions for the establishment of a Living Lab approach in the health sector in Wallonia. The first six months of the project were dedicated to in-depth interviews with a selection of twenty Living Labs. Based on a comparative analysis, a variety of strategies and practices were identified in regard to various needs. The paper highlights the user involvement dimension and questions the link it may have with a Living Lab’s values and missions, either economic-, social- or knowledge-oriented or a combination of them. Extensive mapping of Living Labs was based on four information sources: ENoLL members, Living Lab pointed out by the CETIC (Research Center in Information and Communication technologies, Gosselies, Belgium), word of mouth and scientific publications. In total, we selected 28 Living Labs according to two criteria: the diversification of sources (not to only have Living Labs members of ENoLL) and the existence of a connexion to the health sector. Each Living Lab was contacted by phone or mail. Out of these, twenty Living Labs agreed to take part in our research: two in Belgium, thirteen in France, three in the Netherlands, one in Sweden and one in Canada. Semistructured interviews, mostly with managers, were made on site. Two interviews were made by Skype: the one with the Swedish Living Lab and the one with the Canadian Living Lab. All interviews were recorded and extensively transcribed. Qualitative thematic analysis was made in multidisciplinary team. 3 Analysis Involvement of users, as we just argued, is one of the most important features in Living Labs. End-users can be involved in the innovation process in many different ways, at different moments, and with a variable intensity. We distinguish three ways of involving end-users (the color refers to the table below): -­‐ User-centered innovation (yellow): that is when end-users are taken into account in the innovation process, but not as stakeholders, by answering questionnaires or testing prototypes for example. Users are asked for their specific opinion about a product or service. -­‐ Co-creation of innovation with users (orange): this is a higher level of end-user involvement, which includes them as stakeholders in innovation projects.



Users-driven innovation (red): this is the highest level of end-user involvement, which corresponds to innovation embodied by end-users. For example, users can participate to the Living Lab governance or they can also be stakeholders and even one of the project leaders.

We also distinguish three project’s phases: for each phase, end-users could be involved in a specific way. The first step is the ideation: where does the innovation’s idea come from? Who decides to innovate about a specific thematic, to develop a service or a product? The second step is the development of a prototype or a solution: who’s developing the solution or the prototype? And the last step is the experimentation: how is the product or the service tested? In what kind of environment: real or realistic? We should point out that this sequence of phases is used for analysis and comparison purposes: not every Living Lab talked about any of these phases, just like not all of them go through these three phases. Furthermore, some Living Labs have a very specific innovation process that does not correspond to those three phases. The following table sums up our results for each Living Lab, about how they involve endusers in their innovation process. Each color represents one way of involving end-users in Living Labs. Note that the grey boxes mean that the Living Lab does not include end-users at all. We also draw the attention of the reader on the fact that one Living Lab was withdrawn from the analysis. This Living Lab is dedicated to the rehabilitation of a brownfield. It does not develop innovation projects strictly speaking, but it is in charge of developing land aspects, supporting business creation and connecting researchers with companies. Therefore, assessing end-users involvement in innovation projects was not relevant in that case.


End-users Researcher Seniors Inhabitants Undefined Inhabitants Undefined Teachers & students Seniors Museums Government Inhabitants Health structure Patients Citizens Citizens Hospital services Patients Citizens Seniors / patients Citizens Citizens Citizens Health care Professional Patients






Seniors Patients Health care Professional Undefined

The table clearly shows that the most used way of involving end-users is the co-creation (there is a majority of orange boxes). We also observe that most of the Living Labs endorsing a user-driven approach restrict their user-driven approach to the ideation phase. More specifically, we observe a user-driven innovation during the ideation phase in seven Living Labs. In other words, it seems uncommon for Living Labs to be user-driven in the development and experimentation phase. Therefore, it seems even more unlikely to happen if users were not involved at the very beginning of a project, which is the ideation phase. It might be very important for a project to use that approach from the starting point, though. Indeed, in this way, chances are increased that the innovation meets users’ expectations. Users will probably choose innovations responding to most of their preoccupations. We stress that only two Living Labs have user-driven approach in the development phase. Among these, one Living Lab has a user-driven approach in the experimentation phase too. From our sample, this is the only Living Lab with a user-driven approach through all the innovation process. It is important to note that those two specific Living Labs do not have predefined innovation process phases. They describe a process which is undefined a priori and which is largely constructed by users (and maybe other stakeholders) along the project. This is very different from the process described by some other Living Labs where phases – and the way phases are interrelated to each other – are identified beforehand like in a stage-gate process. These results might suggest that most Living Labs prefer to resume control over the project once the idea is found, at least in term of process. In those cases, we might wonder what criteria are driving decision-making and who exactly is in charge. For example, how is valued the innovative potential of specific ideas stemming out of users’ minds? To continue with, we found that most of the Living Labs that do not involve users for the ideation at all (grey boxes) are the ones using user-centered approach for the following steps (yellow boxes). This observation is very interesting considering the literature (e.g. Dubé et al. 2014, Ballon, Pierson and Delaere, 2005). If Living Labs are supposed to be more user-driven, why do nearly half analyzed Living Labs have user-centered approach (at least for some of their projects) and do not involve users from the beginning of innovation? Can those Labs really be called living? If not, then what are they, exactly, and why would they call themselves Living Labs? More generally, what shall we understand from the fuzzy understanding of what is, or should be, “living” in a Living Lab? To conclude with, we observe two tendencies of end-user involvement in the Living Labs we have analyzed. On the one hand, Living Labs that involve end-users during the entire innovation process mostly use the co-creation innovation (orange boxes), and sometimes use the user-driven approach (red boxes). On the other hand, Living Labs that only involve end-users during the experimentation phase (to test prototypes for example) have an approach that is more user-centered (yellow boxes). Another question emerges from complementary results gathered in the framework of the project: is there a link between user involvement and the values and missions pursued by Living Labs? As suggested by Dubé et al. (2014), we relied on Santoro and Bifulco’s “KBS Framework” (PRO-VE, 2005) which highlights three dimensions to assess values: “knowledge”, “social” and “business”. Results along these dimensions are based on crossing elements related to:


• • • •

values that are explicitly defended by Living Labs ; missions they pursue ; indicators of success ; their intellectual propriety strategy.

Despite the seeming simplicity of the KBS-Framework, it was really hard to characterize the twenty Living Labs in those terms. Our difficulties may be explained by the fuzzy boundaries between the three dimensions and the way they overlap each other both in speech and practices. More specifically, the complexity to define if Living Labs are creating “economical” or “social” value is linked to the hybridization of Living Labs concerns (among which financial autonomy, relationship with public sector and social usefulness). The hybridization is also linked to the strong connection between “knowledge” and “business” that drives the economic policy in Europe since the Lisbon agenda. While the industrial production is moving south, knowledge has become the North’s engine for productivity and economic growth. “The term ‘knowledge-based economy’ stems from this fuller recognition of the place of knowledge and technology in modern OECD economies.” (OCDE, 1996, p. 3) So, is there a link between user involvement and the values and missions pursued by Living Labs? Considering the results presented above, we decided to focus on the ideation phase, which appears to be decisive in understanding the place given to users. Remind that, according to our results: (1) Living Labs that involve end-users during the entire innovation process mostly use the co-creation innovation and sometimes use the userdriven approach; (2) Living Labs that only involve end-users during the experimentation phase assume an approach that is more user-centered. When results along these two dimensions (user involvement and values/missions) are crossed, with a focus on the ideation phase, observations can be represented as follow:

Out of eight Living Labs with a user-driven approach (see the red crosses), six are situated in the “social” area. Two Living Labs with exclusive economical missions have user-driven approach. Most of the Living Labs taking up a user-driven approach defend social values and social purposes, at least partly. We should also point out that, out of nine Living Labs that do not involve users in the ideation phase (see the grey crosses), seven are situated in the economic area. As a conclusion, a user-driven approach seems more suitable when the objective of the Living Lab is to create social value then when its objective is to create economic value. Does it mean that a strong economic approach of the Living Lab methodology automatically exclude user-driven projects? At least, our results invite to question the rhetoric of Living Labs that are largely considered as deeply engaging endusers. 84

4 Conclusion The aim of our paper was to provide an insight on how users are actually involved in the innovation processes that are central to Living Labs’ missions. Two trends emerge from our results. On the one hand, Living Labs that involve end-users during the entire innovation process mostly use the co-creation innovation, and sometimes use the userdriven approach. On the other hand, Living Labs that only involve end-users during the experimentation phase have an approach that is more user-centered. Results also interestingly point out that practice of user-driven approach, unlike what is promoted in Living Lab theory, is rather limited. Besides, when observed, user-driven approach is often restricted to the ideation phase. This might suggest that most Living Labs prefer to resume control over the project once the idea is found, at least in terms of process. In those cases, we might wonder what criteria are driving decision-making and who exactly is in charge. Our results also indicate that most of the Living Labs that do not involve users for the ideation at all are the ones using user-centered approach for the following steps. Nine Living Labs are concerned, at least for some of their projects. Can those Labs really be called living? If not, then what are they, exactly, and why would they call themselves Living Labs? More generally, what shall we understand from the fuzzy understanding of what is, or should be, “living” in a Living Lab? Furthermore, results suggest that a user-driven approach seems more suitable when the objective of the Living Lab is to create social value than when its objective is to create economic value. Of course, future research should further investigate this hypothesis based on preliminary results. Nevertheless, this points at a wide gap between the official rationales of Living Labs, claiming that more user engagement will improve marketization and quality of innovations, and what they do in practice, which is a rather limited users' engagement. Why is that? Is it just a matter of control, as if managers would fear to develop what they say they strive for? Are economic approaches and user involvement mutually exclusive, contrarily to what the literature says? If user-driven methodologies are easier to implement in social and knowledge creation contexts, to what extent less pressure on economic results is part of the explanation? Is it more difficult for businessoriented Living Labs to take distance from the traditional innovation stage-gate process widely used in companies? What material and procedural conditions inhibit users of taking a more active role in the Living Lab processes? More fundamentally, are these preliminary results just an unintended consequence of uncompleted attempts at developing new approaches to innovation with a Living Lab vocabulary or a gloss that investors project on a process that is mostly left unchanged with regard to real engagement of end-users? What role do framework conditions (e.g. public funding schemes) play and how do stakeholders take up the messages and use the resources? We should stress that our paper is based on the discourse of Living Lab managers. Up to now, users have not been interviewed. Managers might either take an instrumental and reductionist stance towards user-involvement processes or they might tend to overemphasize user-involvement. The education and role of the manager in the Living Lab structure may determine the framing he has over the Living Lab’s activities. This is one reason to continue to study Living Labs with participant observation and interactions with users. 5 References Almirall, E., Lee, M. and Wareham, J. (2012). Mapping Living Labs in the landscape of innovation methodologies. Technology Innovation Management Review. September 2012: 12-18.


Ballon, P., Pierson, J. and Delaere, S. (2005). Test and Experimentation Platforms for Broadband Innovation: Examining European Practice. http://dx.doi.org/10.2139/ssrn.1331557 Bergvall-Kareborn, B. and Stahlbröst, A. (2009). Living Lab: an open and citizen-cenric approach for innovation. Int. J. Innovation and Regional Development, 1(4), 356-370. Dubé, P. (dir.), Sarrailh, J., Billebaud, C., Grillet, C., Zingraff, V. and Kostecki, I. (2014). Le Livre Blanc des Living Labs (1st ed.). Montréal : Umvelt. Hoyer, W. D., Chandy, R., Dorotic, M., Krafft, M. and Singh, S. S. (2010). Consumer coreation in new product development. Journal of Service Research, 13(3), 283-296. OCDE (1996). The Knowledge-Based Economy. Science, Technology and Industry Outlook, Paris: OCDE.


A hypothesis driven tool to structurally embed user and business model research within Living Lab innovation tracks Ruben D’Hauwers a, Olivier Rits a, Dimitri Schuurman b, Pieter Ballon a a


iMinds-SMIT-VUB iMinds-MICT-Ghent University ruben.dhauwers@iminds.be

Abstract Living Labs are a structured approach to open innovation and have a potential to focus on the triple combination of technology, user and business model research. Hypothesis driven living labs ensure that the living lab project remains process - and goal oriented. Thus far, the iMinds Living Lab has been using the validation board of Ries (2010) to track the validated learning of hypotheses around the user research aspects. However, the validation board only takes into account user research hypotheses and learning and does not incorporate business model research aspects. In this paper iMinds Living Lab researchers introduce a hypothesis driven living lab framework (LLAVA matrix – Living Lab Assumption and Validation matrix) incorporating both user and business model learning. Keywords Living Lab; Open Innovation; Lean Management, Business Model Innovation; SME 1 Introduction Living Labs are often referred to as public-private-people partnerships (4P’s) (Westerlund and Leminen, 2011). Based on a meta-review of the Living Labs literature, Schuurman (2015) defines Living Labs as an organized approach (as opposed to an ad hoc approach) to innovation consisting of real-life experimentation and active user involvement by means of different methods involving multiple stakeholders, as is implied in the Public-PrivatePeople character of Living Labs. Moreover, he also concludes that Living Labs are emanations of both Open Innovation and User Innovation practices, as external inputs, including end-user contributions, are used to iteratively design and co-create the innovation in development. This opening of the innovation process and the involvement of external actors in a structural process have the potential to increase the value and sustainability of the business model of the innovation (Baccarne et al., 2013). Not many Living Lab initiatives combine the technological, user and business aspect of innovation through open innovation approaches. Rits et al. (2015) point out that the use of the Living Lab to explicate and validate an actual business model seldom occurs. The approach suggested by Rits et al. (2015) implies the structural embedding of business 87

models in Living Labs leading to collaboration between different types of researchers and viewpoints into the living lab platform. Learning to grow a new venture or implementing business model innovation is not a matter of ideation but of iterative experimentation (Thomke 2002). The selection of the right tools and methods to structure and optimize such iterative innovation processes is key to the success rate of a business in the ever-changing economy (Brem and Viardot, 2013). Living labs are complex partnerships, as they facilitate university-industry relationships but also relationships between large companies, SMEs and start-ups. The need to include not only several stakeholders (universities, large companies, SMEs and start-ups) but also several types of researchers (technical, user and business researchers) into the living lab process as discussed above, does however substantially increase the complexity of the Living Lab projects. As a result of the missing link between business modelling and living labs (Rits et al. 2015), the different innovation tools available today either focus on strategy and business modelling, or focus on the process of iterative innovation tracks and Living Labs specifically. None of these tools take the combined effort of strategy/business modelling and iteration/living lab into account. This paper aims to introduce a hypothesis driven living lab framework, which incorporates innovation track design and management and business model innovation allowing living lab researchers to efficiently embed and link user and business modelling research. The focus of the paper is on innovation of Living Labs with start-ups and SMEs as instigators. 2 Tools for hypothesis driven Living Labs The best know business model innovation tool today is probably the business model canvas proposed by Osterwalder (2010). The business model canvas is a strategic framework to develop an innovative business model. This framework does not link to living lab research explicitly nor does it provide clear guidelines on the process of designing and especially iterating the business model, which often leads to a mere fillingin exercise as stipulated by Verrue (2014). So the business model canvas is more focused on the strategy than it is on processes. The Value Proposition Canvas (Osterwalder, 2015) is a derivative or rather subcategory of the business model canvas, making the different sub-categories of the 2 above mentioned components (user and value proposition) much more explicit. Coorevits et al. (2014) compare the usage of the validation board (Ries, 2011) with the Value Proposition Canvas in a Living Lab Framework. The validation board is proposed by Ries (2011) in the Lean Startup where it is used to support start-ups and innovators in being focused on the process of solving the problem or need of a customer through validated learning. The Value Proposition Canvas (Osterwalder, 2015) focuses on the needs of the customers (customer jobs, gains and pains) and the corresponding value proposition (gain creators, pain relievers and products and services). Coorevits et al. (2014) conclude that the Value Proposition Canvas addresses strategy, not processes, while the validation board addresses processes with only limited incorporation of the strategy. Through tests within 4 SME Living Lab cases, they conclude that the Value Proposition Canvas did not provide value throughout the Living Lab project, as it focused more on the strategy and not on the process. The validation board is a tool that identifies not only customer specific strategy assumptions, but also forces researchers to link these to research steps for validation. As such the validation board provided more value by guiding researchers and innovators through the research decision-making processes within Living Labs. In short, the Validation Board was suggested as a tool to develop hypotheses and to set (research) goals within Living Labs. 88 Â Â

Additionally, Coorevits et al. (2014) conclude that the validation board does not take into consideration all aspects which influence the business model, such as customer touch points, partners, revenue model and cost structure: “…Using the Validation board, only the value proposition is researched .A framework to enable validation based business models in Living Labs: integration of business model aspects such as customer touch points, partners, revenue model and cost structure. “ Breuer & Ketabdar (2012) propose the ‘Business Modeling toolkit’, which focuses on eight basic components for validated learning. The eight components are quite similar to the nine components of the Business Model Canvas. The Business Model Toolkit components can be mapped one-on-one to a component of the Business Model Canvas, except for the “Capabilities” component, which aggregates the “Key Activities” and “Key Resources” components of the Business Model Canvas. So at least on the strategic side, they take the same approach as the business model canvas. Breuer & Ketabdar (2012) have improved this strategy-oriented approach by adding a process-oriented framework for tracking and improving the maturity of each business model component. Although the business model kit comprises both a strategy and a process focus, some issues arise for use in a living lab innovation track. On the strategy side, some important business model components are missing or at least not explicitly mentioned. The customer need, addressed by Osterwalder (2015) and by Ries (2011) are both key components when designing and performing user research. The aspect of incorporating competition and the differentiation compared to the competition of an SME are core, as well, to understand the business model. On the process side, the tool is focused rather on creating common ground for teams and allowing for self-assessment based on maturity of assumptions. The sustainability of business models is however not only determined by maturity of validation. 3 Methodology The LLAVA (Living Lab Assumption and Validation) matrix was developed based upon the iMinds Living Lab experience with over 40 SME cases. The methodology utilized in section 4 and 5 to set up the LLAVA matrix was based on the theory of action research. Action research is a flexible spiral process, which allows actions (change, improvement) and research (understanding, knowledge) to be achieved at the same time (Dick, 2002). In this research, the researchers applied action research on the development of a hypothesis driven tool to structurally embed user and business model research within Living Lab innovation tracks. Initially, the researchers started from existing tools utilized for managing Living Lab innovation tracks, but the continuous cycle of action and reflection (Dick, 2002) helped the researchers to further develop the LLAVA matrix in section 4 and 5. In order to receive initial insights in the usefulness of the LLAVA matrix in Living Lab tracks, the researchers generated a discussion and conclusion in section 6 and 7. At the moment, no complete SME/Start-up innovation tracks have followed the current design of the LLAVA matrix. Therefore, in order to generate and analyse data, the ‘participant observation’ methodology (Yin, 2009) including an active observation and interference of researchers was utilized. In practice, this consisted of 10 business model workshops guided by iMinds Living Lab researchers utilizing the LLAVA matrix. Conclusions were drawn out of these ten cases utilizing pattern matching between different workshops (Yin, 2009). The sample of companies diverts from companies who are in a very early stage (less then one year) to companies which have a more stable business model and which are in a less exploratory phase. After the workshops, feedback was gathered on the impact the LLAVA 89

matrix had on the conversation. A limitation to the research is that the data is merely focused on the strategic implications of the LLAVA matrix as the case studies were focused on one single workshop and not on managing the progress of a Living Lab innovation tracks due to the fact no entire Living Lab track was managed using the LLAVA matrix. For further research case studies need to be done in order to investigate the effectiveness of the strategic, process and assessment purpose of the LLAVA matrix as it will be mentioned in section 5. 4 Results: LLAVA matrix: a Hypothesis Driven Living Lab tool with integration of Business Models The LLAVA tool was created on top of an aggregation of principles from Ries (2011), the Osterwalder Value Proposition Design (2015), the business model matrix of Ballon (2007), the business model canvas of Osterwalder (2010) and Porter’s five forces model (1985) and translated into a set of strategic component. The action research methodology offered spiral approach of action and reflection action research (Dick ,2002). The link of business model references to the proposed hypothesis driven Living Lab framework can be found in figure 1. Pain&Relief&

Customer& Hypothesis&


Product& && Service& Gain&


Problem& Hypothesis&

Custo mer& Jobs&

Solu6on&& Hypothesis&

Valida6on&Board,&Ries& Value&proposi6on&Design& (Osterwalder)&


Exis6ng& Compe6 tors&

Bargaining& customer&

Bargaining& supplier&



Business&Model&Matrix,& Ballon& Value& Network&

Business&Model&&Canvas,& Osterwalder&



Cust.& Rela6n& Channe l&


Resour ce&


Value& Proposi6on&


Financial& model&

Func6onal& Architectur e&


Figure 1: Link of business model references to the proposed hypothesis driven Living lab framework

The validation board (Ries, 2011) puts the customers at the core of its framework and therefore focuses on customer hypothesis, (customer) problem hypothesis and solution hypothesis. The approach is process oriented, more specifically for highly iterative (and lean) innovation processes allowing for structured learning and pivoting (Coorevits, 2014). Osterwalder (2015) introduced an alternative with the value proposition design. As mentioned above, Coorevits (2014) found that it is less applicable to the process oriented Living Lab trajectories, but the modules of pain and gain are included in the framework. As discussed above, this process-oriented approach of the validation board is missing some important strategic components that need to be taken into the innovation track at the strategic level. Osterwalder’s (2010) business model canvas has the customer segment and value proposition components in common with the Validation Board, but analysing the other components, it was found that for most of the SME projects, one or more of these components were not always relevant or important to the case at hand. Therefore, the 90

researchers decided to build a matrix based spread sheet format but add different business model modules. The researchers added different modules to the validation board based on utilizing a spiral approach of reflection and action by initially testing the validation board, identifying additional needs for other modules and subsequently trying those additional modules in workshops with SMEs and instigators. The value proposition layer is similar to Ries (2011) and with Osterwalder (2010) and (2015). In order to capture the marketing and positioning of an SME, the iMinds Living Lab researchers replaced the ‘value proposition’ by the ‘value promise’. Entrepreneurs have an idea in mind, often based on a certain technology, which is clear to the start-up/SME but not to the prospective client. Most customers will not purchase a solution SMEs/start-ups offer because of the technical components, but for the value the solution offers to them. Many start-ups tend to give a technical description of their business idea. The goal of utilizing a value promise is to pitch the idea in a more effective and simple way to enable entrepreneurs to sell and market the idea effectively. Based on the spiral approach of action research, researchers identified there is a need to make a clear division between the value promise and the solution. The solution segment in LLAVA is determined by technical components as well as non-technical components, part of the product and/or service. The solution refers to ‘the functional architecture’ of Ballon in the business model matrix (2007). The functional architecture comprises of the technical systems composed of at least one building block (or module), governed by certain rules (or intelligence) that interwork (or not) with other technical systems through predetermined interfaces. The composition of the solution in the key modules and technical systems enables the researcher and the entrepreneur to identify the differentiation of the innovation compared to the competition. This division is less explicitly included in Osterwalder (2010), even though the difference can be important in certain innovations. The value network definition is an alternative to the broad market based approach of the business model matrix of Ballon (2007), though the applicability is more adapted to living labs and to start-ups and SMEs. Ballon (2007) is focused on creating a market overview, in order to describe IT market from a researchers' perspective. The LLAVA matrix is applied in Living Labs and on specific cases with SMEs and start-up, so therefore the purpose of the value networking is different. The researchers goal is to understand the market dynamics, more specifically: who creates value, who delivers value, who consumes value and how is the value captured. Based on these elements, researchers get an overview of the market dynamics in order to define the potential positioning of the innovation in the market. Additionally, through the different value networks, the entrepreneur and the business model researchers can identify potential sales channels.. Ballon (2007) included the financial model in the Business model matrix, which described the revenue model and the revenue sharing model. Osterwalder also (2010) takes into account the revenues model, where the pricing level and the pricing model are being discussed. The researchers opted to utilize the definition of ‘Willingness to pay’, which comprises of the pricing model and the pricing level, and in cases where revenue sharing is applicable this section can be utilized. The action research has shown many start-ups and SMEs face difficulties identifying their pricing model and pricing level, and thus this needs to be included in the LLAVA matrix. It is important to note that the willingness to pay has an important link with how pressing the customer need is and to the associated value the SME/start-up promises to deliver. The value network is linekd to the willingness to pay, especially the ability of the start-up/SME to capture the value. One last, important, missing pillar in Ries (2011), Osterwalder (2010) and in Ballon (2007), is the competition and the differentiation of a SME/start-up. Competition refers to the five market forces of Porter (1985), which draws from five forces model. The five forces make up the attractiveness of a market. The five forces are rivalry within the industry, threat of new 91

entrants, and threat of substitutes, bargaining power of suppliers and bargaining power of buyers. The rivalry of the industry can help to identify the difficulties to enter the market in case of many existing strong players and the need to differentiate compared to them in order to be able to enter the market. In case there are several new entrants entering the market it shows the market is attractive, but that differentiation can depend on how the start-up differentiates compared to other start-ups who challenge the status quo in the market. For some products and/or services one can find possible substitutes, which can serve as an alternative to the specific service and/or product. In the LLAVA matrix the aim is to identify what the differentiation can be compared to the existing and upcoming companies in the industry and which alternatives exists as a substitute. Taking these seven parameters into account, the researchers created the LLAVA matrix (Figure 2). The LLAVA matrix has a similar spread sheet based lay out to the validation board as Ries (2010), enabling to represent different eco-systems. Per column, a customer segment can be filled out with its respective common need, value promise, solution, value network, competition and willingness to pay.

Figure 2: LLAVA: Living Lab Assumption and Validation Matrix

5 The Purpose of LLAVA: Living Lab Assumption and Validation matrix LLAVA has been created to serve 3 main purposes: • A strategic purpose by clarifying and designing the business model. Additionally, the research questions around assumptions and facts, which need to be validated in the Living Lab research, are generated around a workshop with the LLAVA matrix. • A process purpose in order to enable researchers to track and visualize the different research results based on the validated assumptions. • An assessment purpose in order to analyse and challenge the business model of the SMEs based on the 3 guidelines of focus, differentiation and coherence. 92

5.1 The strategy oriented purpose of LLAVA Similar to the business model canvas (Osterwalder, 2010), the LLAVA is used as a tool to create a common understanding and vision on the different key elements of the business model and the strategic roadmap of the start-up/SME. The LLAVA matrix is adapted to the specific components needed for the management of a Living Lab. In order to kick-off the Living Lab track, the researchers facilitate a workshop based on the LLAVA matrix. By putting their business model on paper, the instigator clarifies the business model. Additionally, the LLAVA matrix ensures a common understanding between the instigator team and the research team within the Living Lab. Similarly to Ries (2011) a division is made between unknown aspects, assumptions and facts. In contrast to the business modelling toolkit (Breuer, 2012), the iMinds Living Lab researchers do not incorporate 5 maturity levels in order to simplify the process for the entrepreneur and for the researchers. When filling out the LLAVA matrix, researchers utilize a colour code indicating whether a cell is an assumption (green), a fact (red) or whether a cell is completely unknown (blue) as the example in figure 3 shows. Concerning the research questions, an assumption needs to be validated and unknowns need to be explored.

Figure 3: LLAVA assumptions, facts and unknowns

The task of the researcher is to identify the assumptions and facts in the business model, which need to be validated in the Living Lab. The output of the workshop is mainly a clarification of the research questions around assumptions and facts. 5.2 The process oriented purpose of LLAVA

93 Â Â

The second purpose of the LLAVA matrix is to manage and define the innovation track through the Living Lab by the researcher. The LLAVA matrix is incorporated in the overall management and process of the Living Lab: •

First, it is utilized as a framework to track the learning of different research steps concerning the business model. After each research step, LLAVA matrix the content is updated together with the validation of the content (assumption vs. fact vs. unknown) during STEERCOs. Second, the LLAVA matrix is utilized to create an overview of the business model in order to aid the research steps. The components and the content of LLAVA are utilized to create topic guides for interviews, co-creation sessions, surveys and tests.

5.3 The assessment purpose of LLAVA LLAVA serves as a tool to analyse business models throughout the different research steps. During STEERCOs after each research step, the business model is analysed by business model researchers. The analysis is utilized to challenge the instigator on the user inputs and the alignment of the business model. Three principles are utilized to analyse the business models of the instigator: • Focus: Does the SME/start-up have enough focus within the business model to implement the business idea completely taking into account the principle of the opportunity cost. Since resources are scarce relative to needs, the use of resources for one activity prevents their use in others. Translated to the case of the entrepreneur, this means that if he or she decides to target several customer segments, will he or she be able to execute it completely in order to deliver the intended value proposition? The role of the business model researcher is to identify whether the entrepreneur is sufficiently focused. • Differentiation: Does the SME/start-up offer a sufficiently differentiated business value for the client compared to competitors? What are the core components/capabilities of the SME/Start-up that competitors do not have? Does the customer perceive the value of the SME/start-up higher as the value of competitors or substitutes? In short, what is the reason why this specific team of innovators need to implement this solution, and not another team? • Coherence: In order for a business model to generate the desired business value, the business model building blocks needs to be coherently designed. More concretely, this means that the customer segments their needs need to be coherently communicated in the value promise, which also needs to be solved as promised through he solution in line with the communicated pricing model. The positioning of the company in the value network needs to be in line with the other components in order for the SME/start-up to deliver value and to capture the value. The task of the business model researcher is to identify contradictions in the model. 6 Discussion Based on the ten workshops targeted on the strategic purpose of the LLAVA matrix, iMinds researchers were able to gather different inputs on the utilisation of the LLAVA matrix based on the participant observation methodology (Yin, 2009) based on different cases. The four main outcomes and points of improvement of the LLAVA matrix are discussed below based on a concrete case of a workshop. The process oriented purpose 94

and the assessment purpose of the LLAVA matrix were not tackled, as it concerned only one workshop, and not an entire Living Lab track. i.




Making a distinction between assumptions and facts has proven to be challenging but useful. The latter are easily mixed and entrepreneurs are often unaware of the importance of the difference, which exposes them to the risk of making the wrong assumptions, which might potentially lead to failure. In order to capture this value, the researcher leading the workshop needs to be able to validate the facts and assumptions an entrepreneur indicates, as the entrepreneur might be overly positive about certain facts. Making a distinction between assumptions and facts helps to identify the important research questions which were previously invisible for the instigator. An example is the case of an entrepreneur setting up a loyalty system with different local shops (Oliva Card). The entrepreneur did not distinguish between facts and assumptions, and therefore went into an implementation mode, while some assumptions were not validated. Through the LLAVA matrix, the distinction between assumptions and facts became clear to Oliva Card, as well as the need to validate the unclear assumptions. The LLAVA matrix helps entrepreneurs to focus on a certain customer segment and its business model during a workshop. Entrepreneurs face difficulties to identify the focus of their business model and consequently of their start-up. Some entrepreneurs try to target several customer segments with different business models, which does not enable the to focus on the execution of a specific case. The researcher has the important role to challenge the entrepreneur to focus. As an example, Motosmarty is a start-up focusing on creating a Digital Driving Pass enabling drivers to improve their driving behaviour and to receive reductions from insurance companies based on their driving behaviour. Motosmarty initially had many different customer segments and business models in mind, indicating a clear lack of focus. The LLAVA matrix helped to get an overview of the complexity of serving different customers and the extra effort required to do so. Combined with efforts to challenge Motosmarty, they found a focus on one single business model, which enabled them to focus. During workshops with several team members, the LLAVA matrix sparked different discussions on different opinions about directions between team members. By asking for more concrete and specific use-cases, the discussion can be sparked by the researcher, which evolves into more concrete use cases leading to more focus. This helps to make the research questions of the Living Lab research more concrete and is key to create a good outcome of the Living Lab. As an example case we can mention Yagram, a start-up that designs solutions around digital health facilitated by mobile technologies. During the workshop based on the LLAVA matrix, there clearly were different, sometimes contradictory views on their business model by different team members. The LLAVA matrix provided a clear overview and discussion tool to facilitate the discussion in order to create a common ground by asking for other specific use cases by the researcher. As a point of improvement to the LLAVA matrix, different researchers indicated that the ‘value network’ could become rather complicated in case of many stakeholders involved, which was the case in three workshops. The spread sheet approach did not enable the researchers and the start-ups to create an overview of the market dynamics. A specific example of such a case is a health care project: Zebra Telemedicine. Zebra telemedicine aims to offer telemedicine solutions in ambulances for improved stroke care. Zebra Telemedicine involves several stakeholders in a complicated ecosystem (hospitals, ambulances, insurance 95

companies,…). The business model researcher’s task is to create a structure and model adapted to the case of the entrepreneur, which proves to be challenging. In the future, the researcher will investigate further in what way value network analysis can be combined with the LLAVA matrix in the case of complicated ecosystems. 7 Conclusions The LLAVA (Living Lab Assumption and Validation) matrix is a proposed framework for hypothesis led living lab tracks which includes business model learning. LLAVA is focused on the strategy, process and assessment of user– and business model learning in a living lab trajectory. The LLAVA matrix was created out of the experience of over 40 SME Living Lab projects combined with models and frameworks taken from literature based on action research. The LLAVA matrix has gone through a preliminary test with ten start-ups which we used as cases in our research. The main outcomes were focused on the strategic purpose of the LLAVA matrix. More specifically, the division between facts and assumptions, the ability to focus and to be specific and the power to spark discussions have added to the quality of the workshop. Researchers need to be aware they have an important task to properly support the instigator on these three levels (strategic, process en assessment). As such the LLAVA matrix aims to strike the right balance between being specific enough as to efficiently enable the research team in offering that support to the instigator and being high-level enough as to be applicable to the many different projects with a different context. This balance seems to be especially difficult for the value network aspect of the business model. In the case of complicated ecosystems for example, the LLAVA matrix is potentially more effective when combined with a value network analysis. Further work is required to improve this aspect of the LLAVA matrix. The iMinds researchers will continue to update the analysis and design of the LLAVA matrix while applying the LLAVA matrix on entire Living Lab tracks and additionally on how the value network analysis of complicated ecosystems can be supported through the LLAVA matrix. 8 References Äyväri 1,(2014), Towards a customer-centric tool for building value propositions, ENOLL, 2014 Ballon P. (2007), Business Modelling revisited: the configuration of control and value, Info, Volume 5, Issue 9, Special Issues: The Redesign of Mobile Business Breuer H., Mahdjour S. (2012) Lean Venturing: Entrepreneurial Learning to Model and Grow New Business, ISPIM South-Korea 2012 Bastiaan Baccarne UGent, Dimitri Schuurman UGent and Constantijn Seys UGent(2013) The XXIV ISPIM Conference : Innovating in Global Markets : Challenges for Sustainable Growth, Proceedings. Coorevits, L, and D. Schuurman. (2014) "Hypothesis Driven Innovation: Lean, Live and Validate." XXV ISPIM Innovation Conference. 2014. Dick, B. (2002) Action research: action and research [On line]. Available at http://www.aral.com.au/resources/aandr.html Eisenhardt, K. (1989) ‘Building theories from case study research’, Academy of management review, Vol. 14, No. 4, pp. 532-550. 96

Niitamo, V. et al., 2006. State-of-the-Art and Good Practice in the Field of Living Labs.: Proceedings of the 12th International Conference on Concurrent Enterprising: Innovative Products and Services through Collaborative Networks. Milan, pp. 341–348. Osterwalder A., Pigneur Y., Clark T. (2010) Business Model Generation . Hoboken, NJ:Wiley Osterwalder, 2015, Value Proposition Design: How to Create Products and Service Customers Want, Wiley Porter, M. (1985) Competitive Advantage: Creating and Sustaining Superior Performance. New York: Free Press. Reason, P. & Bradbury, H., (2001) (Ed.) The SAGE Handbook of Action Research. Participative Inquiry and Practice. 1st Edition. London: Sage Ries, E., 2011. The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses 1st. ed., New York: Crown Business. Schuurman, D. (2015). Bridging the gap between Open and User Innovation?: exploring the value of Living Labs as a means to structure user contribution and manage distributed innovation (Doctoral dissertation, Ghent University). Teece D. J. (2010) Business Models, Business Strategy and Innovation , Long RangePlanning Vol. 43, 172-194 Thomke, S. (2002). Experimentation Matters. Unlocking the Potential of New Technologies for Innovation, Harvard Business School Press: Cambridge, MA. Verrue J., (2014), A critical investigation of the Osterwalder Business Model Canvas: an indepth case study Westerlund, M. & Leminen, S., 2011. Managing the Challenges of Becoming an Open Innovation Company: Experiences from Living Labs. Technology Innovation Management Review, (October), pp.19–25. Yin, R. K. (2009) Case Study Research: Design and Methods. Thousand Oaks, California: SAGE Publications, Inc.


Living Labs As Innovation Platforms: The Key Constructs Habib, C. a, Westerlund a, M. & Leminen, S. b a

Carleton University’s Sprott School of Business, Ottawa, Canada b Laurea University of Applied Sciences, Finland Mika.Westerlund@carleton.ca

Abstract Despite the growing popularity of using living lab as innovation platforms, little is known about their characteristics. We use a qualitative research approach to identify constructs that help us to understand the concept of living lab. We used theoretical constructs from the literatures on user innovation, co-creation and living labs to analyze European Network of Living Labs (ENoLL) membership applications. The results from the content analysis of 40 applications revealed nine constructs that are characteristic to living labs: 1) objective, 2) governance, 3) philosophy, 4) stakeholders, 5) funding, 6) advantages, 7) communications, 8) infrastructure, and 9) methods. These findings provide new insight that helps us to provide a research-based definition of living lab platforms. Keywords: Living Labs; Platform; Definition; Constructs; ENoLL 1 Introduction In today’s rapidly changing global economy, economic success requires group creativity that is facilitated through interactive processes (cf. Holst, 2007). The use of living labs (LLS) has become increasingly popular over the last decade, because they offer a multiplestakeholder platform for innovation in real-life contexts. Although Thomas Knight coined the term ‘living laboratory’ in 1749 (Westerlund & Leminen, 2014), the roots of modern LLS are often associated with MIT professor William Mitchell’s real home environment for investigating the application of smart home systems in the day-to-day activities of humans (Eriksson et al., 2005), for sensing, prototyping, refining, and validating technologies within the context of real-life scenarios (ENoLL, 2010). However, many studies seem to ignore American scholars who experimented with LLS before they were associated to MIT (cf. Moffat, 1990; Tarricone, 1990; Bajgier et al., 1991). Since its conception, LLS has evolved into many fields of research and applications. The literature has reviewed living lab concepts, methodologies, and research streams (cf. Følstad, 2008; Dutilleul et al., 2010; Fulgencio et al., 2012; Westerlund & Leminen, 2014). Nonetheless, scholars in the field not only disagree on the definition of LLS (Nyström et al., 2014) but also on the components that make LLS unique from other innovation platforms (Dell’Era & Landoni, 2014). Leminen (2013) argues that the lack of a proper definition is the cause of disconnected research. Multiplicity of definitions has limited the understanding of innovation practices in LLS. Thus, there is a need for research on how LLS view their operations.


This study aims to identify the key constructs of LLS by using a qualitative research approach. We review previous literature on LLS and compare labs with user innovation and co-creation for the purpose of identifying constructs by which LLS can be examined in terms of their defining characteristics. We use these constructs to analyze 40 ENoLL membership applications in order to provide a research-based definition of living lab platforms. The derived constructs help with understanding LLS as innovation platforms. The study concludes with implications derived from our analysis. 2 Literature Review 2.1 User Innovation More and more companies are shifting the task of revealing and understanding user needs to users themselves. By providing users with innovation toolkits and various resources, companies can outsource the innovation activity to customers and other stakeholders, and bundle these actors into the company’s own product development process (von Hippel & Katz, 2002; Bogers & West, 2012). Toolkits can be introduced into user communities, i.e. groups of users who share and disseminate information about a particular good (Parmentier & Gandia, 2013), and therefore put the users to work to harness new and reliable innovation (Sawhney & Prandelli, 2000). To encourage participation and contribution, companies must support users’ intrinsic and extrinsic motivations. The former is the internal gratification a member receives from participating/achieving a goal within the community, and the latter refers to the external forces that encourage participation regardless of intrinsic presence. Extrinsic motivation include, e.g., recognition by the firm (Jeppesen & Frederiksen, 2006), peer reputation (Hertel et al., 2003), monetary incentives (Jeppesen & Lakhani, 2010) and reciprocity of solutions. In addition to motivational factors, proper leadership can steer the evolution of projects and choose the best fitting solutions. Despite hierarchical coordination possibly dispiriting the intellectual creativity, such governance structure needs to be in place to allocate roles and tasks to the members (Bonaccorsi & Rossi, 2003). The most common problem companies are facing when utilizing user innovation is how to create a business model to profit from user innovation (Franke & Shah, 2003). To this end, proprietary business models can attempt to solicit license agreements from the innovators (West & Gallagher, 2006). Management of intellectual property (IP) is central to controlling knowledge and determining ownership of the innovation (Bogers & West, 2012), especially since strong IP regimes by the firm can retard the innovation spirit of the user community (von Hippel & Katz, 2002). 2.2 Co-Creation Co-creation extends the user innovation process by appropriating ideas from customers and stakeholders to enhance the product and create new experiences (von Hippel & Oliveira, 2011). It engages participants in collaboration to develop a “we” competency rather than a differentiated “you” and “I” interaction (Lee et al., 2012; DeFillippi & Roser, 2014). This means working together and consolidating resources over a network (Gassmann et al., 2010). Customers participating in co-creation may not receive direct social or economic value (Chen et al., 2012). Rather, intrinsic factors such as enjoyment (Fuller et al., 2007), a sense of belonging (Zhang, 2010), or potential career advancement (Wasko & Faraj, 2005) contribute to their participation in co-creation. Co-creation consists of five areas: co-ideation, co-evaluation, co-design, co-test, and colaunch (Russo-Spena & Mele, 2012). Co-ideation means that members propose innovative 99

ideas to the community, which are then discussed and refined. Co-evaluation focuses on the appraisal of the ideas; high-ranking ideas are reviewed by top management for business potential and passed onto others to determine the costs and benefits of implementation. Co-design is the implementation of approved ideas and requires resources such as tool-kits and knowledge. Co-testing helps refine the new product and gain feedback before launching to market; the pre-commercialized product is tested, refined, and presented iteratively until it reaches satisfactory levels. Finally, co-launch means that the product is released to market and will have early adopters who promote it via word-of-mouth. Lee et al. (2012) argue that co-creation improves the architecture of products (resulting in better quality) and lowers the costs of production. Due to the parallel nature of collaborative development (cf. Russo-Spena & Mele, 2012), the product lifecycle is shortened allowing for faster launch and increased speed to market (DeFillippi & Roser, 2014). In addition, the diversified collaborative network enables organizations to become more efficient and agile for rapid scaling (Adler et al., 2011). Furthermore, co-created innovations have lower risk of market failure because they are associated with higher customer satisfaction, positive word-of-mouth, and a lower likelihood of customers seeking out competitive solutions. 2.3 Living Labs LLS are an innovation approach that benefits the creation of products and services (Liedtke et al., 2012). Building on co-creation, LLS provide physical and organizational infrastructures (Ponce de Leon et al., 2006) and a methodology to coordinate the experimentation process within the test environment (Almirall & Wareham, 2011). LLS are based on user-driven approach and the open involvement of many stakeholders (Nyström et al., 2014). LLS engage diverse members to collaboratively undertake projects and develop and validate innovations (De Ryuter et al., 2007; Schuurman et al., 2011; Westerlund & Leminen, 2011). Trust is necessary to facilitate the equal and fair exchange of knowledge, resources, and efforts (Leminen & Westerlund, 2012). LLS give insight into consumers’ daily interactivity with firms’ offerings in the real-life contexts (Mulder, 2012). Prior research on LLS (e.g., Pierson & Lievens, 2005) analyzes the activities of consumers; especially their uses of goods in relation to other market offerings that may be disjoint (Liedtke et al., 2012). Information about usage patterns are often collected through the digital network (Intille, 2002), and analyzed to identify patterns and opportunities (Edwards-Schachter et al., 2013). Members are encouraged to socialize, suggest ideas, and engage in innovation development (cf. Russo-Spena & Mele, 2012). The approach mitigates the risks associated with market commercialization (Liedtke et al., 2012) and result in sustainable advantages for the company (Mattson, 2010). Users that participate in LLS are selected from consumer groups, lead user communities, research organizations, or firm’s employees (Niitamo et al., 2012). They are not seen as passive respondents (Schuurman & De Marez, 2012) and are more than an object for testing and feedback (Schaffers et al., 2007). The living lab provides them with resources to convert their ideas into products and services (Sanders & Stappers, 2008). The industry partners take on the role of designers and join LLS to access external ideas provided by the others. They use the lab’s resources, networks, and techniques to find opportunities and develop solutions that meet the needs of users (Levén & Holmström, 2008). Researchers are stakeholders who focus on the generation of knowledge (Dell’Era & Landoni, 2014). LLS offer benefits to participants, including networking opportunities and access to funding and resources (Niitamo et al., 2012). Research conducted with LLS often yields unique knowledge (Dutilleul et al., 2010). The lab carries out research, development, and 100

experimentation with products and services (Schaffers & Turkama, 2012). Consumers know their needs and preferences while firms have the resources and know-how to produce goods (O’Hern & Rindfleisch, 2009). Thus, the lab collects data from users (Følstad, 2008) to study behavior and co-create outcomes for the society (Kanstrup et al., 2010). Such knowledge can validate the innovation and ensure initial demand for the product prior to commercialization (Almirall & Wareham, 2011). According to Kåreborn et al. (2010), the intangible activities and values (e.g., employee support, supplier value, managerial tasks, and societal value) that help business develop and monitor their wellbeing are part of the living lab mandate. 2.4 Common Constructs A comparison of the three reviewed innovation concepts reveals that they share six defining constructs: (1) Stakeholders: Parties who are involved in the innovation process. (2) Objectives: The advantageous benefits of the output from the innovation process. (3) Governance: The manner in which the decisions in the innovation process are made. (4) Tools: The resources required to carry out innovation activities. (5) Motivation: The reasons why stakeholders participate and the techniques used to promote participation. (6) Business Appropriation: The direct or indirect means to capture monetary value from the innovation outputs. 3 Methods According to Baxter and Jack (2008), case study research can facilitate the exploration of LLS allowing for multiple facets to be revealed especially when little is known of the phenomenon or its boundaries are unclear. A case study approach can yield theory that is unified and grounded in practice (Eisenhardt, 1989). Thus, we use case studies and content analysis (CA) on the text generated from the cases. CA is a systematic technique used to evaluate qualitative content by converting textual data into a numerical form that can be subjected to quantitative analysis (Wolfe et al., 1993). This research was limited to the qualitative data extracted from 2011/2012 ENoLL applications which consisted of: 1 Australian, 4 Belgium, 2 Colombian, 1 German, 1 Denmark, 10 Spanish, 5 French, 2 Greek, 1 Irish, 4 Italian, 2 Mexican, 1 Polish, 1 Saudi, 1 Slovenian, 2 Turkish and 2 British data sets. We narrowed the data set from 332 cases down to 40 by focusing on labs that had both application and profile completed. First, we prepared detailed write-ups of cases (within-case analysis) to summarize relevant information. Then, we used CA on the write-ups to find themes. For CA, we conducted manual pre-editing of the data to simplify sentence structures into singular context phrases and convert words into clearly defined nouns. We developed the coding rules used to observe the units within the text by constructing an Excel macro formula: [=OR(IF(ISNUMBER(SEARCH("KEYWORD", A2)),1,0))] The macro was used to group phrases based on the specified key word. A group termed OTHER was added to each search for two purposes: (i) highlight phrases that were not categorized, and (ii) highlight phrases that were categorized multiple times. Using the phrases that were categorized into their respective themes, we were able to further explain each construct’s composition and count the occurrences. Enfolding literature step was used to connect the literature to the findings from the research. This step involved 101

determining what is similar and conflicting, and why such variances exist. By making the connections, we could assure that the results are correct and descriptive. 4 Results After an analysis of the data, it was apparent that the literature-provided constructs required modification. Whereas some of the constructs found in the data were similar with the literature (stakeholders, objective, governance), new constructs (philosophy, funding, advantages, communication, infrastructure, methods) turned out to be useful in understanding LLS (Table 2). Construct Objective

Definition Scope The positive impact that the Collaboration, social impact, innovation output is expected to business development, produce economic development, user impact, test bed, framework Governance A structural or procedural model by Managerial process, which decisions for the innovation managerial structure projects, process or organization are made Philosophy Mindset of the organization that is Innovation culture, reflected in their level of openness and intellectual property rights collaboration Stakeholders Entities that add value to the living lab Participants and their role Funding The means by which the living lab Public funding, private financially supports its innovation funding, revenue stream of activities lab’s business model Advantages The benefits the stakeholders gain Product outcome, framework, from their membership and social value, business participation within the living lab development, validation, resources, networking, knowledge, investment and marketing Communication The channels, technology and Online presence, media techniques used to network presence, person-to-person stakeholders for information exchange interaction Infrastructure The necessary resources and Software tools specialized equipment required to hardware, sensors, facilities carry out the innovation activities Methods The procedural steps used for the Attracting participants, ethics, inception, development and motivational rewards, user deployment of innovation support, data collection, idea generation, design, testing, and commercialization Table 1: Emergent constructs from LLS cases

Appendix 1 illustrates the relative occurrences of scope within each emergent construct. Objectives The studied LLS develop innovations by the communal effort of various actors (Collaboration). They prioritize teamwork and establish joint operations to mutually 102 Â Â

manage incubation space, state-of-the-art technology, and knowledge databases for optimal creativity, cost-reduction, and ecosystem. They pursue social impact on regions by improving citizen involvement in the community, developing technologies that better meet the needs, and building up urban infrastructures. Moreover, labs offer business development to companies by creating resources and services (e.g., product research, incubation space, market trend analysis, and education). They foster employment and entrepreneurship (Economic Development), creation of customized and holistic solutions, and the development of digital infrastructure. Lastly, they provide test beds and a framework for experimenting and testing products in real settings with users (Figure 1). Governance It was difficult to identify a governance structure for LLS, but the responsibilities of governance group include: setting the lab’s vision, making investment decisions, managing IP, organizing activities, appointing roles, maintaining lab infrastructures, and planning research. The governance group ensures that the activities meet the goals by monitoring the performance of the lab. They take on the administrative and managerial work. The governing group is also responsible for the project level decisions. They select the projects to pursue and assign the appropriate members to oversee and run the activities and create user-centric research methodologies. The legal forms of LLS in their respective order of highest occurrence are: Private, Public-private partnership, Public-private-people partnership, Public, and undefined (Figure 2). Philosophy The methods of managing IP in LLS are: Consortium Agreement, OEM, Licenses, Opensource, Case-by-case, Law, and Other. LLS set forth rules and regulations regarding the use, sharing, and licensing of IP prior to the initiation of a project within the Consortium Agreement. The agreements can outline the distribution of cost and gains for each member depending on their role and investment in the developments. These set of rules must be signed by all members. Labs can also give the originators (OEM) full rights to determine the extent of the IP’s usage, or manage IP for each project between the participating members (Figure 3). LLS innovation culture encourages collaborative work to achieve innovation and other goals. Labs ensure that the members respect one another and share knowledge. They reduce barriers through free access to knowledge, and use open standards to enable integration and access to free tools (Figure 4). Stakeholders Stakeholders could not be efficiently analyzed because the data were not properly formatted for CA. However, subjective review of the cases suggested the diverse involvement of companies, universities, unions, governments and public bodies, financers, civic organizations and associations. Funding The majority of funding comes from government grants and private investments. In addition, consulting provides revenues when the living lab receives payment for services rendered to third parties. The services offered in living lab vary, because each lab has a different focus. LLS offer consulting including digital marketing, data collection and analytics, training, and product evaluations. Moreover, LLS produce income from their outputs in the form of royalties and/or sales. However, the members only make profit when they succeed in the commercialization of the products. Labs also lease their resources such as facilities and equipment to third parties for event purposes, lab research, or development (Figure 5). Advantages LLS offer various benefits to their members: business development, knowledge, resources, networking, validation, marketing, social value, and investments. Supportive activities aid lab members to achieve business goals (Business Development). Members benefit from 103

management support, advisory teams, project development, other member’s experiences/expertise, and education. Members can take advantage of lab’s research facilities, incubation space, technologies, and knowledge content. Members can make new connections to access new industries or markets. Through the structured process that enables collaborative work (Framework), LLS help accelerate the development of products at low cost, higher quality, and establish an initial market presence. Their associated activities and ecosystem create visibility for members’ brands, and add legitimacy to members’ businesses (Figure 6). Communication Two-way communication aims at achieving open dialogue for collaborative work in LLS, and helps for brainstorming ideas and gaining feedback from members. LLS also need to consistently update the members of their progress and ongoing activities. Labs use communication for self-promotion to brand, legitimize, and gain public recognition. Furthermore, the technology used for communication serves as management tools, e.g., a database for hosting shared content, tracking project tasks, and collecting and appraising ideas. Figure 7 shows the online, media, and in-person modes of communication. Figure 8 details online channels and Figure 9 details media channels. Figure 10 details in-person channels. Figure 11 illustrates the reasons for communication. Infrastructure LLS have five types of infrastructure necessities: facilities, networks, hardware, software, and sensors. All LLS appear to have facilities, dedicated or shared, to host in-person activities such as events, workshops, and testing in a test-bed. Facilities are either owned by the lab or a stakeholder who permits their use. Information technology infrastructure (networks) includes servers used to host the web technologies and data that facilitate collaboration. Hardware, software, and sensors vary from lab to lab depending on their intended use. In particular, sensors are used within the test environment for observing user behavior and collecting usage data. Methods LLS gain users from associations, events, and random sources such as hot-spots or housing authorities. Before their involvement, the lab informs the users of their role and project objectives, and gain written, voluntary consent. Using lead users as influencers, and extrinsic rewards, the lab motivates the users to contribute to the project. The lab also provides training and tools. During the idea generation, the users and other members discuss problems, brainstorm solutions, and set initial requirements. Universities and small companies often convert the requirements into designs and prototypes. Under the guidance of research experts the solutions are tested with users in real-life environments where data is collected through monitoring technology, digital activity logs, and surveys/interviews. Academics then analyze the data to understand the impact of the solutions. Labs often leave the commercialization efforts to companies, but can use its ecosystem and experts to promote and adopt the solutions (Figure 12). 5 Conclusion The nine constructs (objective, governance, stakeholders, philosophy, funding, advantages, communication, infrastructure, methods) provide a multi-faceted perspective to understanding LLS. Although such constructs could be considered common to innovation platforms in general, they provide a thematic perspective to examining and describing LLS that could be later compared to other innovation platforms. Using the constructs, we can now define LLS in a new manner: “A living lab is a sociotechnical platform with shared resources, collaboration framework and real-life context, which organizes its stakeholders into an innovation ecosystem that relies on representative governance, open104

standards, and diverse activities and methods to gather, create, communicate, and deliver new knowledge, validated solutions, professional development, and social impact”. New knowledge refers to identified problems, ideas for solutions, novel information, content generation, and (scientific) discoveries. Validated solutions include the co-creation, testing, and validation of solutions. Researchers can use this definition to guide their research, refine the constructs, and contribute to even a more precise definition of LLS. Although the new definition of living lab platforms is based on an analysis of how LLS describe themselves in public documentation, it is a significant contribution to the current literature. The study provided further knowledge of the constructs that give rise to the definition. That is, common constructs drawn from innovation literatures (user innovation, co-creation, living labs) that are associated with living labs were only partially supported by the empirical study. For instance, the empirical study revealed nine key constructs as opposed to six derived from the literature review, and only three of them matched perfectly. Moreover, the study revealed communication as an important construct that previous research has not emphasized (cf. Mulder et al., 2008). Surprisingly, the study did not highlight stakeholder roles, user engagement, and real-life contexts as the key constructs of LLS (cf. Nyström et al., 2014). This may be related to the fact that applications reflected an early stage of living lab activity, and that the study searched for common aspects within the three literature streams, whereas real-life context is a unique aspect of living labs. The research helps researchers, entrepreneurs and managers understand the advantages of LLS (business development support, access to resources and partnership networks, as well as product ideas, validation, and commercialization), and join a LLS that provides a particular benefit. Finally, stakeholders can look into the implications of each construct and theme to form LLS that best suits their goals and is aligned with their society/stakeholders to optimize their innovation process. Limitations of the research included restricted number of analyzed cases due to resource constraints. A larger data set could refine the discovered constructs as descriptors of LLS and lead to a more detailed explanation of the results. Likewise, more recent data consisting of 2013-2014 may be more accurate and reliable compared to the 2011-2012 set used. Interpretation of the data is dependent on the researchers’ understanding of the subject. Thus, content analysis was used to limit the bias of human interpretation. However, codifying a semantic category counter based on the frequencies of occurrences is difficult due to diversity of the cases. Data that are nouns, such as names, require additional work to determine their equivalent pronoun (e.g., user, designer). This problem occurred for the infrastructure and stakeholder constructs. This issue may also be related to the fact that we were unable to identify living labs where users in a dominant role (cf. Leminen, 2013). The data requires extensive formatting prior to analysis, which means heavy investment of time and effort. We propose the following future work to be done: (i) the discovered constructs could be confirmed using a larger set of data, (ii) future researches could focus on the individual constructs to deepen the knowledge of LLS, and (iii) the constructs may be applied to other innovation concepts to examine unique patterns in those concepts, and (iv) other type of data should be incorporated to avoid cause-effect problems associated with analyzing characteristics of members based on their membership applications.


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Figure 2 Governance/legal structures 35 30 25 20 15 10 5 0

Figure 3 IPR management techniques 35 30 25 20 15 10 5 0 Agreement








Figure 4 Innovation culture 60 50 40 30 20 10 0 Collective Effort

Accepting Open Source Agreement Members

Open thinking


Figure 5 Revenue streams 60 50 40 30 20 10 0 Consulting



Membership Fees




Figure 6 Advantages to members 20 18 16 14 12 10 8 6 4 2 0

Figure 7 Modes of communication 45 40 35 30 25 20 15 10 5 0 Online

Media Presence

Physical Presence



Figure 8 Online communication channels 60 50 40 30 20 10 0 Website Social Media











Figure 9 Media channels 25





0 tv



Figure 10 In-person communication channels 30 25 20 15 10 5 0

Figure 11 Reasons for communication 40 35 30 25 20 15 10 5 0


Figure 12 Methods categories used for innovation 25 20 15 10 5 0


Getting personal Exploring the usage of persona in order to optimize the involvement of a living lab panel Sara Logghe a a

iMinds-MICT-Ugent sara.logghe@iminds.be

Abstract iMinds Living Labs started with living lab research in 2009. Living lab research involves gathering user feedback on innovations implemented in a real-life context (Eriksson et al., 2005). This can be facilitated by means of a panel-based approach (Schuurman et al., 2012). In order to keep a panel motivated for participating in living lab research it can be beneficial to generate a sense of belonging to a community. Logghe et al. (2014) examined the motivations and behavior of the panel members and concluded that there are four groups of panel member types, each with their own motivations and behavior patterns. But how can a living lab get to know its panel members better? How can every panel member be approached in their preferred way? How can every panel member be stimulated to keep on participating in living lab research? How can a community feeling be created? In order to gather more information about each panel member type, we developed a four way segmentation of the panel which we translated into four distinct persona. These persona will be used as a basis for community building, a future panel kit, experimenting with research approaches,… supplemented with other methodologies. Keywords Persona; User research; Living Lab research; Community building; Quantitative research; Qualitative research; 1 Introduction One possibility for users to contribute to an innovation and for companies to involve users during their development phase is living lab research. Living Labs are an organized approach (as opposed to an ad hoc approach) to innovation consisting of real-life experimentation and active user involvement by means of different methods involving multiple stakeholders (Schuurman, 2015). The living lab approach is a framework that introduces new ways of managing innovation processes (Ståhlbröst, 2008). The underlying idea is that people’s ideas, experiences, and knowledge, as well as their daily needs of support from products, services, or applications, should be the starting point in innovation 115

(Bergvall-Kareborn & Ståhlbröst, 2009). The living lab approach is also a form of open innovation, because technology can be developed and tested in a physical or virtual reallife context, and users are important informants and co-creators in the tests (Kusiak, 2007). Therefore, living labs are user-centric with user involvement as an essential characteristic of living lab research. Not only are users empowered by living labs (Veeckman et al., 2013), living labs depend on the involvement and motivation of these users in order to generate useful user contribution (Schuurman, 2015). It is important to get to know the motivations and behavior of users who participate in living lab research in order to keep them motivated to participate in living lab research. This paper aims to shed light on using persona to gather insights on the motivations and behavior of living lab panel members. 2 Methodology 2.1 What preceded: scenarios as a user-centered design method Participatory or cooperative design focuses on the eventual users of a system or application (Pruitt & Grudin, 2003). Early participatory design efforts were explicitly focused on improving the quality of working life for those workers most at risk of unrewarding consequences of information technology (Ehn, 1988) and included a strong focus on sociopolitical and “quality of life” issues. Realistic scenarios appeared to be a perfect tool for design: they depict the work practices one hopes to support (Pruitt & Grudin, 2003). Scenarios are a natural element of personabased design and development. In Carroll’s words (2000), a scenario is a story with a setting, agents, or actors who have goals or objectives, and a plot or sequence of actions and events. Given that scenarios have “actors” and personas come with scenarios, the distinction is in which comes first, which takes precedence. Actors or agents in scenariobased design are typically not defined fully enough to promote generative engagement. The lifelessness of characters in such scenarios has been critiqued from a writer’s perspective (Moore, 1999) and by scenario-based design researchers who suggest using caricatures, perhaps shocking or extreme ones (Bødker, 2000; Djajadiningrat et al., 2000). They argue for extreme characters were personas try to expose those emotions and character traits which remain hidden in scenarios for supposedly real-life characters because they are incorrect or embarrassing (Djajadiningrat et al., 2000). That is also why Bødker (2000) argued for caricatures, unrealistic extremes that are more engaging, more memorable. According to Grudin & Pruitt (2002) personas can help restore elements which get lost within participatory design approach: (1) long-term engagement with particular participants, and the empathy, commitment and deep understanding that such engagement can bring and (2) attention to the sociopolitical and ‘quality of life’ issues that marked much of the early work, including values, fears, aspirations, and so forth. Contextual Design (Beyer & Holtzblatt, 1998), a powerful approach for obtaining and analyzing behavioral data, is a strong candidate for informing personas. Ethnographic data may help the most in developing realistic personas, when available in sufficient depth. Quantitative data may be necessary in selecting appropriate personas, but does not replace observation (Pruitt & Grudin, 2003). 2.2 What are personas? Personas are a method for enhancing engagement and reality. It is a medium for communicating data that are collected using other research methods (Grudin & Pruitt, 2002). They are an interaction design technique with considerable potential for software product development. Personas are an established method for bringing different types of 116

users to life (Cooper, 1999). They are fictional people and have names, likenesses, clothes, occupations, families, friends, pets, possessions, and so forth. They have age, gender, ethnicity, educational achievement, and socioeconomic status. They have life stories, goals and tasks. They are not ‘agents’ or ‘actors’ in a script, they are people (Grudin & Pruitt, 2002). Second, a persona is described in narrative form. This narrative has two goals: (1) to make the persona seem like a real person, and (2) to provide a vivid story concerning the needs of the persona in the context of the product being designed (Miaskiewicz & Kozar, 2011). The use of abstract representations of users originated in marketing, but Cooper’s (1999) use of personas, their goals, and activity scenarios are focused on design (Mikkelson & Lee, 2000). Well-crafted personas are generative: once fully engaged with them, you can almost effortlessly project them into new situations. In contrast, a scenario covers just what it covers. Persona use brings sociopolitical issues to the surface. Each persona has a gender, age, race, ethnic, family or cohabitation arrangement, socio-economic background, work, or home environment. This provides an effective avenue for recognizing and perhaps changing assumptions about users (Pruitt & Grudin, 2003). Grudin & Pruitt (2002) feel that persona use needs to be complemented with a strong, ongoing effort to obtain as much quantitative and qualitative information about users as possible, to improve the selection, enrichment, and evolution of sets of personas. The highest priority segments get fleshed out with user research including field studies, focus groups, interviews and further market research. Links between persona characteristic and the supporting data should be explicit and salient. Communicating about your personas should be multifaceted, multimodal, on-going, and progressively unfolding. Generally, they think of the persona effort as an on-going campaign (Grudin & Pruitt, 2002). In the same vein, Nielsen (2002) argues that personas, as described by Cooper (1999), are too flat to engage designers. With examples from movie manuscripts she suggests the development of characters with richer personalities and better descriptions (Johansson & Messeter, 2005). McGinn & Kotamraju (2008) on the other hand, take the broader perspective of Mulder & Yaar (2007) and Pruitt & Adlin (2006), that there are many types of personas, which are differentiated by the methods used to create them. 2.3 Why use personas? Personas can create a strong focus on users and work contexts through the fictionalized settings. The act of creating personas can help to make assumptions about the target audience more explicit. Once created, personas help to make assumptions and decisionmaking criteria equally explicit. Personas are a medium for communication, a conduit for information about users and work settings derived from ethnographies, market research, usability studies, interviews, observations, and so on. Personas utilize the power of narrative and storytelling to enhance attention, memory, and organization of detailed user data (Grudin & Pruitt, 2002). Similarly, two other important benefits, prevention of self-referential design and challenge assumptions, point to the personas’ ability to establish a truly consumer-centered design attitude (Miaskiewicz & Kozar, 2011). As Alan Cooper (1999) and others have observed, personas can engage team members very effectively. They also provide a conduit for conveying a broad range of qualitative and quantitative data, and focus attention on aspects of design and use that other methods do not (Pruitt & Grudin, 2003). Personas create a strong focus on users and work contexts through the fictionalized setting. They utilize our mind’s ability to extrapolate from partial knowledge of people to create coherent wholes and project them into new settings and situations. The act of creating personas makes explicit our assumptions about the target audience (Grudin & Pruitt, 2002). 117

Determining an appropriate range of personas is a balancing act between having too few, which means that sufficient capability variation cannot be adequately represented, and having too many, which makes them more difficult to apply and makes it harder to maintain focus. Drafting a prototype set of personas and then iteratively updating is a good way of getting the balance right (Hosking et al., 2010). That is what we are planning to do with the iMinds Living Labs panel persona. 2.4 iMinds Living Labs personas Based on Pruitt & Grudin (2003) we also used a central foundation document (attachment 1) for each persona as a storehouse for information about every persona (data, key attributes, photos, reference materials, and so on). Note that the foundation document is not the primary means of communicating information about the persona to general team members. Likewise, the foundation documents do not contain all or even most of the feature scenarios. Instead, the foundation document contains goals, fears, and typical activities. Links between persona characteristics and the supporting data are made explicit and salient in the foundation documents (Pruitt & Grudin, 2003). In the original notion of personas, as presented by Cooper (1999), they are rich but static descriptions of fictive users. Once they are established, the contents of their description is frozen. In contrast we tend to follow Johansson & Messeter (2005) who worked with a dynamic take on representing the user where we allow new information and different perspectives to enrich the user description as deeper knowledge of users. We chose to continuously construct personas in order to allow the user to become an entity of its own right in design worlds. Personas are typically based on interpretations of interviews, surveys or studies. We tend to follow this methodology, in contrast with Johansson & Messeter (2005) who suggest that the interpretation process should become part of the design process. To create the iMinds Living Labs persona we used previous research on the panel members as a foundation for our persona. A first already completed research step was a survey on motivations of the iMinds Living Labs panel members to participate in living lab research in 2013 (figure 1).


Goodwin (2001) tells us to use patterns of behavior to drive the persona development. So that is why next to this survey (n=725), we analyzed the behavior of our panel members and noticed three types of behavior. The behavior of 19.403 respondents between 2010 and 2013 was analyzed. In total, 22 Living Lab projects took place during this period with a total of 59 research activities in which panel members could participate. According to the frequency of their Living Lab participation, the panel members were divided into three groups: active (3.4%), sleeping (33.3%) and passive (62.4%) panel members. We also discovered a small 118 Â Â

group of panel members being extremely active. We called them the alpha users (0.8%). In order to find out whether they have other motivations to participate in living lab research than regular panel members, we interviewed 15 of these alpha users and found out that they do have other motivations (table 1).


During a later research project, we compared the participation of the different panel member types in different research phases. In a first step we recorded which user types participated in every co-creation session (qualitative research) held in 2014. We expected alpha users to represent the largest amount of participants, but we noticed that sleeping users also were frequently represented. We defined an extra group of users as “other”, these are friends or family of our panel members joining the panel members at co-creation sessions.


As a next step, we compared the participation of all our panel member types in the different research phases we organized in 2014. We noticed that there are significant differences between the four panel member types.



Finally, we gathered all this data compose central foundation documents as advised by Pruitt & Grudin (2003) (attachment 1). Based on this documents, we created four persona of the iMinds Living Labs panel members (figure 1). Because iMinds Living Labs researchers work with the panel members in a rather intense way, we know our panel members in a sometimes quite personal way. We had some panel members in mind during the creation of our personas, but we never used private information to complete the personas. We tend to follow Pruitt & Grudin (2003) who state that personas should be seen as complementing other approaches, or used where another approach is impractical. Therefore we organized a co-creation session and survey in march 2015 to complement our personas in order to brainstorm about a future community platform. We thus based our research on the findings of Tu et al. (2010) who propose an approach that combines the quantitative and qualitative methods in the creation of the personas. In this way, the final personas are more representative and less ambiguous upon which all the team members can agree. As a result we created four iMinds Living Labs persona (1) Passive Peter, (2) Sleeping Sophie, (3) Active Alain and (4) Alpha Anna. For each persona (figure 1) we defined the preferred research type, the main motivation and the research question we should try to answer. We also dedicated an adoption phase (Rogers, 1976) to every persona, based on the experiences with the iMinds Living Labs panel members.


The four persona (figure 1) are already in use for communicative issues such as different types of communication forms (texting versus email), different survey elements (e.g. socio 120 Â Â

demo we already know), focus on the reward or not,… In the nearby future, iMinds Living Labs wants to build a community platform inspired by and together with representative panel members for these four persona. With this platform we can connect interests, topics, research steps, … of panel members with their persona to get even more detailed information on our panel members to organize our research in the way our panel members prefer. We can adapt invitations, locations, research types, research approaches, rewarding,… based on these persona. It became clear to us that personas focus attention on a specific target audience. The method helps establish who is and consequently who is not being innovated for. Personas explicitly do not cover every conceivable user. They also help focus sequentially on different kinds of users. 3 Conclusion In order to get a better understanding of the different types of panel members we created persona. Following Tu et al. (2010), who propose an approach that combines the quantitative and qualitative methods for the creation of personas, we designed four persona of iMinds Living Labs panel members (Passive Peter, Sleeping Sophie, Active Alain and Alpha Anna). We gathered data from earlier research on the iMinds Living Labs panel and supplemented the persona with information on the panel members from a cocreation session with our alpha users –the panel members who participate the most and in both qualitative and quantitative research- and we surveyed the alpha users who were absent on this session. Contrary to McGinn & Kotamraju (2008) we created personas from existing data because we did not start a living lab in order to create persona. Also, this method takes less time. Although the data has not been gathered specifically for the purpose of creating personas, we can state that the data is real because every aspect of the persona was gathered from different living lab projects and research phases in an academic way. The time to complete the data gathering and analysis does take longer than the data-driven persona development of McGinn & Kotamraju (2008). Still, the persona give more insights in the behavior, motivations and interests of the different panel member types. In this way the living lab can try to offer services which are convenient for every panel member. It is important to pay attention to every panel member persona, because in order to cumulate representative feedback a living lab needs to gather information from different types of people. In making choices to create your personas, it becomes clear that choices have consequences. The iMinds Living Labs personas will be used to guide participant selection for future studies and could be used to filter out data from sources not matching one of the persona profiles. Related to this is the temptation towards persona reuse. There can also be a temptation to overuse personas. At worst, they could be used to replace other usercentred methods, ongoing data collection, and product evaluation. They should augment existing design processes and enhance user focus. In other words, personas are not without problems and can be used inappropriately, but based on experience and analysis it has extraordinary potential (Grudin & Pruitt, 2002). Persona use does require decisionmaking. It is not a science. If not used appropriately, any powerful tool can take one down the wrong path, as in lying with statistics or using non-representative video examples (Pruitt & Grudin, 2003). For future research, we tend to follow Johansson & Messeter (2005) and aim at continuing to broaden and enrich our understanding of the user through design moves where early concepts, ideas and mock-ups function as probes. In our future work we will continue to explore and develop the persona of the iMinds Living Labs panel members in order to communicate and involve our panel members in the way every panel member prefers.


4 Bibliography Beyer, H., & Holtzblatt, K. (1997). Contextual design: defining customer-centered systems. Elsevier. Bergvall-Kareborn, B., & Ståhlbröst, A. (2009). Living Lab: an open and citizen-centric approach for innovation. International Journal of Innovation and Regional Development, 1(4), 356-370. Bødker, S. (2000). Scenarios in user-centred design—setting the stage for reflection and action. Interacting with computers, 13(1), 61-75. Carroll, J. M. (2000). Making use: scenario-based design of human-computer interactions. MIT press. Cooper, A. (1999). The inmates are running the asylum:[Why high-tech products drive us crazy and how to restore the sanity] (Vol. 261). Indianapolis: Sams. Djajadiningrat, J. P., Gaver, W. W., & Fres, J. W. (2000, August). Interaction relabelling and extreme characters: methods for exploring aesthetic interactions. In Proceedings of the 3rd conference on Designing interactive systems: processes, practices, methods, and techniques (pp. 66-71). ACM. Ehn, P. (1988). Work-oriented design of computer artifacts (Vol. 78). Stockholm: Arbetslivscentrum. Eriksson, M., Niitamo, V. P., & Kulkki, S. (2005). State-of-the-art in utilizing Living Labs approach to user-centric ICT innovation-a European approach. Lulea: Center for Distancespanning Technology. Lulea University of Technology Sweden: Lulea. Goodwin, K. (2001). Perfecting your personas. Cooper Interaction Design Newsletter. Grudin, J., & Pruitt, J. (2002, January). Personas, participatory design and product development: An infrastructure for engagement. In PDC (pp. 144-152). Hosking, I., Waller, S., & Clarkson, P. J. (2010). It is normal to be different: Applying inclusive design in industry. Interacting with Computers, 22(6), 496-501. Johansson, M., & Messeter, J. (2005). Present-ing the user: constructing the persona. Digital Creativity, 16(04), 231-243. Kusiak, A. (2007). Innovation: the living laboratory perspective. Computer-Aided Design and Applications, 4(6), 863-876. Logghe, S., Baccarne, B., & Schuurman, D. (2014). An exploration of user motivations for participation in Living Labs. In International Society for Professional Innovation Management Conference. McGinn, J. J., & Kotamraju, N. (2008, April). Data-driven persona development. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 15211524). ACM. Miaskiewicz, T., & Kozar, K. A. (2011). Personas and user-centered design: how can personas benefit product design processes?. Design Studies, 32(5), 417-430. Mikkelson, N., & Lee, W. O. (2000). Incorporating user archetypes into scenario-based design. In Proc. UPA. Moore, G. A. (1999). Crossing the Chasm (2nd edn, 1st edn in 1991 by HarperCollins Publishers). Mulder, S., & Yaar, Z. (2006). The user is always right: A practical guide to creating and using personas for the web. New Riders. Pruitt, J., & Grudin, J. (2003, June). Personas: practice and theory. InProceedings of the 2003 conference on Designing for user experiences (pp. 1-15). ACM. Pruitt, J., & Adlin, T. (2010). The persona lifecycle: keeping people in mind throughout product design. Morgan Kaufmann. Rogers, E. M. (1976). New product adoption and diffusion. Journal of consumer Research, 290-301.


Rosson, M. B., & Carroll, J. M. (2009). Scenario based design. Human-­‐‑computer interaction. Boca Raton, FL, 145-162. Schuurman, D. (2015). Bridging the gap between Open and User Innovation?: exploring the value of Living Labs as a means to structure user contribution and manage distributed innovation (Doctoral dissertation, Ghent University). Schuurman, D., Lievens, B., De Marez, L., & Ballon, P. (2012, July). Towards optimal user involvement in innovation processes: a panel-centered living lab-approach. In Technology Management for Emerging Technologies (PICMET), 2012 Proceedings of PICMET'12: (pp. 2046-2054). IEEE. Ståhlbröst, A. (2008). Forming future IT the living lab way of user involvement. Veeckman, C., Schuurman, D., Leminen, S., Lievens, B., & Westerlund, M. (2013). Characteristics and Their Outcomes in Living Labs: A Flemish-Finnish Case Study. In XXIV ISPIM Conference: Innovating in Global Markets: Challenges for Sustainable Growth. Tu, N., Dong, X., Rau, P., & Zhang, T. (2010, October). Using cluster analysis in persona development. In International Conference on Supply Chain Management and Information Systems.


Living Lab cases Session III


Care Living Labs Flanders: Social and Open Innovation Mark Leysa, Lukas Versteelea, b and Lien Potsa, c a

Vrije Universiteit Brussel, Brussels, Belgium Vrije Universiteit Brussel, Brussels, Belgium c KIO, interuniversity consortium on innovation in elderly care, Belgium mleys@vub.ac.be b

Abstract In 2012 the Flemish Minister of Innovation launched an initiative to enhance innovations in elderly care using a living lab methodology: the ‘Care Living Labs Flanders’ (CLLF). The main purpose of CLLF is to accelerate innovations tackling social and economic challenges in elderly care. The main difference between many other types of “living labs” (also in other countries) and the CLLF is this differentiation between “projects” and “platforms”. Today, six platforms host 23 projects. This paper tries to contribute to the question on how living lab (LL) methodologies could integrate insights of social and open innovation perspectives as a ground to optimise the LL methodology. Based on a content analysis of the ambitions and scope of the Flemish government programme, this paper tried to disentangle a number of (scientific) debates to which the CLLF can be connected to better identify the role of a platform (LL) and the role of projects in the strategy to seek innovative approaches in elderly care. In the start-phase of the implementation most attention was spent on implementing the projects, rather than giving form to the LL as an infrastructure. None of the initiators had clear and well developed ideas on the role and the form of what could be a LL. Many efforts have been paid by the support organisms in CLLF to introduce and explain the notion of a LL, especially with the ambition to create sustainable LL infrastructures. The diversity of partners in a platform can trigger innovations, but also make meaningful collaboration difficult. Collaboration between LL partners is a crucial issue. As they are influenced by their profession, discipline, organisational membership, socio-cultural habits, their own vocabulary, etc. this collaboration should be better structured and governed. For this purpose lessons can also be learned from the (inter organisational) network literature. Key words Living lab, Social innovation, open innovation, elderly care 1 Introduction This paper tries to contribute to the question on how living lab methodologies could integrate insights of social and open innovation perspectives as a ground to optimise the LL methodology. The paper addresses the question how a LL method supports innovations in elderly care and how this is taking form in Flanders. 125

In 2012 the Flemish Minister of Innovation launched an initiative to enhance innovations in elderly care using a living lab methodology: the ‘Care Living Labs Flanders’ (CLLF). The main purpose of CLLF is to accelerate innovations tackling social and economic challenges in elderly care. Flanders is confronted with a so-called “double greying” of society: one out of four Flemish people is older than sixty. This ratio will increase over time to one out of three in 2040. People who are older than eighty will triple in the next decades. This demographic evolution is expected to vastly increase the demand of care (Department of Economics, Science and Innovation, Flemish Government, 2013). Moreover, a shortage of nurses and other professional care givers is expected in Europe (Ellenbecker, 2010). Connected with these developments a movement is initiated where elderly persons strive to stay and to be cared for at home as long as possible. Older adults prefer to live in their own houses as long as possible and as close as possible to their (social) environment and family (Panigrari, 2009). Professional care systems should only support on a needs-based basis. The CLLF program aims to stimulate innovations on the one hand tackling problems in elderly care and on the other hand enhancing innovative economic activities. From a social and policy perspective one is seeking innovative approach of organising support and care for an ageing population, to maintain elderly persons as long as possible at home, and to create opportunities to increase their active participation in society. The new models of elderly care focusses a lot more on self-care and informal caregivers, complemented and integrated (when needed) with professional care. It endorses the central position of the elderly person in the care process. Moreover, Flanders is also seeking connection with the internationally emerging trend of active ageing, seeking ways to activate elderly persons and develop strategies to make or let them participate in society. If these innovations can also contribute to increase the “economic” assets of Flanders in a care economy, this would be very welcomed. This paper is based on a literature review, document analysis and interviews with the partners involved in CLLF. Part of the reflection is “experimental based” relying on participatory observations in implementation activities in the programme. Section one discusses the CLLF programme design. The following section discusses the specificities of the CLLF from the perspective of social and open innovation. The last section draws some conclusions and issues for further reflection. 2 Care Living Labs Flanders The CLLF was set up to tackle challenges in elderly care. The objective of the initially three year program is to create and test new care concepts, services, processes and products in a participatory process with the end users. The program expects the Care Living Labs (platforms) (CLL) to become sustainable and that the CLL methodology will enhance economic as well as social innovations in elderly care. The Agency for Innovation by Science and Technology (IWT, 2012bis) defines the Care Living Labs as: a structured test environment where organisations can test their innovative technologies, products, services and concepts using a representative group of individuals who can be used as testers for innovations in their own habitat and workplace (IWT, 2012b). The CLL offers a platform or infrastructure where products and services can be tested in a real life environment. It should be conceived as an experience room for users, and testing will be used as input for further development of the innovation. The end user (client, patient, informal caregiver and professional care giver) should be highly involved in the design and adaptations of the innovations (Zorg Proeftuinen, 2015).


The Flemish government has developed an initially three year programme framework rather than a closed set of guidelines for platforms or projects, opening the door for a wide range of initiatives (Zorg Proeftuinen, 2015). 2.1 Design of the program The program has platforms and projects at its core (figure 1). These are supported by three organisms (Sounding Board Committee, Programme Office and Scientific Consortium).

Figure 1: Structure of the 'Care Living Labs Flanders'

A Program Office (PO) supports and facilitates both projects and platforms for developing their living lab methodology as an instrument for innovation in care (Zorg Proeftuinen, 2015). The Scientific Consortium KIO (Knowledge Innovation Centre for Elderly Care) collects scientific knowledge about the platforms and projects, realises knowledge transfer and develops a model of indicators to monitor the impact of projects and platforms (Zorg Proeftuinen, 2015). The ‘Sounding Board Committee’ consists of representatives from Flanders' Care (a Flemish organisation stimulating medical and care innovations) and various actors from the field. This committee can bring in ideas and reflections to support the implementation of the programme (Zorg Proeftuinen, 2015). 2.2 Platforms and projects Today, six platforms host 23 projects (Figure 2). The main difference between many other types of “living labs” (also in other countries) and the CLLF is this differentiation between “projects” and “platforms”.


Figure 2: Active platforms and projects in the 'Care Living Labs Flanders'

A platform consists of an infrastructure and hosts a database and a network of a test population (a panel of end-users). The panel consists of elderly, informal caregivers, volunteers, professional caregivers and partner organizations. End-users are supposed to be actively involved in conceptualisation, development, research and evaluation of the innovation process (IWT, 2012bis). Every platform needs to have a user’s committee: there is no predefined form or format to involve this userscommittee: the from and activities are left to the responsibility of the platforms. On these platforms, projects can test their product, process or service. So each platform can host a range of projects. The timeframe of developing the projects is limited. Every platform is governed by a mix (public and private organisations, individual professionals) of partners (multidisciplinary perspective). The “scope” or identity of the platforms differs: some platforms define their activities more on technological and person oriented activities to support elderly, while other platforms focus more on social community based approaches. The domains of the projects vary from adaptations to individual housing, to technological support in home care, over food delivery innovations to community based support systems. The range of projects and platforms is clearly a result of the bottom-up call and illustrate how a wide range of meanings is given to seek innovation in the organisation of elderly care. The number of sectors involved in the platforms varies between four (AZoB, LiCalab, CareVille and Online Buurten) and six (AIPA and InnovAGE). The number of partners in a platform ranges between five and seventeen16. 16

A more detailed description of the platforms and programs can be found in the Flemish written report “planevaluatie” and some English written background information on platforms and programs can be found on http://www.zorgproeftuinen.be/en 128

3 “Thinking grounds” of CLLF In this section we briefly sketch approaches to which the CLLF is connected. We try to trace back how the CLLF government programme aims to support the development of adequate innovation environment. A number of issues can be found explicitly in the programme documents, other aspects are more implicit to the CLLF. 3.1 Social innovation Although not explicitly stated in the program documents, some direct links can be made between CLLF and social innovation. The concept of social innovation is initially used to differentiate it from technological innovation, although openings are created towards the use of technology to find solutions. Technology is merely one component in the process of (social) innovation because technology has to become embedded in social practices. Secondly, social innovations sees that the drivers for innovation are not only “entrepreneurs” but that other parties can surely contribute to the development of ideas and new social practices. Thirdly, social innovation mainly focuses on social issues or problems, very often those where “governments” of “markets” did not fill in activities: sometimes referred to as “institutional voids”. Some key characteristics of social innovation can be deduced from a sample of definitions (see box). • Social innovation is “the development and implementation of new ideas (products, services and models) to meet social needs and create new social relationships or collaborations. It represents new responses to pressing social demands, which affect the process of social interactions. It is aimed at improving human well-being. Social innovations are innovations that are social in both their ends and their means. They are innovations that are not only good for society but also enhance individuals’ capacity to act.” European Commission (2013) • “Social innovation seeks new answers to social problems by: identifying and delivering new services that improve the quality of life of individuals and communities; identifying and implementing new labour market integration processes, new competencies, new jobs, and new forms of participation, as diverse elements that each contribute to improving the position of individuals in the workforce. Social innovations can therefore be seen as dealing with the welfare of individuals and communities, both as consumers and producers. The elements of this welfare are linked with their quality of life and activity.” Organisation for Economic Cooperation and Development (OECD) (2010). • Social innovations are “new ideas (products, services and models) that simultaneously meet social needs and create new social relationships or collaborations. In other words, they are innovations that are both good for society and enhance society’s capacity to act.” (Murray, Caulier-Grice & Mulgan (2010)) Common elements in these definitions are the focus on social problems, needs and demands, on participative approaches, on capacity development to develop alternative (innovative) ways to react to social problems. The empowerment of society and social groups is a key dimension of social innovation. Initiators of innovations are not necessarily the more “traditional” actors such as industry or science but can also be end users or societal partners. “Social innovations can be generated from within any sector – public, private or social – or from citizens and social movements. They may generate financial value, but don’t have to.” (Gabriel, 2014; Bulut, Eren & Halac, 2013) Ideas from within society become the starting point for the innovation.


Social innovation was introduced as a counterweight to the policies and discourses that originally focussed on “hard innovations”, in particular technological innovations. The social innovation paradigm assumes that a top-down imposing of change strategies or solutions can harm the acceptability and effectiveness of an innovation. In social innovation the search for value is less concerned with profit and more with issues such as quality of life, solidarity and well-being. The social innovation process itself is an outcome as it produces ‘social capital’ (European Commission, 2011) which can foster social participation. However it is also clearly stressed that social and other forms of innovation are not mutually exclusive: in many cases technological innovations are triggered by social innovations (Bulut et al., 2013). Due to the complexities of (health and social) care problems, different levels of policymakers are seeking for alternatives to organise care. Social problems, also in the field of health care, are very often ‘wicked problems’. A wicked problem is difficult or impossible to solve because of incomplete, contradictory, and changing requirements that are often difficult to recognize (Rittel & Webber, 1973). Many factors are involved and causal relationships are numerous, interrelated and difficult to identify (van Bueren, Klijn & Koppenjan, 2003). ‘Wicked problems’ require collaboration among multiple actors, as interventions by single agencies have limited or even perverse effects. For many of these wicked problems the traditional market fails to come up with adequate innovation strategies as well as the state or civil society. It is assumed that a participative process, involving a number of actors and stakeholders who have a vested interest in solving a social problem also directly empowers the beneficiaries (capacity building). It is believed that ‘complex and wicked’ social problems require collective action from a network perspective (van Bueren et al., 2003). Government departments are often poorly equipped to tackle the complexity of the problems which cut across sectors and civil society often lacks the capital, skills and resources (Murray et al., 2010). In the care of elderly people collaboration is required between health care, social care and voluntary sector agencies as well as with informal caregivers. Single agency based initiatives may have negative effects because of a lack of integration (see also paragraph on open innovation infra). Because of complexity of the problems and the objective to develop a patient centred approach of elderly persons, numerous viewpoints and perspectives can contribute to a better understanding of a problem. The underlying assumption of social innovation is that investing in human needs is potentially key for growth and tackling social challenges. Although certainly not grounded in social innovation, Porter and Kramer (2011) come up with comparable ideas rooted in their “shared value” concept: social and economic progress will be realised when innovative ideas create both social and economic value. 3.2 Open Innovation The CLLF approach is embedded in the open innovation paradigm. Chesbrough (2003) argued that closed innovation as a paradigm should be replaced by open innovation, which integrates external ideas and knowledge mainly focussed on technological and economic issues. The ‘open innovation’ paradigm stresses the relevance of interactions between different stakeholders within the innovation processes, as a reaction to older more “linear” approaches to innovation. The open innovation logic suggests that valuable ideas can come from inside or outside the company (Chesbrough, 2006). Open innovation recognises that views, knowledge and capacity to be innovative is not to be found in a single corporation (Chesbrough & Crowther, 2006; Herskovits, Grijalbo & Tafur, 2013). Collaborative “open” practices will lead to solutions that go far beyond the scope of what any individual actor can. Ideas and different points of view from a wide range of 130

stakeholders become shared to develop new understandings of a problem and new perspectives on solutions (Chesbrough, 2003; OECD 2008). 3.2.1 Helix and ecosystems thinking The open innovation approach was initially grounded in the so called “triple helix” thinking (Etzkowitz and Leydesdorf, 2000). The “Triple Helix” refers to universityindustry-government interactions (OECD, 2008). It is proposed as a spiral model of innovation representing reciprocal relations in different moments in the knowledge process. It holds three dimensions: (1) internal transformation of each of the “helices” (University–Industry–Government), (2) mutual influence among the three “helices” and (3) creation of trilateral networks resulting from interaction between the three “helices”. The spiral Triple Helix model positions the university as a strategic actor in the innovation process and assumes that research bodies, the government and industry can contribute to a country's economic growth through the development of “generative relationships”. The transfer of scientific and technological knowledge from universities to industry and vice versa is considered as a conditioning factor in a country's economic development. It focusses on processes where the university is proactive in putting knowledge to use for firms. Firms are expected to raise their technological level as they collaborate with academia to enhance their capacity through knowledge sharing. Government is considered as one of the partners in this process as it will create the conditions, as well as it is a partners in the sharing of knowledge. The “core” Triple Helix model is broadened as the Quadruple Helix, (even “quintuple helix” adding other groups) where government, industry, academia and civil society work together to co-create the future and drive structural changes. The Triple Helix places the emphasis on knowledge production and innovation in the economy and addresses the knowledge economy, while the Quadruple Helix introduces the perspective of the knowledge society, and knowledge democracy for knowledge production and innovation. (Carayannis, Barth, & Campbell, 2012). The underlying reasoning is that innovation is not only a matter of bringing in technical knowledge, grounded in interaction with different groups or partners, but also requires a different culture, learning how to collect and grasp different sources of relevant knowledge. Open innovation is often directly connected to (business) ecosystems thinking. The ecosystems theory relies on the assumptions of open innovation and ultimately addresses the question of value creation (“co-created shared value”). It is a theory focussing on the question on how synergies can be created between partners coming from different backgrounds. Borrowing insights from ecology, an ecosystems framework addresses issues of interdependency and collaboration between many different types of players and the “environmental conditions” of these actors and relationships. It focuses on the “organisms” constituting an ecology and on the “conditions” that impact on the type of organisms that can exist as well as on the relationships between these organisms. The underlying theoretical assumption is that environmental conditions also determine what types of organisms will live or die. Ecosystems approaches stress the importance from the start of an innovation initiative to clearly map the players (the organisms) in the “ecology”, and focus on a clear understanding on what the characteristics and expectations are of players engaging in an innovation approach. It also stresses the importance to better understand the “environmental conditions” in which both the individual players and well as the collaboration itself functions in order to understand how individual players, the collaboration and the users could get value from the efforts.


The ecosystems approach is clearly associated with Porter & Kramer’s (2006) notion of shared value creation. Shared value creation focuses on identifying and expanding the connections between societal and economic progress. It focuses on creating economic value in a way that also creates value for society by addressing its needs and challenges. Moreover, the concept of shared value blurs the line between for-profit and non-profit organizations. In their logic companies can create economic value by creating societal value. Through three distinct ways: (a) reconceiving products and markets, (b) redefining productivity in the value chain, and (c) building supportive industry clusters at the company’s locations. Each of these are part of the mechanisms to create shared value as improving value in one area will give rise to opportunities in the others. 3.3 Collaborative networks In previous sections we discussed arguments that collaboration and open sharing of knowledge is considered a key for solving innovative solutions for social “wicked” problems. In situations where one has to rely on complex knowledge, and where the sources of expertise are dispersed, the locus of innovation will be found in networks of learning, rather than in individual firms (Powell, Koput, & Smith-Doerr, 1996). The traces of collaboration can also be clearly found in open innovation, ecosystem or helix thinking. Collaboration is grounded in the assumption that by joining forces, parties can accomplish more as a collective than they can achieve by acting as independent agents. Interorganizational networks in which actors with different backgrounds are involved are seen as one of the critical success factors for innovation (Brass, Galaskiewicz, Greve, & Tsai, 2004; Hoberecht, Joseph, Spencer, & Southern, 2011; Provan & Lemaire, 2012; Popp, MacKean, Casebeer, Milward, & Lindstrom, 2013). People construct (and have to construct) their meaning on problems and potential solutions based personal preferences, backgrounds, professional training, education, organizational affiliations. Based on this insights it is not difficult to understand that people differ in their process of giving meaning and why these characteristics predispose them to see the world in different ways. The creation of inter-organizational networks can be a strategy for developing an organizational structure that is able to create change and/or be more responsive to change, as it will on a structural way create a model where these different viewpoints are coordinated. From a different viewpoint, a certain branch of innovation literature also shows that innovation is strongly influenced by “clusters,” or geographic concentrations of firms, suppliers, service providers, academic or research types of institutions, logistical infrastructure. These clusters can be field specific. However there are also known challenges to working in inter-organizational networks (e.g., achieving consensus on the network purpose and goals, culture clashes, loss of autonomy, coordination fatigue, the development of trusting relationships, power imbalances) that should be considered. Network literature differentiates between more informal “social networks” and more formalised forms sometimes studied as “whole networks” and “emerging networks” are to differentiated from “mandated networks”. Trust, power and contract are mechanisms that govern activities inter-organizational value networks and these mechanisms seem to be different according to the stage of service innovation. A mandated network can provide a powerful incentive for organizations to work together. An emergent network, on the other hand, may start with higher levels of trust due to its voluntary nature. Allowing sufficient time for trust building is critical to the longer-term effectiveness of all networks (Popp et al., 2013). Overall network effectiveness can be significantly enhanced when network goals and interests are understood and accepted through meaningful involvement by multiple members of organizations in the 132

network, especially for those organizations that are critical to overall network success (Provan & Lemaire, 2012). Three interrelated themes for effective network development and growth, are network governance, management and leadership of and in networks, and network structures. Many questions remain on how to increase the effectiveness of these collaborative networks especially to better understand what works in what circumstances in a particular domain (see Provan & Fish, 2007). It raises the question on how collaboration between different types of partners can be managed and maintained. Argued that in the field of whole networks, structure and governance (a way of coordinating interactions between different types of partners), should be the subject of future research. 3.4 Sustainability and scaling up of innovations To maximise the impact innovative interventions found to be effective in tackling needs, should be become part of wider social practices. However the transfer of new knowledge from a lot of local initiatives and test projects into practice, is sub-optimal and many individual initiatives become institutionalized. Porter and Kramers’ core argument that creating shared value will be more effective and more sustainable than other types of initiatives is highly reproduced today in policy making discourses (also on the European Level). Indeed, the question on how investments in innovation research and pilot applications can lead to more sustainable solutions is considered as a key question ‘Sustainability’ refers to the stadium where innovations have become ‘the norm’ in the system, when they have become integrated or become the mainstream way of working. Many innovations (especially in a care setting) rarely become embedded in the wider system (Greenhalgh, Robert, Bate, Macfarlane, & Kyriakidou, 2005). Sustainability is connected to the notion of scaling-up. Scaling-up is the process by which interventions (shown to be effective and efficient on a small scale) are expanded under real world conditions into broader policy or practice. The concept of scaling up differs from routine adoption as an intervention tries to reach to new settings or target groups. In public health a recent stream of literature discusses the barriers of scaling up public health interventions. Research learns that scaling up can be supported by producing information on effectiveness, reach, and adoption, human, technical, and organizational resources, costs, intervention delivery arrangements, contextual factors, and applying appropriate evaluation approaches. If these “scalability considerations” are addressed in the funding, design, and reporting of intervention research, it could advance the quality and usability of research for decision makers, and improve uptake and expansion of programs into practice (Milat, King, Bauman, & Redman, 2013). 3.5 Living labs supporting innovation Paying more attention to the role of users as contributors the innovation process is part of the new open and social innovation paradigm. However, the collaboration process between different players including the users very often lacks structure and governance. Therefore many efforts are paid to seek a (sustainable) environment for a wide range of users to propose and carry out projects in order to prepare the “rolling –out” of practices in real-life. LL have been introduced as a user-driven open innovation business – citizens– government – (academia) partnership (an ecosystem) which enables users to take an active part in the research, development and innovation process also allowing for early assessment of the implications of new (technological) solutions and testing the effectiveness and efficiency of innovative services and business models. Living labs (LL) 133

are being promoted as a method to implement the principles of open innovation: platforms where all actors, including end users can interact and new ideas can be captured (European Union, 2014; Edwards- Schachter, Matti, & Alcantara, 2012). LL are conceived as open-innovation ‘ecosystem’ in a real- life setting to create value, based on co-creative collaboration between all actors in society (Leminen, Westerlund, & Nyström, 2012). There is a large number of Living Labs in Europe with a variety of characteristics, as this and previous ENoLL conferences demonstrate. So it is impossible to identify precise working methodologies, because working practices to realise these ambitions depend on the context, the sector or field characteristics, the players involved and the resources available. 4 Discussion and Conclusion In the context of Care Living Lab Flanders, a multitude of stakeholders from a wide range of sectors are collaborating in pursuit of innovative solutions that respond to the needs of the elderly persons. The ambition of the CLLF program is to foster intersectorial collaboration, including business sectors, local governments, organised social actors and local communities to engage in the development and testing of potential interventions that stand at the verge of real-life implementation. Based on a content analysis of the ambitions and scope of the Flemish government programme, this paper tried to disentangle a number of (scientific) debates to which the CLLF can be connected. Our ambition with this exercise is to better identify the role of a platform (LL) and the role of projects in the strategy to seek innovative approaches in elderly care. CLLF responds to the principles of open and social innovation connect with helix and ecosystem thinking and addresses the question of sustainable innovative interventions that can be scaled up. The program focusses on social value and not only for financial and economic value. CLLF combines social with economic ambitions. Value creation should go beyond “business value” or “financial value” but include social value creation regarding like effectiveness of care, efficiency of care, quality of care and quality of life, solidarity, etc. The government call to obtain funding allowed for a lot of freedom (bottom-up approach) within a general framework in the way a LL infrastructure could be given form. However what we have seen in the beginning period of the implementation that most of the attention was spent on implementing the projects, rather than the LL as a support infrastructure. A lot of time and energy was spent in trying to mobilise a user panel. The implementation experience also learned that many projects struggled with a lot of nonanticipated activities that had to be performed within the CLLF. None of the initiators had well developed implantation strategies on the role and the form of what could be a LL, and according to what collaborative approach one would work. In the first years of implementation many efforts have been paid by the support organisms in order to introduce and explain the notion of a LL, especially with the ambition to create sustainable LL infrastructures. A learning process is ongoing on how different partners can become committed to work and identify the (common) LL goal(s) and visions. If a LL wants to become sustainable, the partners need to have a shared vision on the role of the platform and on the position of the platform in relation to their projects. The diversity of partners in a platform can trigger innovations, but also make meaningful collaboration difficult. Collaboration between LL partners is a crucial issue. As they are influenced by their profession, discipline, organisational membership, socio-cultural characteristics, their own vocabulary (Hovenier, de Joode & Bijsterveldt, 2014), this collaboration should be better structured and governed. The diversity of organizations can be a source of conflicts and failing projects (Du Chatenier, Verstegen, Biemands, Mulder &


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Experimenting with location-based service applications: exploring a new methodology for Living Labs Uschi Buchinger a, Heritiana Ranaivoson a, Pieter Ballon a Karel Verbrugge b a

iMinds-SMIT-Vrije Universiteit Brussel, Belgium b iMinds-MICT-Universiteit Gent, Belgium hranaivo@vub.ac.be

Topic Living Lab domain specific cases (privacy and value of data); Living Labs involved service design and user experience Previously published No Abstract This paper argues and illustrates how experiments could support and complement traditional Living Lab research methods. It takes as a starting point insights and results of a pre-study on the value of location privacy, which was conducted outside of a Living Lab. The experimental approach aims at assessing how smartphone users value their location privacy vs. benefits brought by location-based special offers and deals. Results from the pre-study show that participants demand more recompense in the revision of their “bids” regardless of how we reverse the conditions (i.e. enabling or disabling special offers and deals). Explanatory qualitative data is needed to understand the reasons and intrinsic factors of such decisions. As an eventual resolving, we propose the replication and continuation of the study in a Living Lab, which can result even in a multitude of complementary research methods. Keywords Privacy, location-based services, experimental economics, living labs


1 Conception/Idea In the traditional understanding Living Labs are used as a research and development environment where a multitude of stakeholders create and validate innovations like services, products or application enhancements in collaborative, multi-contextual empirical real-world settings. They therefore are one way to bring technology into the market (Ballon, Pierson & Delaere, 2005). This is especially true and relevant for the ICTenabled application sector that is mainly concerned with the enhancement of innovation, inclusion, usefulness and usability of ICT and applications in the society (Eriksson, Niitamo, & Kulkki, 2005). Living Labs have thus proven to constitute a useful setup to hold co-creation sessions and focus groups to let users partake in the design and shaping of (technological) products and services (Mulder & Stappers, 2009; Veeckman, Schuurman, Leminen, Lievens, & Westerlund, 2013). However, using other research methods is yet rarely exploited in Living Labs despite their vast potential to facilitate it. The aim of the paper is to present how experimental methods could benefit Living Lab research. Experimental research is a now common social research method that remains largely out of the scope of Living Labs, in particular experimental economic research. To reach this aim, the paper focuses on an experimental research case that has been conducted around users’ perception of location-based service (LBS) applications, in particular the way LBS use one’s personal data. The paper concludes on how this peculiar case could be expanded based on a Living Lab setting. Thus the authors also aim at providing a framework that could be replicated in other Living Lab research fields. More generally, introducing new methodologies for Living Labs is important especially to allow Living Labs to succeed in the long run. 2 Experimental research: advantages and drawbacks This paper illustrates and argues that economic experimental research can be an interesting contribution to Living Labs. Experimental research has been adapted for, and applied to a multitude of areas and research fields, such as technology design (Staelens, 2012), psychology or social science (Ariely, 2008). In principle an experiment requires the arrangement and management of two groups: an experiment group and a control group, which are exposed to experimental manipulation of variables. Usually an independent variable is manipulated to test the effects of the dependent variable between the groups. Real experiments command strictness on several conditions, e.g. the recruitment and division of participants (Bryman, 2012). Given the limited possibilities that such strictness entails, deviations from this method are common. Quasi-experiments are normally less constrained. They fulfil many – but not all – criteria of a real experiment. Yet, they are often a realistic alternative and provide valuable results (Bryman, 2012). In a Living Lab setup, an experiment could introduce a more subtle form of analysis, where, different to usual Living Lab research, research objects and questions are not directly exposed to the participants but aid or spearhead the development phase. The greatest benefit of experiments are their artificiality (Webster & Sell, 2014). In experiments only the theoretically presumed causes of certain phenomena are selected while other factors are eliminated or minimized. This allows to obtain settings that would not happen in real life. One can be more certain than with any other design about attributing cause to the independent variables (Vogt & Johnson, 2011). Most importantly, such settings can then be replicated, notably to allow other researchers to check the results (Bryman, 2012; Webster & Sell, 2014). This is unlike findings in natural or real-life settings.


On the other hand, experiments receive a lot of criticism due to… their artificiality (Webster & Sell, 2014). Actually all their advantages turn out to be disadvantages with a different view on them: subjects are isolated from the context that might influence their behaviour (Vogt & Johnson, 2011); therefore experiments cannot mirror any real setting (Webster & Sell, 2014); and it may be inappropriate to generalize results beyond the experimental context (Vogt & Johnson, 2011). Beyond the apparent paradox, experiments are more fit for some research purposes and less for others. They cannot attempt to simulate all the complexities of particular settings. But they are well-suited to test the validity of theories (Webster & Sell, 2014). 3 Research field: value of location privacy The experimental structure presented in this paper is situated in the field of location privacy and the value of personal data collected by LBS applications. It especially considers the economic aspect of these applications by relating it to location-based commercial benefits. Benefits often constitute products and services promoted by commercial entities (here: third parties) via the LBS applications (Cramer, Rost, & Holmquist, 2011). In return, app providers share user data with these third parties (Chang & MacMillan, 2012). For the users, this concept is ambivalent: On the one hand, commercial benefits are appealing as they enable monetary gains in their shopping and leisure activities. On the other hand, users might take up a sceptic attitude toward such applications as research and media alike reveal detrimental data sharing mechanism. They principally condemn the collection and usage of personal data for commercial interest (Chang & MacMillan, 2012; Couts, 2013; Fuchs, 2012). In this area, research methods that resolve around direct questionnaires have to be careful, as they have to recognize this ambivalence, also presented in the privacy paradox. The paradox describes the discrepancy or relation between “individuals’ intention to disclose personal information and their actual personal information disclosure behaviors” (Norberg, Horne, & Horne, 2007 p.100). While the former is supposedly very limited, the actual disclosure contradicts this intention. This is especially true for mobile applications and can be based in great parts on the fact that there are only few or no alternatives to the privacy-intrusive app versions. In an exaggerated form, users often seem to face a trade-off: the more personal data they disclose, the more benefits they gain. Consequently, users start to weigh and valuate the benefits and implicitly the value of their own data. Our research is mainly based on the disclosure of location data and juxtapose it opposite the value of location-based commercial offers, deals and promotions. 4 Encompassing research approach - the SoLoMIDEM17 project The experimental conception was part of a research and development project on the matter of location-based service applications. The aim of the project was to build a secure and privacy-friendly mobile app development environment that allows exploitation of big data for multiple stakeholders whilst respecting the users’ rights and preferences of disclosure or concealment of personal data. The platform and LBS app prototypes developed in the project are foreseen to be tested and adapted with the therein-situated Living Lab. 17

Project outline can be found at: https://www.iminds.be/en/projects/2014/03/18/solomidem The project entails to make available an iterative Living Lab to monitor users and gather feedback in the context of converging Social, Local and Mobile consumption patterns. An entire workpackage is working on the management and organization of the Living Lab. 139

In this paper, the project is used as a case study to demonstrate the expected possible and positive spillovers between different research methods, in particular in using experimental research in Living Labs. We argue that Living Labs cannot only be used for the creation and design of products and services, but moreover can herald the start of complementary research work. Due to data collection and management tools, Living Labs typically hold enormous potential as a recruitment and experimentation pool where profiling and selection of participants is easily possible and deployable. 5 Concept and background The framework of the experimental setup is based on two previous studies in the area of location-based services: Cvrcek, Kumpost, Matyas, & Danezis (2006) and Danezis, Lewis, & Anderson's (2005),,which share a similar experimental structure. They pretend to recruit volunteers for a study about localization of mobile phones. They then assess the recompense that people request in return for participating in the study and revealing their location information for one month. We roughly follow this method to herald multiple further studies and experiments and the actual development of prototype applications as foreseen in the project. However, there is a need to adapt the previous research to the current technological state-of-the-art: For smartphone users nowadays, the localization of their devices, especially within applications, is no longer unfamiliar. This feature can provide a multitude of benefits – like viewing one’s own, or friends’ position, get route descriptions or see nearby localities or points of interest on a virtual map. Consequently users have developed experiences, expectations and demands towards them. The applications developed in the project have to understand current market versions and entail, alter and improve their conception. In this research, the commercial component of LBS apps is central to derive the value and perceived benefit of this feature for LBS apps. As mentioned, present-day LBS applications often include commercial entities (third parties) to promote their products and services to users based on the collection of their data and bring monetary benefits (Cramer et al., 2011; Hui & Png, 2006). Coming from this viewpoint we try to assess if people value the concealment of location information more or less than access to special offers and discounts from third parties and outline how application providers can react. We formulated the following hypotheses: H1: People value their location information more than access to special offers and deals. H1a Enabling special offers and deals leads to people increase the amount they demand to participate in the study. H1b: Disabling specials offers and deals leads to people decrease the amount they demand to participate in the study. H1c: The increase (in H1a) is higher than the decrease in H1b. 6 Methodology – Auction structure To identify the discrepancy between the value of location data versus the value of locationbased commercial deals and offers we use a first-price sealed-bid auction (Milgrom & Weber, 1982) introduced and used by Danezis et al., (2005) and Cvrcek, Kumpost, Matyas,


& Danezis (2006). We will adapt this concept to look for the minimum bid that participants claim for their participation in the research about location information. Constituted as a quasi-experiment, the study will work with a division of the sample into two groups (Group 1 and Group 2) that will be exposed to different configurations and manipulation of variables. The initial cover note will be the same for both. We will start with an introduction to a research study on location-based applications, which focuses on the collection and processing of individuals’ location information. It will inform the addressees that we recruit participants for a study about LBS applications. For the study, participants will need to download a smartphone application that will record the whereabouts for a stated period of time at a certain level of accuracy. The application will have certain features and will allow interaction with participants, which are: • Seeing one‘s location on an interactive map • Sharing location through social media such as Facebook • Collecting badges based on the usage of location In addition, and only students of Group 1 will receive the information that via the application it will be possible to • Get special offers and discounts from nearby merchants The addressees will have to specify how much monetary compensation they demand to participate in the study. We will inform them that we only include the 60 people with the lowest “bids” in return for the requested amount. By this, we strive to evaluate the smallest amount that people are willing to accept for disclosing their location information. Following the cover note, several questions about smartphone usage, location-based services and the attitude towards commercial location-based benefits will be asked asked. These questions enable and support subsequent profiling. In a timely follow-up e-mail, we will notify the respondents that the features of the application are changing. The feature ‘Get special offers and discounts from nearby merchants’ will be abolished for Group 1 while added for Group 2. We will record if and to what amount this change influences the changing of “bids”; or in other words, we will record if participants bid higher, lower or the same amount for participating in the study under the new conditions. For the Living Lab testing, two prototype applications will be developed and the 80 selected members in the groups will receive the application they were informed of lastly (i.e. Group 1 will get the application without special offers and deals; Group 2 will get an application with special deals and offers). Special offers and deals are possible due to the collaboration with a project partner with a network of local merchants and commerce. The business network and testing is foreseen be located in the city of Leuven in Belgium. After the actual conduction of the tracking, follow-up questionnaires and focus groups are planned in multiple research fields. We plan to evaluate the value of the application and the general attitude towards the technology, the design and functionality and to develop the apps further as in regular co-creation approaches. Moreover, the aim is to include questions about the utility and appeal of third party offers to cover the economic viewpoint. Thirdly, from a user research perspective we enquire the self-estimation about the fairness of the recompense and the motivation to participate. Again, due to the division into two experimental groups and the exposure to two different app configurations, the differences shall be juxtaposed opposite each other and the differences shall draw inferences about the commercial component of the application.


6.1 Initial or pre-study to the current research Before the Living Lab research will be conducted, the first part of the research has already been tested, though outside of a Living Lab setting. In a limited pre-study we conceptualized and tested the basic configuration of the setup and user addressing and collection of bids but the actual tracking was not conducted. We however pretended that we would and revealed the deception to participants only after we collected the change of bids. The pre-study served multiple purposes: • outlining how to preserve the basic research framework introduced by Danezis et al., (2005) while altering the conditions and features of the research object to reflect current, real-life, state-of-the-art technology • discovering the average and the modal value that people ask for participating in the study, i.e. what needs to be considered for compensation • evaluating the initial reaction of participants towards the option to receive or notreceive commercial offers and discounts in a location-based service application • assessing which data needs to be asked or ascertained to enable profiling and segmentation of users in succeeding analyses • estimating how bid the groups have to be to deliver significant results in comparison • In other words, in the pre-study, the tracking with the application was not conducted for real. Only the collection of the bids and the change of conditions were enquired. Participants were informed about the fictional nature of the study and were compensated with a voucher. 7 Preliminary results As stated previously, the experimental setup is conceived for comparing two test groups. For the pre-study, addressees were divided according to the two participating universities, the Vrije Universiteit Brussel (Group 1) and the Universiteit Gent (Group 2). Group 1 was initially informed about the possibility to ‘Get special offers and deals from nearby merchants’ via the application. This parameter was disabled in the follow-up e-mail. Group 2 was not informed about this feature originally; it was enabled in the follow-up email. The final pre-study sample included 94 participants, 55 in Group 1 and 39 in Group 2. Table 5 compares the results of Group 1: initial bids and revision of the bids.

Mean Median Mode Minimum Maximum

Bid 84.20 EUR 40.00 EUR 30 EUR .0 750 EUR

Bid revision 91.51 EUR Disabling 50.00 EUR “special offers and 50 EUR .0 deals” 900 EUR

Table 5: Statistics for bids and revision of bids - Group 1 (n=55)

In average, people claimed 84,20€ to partake in the study. This value increased by 7,31€ (6,16%) after the change of the app’s condition. While it was previously 30€ that was mentioned most often as a compensation, it changed in the alteration of the question to 142

50€ (followed by 100€ and 30€). We assume that for the participants, the change of condition constitutes a loss of benefits when the service of having benefits from merchants is abolished. The maximum value rose to 900€ from 750€. Looking at the delta between the original bids and the revision, for Group 1, 55% did not change their bids, 31% increased the amount, 14% decreased the amount. The 39 people from Group 2 first got no information about special offers and deals in the outlined application. For them, this condition was enabled in the second mail whereupon they could change their original bids. Table 6 shows the result for this group.

Mean Median Mode Minimum Maximum

Bid 48.00 EUR 35.00 EUR 50 1 250

Bid revision 52.10 Enabling 40.00 “special offers and 50 deals” 1 270

Table 6: Statistics for bids and revision of bids - Group 2 (n=39)

On average, the students in this Group claimed 48€, only 60% of the amount of their opponents. After the revision, this value increased by approximately 8,5% or 4,10 €. Similar to the first group, 54% did not revise at all, 36% increased and 10% decreased their bids. The direct comparison shows that whatever way the conditions change – i.e. enabling or disabling special offers and deals – in average students ask for more compensation in the revision of their bids. However, the majority of participants in both cases did not change their bids. They might thus be indifferent for this feature of the application. Within the limited sample size we answer the hypotheses preliminary: H1: People value their location information more than access to special offers and deals. H1a: Enabling special offers and deals leads to people increase the amount they demand to participate in the study. This hypothesis refers only to Group 2. Within the current sample this statement can be verified if we start out from the average bid. Participants in this group increased their bids in average by 8,5%. Certainly multiple factors that we have not enquired can be the reason for this increase. Privacy of location information is only one explanation. Others can be that the participants suspect extra effort for this feature (coming with learning costs, unwanted advertisement, etc.) that they are not prepared to accept. Therefore we cannot draw inferences from this analysis directly to privacy concerns. Moreover, the analysis showed that the majority of participants (54%) did not change their bids at all. H1b: Disabling special offers and deals leads to people decrease the amount they demand to participate in the study. This hypothesis is based on the conditions given to Group 1. Contrarily to the assumption, disabling special offers and deals equally lead to an increase in the amount the participants ask. Thus, the hypothesis must be falsified for the sample. Paradoxically, in absolute values the increase in the amount is even higher than in Group 2 (7,31€ (6,16%) vs. 4,10€ (8,5%)). We assume this result emerges because participants feel that a benefit, which was initially promised, is withdrawn. Yet again, no explicit link to (location-) privacy issues can be made. We assume that in 143

general the participants of this group were not concerned about privacy or data sharing with third parties via the application. As in the previous group, we can see that the majority of participants did not change their bid between the first query and the revision. H1c: The increase (in H1a) is higher than the decrease in H1b. Seen that we had to falsify the previous hypothesis, this applies also to H1c. Both groups raised their bids after the change of the conditions for the application. It is important to point out that the sizes of the test groups have been small; comparison between them is not significant. To achieve this, bigger sample groups are necessary. Additional, explanatory qualitative data is needed to understand the reasons and intrinsic factors of the decisions. This can also influence the development of the later technology. At the moment we can only assume multiple factors causing the increase or decrease of the bids. The assumptions demand adequate follow-up research. As an eventual resolving we propose the replication and continuation of the study in a Living Lab. 7.1 Envisaged deployment in Living Lab setting As indicated, the pre-study fulfilled multiple purposes though the current intention is to deploy this research in a Living Lab where it is possible to further involve the participants. Living Labs and quasi-experiments are in essence very different but we argue that they are complementary rather than incompatible. There is a huge contrast between both in terms of artificiality with Living Labs aiming at providing a naturalistic context while experiments aim at isolating the impact of tested independent variables. Such contrast may explain why experimental methods are not typical in Living Labs. However, expanding quasi-experiments into Living Labs allows, after a preliminary phase of verification of isolated specific phenomena, to expand the understanding of dynamics within the Living Labs. Being able to control variables is the essence of an experiment, and it can help explain economic or psychological processes that are otherwise hard to explain or infer from surveys, interviews or cocreation methods. The Living Lab approach allows to support the constant, transparent and direct communication with the participants. Also the (random) sampling of the participants or the pre-division into LBS-users and non-LBS-users is facilitated in such an environment compared to universities or other sample pools. The research entails the management of two similar app prototypes and two test groups that enable a broad range of further research possibilities and direct comparison between groups in all further research. In the Living Lab it is foreseen to execute the proposed study for the requested compensation followed by research throughout the tracking phase and post-evaluation. A multitude of questionnaires and surveys are foreseen in different directions. Regarding the privacy aspect, they entail participants’ perception of privacy intrusion or (undesired) personal data sharing especially regarding the location data. The economic angle will focus on the value of the commercial benefits. We prepare to evaluate the self-estimation and assessment of the users versus the data from the actual usage. Regarding the design and technology, the aim is to get insights for the value of the application, the design and look and feel and suggestions for improvements. Naturally, these follow-up and/or comparative research can leverage a multitude of methods, amongst them focus groups, in-depth interviews, surveys and other forms of questionnaires. Finally, while we have argued that Living Labs and quasi-experiments are complementary, there are rmethodological challenges. Living Labs by definition have always been about involving all stakeholders in innovation, and covering all relevant aspects of the 144  Â

innovation, including functionality, design, usability and business model aspects. In such a view, user-driven innovation and open innovation are supposed to go hand in hand. However, in practice, Living Labs have focused on user innovation as well as societal impacts. Therefore, making the shift (e.g. to introduce quasi-experimental approach) is a challenge because most Living Labs have good experience working with end-users, setting-up user panels, etc. The case we have developed gives oneway to remedy this based on the strengths of a Living Lab, i.e. its user panel and user involvement. 8 Conclusion Though Living Labs proved their usefulness and deployability for some time, only a limited potential of Living Labs is used – mainly the shaping and development of technology in co-creation sessions with users. In this paper, we have argued that Living Labs can and should be used for other (social) research methods, such as experimental research, in particular with an economic approach. The paper also explains why and how, thanks to the management of its participants, Living Labs can build a perfect pool to conduct experiments (or - less restrictive - quasi-experiments). Furthermore, they can facilitate recruiting, communicating, sampling and profiling of participants more easily than any other means of engaging participants. Living Labs therefore enable a longer engagement of participants in the experimentation and eventual combinations with other research methods. A field that we see profiting from the deployment in a Living Lab is research on locationbased services and its controversial position between personal data sharing and benefit dispersion. Usually, studies in this area are risking distortion and inaccuracy, caused amongst others by the privacy paradox or discrepancy between the responses of people and their actual behavior. By (initial) deception, the experimental approach aims to bypass this problematic or make the people aware of its existence to derive more accurate results. The experimental approach suggested in this paper has been previously tested with two research groups according to two universities in Belgium but was limited to only to the first part of the study. Like in previous research, participants were deceived to reveal their request for participating in a study that was not conducted for real. The deception was used as a trick to collect data about the value of personal location data. Two LBS applications were outlined and provided to the two test groups: one where special offers and deals were enabled, one where it was disabled. Paradoxically, both groups raised their bids after the change of the conditions for the application. Further research is needed to find an explanation of this result and recommendations for application providers. We argue that in a Living Lab setting, this (so far fictional) study could be conducted for real and bring more relevant value of a multitude of research fields – such as privacy, the value of data, the economics of personal data sharing and the design and technology of modern LBS applications. The (quasi-) experimental approach proposed here is complementary to the typical Living Lab approach. In conclusion, this would contribute to Living Lab’s mission of bridging experimental setting and real-life use or adoption of technology. 9 Bibliography Ariely, D. (2008). Predictably irrational: the hidden forces that shape our decisions (1st ed). New York, NY: Harper. Ballon, P., Pierson, J., Delaere, S. (2005). "Test and experimentation platforms for broadband innovation: examining european practice", in Conference Proceedings of 16th


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Organisation of labour, quality of work, and relational coordination in Care Living Labs Leen De Kort a, Ezra Dessers a, Geert Van Hootegem a a

Centre for Sociological Research (CeSO) of the KU Leuven (Belgium) Leen.DeKort@soc.kuleuven.be

Abstract A growing interest can be noticed in living labs as a method to test and develop innovations in health and social care. This paper argues that, apart from the care clients, also care professionals deserve attention when care living labs are designed. The Care Living Labs program in Flanders (Belgium) is used as a case to show that innovations in a living lab context can profoundly influence the work of the care professionals. After a brief theoretical description of the concepts ‘organisation of labour’, ‘quality of work’ and ‘relational coordination’, the paper explains how these concepts are applied in the Flemish Care Living Labs. The paper concludes that care professionals can best be involved from the start as a separate target group in future care living labs. Keywords Organisation of labour, quality of work, relational coordination, care, living labs 1 Introduction With the aging of the population, the number of older adults in Europe increases, leading to a growing number of people in need of some form of chronic care (European Commission & Economic Policy Committee, 2014). This demographic trend can also be seen in Flanders (Belgium) (Paulus, Van Den Heede, & Mertens, 2012). In order to tackle this disequilibrium, innovations in the older adult care are becoming increasingly important. Recently new methodologies that help stimulate innovation have made their appearance. One of those methodologies is the living labs approach (Mulvenna et al., 2010). The living labs grew from the idea that innovations should be tested in real life situations by the actual end users. In the field of older adult care, the older adults are the end users. Because of the growing need for chronic care for older people, in 2012, an extensive, three-year, ‘living labs’ based program has been initiated in Flanders to stimulate innovation in the domain of older adult care. The program goes under the name ‘Care Living Labs’ (in Dutch: “De Vlaamse Zorgproeftuinen”). A scientific consortium is entrusted with the scientific support of the program. The program is funded by the Flemish Agency for Innovation by Science and Technology (IWT), and kicked off in September 2013. It comprises 23 projects, grouped in six regional platforms. The projects are very diverse, with topics including technology, housing, informal care networks, 148

mobility, care and cure integration, and care management. ‘Enhancing the quality of life of older adults’ being the purpose of this initiative, older adults were defined as the target group. As can be seen from the list of topics above, innovations in care involve more than testing technologies or user interfaces. Even when technology finds a place in care Living Labs, it is always as part of a broader social innovation. Not only older adults, but also other stakeholders are involved in such a social innovation. The innovations may directly or indirectly influence daily practices of caregivers and care professionals. This paper argues that, apart from the care clients and the informal caregivers, also care professionals should be involved as a target group in a care living lab. A care professional is defined as someone who acquired a care-related certificate and is legally authorized to offer care or advise about care, in exchange for a remuneration (FOD Sociale Zekerheid, 2014). The paper has four parts. First, the relevance of care professional-related issues in the Care Living Labs in Flanders is described. Second, an overview is given of the three concepts that are used to analyse these issues: ’organisation of labour’, ‘quality of work’, and ‘relational coordination’. Third, the application of these concepts in living lab-related activities are presented. The paper ends with some concluding remark. 2 The Care Living Labs in Flanders As explained in the previous Section, in the Flemish Care Living Labs, six platforms were established who conduct all together 23 projects. Although the care professionals were not explicitly declared as a target group, it was implicitly mentioned that they are part of the end users, by stating that ‘testers in the own working environment’ should be involved. Based on the original platform and project plans a plan evaluation study was made (Leys et al., 2015). The study describes the goals, target groups, collaborations, organisation of labour, technology and the scope of the platforms and the projects. It was striking that none of the platforms expressed the aim to work around themes as ‘organisation of labour’ and ‘quality of work’. The concept of ‘organisation of labour’ indicates the way in which a set of tasks, needed to create a product or service, is divided into different work packages (Van Hootegem, 2000). ‘Quality of work’ refers here to the stress and health risks resulting from one’s job and is seen as the result of the combination between the amount of workload and the ability to handle challenges the job imposes on the worker (Van Hootegem, 2000). Only one project plan explicitly mentioned these aspects. It needs to be said that when the Flemish government in 2012 launched the call to establish care living labs in Flanders, it was not stated that platform and project proposals needed to pay attention to the organisation of labour or to the quality of work of the care professionals. The scientific consortium however introduced this dimension, because the plan evaluation study revealed that aspects of organisation of labour and the related quality of work could be crucially important for the projects within the six platforms. An example is that various project plans strive to apply technological tools to increase cross-organisational coordination, encompassing a possible risk for increased bureaucratization. Another example is that the introduction of care managers could draw attention away from the underlying problem, being the fragmentation of the organisation of labour. A third example is that various projects are focused on care integration at the micro-level of care professionals and informal caregivers, which could affect tasks and roles of both groups.


3 Organisation of labour, quality of work, and relational coordination To capture the concepts ‘organisation of labour’ and ‘quality of work’, a sociotechnical approach (De Sitter, 1994) is used. The notion of ‘relational coordination’ is coming from the work of Jody Hoffer Gittell (2002). 3.1 Organisation of labour The concept of ‘organisation of labour’ refers to the way in which a set of tasks, needed to create a product or service, is divided into different work packages (Van Hootegem, 2000; Van Hootegem et al., 2008). Essentially there exist two ways of dividing labour. A functional organisation of labour stands for an organisation that is focused on the different operations needed to complete a product or service. These different operations are identified and isolated in specialized units. This extensive division asks for a lot of additional coordinating tasks, which are usually assigned to a separate unit, located higher in the organisational hierarchy. On the other hand, when organising labour in ‘streams’, the focus is on types of products or clients, and work is organised in parallel streams. Relatively independent teams are formed around the different types of orders. The way in which these tasks are divided, influences the amount of job control. When labour is organised in ‘streams’, job control can be higher than when work is organised in a functional way. With a functional organisation of labour, each unit is dependent on the work of the units in which the specialized tasks earlier in the production process happen. Therefore a high level of alignment is needed. To be able to overlook all the different alignment tasks that are needed, coordination will be centralized on a higher level, which results in less job control in individual jobs and units. Organising labour in ‘streams’ allows for a more decentralized approach because there is less need for alignment. This reduced need for alignment makes it possible to assign more job control to individual jobs, teams and units. (Van Hootegem et al., 2008). Within the context of the Flemish Care Living Labs, the organisation of labour actually concerns the organisation of care processes. These are the processes that need to coordinate between interoperating care professionals and organisational units (Lenz & Reichert, 2007). A care client rarely has to deal with only one care unit. Because of the functional way in which traditional care organisations in Flanders often are organised, they usually run through a chain of activities located in different units (Kuipers, 1992). Activities of these different unites need to be planned, prepared, executed and supported. The more alignment is needed between these different tasks, the higher the chances that malfunctions emerge. This can result in errors and long waiting times for the care clients (Lenz & Reichert, 2006). Rethinking the organisation of the care process in terms of care client flows may radically diminish malfunctions that arise from alignment problems (Kuipers, 1992). 3.2 Quality of work The interpretation of ‘quality of work’ comes from the Job Demand / Control (JD/C) model of Karasek (1979). This model has been validated by over 30 years of


scientific research. The model describes how functional characteristics of a job can influence stress and health risks. The model seeks to predict stress and health risks based on the features of the job within the organisation (and not based on other factors, such as personal characteristics of the person who performs the job). The tasks which are connected to a specific job have regulatory requirements: when malfunctions and deviations appear and when unexpected events happen, decisions have to be made to deal with these. The decision-making power of the worker determines whether the worker is able to face these demands. In the JD/C model, two dimensions regarding the characteristics of jobs are defined (figure 1): on one side there are the job demands or the workload, on the other side there is the level of job control, or, in other words, the decision-making power one has over his/her job. The JD/C model indicates that psychological strain is not so much the result of the workload, but the result of the joined effect of workload and the level of decision-making power a worker has to handle the demands that result from this workload. Four different types of jobs arise from the combination of these two dimensions. The jobs in which both job demands and job control is low are called ‘passive’ jobs. In ‘low strain’ jobs, the job demands are low, but the job control is high. Probably the worst case is the ‘high strain’ job, in which the job demands are high, but job control is low, which makes coping with challenges difficult. In ‘active’ jobs a good equilibrium is found between high job demands and high job control. Employees with an active job have the ability to regulate their own work. They can autonomously develop working strategies and improve and change these when the tasks demand so. Karasek (1979) concludes that a demanding job as such is not necessarily stressful, as long as the worker has enough decision-making power to cope with challenges related to the job.

Figure 1: The JD/C model (Karasek, 1979)


The JD/C model has been validated across the years in many different studies. The negative impact of high strain jobs on health and wellbeing has been described in many papers. Next to a poor general health (Karasek, 1990; Söderfelt et al. 1997) it can lead to mental strain (Karasek, 1979), emotional exhaustion, physical complaints and job dissatisfaction (De Jonge et al., 2000), burn-out and rebellious behaviour (Bakker et al. 2001), increased blood pressure and cortisol levels (Fox et al. 1993; Everson et al. 1997; Schaubroeck & Merrit, 1997), and an increased risk at cardio-vascular diseases (Johnson & Hall, 1988). 3.3 Relational coordination Care processes usually require a lot of cooperation and coordination between different units and between people working in different disciplines. Organisational rules define how this alignment officially happens. Research by Gittel (2002) demonstrates that the performance of a care organisation is not only mediated by the way the care process is formally structured, but also by more spontaneous forms of coordination. For these spontaneous forms of coordination the term ‘relational coordination’ was coined. In relational coordination much importance is attached to the role of relationships. Shared goals, shared knowledge and mutual respect are considered to be the key factors for effectively coordinating a care process. Gittell states that when workers have shared goals, they might be motivated to move beyond the sub goals attached to their own tasks, which would make them act in order to contribute to the overall care process. Shared knowledge could enable the care professionals to see how their own tasks fit with the tasks of colleagues and could therefore give them an understanding of the overall work process. Having respect for the work of others would have as a consequence that workers will value the contribution of other actors in the care process and it might make them consider the impact of their own actions on others. This could lead them to act with respect to the overall care process. She suggests that when these characteristics of a relationship are present frequent, it could stimulate an in time, accurate and problem solving way of communicating. This type of communication in turn, would decrease obstacles to coordination and thus enable employees to more effectively manage their task interdependencies. As a result more effective and qualitative performances could be expected (Gittell, 2002). 4 Care Living Lab activities Although the initial platform and project plans do not mention organisation of labour, quality of work, and relational coordination, they do describe the need for cross-organisational coordination and integration of care between care professionals and informal caregivers. Also the installation of new functions such as ‘case managers’ was indicated. These actions can affect the tasks and roles for the care professionals. Thus, the scientific consortium took steps to engage the platforms and projects to work on the concepts of ‘organisation of labour’, ‘quality of work’, and ‘relational coordination’. In a first step, the platforms were asked to add the care professionals involved in their projects to their user panels. Surveys were developed to assess the quality of work and relational coordination in different groups of care professionals involved


in the projects. Quality of work was conceptualized through the dimensions job demands and job control. Relational coordination concerns both the characteristics of the relationships (shared goals, shared knowledge and mutual respect) and characteristics of communication (frequency, accuracy, constructiveness and in time). These surveys are send out to the care professionals in the user panels. The results of the surveys should give a general indication of the situation regarding quality of work and relational coordination in the projects, and provide concrete starting points to tackle issues concerning these themes. In a second step workshops will be organised per platform in which the projects can dive deeper into these matters. During the workshop the concepts ‘organisation of labour’, ‘quality of work’, and ‘relational coordination’ are first briefly introduced, after which people from the different projects will apply the concepts to the care processes in which their innovations take place. With support from researchers from the scientific consortium, they will investigate whether their innovations influences the organisation of labour and the quality of work of the care professionals that are involved in their projects. The results from the survey that was mentioned above will serve as a starting point. After identifying specific issues, the projects can look into possible structural interventions, with support from the scientific consortium. With the information retrieved from the surveys and the workshops, the scientific consortium can draw lessons concerning the use of living labs methodology in the care domain. The collected information should allow to answer the question to what extent it would be useful to involve care professionals and in which way this can best be done. Finally the information can help to understand in which way an optimized organisation of labour could be a breeding ground for care innovations. 5 Conclusion Innovations in older adult care involve more than testing technologies or user interfaces. These innovations always take place in a broader social context. Therefore, when using a living lab approach to test and develop innovations in older adult care, also the care professionals are an important end-user group. The case of the Flemish Care Living Lab program shows that this end-user group is not always given a lot of attention in care living lab activities. This paper gives an overview of three concepts that can be used to analyse care professional related issues. These concepts are ‘organisation of labour’, ‘quality of work’ and ‘relational coordination’. Also does the paper present how these concepts can be applied in living lab related activities. The current research in Flanders suggests that organisation of labour, quality of work and relational coordination can play an important role in care living labs. For that reason, care professionals should best be involved as a separate target group in future care living labs. 6 Acknowledgements This research is part of KIO, an interuniversity consortium studying innovations in elderly care in Flanders. The consortium consists of Mark Leys & Lien Pots (OPIHVUB), Ellen Gorus & Charlotte Brys (GERO-VUB), Ezra Dessers, Geert Van


Hootegem & Leen De Kort (CESO-KUL), Marc Jegers & Lukas Versteele (iCher), Patricia De Vriendt (GERO-VUB, Arteveldehogeschool) & Juul Lemey (Arteveldehogeschool), Bart Jansen (ETRO-VUB), Bart Mistiaen & Bart Grimonprez (HOWEST). The consortium is financed by the Flemish Agency for Innovation by Science and Technology (IWT). 7 Reference list Bakker, A.B., Demerouti, E. & Euwema, M.C. (2005). Job resources buffer the impact of job demands on burnout. Journal of Occupational Health Psychology, 10(2), 170 –180. Dhondt, S., Pot, F. & Oeij, P. (2012). Social innovation of work and employment. In: H.W. Franz, J. Hochgerner & J. Howaldt (Eds.), Challenge social innovation. potentials for business, social entrepreneurship, welfare and civil society (pp. 261-274). Berlin, Germany: Springer Verlag. de Jonge, J., Bosma, H., Peter, R. & Siegrist, J. (2000). Job strain, effort-reward imbalance and employee well-being: a large-scale cross-sectional study. Social science & medicine, 50(9), 1317-1327. De Sitter, L.U. (1994). Synergetisch produceren. Human resource mobilisation in de productie: een inleiding in de structuurbouw. Assen, The Netherlands: Van Gorcum. [in Dutch] European Commission (DG ECFIN) & Economic Policy Committee (AWG). (2014). The 2015 Ageing Report: Underlying Assumptions and Projection Methodologies. European Economy, 8. Everson, S.A., Lynch, J.W., Chesney, M.A., Kaplan, G.A., Goldberg, D.E., Shade, S.B., Cohen, R.D., Salonen, R., Salonen, J.T. (1997). Interaction of workplace demands and cardiovascular reactivity in progression of carotid atherosclerosis: population based study. British Medical Journal, 314, 553-558. Federale overheidsdienst (FOD) sociale zekerheid. (2014). Wet betreffende de erkenning van de mantelzorger die een persoon met een grote zorgbehoefte bijstaat. Publicatie: 2014-06-06. [in Dutch] Fox, M. L., Dwyer, D. J. & Ganster, D. C. (1993). Effects of stressful job demands and control on physiological and attitudinal outcomes in a hospital setting. Academy of Management Journal, 36(2), 289-318. Gittell, J.H. (2002). Coordinating mechanisms in care provider groups: relational coordination as a mediator and input uncertainty as a moderator of performance effects. Management Science, 48(11), 1408–1426. Johnson, J.V. & Hall, E.M. (1988). Job strain, work place social support, and cardiovascular disease: a cross-sectional study of a random sample of the Swedish working population. American Journal for Public Health, 78, 1336-1342. Karasek, R. A. (1979). Job demands, job decision latitude, and mental strain: implications for job redesign. Administrative Science Quarterly, 24 (2), 285-308. Karasek, R.A. (1990). Lower health risk with increased job control among white collar workers. Journal of Organisational Behavior, 11(3), 171-185. Kuipers, H. (1992). Sociotechniek in de gezondheidszorg. Paper gebaseerd op een lezing gehouden tijdens het symposium Sturing van zorgprocessen. [in Dutch]


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Creating a Smart City Vision in a Living Lab Case Study of Smart Kalasatama Vision-building Process Veera Mustonen a a

Forum Virium Helsinki/ Aalto University, Helsinki Veera.mustonen@forumvirium.fi

Abstract This paper examines collaborative vision-building process as a key ingredient of a Smart City Living Lab. As a case study, the Smart City district Living Lab, Smart Kalasatama, vision-building process is analyzed. Part of the process was benchmarking various Smart City visions and objectives. Most Smart city visions were analyzed as rather system-centric. Contrary to that, the outcome of this Living Lab vision process was integrating systemic and human goals. “One more hour of own time a day” Smart City vision statement was co-produced in public-privatepeople partnership (PPPP). As a conclusion, two hypothesis are formed proposing that Living Lab methods and PPPP-process (1) yield more balanced yet humancentric Smart City visions which (2) appear engaging to a variety of stakeholders. Keywords Smart City, Urban Living Lab, Vision, PPPP-process, Quadruple helix, Smart Kalasatama 1 Introduction Living Labs have become places to drive open innovation in real life context. Recently many Living Labs have started to operate in the Smart City context addressing real urban development (Cosgravea;Arbuthnot;& Tryfonas, 2013). How the Living Labs impact what the Smart City innovations aim at? This paper examines how a Living Lab can contribute to a shared Smart City district vision – building process. To date, there is very little research of the collaborative vision building in Living Lab context. In order to understand the ingredients of visionbuilding the Smart City visions are approached through four different analytical focus. First, the dimensions of the Smart City visions are scrutinized using two different frameworks. The first framework is used in many Smart City concept analysis: topdown vs. bottom-up approaches to Smart City development (Townsend, 2013) (Breuer;Walravens;& Ballon, 2014). The second framework contrasts the ends the


cities are seeking. Here we hypothesized that most cities take the ultimate vision of Smart City development to be linked either to improve sustainability or quality of life. A balanced middle is proposed for both frameworks. Secondly, this paper analyzes how the two frameworks appear empirically in Smart City visions. Thirdly, we present and analyze quadruple helix model vision-building process case study of Smart Kalasatama vision building-process. The fourth analytical focus is to evaluate the outputs and early outcomes of the vision-building process. We conclude by providing two hypothesis of how a Living Lab process of Smart City vision-building impacts the content of the vision. This paper is structured so, that first we discuss smart city and benchmarking of smart city visions and propose a framework for those.. Then we present the case study of the Smart Kalasatama district programme Living Lab vision-building process. Finally we analyze and discuss the learning. 2 Building a Smart District Kalasatama in Helsinki Building smart city districts and creating smart city initiatives has become a major trend in municipal development during the past decades (Neirotti;Marco;& Cagliano&al, 2014) (Andrea & Peter, 2011). Respectively, the City council of Helsinki decided 2013 that Kalasatama will be the model district of smart urban development, thus the primary lieu of the Smart City innovation in Helsinki. Kalasatama can be viewed as part of the global Smart City trend, where the municipality is seeking new ways to address public issues with diverse partnerships and utilizing ICT and data as enablers. The Smart City concept has been defined in many ways (Hollands, 2008) (Neirotti;Marco;& Cagliano&al, 2014) (European Parliament, 2014)) and the concept remains controversial. Still, a Common frameworks can be identified behind the definitions, consisting of the drivers (urbanization, climate change, digitalization), the enablers (ICT technology, data), the collaborative public-private-people partnership (PPPP-) model and the targets (resource efficiency, better quality of urban life and economic growth) (Mustonen;Koponen;& Spilling, 2014), (Neirotti;Marco;& Cagliano&al, 2014) (Chourabi & al., 2012). The new Kalasatama district of Helsinki, under construction on former harbor is located by the sea close to the old city center. The district will see some 175 hectares re-developed with a total of 1.3 million square metres of homes, offices and service areas. Construction of Kalasatama began in 2011 and will continue until the 2030s, by when it will be home to over 20,000 residents and a working district for 8,000 people. The City hall initiated a smart city innovation platform program called Smart Kalasatama. The program has wide scope and concept, including a number of different industries and different solutions from smart grids to eHealth and smart retail. Further, the wish of the public governors is that innovations developed and tested in Kalasatama will scale up elsewhere thus creating jobs and wealth in the region. Globally, a lot of critique of the smart city concept has been presented, especially that the approach is too technocentric, top-down, driven by big global industry players (such as Cisco or IBM) and leading municipalities to vendor/technology lock-in (Kitchin, 2014). However, that critique seems already outdated, as the second wave of the smart city development emphasizes more the role of


municipalities, entrepreneurs and citizens. There is a considerable bottom-up interest in smart city scene to utilize new digital enablers to create more participatory urban solutions and increase livability (Hill, 2013). The Smart City concept has evolved from rather techno-driven approach to more smart citizen centric. (Baccarne;Schurman;Mechant;& Marez, 2014). The urban Living Labs have a role to play to facilitate quadruple –helix collaboration, to balance the interests and enable engagement of the citizens in the smart city development. (Paskaleva, 2011). 3 Smart Kalasatama Living Lab To make Smart Kalasatama grow from the genuine collaboration between the city, companies, academia and the residents a Living Lab approach was chosen. Smart Kalasatama Living Lab can be seen as an engagement platform (Ramaswamy & Gouillart, 2010) following open innovation 2.0 quadruple helix model, where the municipality, industry, academia and citizens collaborate to co-create new smart city ideas, services and prototypes (Baccarne;Schurman;Mechant;& Marez, 2014). The City of Helsinki assigned the co-ordination of Kalasatama Living Lab activities to its development and innovation agency Forum Virium. The City finances the Lab with help of other public funds. The Living Lab started virtually in the fall of 2013 and is looking for physical premises to open in the fall of 2015. Currently the Living Lab defines itself as an orchestrator, or innovation intermediary, of Smart City development. The focus in Kalasatama is in agile smart city service piloting. There are around 20 projects in the program portfolio and the Living Lab works to define new solutions to be co-created and tested in Kalasatama. A key role of the Living Lab is to find system integrators to drive co-designing and testing of new Smart City solutions such as Mobility as Service trials or Internet of Things LANs serving sharing economy in residential buildings. The Living Lab facilitates new project creation, ecosystem building, helps with collaborative methods and organizes workshops and other events. The projects themselves are owned and carried out by city departments, large and small companies, NGOs and resident organizations. The funding of the projects varies accordingly, some of them being large scale industry investments, others procurements by the City itself. The Living Lab is involved in finding funding for small partners (SMEs, NGOs) and is running itself some small-scale agile piloting. All in all, Smart Kalasatama Living Lab orchestrates a complex network with hundreds of different stakeholders coming from diverse different public and private organizations, having expertise in varied domains. Thus, the Living lab faces the challenge of leading a complex system where the stakeholders have very different targets for the new district being built. From the beginning, the Living Lab has chosen a strategy to embrace the complexity: All stakeholder groups from quadruple helix model are encouraged to participate. The smart district development allows multitude of different and even competing approaches simultaneously. Still, to keep the loose network together, a common purpose or shared vision was needed. The necessity to share a loose goal to direct the different smart city initiatives towards the same direction, initiated a vision process.


4 Role of Living Lab in Forming a Shared Vision of a Smart City District So, upon starting the Kalasatama Living Lab work 2013, the need for common vision to form a basis for multistakeholder collaboration. The importance of a shared vision as success factor of Smart Cities is already recognized by institutions, such as EU Open innovation strategy and policy group stating that: ”Shared value is the value created at the intersection of corporate performance and society when big problems are solved. Shared value is best achieved in the context of a shared vision.” (Curley & Salmelin, 2013). In a complex network, a good vision engages a variety of stakeholders. It defines a common dream state and leads the network loosely to the same direction. Moreover, a common vision is needed to operationalize smart city implementation in the city organization. As a study (ARUP, 2013) of European Smart Cities suggests, a vision of ”smart” is needed to supports strategic alignment and investment in technology across departments. Furthermore, it enables coupling SME’s and bottom-up development with larger scale city-driven initiatives. The sought after vision was defined as the dream state of which Smart Kalasatama will be known in 20 years by the project steering group (which consisted of the City and industry directors) in January 2014. Further, the criteria for the vision consisted of the following attributes: The vision should be compelling and inspiring for most of the diverse stakeholders, showing common direction for the smart city developers and still being broad enough to encompass variety of mindsets. The vision should be “born in Helsinki”, underlining the local needs and history of the district and thus also differentiating it both nationally and internationally. The main motivation of the vision building process in the Living Lab was to fortify the commitment of the stakeholders representing all the sides of the quadruple helix and having different interests. Thus a common vision addressing simultaneously at least potentially controversial goals such as social inclusion, economic growth, sustainability and improved quality of living, could become an essential tool to negotiate possible conflict in the Smart City development. 5 Benchmarking Smart City Visions Staring point of our vision building process was to benchmark other smart city and district visions. As Hollands (Hollands, 2008) already remarks, cities are branding themselves as smart. The self-celebrating branding of smart cities can be seen as municipal storytelling, similar to the smart city corporate storytelling (Söderström;Paasche;& Klauser, 2014). Regardless how the visions relate to reality, we benchmarked the smart city visions as sought after futures. Our special interest was in smart district development, so we paid attention to such cases as Masdar (Abu Dhabi), Royal Seaport (Stockholm) and Nordhavn (Copenhagen). The benchmarking material was used as props in the subsequent participatory workshops. Our benchmarking activities consisted of study visits and desktop studies. Copenhagen, Dubai and Masdar in Abu Dhabi were visited. Desktop studies concentrated on European leading smart cities (as according to EU study (European Parliament, 2014)) and neighbouring capitals: Wien, Amsterdam, Barcelona, Stockholm, Copenhagen, London, Lyon, Paris, Oslo, Tallinn. Material


for the benchmark was the web sites of the cities/districts, studies and reports made of the smart cities (e.g. (ARUP, 2013) (Bakiti;Almirall;& Wareham, 2013) and conference materials. 5.1 Smart City Visions and Objectives- Learnings from the benchmark material Smart City development is often seen to embrace all aspects of digitally enabled urban development, so forming a clear vision is not trivial. Most cities bluntly state that their aims are sustainability (resource efficiency/carbon neutrality), livability (quality of life) and economic growth through their smart city initiatives. Thus, they repeat the basic targets of any Smart City initiative, without adding local flavor or more direction in their visions. Unlike the corporations, the smart city visions do not emphasize the technological advancement, rather they tend to focus on the municipal benefits. In our benchmark material we found few clear visions. Vision statements may be foreign to public administration, which rather tries to express its wide responsibility and accountability. Many of the cities we studied mixed vision, mission and strategic objectives. So, we decided to scrutinize a greater variety of “objective statements” than just straight vision statements. Sustainability seems to the most underlined objective of Smart City initiatives, following earlier popular concepts such as “eco city”, “sustainable city” or “green city”. Many cities and districts have bland sustainability related visions like Stockhom’s Royal Seaport: A World class environmental urban district (City of Stockholm, 2015). Copenhagen’s vision is to be the first carbon neutral capital by 2025 (City of Copenhagen, 2015). That is both concrete and ambitious sustainabilitydriven vision. Copenhagen has also sub-objectives sand strategies serving the big target or carbon neutrality. For example the Danish capital has very clear bicycling vision supported by concrete targets and policies. One Smart City district having a concrete vision is Masdar City in Abu Dhabi. Their vision is to drive sustainable energy industry (Wikipedia, 2015). Many urbanists have overlooked Masdar as not a city at all rather a smart technology driven campus built in the middle of desert. However, Masdar has never claimed to become an European style city and has not sought citizen driven approaches. Instead it has tried to follow its own vision, working on new energy related innovations with strong industry partners. Masdar had indeed combined the two of Smart City benefits, innovation (economic growth) and sustainability, in its vision statement. The vision of smart city bringing happiness to all (Emirates 24/7, 2014) was taken by Dubai during spring 2014. That vision is truly human-centric putting the subjective experience to be the ultimate measure of the advancement of the Smart City. Dubai has followed the vision by launching a happiness index to measure its Smart City success (Dubai Smart Gov, 2015). As we predicted, later during the year 2014 more and more cities started to mix sustainability and wellness in rhetorical level in their smart city visioning. Good example of that is Wien, which has a very comprehensive Smart City strategy. Still, they keep their vision in the generic Smart City definition level: quality of life, resource preservation and innovation (City of Wien, 2015). In Barcelona Smart City Expo 2014 a big number of cities were proudly presenting that Smart City is not just about smart solutions, but about smart citizens. Instead of yielding interesting visions, the mixture of different targets


seems to have turned the Smart City discussion even more abstract and all embracing. Apart from Dubai, clear vision statements emphasizing the quality of life are hard to find. In Dubai’s case the connection between the Smart City development and happiness is yet not clearly pronounced, although happiness is measured (Dubai Smart Gov, 2015). The cities benchmarked do not combine the sustainability and quality of living targets in their visions. Closest comes City of Barcelona (City of Barcelona, 2015), which had a human-centric vision statement Barcelona as a City of People to win the award of European innovation capital. Amsterdam is often appointed as one of the leading Smart Cities in Europe in (e.g. (European Parliament, 2014)). However, their strategy has been not to have a vision, just an innovation platform to bring quadruple helix model partners together to innovate (City of Amsterdam, 2014). Their philosophy is to enable bottom-up urban development and not to restrict it by centralized top-down visions. Most other European cities benchmarked had similar visions/objective statements as Wien or Stockholm’s Royal Seaport. All in all, the level of the Smart City/district visions/ objective statements was not very crisp, even though the actual development of those cities/districts may be of high quality. Table below summarizes the main benchmarks. City/District

Vision/Objective statement


First carbon neutral capital by 2025.

Stockholm: Royal Seaport

A world class environmental urban district


“Quality of Life, sustainability, Innovation”




Barclona as a city of people.

Masdar City

Driving sustainable energy industry.


Happiness of all citizens.

To sum up our benchmarking, we placed the visions in two axis. The X-axis places sustainability and quality of life targets in different ends, leaving the balanced sweet spot in the middle. The other axis we used to examine the cities vision statements was top-down vs. bottom up. The current academic Smart City discussion favors a balanced middle for successful smart city development (Breuer;Walravens;& Ballon, 2014) (ARUP, 2013). According to research, change and innovation have better chance to arise when top-down and bottom-up systems and processes are integrated (Shephard & Simeti, 2013). Interestingly, most of the examples above, are rather top-down. Although the outcome of Smart Cities in Masdar and in the Scandinavian capitals is very different, their approach and vision is focusing on the systemic top-down


efficiency. Likewise in Dubai, the system of happiness is centralized, the state optimizing the happiness of the people top-down. The smart city visions benchmarked were mainly stories written by the cities, which explains their rather centralized top-down approach. The cities suggest large scale (infra) projects pushing new solutions to cities to achieve common good. This approach is at least partially contradictory to the Living Lab as a Smart City platform (Breuer;Walravens;& Ballon, 2014) paradigm to involve citizens and other bottom-up developers like SMEs in the process. Although, we do not know the processes behind in forming the benchmarked smart city vison/objective statements, it seems that citizens and other bottom-up focused stakeholders were not involved. Seems that as the first wave of Smart City vision were rather technocentric and driven by the industry, the current wave is municipally led. The learning from the benchmarking taken to the Kalasatama vision process, was to focus on the middle and try to encorporate views of all the quadruple helix groups. The table below summarizes the benchmarks in two axis:

Smart&City&Visions& Masdar&



Stockholm:*Royal*Seaport* ** Copenhagen&

Wien& Barcelona& Quality&of&Life&

Sustainability/& Resource&efficiency/& Energy&efficiency& &

Amsterdam& Bo4om0up&

6 The Kalasatama Vision –building process The Vision-building process consisted of a series of workshops and benchmarking activities facilitated by a team of five from Forum Virium. All in all almost 200 people participated in the vision forming process presenting all stakeholders of the Quadruple Helix Model. They participated in seven separate workshops during winter-spring 2014. The final decision was made in August 2014 in a steering group meeting chaired by the deputy Mayor of the City of Helsinki.The seven workshops organized had different participant profiles, including civil servants and government representatives, residents, academia, designers, large industry and SME managers, start-ups, ICT & building technology industries, local kindergarden kids, local senior home residents and city leaders.


December'2013,March2014:'Material'collec6on'and'crea6on.' • Civil&servant&workshop&12.12.& • Smart&city&benchmark&reports&& • Stakeholder&interviews&


March'2014':'Workshop'4.3.'' Mixed&audience&(PPPP)& April:'Workshop'11.4.'' ICTC&and&building&industries&workshop&



Benchmark&to&Masdar&City& May'2014:'' Two&residenFal&workshops&



TesFng&and&reframing& June'2014:'Summing'up,'different'proposals' Mixed&(PPPP)&workshop&and&City&directors&workshop&

Final&decision&August& 2014& Picture 1: Process model

In total, the vision process lasted nine months. So between the workshops the people involved interacted with each other, discussed the process in different formal and informal settings and learnt considerable amounts about smart city development on the go. All the workshops were tightly structured and lasted 2-3 hours each using a variety of co-working methods. In each workshop a common target was presented: To be able to tell in one sentence what Smart Kalasatama is about. One method used to issue this question was to ask participants to fill in a sentence what Kalasatama will be known in 20 years of time. 7 The Final Vision Statement Forming a compelling vision statement proved to be a challenging puzzle. On the one side there were the different viewpoints of the PPP partners, on the other side the all-embracing general Smart City targets. The differentiation requirement of the vision statement both nationally and internationally had to be considered. The learning from the benchmarks suggested us to seek a deliberate middle point in both of the axis taken as a framework to analyze the visions. Finally, the vision-building process ended up to a statement, that each citizen living in Kalasatama should gain “one more hour of own time a day”. In a smart district the time savings may result from good urban planning, where live, work and play take place in proximity. Smart mobility, logistics and services coming to the citizen may


contribute to the time savings. “One more hour of own time a day” vision shifts the focus into smart lifestyle supported by services. “One more hour” statement has taken a human-centric approach: all the smartness of a Smart City should eventually turn to give more capabilities or choice to the citizens by saving his/her time. “One more hour” tries to incorporate the sustainability aspect in the personal lifestyle. Thus it is deliberatively in the balanced “sweet spot” of Smart City visions, taking the citizen to be central part of the “system of systems” aiming simultaneously at resource efficiency and quality of life. Or one could argue, that it may integrate the approaches: you may create timesaving solutions from top-down (e.g. traffic infra including subway and EV infra) and pair them with bottom-up solutions (e.g. sharable EV services). “One more hour” incorporates the citizen as a key actor to make a Smart City successful. 8 Learnings of the workshop process The Kalasatama vision –building process reinforced the presumptionthat the viewpoints of the different quadruple helix participants differed. As expected, the City emphasized more systemic goals such as reduction of CO2 emissions, other sustainability measures and better overall public management. The City also pushed systemic solutions to the district: smart grid, waste collection tubes and open public governance led by the City hall. The City wishes to have control over the quality of construction. Citizen viewpoints were emphasizing fluent everyday life, services, social aspects and surprises. The developers (representing large and small companies developing smart city solutions) had quite different standpoint. They would like to have Kalasatama as a test bed with minimal regulation, where it is easy to test new solutions. Developers were excited of the possibility of innovation and open horizon of future technologies and business. The developers paid more attention to means than the ends. Still, despite their different strategies, the different quadruple helix stakeholders seemed to share a lot of common values like sustainability, resource efficiency and urban livability. The workshops with mixed PPPP participants worked best. They resulted the richest in detail and more through-out outcomes, where more processing was done at the workshop to synthetize different view points. So, it seems that heterogenous participant groups foster learning and may accelerate innovation as argued in Living Lab literature (Leminen;DeFillippi;& Westerlund, 2015). The diverse interests might also yield conflicts or tensions. In this case, the tensions did not explode. Still, a key role of a Living Lab as a process facilitator could be seen to negotiate the different views and possible conflicts when they emerge. Also the participants seemed to value more the workshops where they met different kind of actors. They learned more. Especially, the residents seem to rather participate in events and workshops where they can meet public or private developers. They feel that their input is taken into a process and they also learn more of the expert processes. 9 Conclusion


The Smart City Living Lab vision-building process described in this paper, yielded clearly differentiating smart district vision: Kalasatama will be so smart and resource efficient that it will promise “one more hour” for a resident. Most other Smart City vision and objective statements analyzed were rather system-centric (top-down), emphasizing either sustainability goals or aiming at livability and economic growth from the top-down perspective. Based on our learning, living lab PPPP co-creation methods are powerful in mixing different viewpoints and finding balanced outcomes. Based on this process, we could suggest two hypotheses, which could form a basis for a further research: Hypothesis1: Living Lab methods and PPPP-process yield more balanced yet humancentric Smart City visions (and strategies). Hypothesis2: Living Lab methods and PPPP-process yield more engaging Smart City (or other domain) visions, than visions created e.g. by City (or another “process/ domain owner”) alone. Based on only this particular case study, we can not generalize the Hypothesis1 to be true in other cases. More studies and examples are needed to validate it. The Hypothesis2 was supported by our experience: an unexpected Smart City vision raises discussion, comments and activates brainstorming and curiosity to participate among all quadruple helix stakeholders. However, as our Smart City Living Lab is just less than two years old is too early to evaluate weather a compelling vision helps to achieve longer term commitment and targets. Obviously more cases and research are needed to validate this kind of hypothesis. Kalasatama Smart City Living Lab managed to take the role of a participatory platform in the vision-building process. The outcome of the vision process merged top-down and bottom-up approaches as well as integrated seemingly contrasting ends of sustainability and quality of life. One could conclude, that Living Labs as truly open innovation platforms, may take a powerful role in balancing visions of smart cities to engage all different stakeholders. 10 Bibliography Andrea, C., & Peter, D. B. (2011). Smart Cities in Europe. Journal of Urban Technology , 18 (2), 65-82. ARUP. (2013). International Case Studies on Smart Cities. The Department for Business Innovation and Skills. London: Arup. Baccarne, Schurman, Mechant, & Marez, D. (2014). The role of Urban Living Labs in a Smart City. The Proceedings of ISPIM Conference for Sustainable Economy and Society. XXV, pp. 1-14. ISPIM. Bakiti, Almirall, & Wareham. (2013). A Smart City Initiative: the Case of Barcelona. Journal of Knowledge Economy , 4 (2), 135-148. Breuer, J., Walravens, N., & Ballon, P. (2014, June). Beyond Defining the Smart City. Meeting Top-Down and Bottom-Up Approaches in the Middle. TeMa. Journal of Land Use, Mobility and Environment , 153-164.


Chourabi, & al. (2012). Understanding Smart Cities: An Integrative Framework. Hawaii International Conference on System Sciences proceedings. 45th, pp. 2289-2297. IEEE computer society. City of Amsterdam. (2014, 4 15). Amsterdam Smart City. Retrieved 4 26, 2015, from Amsterdam Smart City: http://amsterdamsmartcity.com/ City of Barcelona. (2015, 4 26). Retrieved 4 26, 2015, from iBarcelona: http://ibarcelona.bcn.cat/en City of Copenhagen. (2015, 4 26). https://stateofgreen.com/. Retrieved 4 26, 2015, from StateofGreen: https://stateofgreen.com/en/profiles/city-of-copenhagen City of Stockholm. (2015, 4 26). Retrieved 4 26, 2015, from Stockholmroyalseaport: http://www.stockholmroyalseaport.com/en/ City of Wien. (2015, 4 26). Smart City Wien Framework Strategy_o ne page. Retrieved 4 26, 2015, from Smart City Wien: https://smartcity.wien.gv.at/site/files/2014/09/SmartCityWien_FrameworkStrategy_ english_onepage.pdf Cosgravea, E., Arbuthnot, K., & Tryfonas, T. (2013). Living Labs, Innovation Districts and Information Marketplaces: A Systems Approach for Smart Cities. (2. P.–6. Volume 16, Ed.) Procedia Computer Science , 16, 668-677. Curley, M., & Salmelin, B. (2013). Open Innovation 2.0: A New Paradigm. OISPGOpenInnovation20ANewParadirm-WhitePaper, (pp. 1-12). Dubai Smart Gov. (2015, 4 26). Dubai Smart Government has officially activated “Happiness Meter” in 14 government entities so far. Retrieved 4 26, 2015, from Government of Dubai: http://dsg.gov.ae/en/mediacentre/DegNews/Lists/NewsCentre/DispForm.aspx?ID=1 46 Emirates 24/7. (2014, 3 5). Mohammed launches Dubai Smart City. Retrieved 4 26, 2015, from Emirates 24/7: http://www.emirates247.com/news/government/mohammedlaunches-dubai-smart-city-smartphone-to-be-key-pivot-2014-03-05-1.540576 European Commission. (2014). Open Innovation 2.0 -Yearbook 2014. Luxembourg: European Commisssion. European Parliament. (2014). Mapping Smart Cities in the EU. European Union. Hill, D. (2013, 2 1). On the smart city: Or, a 'manifesto' for smart citizen instead. Retrieved 6 15, 2015, from City of Sound: http://www.cityofsound.com/blog/2013/02/on-thesmart-city-a-call-for-smart-citizens-instead.html#more Hollands, R. (2008). Will the real smart city please stand up? City , 12 (3), 303-320. Kitchin, R. (2014). The real-time city? Big data and smart urbanism. (SpringerLink, Ed.) geoJournal , 79 (1), 1-14. Leminen, DeFillippi, & Westerlund. (2015). Paradoxical tensions in living labs. The Proceedings of The XXVI ISPIM Conference. Budapest: ISPIM. Mustonen, V., Koponen, J., & Spilling, K. (2014). Älykäs kaupunki -Smart City. Katsaus fiksuihin palveluihin ja mahdollisuuksiin. Helsinki: Ministry of Transport and Communications. Neirotti, Marco, D., & Cagliano&al. (2014). Current trends in Smart City Initiatives: Some stylised facts. Cities , 38, 25-36. Paskaleva, K. (2011). The smart city: A nexus for open innovation? Intelligent Buildings International , 3 (3), 153-171. Ramaswamy, V., & Gouillart, F. (2010). The Power of Co-creation. New York: Free Press.


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Use of Living Lab in Innovative Public Procurement: Case Keyless Home Care Haukipuro Lotta a, Torvinen Hannu a, Väinämö Satu a, Mattila Pasi a a

University of Oulu, Finland

Abstract Recent shifts in public procurement from traditional towards innovative has opened up new opportunities for operators providing tools and services for userdriven development. Living Labs have strong expertise in the field thus being appropriate actors in innovative public procurement activities. This paper presents empirical findings of an innovative public procurement case in health care field where the service provided by a Living Lab was in significant role. Living Lab was involved in the process from the beginning until the end of the procurement. The results indicate that use of Living Lab tools and services may foster innovative public procurement in the field of health care. Keywords Innovative Public Procurement, Living Lab, User Engagement, Home Care 1 Introduction In present research, innovation is defined as “novelty or reform with significant productivity-, economic efficiency- or other value-adding effects on the organization’s performance” (Yliherva 2006). Lee, Olson and Trimi (2012) see innovations necessary for public sector’s better productivity and new more costeffective operations. The desire to create new innovations is one of the key drivers behind the utilization of new differentiated public procurement approaches (Edler & Georghiou 2007). An extremely prominent source for innovations are customer interfaces favourable to the exchange of know-how, information, viewpoints, experiences, cultures and resources (Yliherva 2006). The possibility to enhance the involvement of the end-user in the procurement process is partly the result of advanced technology, and partly citizens’ increased enthusiasm to participate in the co-production of the services (Bovaird & Loeffler, 2012). According to Uyarra & Flanagan (2009), public procurement is seen as having a potentially crucial role in enhancing the innovations in Europe, thus creating wellbeing. As current trend in public procurement is to add innovativeness through


end user involvement, a new opportunity has opened for Living Labs to provide their expertise of user-driven methods and tools to be utilized in public procurement field. So far, the involvement of end users into procurement process has raised some interest and attempts in practice as well (Ng et al., 2013). A long-standing and several successful co-development projects with public sector conducted Living Lab OULLabs,18 located at the University of Oulu, Finland, was providing Living Lab services in an innovative public procurement of the City of Oulu. The aim of this “Keyless home care” process was to implement public procurement of a keyless mobile door opening service for home care in a new, innovative way through product testing and user involvement. The aim of the city was to purchase service that allows home care personnel to open customer’s door with a mobile device. The Keyless home care project’s product testing phase was implemented within an EU funded, Living Lab environment developing project19. The project team implemented Keyless home care purchase product testing, led by a usability specialist. PATIO forum (www.patiolla.fi) was used for involving home care workers who were testing the service in a real environment. As a result, innovative public procurement of a mobile door opening service where product testing was for first time in significant role, was successfully implemented. Furthermore, as a result of the process, the winning mobile door opening service was put in use in certain districts of the City of Oulu home care, and the aim is to further spread it to the whole city. 2 Innovative public procurement The public sector acquired infrastructure and services can be regarded as essential for maintaining society's economic and social structures (Lähdesmäki & Kilkki, 2008). Traditional competitive bidding procedures carried out in public procurement have experienced in recent years an increasing pressure for change, including increased demand for services due to aging population, challenging economic situation and as a result of new technology solutions (Pekkarinen et al., 2011; Jamali, 2007). According to Aho et al. (2006), along changing procurement environment, innovative public procurement has emerged as a central theme in the 2000’s demand-driven innovation policy at the national level as well as in the European Union. Specifically, new market-oriented public procurement models aimed at generating innovations but also accelerating the spread of innovations by strengthening the demand for new solutions, have attracted attention. Increased demand-orientation may have blurred the line drawn between the public and the private sector as in the private service provider carry increasing responsibility for public procurement holistic implementation. Furthermore, public procurement has multitude of social goals to serve, and its use as innovation tool entails various challenges (Uyarra & Flanagan, 2009). General benefits of innovative procurement in addition to increased innovation have been considered to consist of increased higher overall efficiency of procurement, quality, efficiency, risk management and transparency (Majamaa, 2008a; Yescombe, 2007). Innovative public procurement, in a wider perspective, 18


Oulu Urban Living Labs www.oullabs.fi/en MAINIO project, www.mainio.eu


also improves the dynamics of innovation (Edler & Georghiou, 2007). At best, public procurement can have greater incentive effect on firms' innovation activities than traditional public sector funded research and development activities. The greatest obstacles for the implementation of innovative procurement do not lie so much in the legal instruments guiding procurement, but in the procurement departments’ ability to study and apply procedures that allow the development of providing innovative solutions. In addition, innovative procurement often contain higher risks, the result of which division of responsibilities of the risks caused by procurement should be clearly specified in advance. Public procurement potential as source of innovation is based, above all, on the public sector’s large but still widely unutilized economic volume. Although the public procurement has already been used as a tool to promote innovativeness in many countries, innovative public procurement can be viewed as a rather new phenomenon. The most common cases for innovative public procurement have so far been the major infrastructure projects and defence industry procurement. The most advanced in the development of innovative procurement are generally seen the United Kingdom and the United States. In Finland, the promotion of innovation has not usually been the main goal of public procurement even in new procurement, but rather as a minor aim of the projects. The choice of innovative procurement method in Finnish public procurement projects has been justified mostly with achievable savings instead of innovativeness. Not only exclusive existing demand gives rise to innovation, thus essential for innovative purchase models is a dialogue between end users and other key actors considering the functionality of a procurement. Demand-driven public procurement can say to reach for higher customer orientation in procurement. Publicly acquired infrastructure and services should not be judged not so much according to decision-makers’ interest, but based on what the end-user sees as valuable. In practice, the customer and the service provider should pay attention to, as well as the procurement of current and future functional requirements, and be able to define the demand in more broader and clearer scale. The interaction between the actors in innovative procurement is seen in present research, as a triad of the customer, the supplier and the value co-producer (Havila et al., 2004; Majamaa, 2008). The triadic nature of the focal procurement relationships means the existence of an intermediary that has constant contact with both the selling party (supplier) and the buying party (procurer), while the selling party and the buying party have also their own simultaneous contact with each other (Havila et al. 2004). Important for the triadic relationships are social bonds and trust especially at the operational level (Holma 2012). A starting point for many of the new procurement practices is considered to be the rise of New Public Management movement gaining its popularity since early 1990s. The main aim of NPM trend has been to modernize and enhance public sector operations with a more market-based approach on organizing public services (Hood, 1991). Market-based approach on public procurement opens opportunities both for mobilizing innovation and at the same time better achieving public policy goals and delivering better service to the citizens. Public procurement practitioners tend to often lack a clear understanding of who the client of the public service is and, therefore, do not know whose needs they are supposed to satisfy (Bovaird 2007). Even though no generally agreed upon definition of public procurement


partnerships is known to exist (e.g. Lawther & Martin, 2005; Yescombe, 2007), some market-based models like public-private partnership and pre-commercial procurement (PCP) have gained vast interest from both the researchers and practitioners in the public procurement field. In Public-Private Partnership (PPP) model aka life cycle model the supplier carries a larger liability of the procured object or service for a longer period of time also called the life cycle of the procurement. In other words, public sector sets end targets for the outcomes of the procurement, but doesn’t define in advance how to reach these goals (Yescombe, 2007). PPP model has emerged as a worldwide trend by public procurement practitioners especially within infrastructure acquisitions (Ng et al., 2013). The most vital aspect on describing innovations within PPP model is the added value the innovation creates for the end-users (Yliherva 2006). If PPP method was chosen more regularly on the basis of value gained by the end-users, then cooperation, commitment and networks would more often be considered as the prime benefits of the model instead of the financial arguments (Lähdesmäki & Kilkki 2008). PCP model can be applied to innovative procurement in which more research and development is needed. The PCP model aims to achieve user-friendly solutions developed together with businesses, avoiding monopolistic structures by involving at least potential suppliers in field test phase. The benefit of the model for the customer in procurement is sharing the risks related to product development between public customers and potential suppliers (Mattila & Silander, 2015). 3 Living Lab’s role in innovative public procurement As open innovation emerges in new service development, elaborate networks where organizations co-create to generate new products and services have been increasingly researched and established (Chesbrough & Appleyard, 2007). The open innovation model (Chesbrough, 2006) shows that ideas are generated both inside and outside organizations. External knowledge is seen to play an equal role as that afforded to internal knowledge in the earlier conception (Chesbrough, 2006). Open innovation builds strongly on voluntary collaboration, which makes Living Labs a fruitful environment for deploying open innovation (Chesbrough & Crowther, 2006; West et al.2006). Though there are several definitions of Living Lab, no coherent definition yet exists. According to most recent research Living Lab can be defined an embodiment of both the open and user innovation paradigms (Schuurman, 2015). According to Leminen et al. (2012) a Living Lab is a network that integrates both user-centred research and open innovation. Living Labs are driven by two ideas: involving users as co-creators on equal footing with the other participants and experiments in real-world settings (Almirall, Lee & Wareham, 2012). Living Labs are thus seen as separate from other innovation approaches due to two dimensions; a high degree of realism and a high degree of user involvement (Schuurman & De Marez, 2012). Compared to, for instance, field trials or user testing, a Living Lab involves users in all stages of R&D and all stages of the product development lifecycle (Ballon, Pierson & Delaere, 2005). Following Almirall & Wareham (2012) and Leminen et al. (2014), Living Labs can also be defined as an organized approach (as opposed to an ad hoc approach) to innovation consisting of real-life experimentation and active user involvement by means of different


methods involving multiple stakeholders, as is implied in the Public-Private-People character of Living Labs. (Schuurman, 2015). Living Lab’s role in innovative public procurement can be seen significant as implementing innovative procurement requires cooperation among all actors; customer, supplier and end users (Mattila & Silander, 2015). Even though the cooperation with users and the surrounding community has been recognized essential for public procurement’s success, the resources given to end-user’s engagement to the public procurement processes are often slim (Bovaird & Loeffler, 2012). The desires of end-users get neglected too often which leads to solutions unsuitable for the actual user of the public service creating e.g. financial losses caused by the additional fixing costs and dissatisfaction’s effecting on the supplier’s life cycle payments (Ng et al. 2013; Satish & Shah 2009). The early detection of user requirements and needs guides the procurement project towards better end results, efficiency and innovative solutions straight from the beginning (Laine & Junnonen 2006; Majamaa et al. 2008; Satish & Shah 2009). In addition to creative mind, users can also bring other resources to the process for instance by positively influencing other users and lowering the public opposition (Bovaird & Loeffler, 2012). Thus, Living Lab user communities can be useful when involving end users in innovative public procurement cases. The supplier and end user share a common need to develop a new product or service for the market, aiming to create added value e.g. through better quality, more efficient production processes, lower life cycle costs, environment friendliness or usability (Mattila & Silander, 2015). By developing innovative procurement, end users are able to participate in the process from the early planning to implementation. Living Labs’ basic idea, early involvement of end users makes possible corrections or changes cost-effective also in procurement cases. 4 Methodology The study applies case study as the primary research approach. According to Yin (2003) a case study design should be applied when: the focus of the study is to answer “how” and “why” questions, or behaviour of those involved in the study cannot be manipulated, or contextual conditions are thought to be relevant to the phenomenon under study, or the boundaries are not clear between the phenomenon and context. In this study, Living Lab approach and multiple Living Lab methods were used in order to collect diverse data and form a comprehensive view of the Keyless home care case. Interviews, online end user involvement tool PATIO (www.patiolla.fi), quantitative measurement, and surveys were used in this study. Primary data of the study is qualitative: project team was informally interviewed and identified key persons’ in-depth interviews were conducted. All interviews were recorded and transcribed into text documents. Approximate duration of an interview was 1 hour each. The interviewees were: • Technology Specialist from the City of Oulu who was at the time of implementation of the Keyless home care case in a role of Purchase Planner in the City of Oulu’s strategic procurement department. • Project Manager of MAINIO project who was actively participating in planning and in charge of product testing as a part of purchase, and


Usability Specialist in main role of product testing implementation and reporting in Keyless home care case.


Furthermore, qualitative data was collected through online discussion where test users were able to provide feedback of product testing they were involved in. Quantitative data was collected through product testing which included objective technical measurement such as time (duration of opening a door), and several questionnaires for test users. Project related internal reports and documents as well as public information available regarding the Keyless home care case were used as secondary data. 5 Case Keyless home care Involving users may make a traditional purchase innovative, which is growing trend in public procurement, and also included in the strategy of City of Oulu: the aim for 2016 is that 20% of the purchases have been made using innovative procurement procedures. The Keyless home care project was implemented during approximately eight months in 2013-2014 as a pilot project of an EU funded project in cooperation with the University of Oulu and the City of Oulu. The need for this kind of pilot project arose from initiation of the Social Welfare and Health Services and specifically home care services of the City of Oulu, which aims to search for cost-efficient services and cost-efficient tools for service production. Home care workers visit over ten patients in their homes during a shift, thus using ten different keys for opening patients’ doors. The keys are stored in the office of home care workers from where they have to pick them up individually between patient visits. The need for Keyless door opening system arose thus from practical reasons – need to save home care workers’ time, ease their work and improve safety through minimizing the risk of losing keys. In few cities in Finland the home care has been already made 100% keyless. Good general experiences of Keyless home care based on pre-study and practical needs of home care in the City of Oulu led to a project where product testing was for first time in significant role as a part of public procurement in the City of Oulu. Living Lab resources and user involvement as well as usability knowhow that were necessary for implementing the Keyless home care pilot project, were provided by OULLabs. In addition, expertise of the field (home care) and project management were needed in the project. The Keyless home care mobile door opening service was purchased partly (40%) on the basis of a product testing of four door opening system (lock module, application and software for administration of the door opening). Product testing was planned and implemented by OULLabs’ specialists. Planning took two months and implementation including official decision making process six months, overall duration being thus eight months. Relatively long time was spent in planning as product testing within public procurement of the City of Oulu was novel: preliminary work including search for references, minimization of risks and consideration of legacy aspects was time-consuming. Selected group of users, seven home care workers and their four supervisors (n=11) performed product testing of the four mobile door opening systems delivered from different companies during their two week shifts in a real home care environment,


sheltered housing. The more precise task of the home care workers was to test the opening of lock modules and use of a “key”: a mobile application installed in their work mobile phones through which the lock modules can be opened. The products were anonymized and coded with colors: red, green, yellow, and blue. The supervisors tested PC software through which the system is administered, e.g. access rights given to users. In addition, a usability specialist tested both the lock modules and software of all companies. The test was based on usability standard ISO9241-11 (ISO, 1998) and they were implemented in such way that all test cases were measurable. Evaluation feedback and scores were collected from users through a questionnaire. Additionally, a Living Lab user involvement online platform PATIO (www.patiolla.fi) was used for collecting feedback in a private online discussion area from home care workers about product testing process in order to develop the procedure of innovative procurement within the City of Oulu. Criteria Price Quality Questionnaire, users Questionnaire, administrator users Timing/lock Timing/software

Score % 60 40 12,5 12,5 7,5 7,5

Table 1. Evaluation Criteria

The evaluation criteria for purchase were price (with a 60% weighting) and quality (with a 40% weighting). Scores given by users with scores given by the usability specialist together formed quality: user feedback (questionnaire) and supervisor’s (administrator user) feedback both with a 12,5 % weighting, product efficiency 7,5% and time spent for software usage 7,5%, altogether with a 40% weighting (Table 1). Figure 1 illustrates the overall process of the Keyless home care public procurement process. The process consisted of several elements such as planning, bidding, installation, product testing, analysis and decision. Duration of planning phase was two months as the project was unique without existing references to be exploited in planning. Living Lab was involved in the planning phase as expertise of conducting product testing and user involvement was needed. In the bidding phase, official bidding announcement in co-operation with project team was made. On the basis of announcement, four offers from suppliers were received and four products (lock module and software) were installed in a testing environment. Suppliers introduced their products for usability specialists to enable planning and implementing and to ensure efficient testing. Product testing was conducted in a real use environment during two weeks. At the same period, usability specialists conducted usability testing for products and software. Analysis of product testing results was made in cooperation with public procurer after which official decision making process was started.


Figure 1. Process of Keyless home care innovative public procurement

6 Results On the basis of scores formed by quality features and price, mobile door opening system was procured. The overall size of the purchase was 500 lock modules and software, the total value of the purchase being 250 000 EUR. Compared to traditional public procurement where product with lowest price usually becomes selected, the result of the Keyless homecare procurement differ considerably: the selected mobile door opening system was not the cheapest one but the one with highest scores obtained from overall price and quality together. This means that quality and user assessment were in significant role in the procurement. What was also interesting result was the fact that the product with the lowest price did not receive good scores on quality. As there were several stakeholders involved, the results of the Keyless home care project can be viewed from different angles: from the City point of view, first-hand experience on conducting a successful procurement pilot was valuable considering the further development of procurement. Costs were saved, effectiveness of home care working hours was improved and home care workers’ satisfaction was increased as they themselves were able to choose their “tools”. The effect of increased work satisfaction was not studied here but there might be far reaching positive impact. From users, home care workers’ point of view, usability of a daily used product was ensured through comprehensive product testing: in addition to basic testing, the users were able to express their opinions and feel obtaining a significant role in the project. From home care patient’s point of view, service provided for them was also improved as home care workers are able to enter patients’ homes more quickly without additional office visits between patient visits. To set up the service, patients’ lock modules had to be changed and a small service fee was set by the City of Oulu but on the other hand, other costs such as ordering new keys were saved by patients at the same time. From the Living Lab point of view, valuable experience of successful use of a Living Lab in innovative public procurement was obtained, and conditions for using Living Lab in future public procurement cases were created. Furthermore, experience of the suitability of


Living Lab methodology for innovative public procurement where i.a. legal aspects must be taken in account, was gathered. Figure 2 illustrates the setting of the Keyless home care public procurement, especially the role of Living Lab in the case. The importance of Living Lab services and expertise was crucial in the planning phase where a product testing plan, which was an important part of bidding announcement, was planned and implemented by Living Lab usability specialist.

Figure 2. Living Lab as a part of “Keyless home care” innovative public procurement

7 Conclusion The study presented a public procurement case where product testing service provided by a Living Lab was for the first time included in a public procurement in the City of Oulu. The case of Keyless home care was unique and raised a lot of interest among stakeholders. Successful implementation of the procurement process as well as exceptional results are extremely important for all stakeholders, but especially the City of Oulu and Living Labs. New means of shifting from traditional procurement towards innovative public procurement were identified and tested in the process. Product testing within public procurement was carefully planned and documented and thus serve as a reference and easily exploited in the coming procurement cases where product testing is included. In general, the promising results of the case Keyless home care indicate that Living Labs’ expertise is useful in implementing innovative public procurement. For instance, in a case where citizens would be involved in a public procurement, the role of Living Lab could be even more significant as user engagement tools and methods for facilitating users are among the strengths of Living Labs. First experiences such as Keyless home care provide opportunity to practice cooperation and build trust between operators in multi-stakeholder projects. For instance, experience of close co-operation between local Living Lab and the City of Oulu in several different development activities has built strong confidence and knowledge of each other’s expertise between the organizations, which cannot be underestimated when operating in such strictly regulated field as public procurement. However, there is need for further research in order to efficiently


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Towards a sustainable panel-based living lab approach in older adult care innovation Juul Lemey1, Charlotte Brys2, Koen Vervoort3, Patricia De Vriendt2,4 & An Jacobs3,5 on behalf of KIO6 and PO3 1

Department of Bachelor in Nursing, Artevelde University College Ghent, Ghent, Belgium 2 Frailty in Ageing (FRIA) Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Belgium 3 iMinds, Flanders’ digital strategic research centre, Ghent, Belgium 4 Department of Bachelor in Occupational Therapy, Artevelde University College Ghent, Ghent, Belgium 5 iMinds, SMIT, Vrije Universiteit Brussel, Brussels, Belgium 6 KIO, interuniversity consortium studying innovations in older adult care in Flanders. Juul.Lemey@arteveldehs.be This submission has been previously published elsewhere.

Abstract To tackle the current challenges in the care for older adults innovative solutions should be created. Herefore a panel-based living lab approach can be used. This requires a sustainable involvement of older adults and their caregivers, which is challenging. Based on the experiences in the ‘Care Living Labs Flanders’ program this paper will discuss how a panel based approach can be achieved. This case study was a combination of a plan evaluation and action research. A comparison between the initial plans and the steps towards a sustainable panel for the Care Living labs is provided. Keywords Older adult care, user involvement, panel-based living lab 1 Introduction Worldwide the care for older adults faces problems as budgetary restrictions and staff shortages (Ellenbecker, 2010) while the demand for care is rising (Hussein & Manthorpe, 2005). In addition most older persons indicate that they prefer to live at home and close to their familiar social environment (Buffel et al., 2014) which results in a growing pressure on informal caregivers. To tackle these challenges


policy makers funded several care living labs (CLL) to create social and technical solutions that enable older adults to live longer and independently at their homes. Essential in these CLL is the active participation of older adults, informal caregivers and professional caregivers in the creation and testing processes. In a panel-based living lab approach, they form the panel, which is the core of the lab. Nevertheless the formation of a sustainable panel with these groups is associated with several difficulties, such as getting access to the future users, striving for representativeness and keeping participants attached to a panel. In this paper possible strategies to tackle them will be discussed. 1.1 Care Living Labs Flanders The case study used in this paper to reflect on the challenges for a panel-based living lab approach is the program ‘Care Living Labs Flanders’. It is initiated by the Flemish government to tackle the challenges in the care for older adults. Currently six CLL (CareVille, InnovAGE, AIPA, AzoB, Online Buurten and LiCalab) and 23 projects are funded from 2013 to 2016. ‘A project’ is a string of activities creating and testing an innovation iteratively. In the first year (2013-2014) the CLL’s started with the creation of their panels. Between the CLL different strategies are observed to recruit and commit their end-users, which will be discussed in this paper. 1.2 The panel-based living lab Panel research is a term used in literature with many different connotations, most often it refers to repeatedly asking questions or profiling people over time. In social sciences and market research it is used for longitudinal survey studies on change in behaviour and attitudes resulting in larger scale results with stronger validity (e.g. Estrada, 2014). In medical practice one is experimenting with panel approaches to peruse an enhanced profiling and thus better care (e.g. Neuwirth et al, 2007). Schuurman & De Marez (2012) defined ‘panel’ in panel-based living lab as a part of the “infrastructure”, where users are recruited thematically and are profiled. They also studied its added value versus the more traditional living lab approach by analysing several Flemish cases. Ease of user recruitment based on specific characteristics is key. It makes implementation of a test phase for example faster: there is accurate and up to date data on potential participants to make the selection more specific, they already opted in regarding privacy and other operational aspects are also already covert, pre-activity information is available and it is easier to collect ex-post measurements because of the sustained relationship with the panel members over the different projects. But they also warn that to cherish these advantages time and effort needs to go to the recruitment and management of your panel. Also in classic social sciences longitudinal survey studies retention of participants is a challenge. Based on social influence and relationship research Estrada et al. (2014) built a “tailored management approach”, which makes sure communal norms are created that stimulate commitments to stay active as a participant during the subsequent studies. Commitment is created by working on compensation (built reciprocity by giving compensation before activities, focus on intrinsic motivation), communication (bidirectional, choice to multiple channels, personalised


communication and tailored to the participants, creation of group identity), consistency (messages predictable and recognisable over time, don’t overburden, be clear on the rules, roles and values of engagement) and credibility (the organiser and the study are perceived as legitimate). This advice is in line with the panel management experience within iMinds in domains not related to older adult care. Vervoort (2012) presented seven steps to create and maintain a panel based living lab on his team’s experiences with panel management in several Flemish living lab cases (table 1). Steps Step 1: Define the purpose of the panel

Step 2: recruit users

Step 3: support the panel

Step 4: live the lab

Step 5: handle privacy

Step 6: reward users Step 7: maintain the eco-system

Explanation and instructions What is the role of the panel? What are the parameters of the panel? What are possible motivators for the participants? Define the profile of the panel members, the recruitment channels, the communication and the project flow (who when why). Participating should be fun. Organise the helpdesk. Give the living lab a face through a single point of contact (SPOC). Training and inform panel members. Set up a system to share experiences. Feedback is a twoway street. Capture central data. Measuring is knowing. What is the mixture? Keep track of linking devices and services to members. Protect members’ personal space. Develop a procedure to handle personal data towards stakeholders (on need to know base). Provide motivators to cooperate (intrinsically, financially) (offer a mixture). Define an entry and exit strategy. Build the community through ‘member-getmember’. Expectation management is a continuous effort over the lifetime of the panel.

Table 1 Steps to create and maintain a panel in living labs

This experience is used for the coaching of the build-up of the CLL in Flanders. This experience was merged with specific knowledge on older adult care to improve the coaching as it is challenging to involve the multiple actors in this sector.


1.3 The challenge of multi actors and heterogeneity The Flemish government required to include older adults as the central target group. Today, 20% of the Flemish people are 65 years and over. This ratio will increase to 25% in 2030 and 33% in 2040 (Federal Public Service Economy, 2015). A similar demographic change occurs in Europe (European Commission, 2015). However, 'the' older person does not exist. In fact they are a heterogeneous group with diverse needs and capacities. Using solely a certain age range is misleading (European Commission and Spanish Ministry of Health and Social Affairs, 2010). Differences between older adults are characterized by their health status, degree of dependency, social network, cultural background, socio-economic status, level of citizen participation, ... These aspects change during the life course. Including this heterogeneous group of older adults to create and test innovations for elder care is necessary. Nevertheless there are other involved actors, like informal and professional caregivers. They may experience major direct and indirect effects from the innovations that are created. For instance social innovations where older adults help each other out may lead indirect to a decreasing burden of family caregivers (Lemey et al., 2015). There are also innovations (e.g. communication technology) to support caregivers directly. In both situations family caregivers, volunteers and professional caregivers should participate in the CLL. Informal caregivers are also a heterogeneous group. There are spouses, children or other family members and volunteers. In Europe 21% - 43% of the noninstitutionalised population of 65 years of age or over receive help or support at least sometimes on an informal basis (Riedel & Kraus, 2011). In Belgium the age of informal caregivers varies between 20 and 89 years (Panel study on Belgian households, 2001). About 6% of the European population aged 50 or over provides personal care for an older relative or family member. Almost 60 % of them is female (Riedel & Kraus, 2011). Other differences can be seen in terms of employment, marital status and hours of provided care. The group of professional caregivers is also very broad and consists of nurses, nurse-assistants, doctors, dentists, pharmacists, physiotherapists and other paramedical professionals like dieticians, occupational therapists, speech therapists, hearing-aid specialists, audiologists, podiatrists, pharmacist assistants and non-urgent medical transporters. Also social workers and other staff (e.g. hygienic staff) from healthcare institutions and nursing homes should be included as they are part of the network of older adults. These professional caregivers also differs for variables like age, experience, job motivation, … This heterogeneity of the multiple actors is an important point of attention for CLL when building a panel. 1.4 Recruiting older adults and their caregivers as future users This heterogeneity and the dynamic characteristics of the population of older persons and their caregivers makes their recruitment for a panel in a CLL a challenging task. Several barriers can prevent them to participate (Mody et al., 2008, McMurdo et al., 2011; Law, Russ & Connelly, 2013; Wilding et al., 2013). The most common practical barriers are high travel costs and lack of time. Health


related barriers can be divided in physical and psychological problems (e.g. cognitive impairment). Older adults with health related problems need assistance to participate in a CLL. Social and cultural issues also occur frequent. These are problems with language and literacy, financial problems or different cultures. Immigrants are often more sceptical towards research. To conquer these barriers a fine recruitment plan should be made. The identification of the target groups needs to be the starting point. Hereby inclusion and exclusion criteria should be set. These criteria should be in line with the goals of the innovation. Moreover it is important to make an overview of the sources were future users can be recruited. Community-based settings such as senior centres are effective sources to find community-dwelling older adults (Wilding et al., 2013). Care institutions and nursing homes can also be useful sources to find older adults and their caregivers. Gatekeepers, such as family, community leaders, institutional leaders and physicians, nurses, or other direct care workers can provide access to those sources, identify potential subjects and can be a decisive influence on participants’ decisions to enrol (Mody et al., 2008; Wilding et al., 2013). Creation of an advisory board with these gatekeepers can be of value with information about the needs and concerns of the future users (Mody et al., 2008). During the identification of the future users it is also important to identify their motivation to participate in a CLL. Intrinsic values (loyalty, civic duty and the wish to improve the government), personal traits (education, family composition), being responsible, trust in co-creation initiatives and the perceived abilities influence the willingness of older adults and their caregivers to participate (Elad et al., 2000; Law, Russ & Connelly, 2013; Voorberg et al., 2014). In a next step the future users’ needs to be contacted and a trust relationship must be built up (McHenry et al., 2012). Personalized outreach such as in-person contact or personalized invitations is highly effective across all populations (McHenry et al., 2012; Wilding et al., 2013). Face-to-face contact can be achieved through gatekeepers, active participants of the CLL or representatives of the CLL, like a panel manager. Both written and digital media can be used. Written folders with information about the CLL should be placed in spaces where older adults and their caregivers come along (e.g. waiting rooms for practitioners or churches). Other possibilities are an article in the local newspaper or an announcement on the local radio or television. Social media can be used to recruit younger caregivers. Explaining the goal and expectations is important during this contact, as well as convincing them of the possible benefits like access to helpful treatments, services, or diagnostic tests; social interactions with staff or other participants; recognition of one’s contribution; or general altruism (Mody et al., 2008). 2 Method In this case study insights from a plan evaluation and action research were used to map how the CLL’s and their projects plan and organise to recruit future users for their panels.


2.1 Plan evaluation A plan evaluation of the CLL was done through a document analysis of the submitted proposal of the CLL’s and semi-structured interviews with their representatives. A content analysis on six themes (innovation goals, target population, networks, labour organisation, geographical area and technology) was performed in several steps. At first a close reading of the proposals of the CLL, submitted to the funding agency IWT, was performed. Meanwhile all information relevant for the six themes was selected. In the second phase this information was used to explore the CLL’s views on innovation within the different themes. Thereafter these visions were compared with prevailing theories through deductive analysis. Data-extraction and the first step of the analysis were performed independently by two researchers. Differences were discussed with all researchers (n=5) leading to research triangulation (Denzin 1989). Additionally 29 semi-structured interviews were conducted with the CLL’s representatives to collect missing data and to verify the results (membercheck) (Hannes, 2011). The coordinators of the CLL’s were contacted by email. They invited other representatives for the interview through mail, telephone or personal contact. Mostly there were two researchers to perform the interview. One researcher led the interview, while the other took notes. Interviews were recorded digitally (45-150 minutes). The interview locations were chosen by the CLL coordinators. The same method for analysis as in the documents was used for the interviews. Additional insights from the interviews were integrated into the results. 2.2 Action research coaching session The action research was presented to the CLL as a coaching trajectory. It started in 2013 with a half day workshop where all representatives of the CLL were invited. At least the panel manager and the CLL’s coordinator was expected. The four CLL’s which were active at that time were represented. During this workshop presentations and Q&A was given on the background knowledge of iMinds on good practices (see Panel-Based approach). When two additional CLL’s joined the CLL, an information meeting was kept for them communicating the information of the workshop. Based on the information of the workshop each CLL received the opportunity to upgrade their plan to recruit participants for one of their first projects. A three hour coaching session with the coordinator and panel manager took place with two iMinds coaches, one with experience in panel management and one with experience in user research on digital tools for older adult care. This two-way process learned the starting CLL’s how to make the advice operational for their own situation, and the iMinds coaches gained insight in the specificities of panel management in the domain of older adult care. 3 Results These two methods showed different lenses on the CLL case. First, insights from the plan evaluation will be discussed, subsequently those of the action research approach.


3.1 The initial plans of the six platforms LiCalab, AzoB and CareVille wanted to set up a stratified panel in line with the demographical composition of their regions (using age, sex, nationality and social economic status as variables). Only three CLL’s (LiCalab, AIPA and CareVille) described the plan to include informal caregivers in their panel. AzoB and Online Buurten stated that they wanted to include informal caregivers during the interview. InnovAGE did not plan to include informal caregivers, but uses an organization of informal caregivers as representative for the actual informal caregivers. Only few CLL’s set a goal for the size of their panel. AzoB wanted two samples from the inhabitants of two different districts in two different urban regions. Each sample had to consist of 200 older adults. AIPA aimed at a broad and representative test population of at least 1000 older adults and professional caregivers in homecare services. The participants will all be inhabitants from semiurban and rural regions. CareVille wanted to include 250 informal caregivers in their panel. InnovAGE stated that they have access to 8800 65+ vulnerable older adults from an urban region. However they did not write explicitly the intention to include them all in their panel. All CLL’s described inclusion criteria to recruit older adults. Only three CLL (LiCalab, AIPA and CareVille) described inclusion criteria for informal caregivers. Five CLL will include both healthy and dependent older adults. One CLL (InnovAGE) will only include frail older adults with a complex care situation. CareVille will include older adults with acute and chronical care requirements. AIPA, AZOB, LiCalab and Online Buurten described broader criteria which are not related to pathologies or care requirements. Criteria for ages varied between al CLL. All inclusion criteria are enlisted in table 2. CLL AIPA LiCalab



Inclusion criteria Every type of older adult, 50-55+, living at home, 20% socially vulnerable 20% 50-60, 50% 60-70, 20% 70-80, 10% 80+; 40%-45% light care requirements, 30% in need for chronical care, 15-20% high care requirements, 10-15% immigrants living at home, healthy older adults 65+ older adults, with acute or chronical care requirements, older adults from different cultures, living at home and in residential settings, attention for deprivation Fragile older adults with complex care requirements, 60+, living at home , a service flat or in residential setting, attention for socio-economical profile



65+, living at home or in a service flat, attention for socio economic status and origin Wide focus, 65+, healthy older adults, living at home, social vulnerable older adults

Online Buurten

Table 2 Initial inclusion criteria for older adults of the CLL based on a plan evaluation

The CLL’s planned to recruit older adults through various channels such as senior organisations, social housing companies, city councils or municipalities, several aid and care actors (like hospitals, nursing homes, public centre for social welfare, ...) media, personal contact, actions on events, fairs and campaigns. Table 3 provides an overview of the recruiting channels from the CLL. AIPA LiCalab CareVille InnovAGE AzoB Online Buurten Senior organisation





Social housing X company City council or x municipality




Aid and care x actors








Personal contact




Actions on social events


Actions on fairs and campaigns




x x

Table 3 Initial recruiting channels from the CLL based on a plan evaluation

Methods to capture the wishes and needs of the older adults and informal caregivers varied. Most CLL planned to use a combination of online surveys, focus groups, interviews, written surveys, brainstorming, user testing. AIPA only mentioned the use of focus groups. Plans to recruit voluntary caregivers and professional caregivers were not found in the initial documents of the CLL. However it is possible the CLL had such plans as the researcher did not check this during the interviews.


3.2 The adapted approach of the six platforms Due to the heterogeneous group of older adults and the need of involving multiple actors a more systematic approach was needed without dropping the seven steps (see table 1) within the CLL case. Because both living labs and projects were starting up at the same time, the first two steps needed a lot of attention. Step 1 Define the purpose of the panel: start with mapping multiple actors in the projects Within the first step “Defining the purpose of the panel” an extensive analysis of the living lab panel was performed, based on the findings that all CLL defined their panel too closed and focused on older adults, forgetting all other involved panel members needed within a multiple actors panel. To help them make this analysis we mapped together their users on a diagram with concentric circles with the primary user in the middle (figure 1). For example in one project the medication process of 50 residents in a nursing home will be studied and adapted. This implies not only that 50 residents need to be included, but also at least their family and professional caregivers. They are involved to give valuable feedback and are gatekeepers for access to the residents. In addition, organisations giving access to care professionals or family should not be forgotten, to provide access and give feedback. In every coaching session each CLL was made aware of the need to map the actors, to include and create a panel plan for every project.

Figure 1 Example of mapping multiple actors for a project to be supported by a CLL

Step 2 Recruit users: keeping a systematic overview with a panel matrix


The heterogeneity within and between projects made it necessary to develop another tool to support the panel manager in knowing when to recruit who for what. In figure 2 an example is provided of the basic format for the same project example about the medication process and adaptation. The matrix has to be used in two steps. First there must be identified which panel members are required during which activity in each project phase by ticking to right boxes in the matrix. Next, the number of people with that profile to be recruited need to be filled in those ticked boxes. Doing this exercise for all projects helped the CLL’s to determinate their communication and recruitment strategy. If vulnerable inhabitants in nursing homes are needed in the first project activity, there is less need to do a large communication campaign to recruit active older adults. This implies also that the organisational plan of the helpdesk becomes more clear and a financial plan on the budget for all panel activities can be made. It also reveals which type and how many of the needed panel members are not reached yet. For example it is classic that people of different origin and weaker socioeconomic status are less likely to be reached with classical city communication. Other activities are then planned, like house calls for example. The matrix is of course a living document, to be updated over time. The nearby activities need to be more detailed, than the ones planed in the further future. It is essential to determine the success parameters for these nearby activities up front. These parameters can also be used during the evaluation. The matrix can also be used to check if a new project request fits with the current profile of the CLL panel.

Figure 2 Support and interact with the panel: use of a SPOC and feedback is a two-way street

Step 3 Support and interact with the panel: use of a SPOC and feedback is a twoway street


In the CLL’s plans the importance of the function of a panel manager as a fulltime job offering a centralised approach, with a known and trusted person for the panel (SPOC), was often underestimated. The workshop introduction, the coaching and the day-to-day experience of panel management made that CLL’s without this function decided that they need it and had to find budget for it. The background of people performing this function (e.g. knowledge institute, care organisation, city) is divers, and not every CLL was able to create one full time position. AIPA for example tackles this challenge by involving a call centre, which is a partner in the CLL, to monitor and triage the questions and to provide first line information on planned activities. Every platform was suggested to create a helpdesk structure. Also the creation of material to make participation as easy as possible, as well as ways to communicate feedback and results about the activities are essential ingredients. In the start-up phase the material was created to inform people about the projects on websites, leaflets, during information sessions on a broader topic, … These activities are closely related to the next step. Step 4 Live the lab: keep your panel involved This step targets long term involvement over different activities supporting different projects. Crucial advice at the start was to change the plans of bulk recruitment at the start, which some CLL’s had. Making use of the panel matrix helped to alter these plans. Creating a brand for the CLL, overarching the different projects was another tip, to enable to group identification leading to commitment and norms of reciprocity as described in the ‘Tailored management approach’ (e.g. figure 3). Platforms developed a logo and a website as a starting point, but differ in communication to present the CLL to stakeholders as well as older adults. Herefore folders, videos and events were used. At the start it was difficult to communicate both the goal of the CLL and the project in one message. This resulted in miscommunication on the expectations to the participants. Most opted for a double strategy communicating in general about the CLL and specific about the projects to the people involved, informing them on the fact that this is part of a larger initiative. The heterogeneous group of older adults makes it not possible to take the use of internet and social media for granted. Although some platforms like Online Buurten, Licalab, AzoB and CareVille plan to use digital tools to communicate with their panel members, which is a project endeavour in itself, but opens up opportunities for the future tailored communication.


Figure 3 Example of visual and branding of a CLL (Careville)

Step 5 handle privacy: beyond privacy when discussing care related subjects In every living lab handling the personal information of participants carefully is the key to build a trust relationship. It is important to offer information about the reason to collect information, the person who can see and use it and the purpose it is required for. The panel manager was suggested to be the key person to both inform and decide what the need to know basis of information is of every request made. Understandable informed consents for all participants, information sharing agreements with partners accessing this data are essential, as well as filling the platform activities with the Belgian privacy commission. Some care institutions, as gatekeepers, demanded extra precaution with their clients. The caregiver was then the contact person for the panel, serving as a trusted person, collecting the data for the project, without personal information. All subsequent contacts in the panel with this client have to go through the trusted caregiver. This request implied adaptations in the initial panel management approach of this CLL. In Before the coaching sessions and workshop on panel management took place, a dedicated workshop on privacy and the need for an ethical committee was organised. In every project in this domain one needs to reflect on the need to file for an approval of a medical ethics committee. Not every project innovating in the domain of care is required to do that, but it is an additional point of attention. Step 6 reward users: recognition and fun more important than payment In all living lab projects, and also the CLL projects the experience is that feedback is more important than presents or payment (e.g. Logghe et al., 2014). Today the first results and practical examples of the activities that can help to motivate current members as well as recruit new participants for future activities become visible (e.g.


co-creation movie https://youtu.be/88IhYOAeriY). Providing a museum visit with a field test was an approach AIPA planned. Licalab organised two days to hear and celebrate their panel members. Three hundred and fifty people took part and 106 questions and suggestions were made. The event was celebrated on different media channels (twitter, their website and the local radio station). Step 7 Maintain the eco-system: working with older adults, needs more follow up and attention to exit strategies To let the panel grow over time, the advice is to create an environment where it is easy for current members to suggest new members, to pamper panel ambassadors, give people a central place where information about several projects can be shared (e.g. a website, a newsletter, …). It is important to realize that people can also leave the panel. Understanding why they do not wish to participate further in the CLL is crucial. Older adults can experience a lot of life changing events (e.g. illness, increased dependencies, loss of loved ones). These life events may change their commitment to the community, or may lead to the perception that activities are not appropriate for their condition. CLL should look for adaptations in the format of the activity to improve the participation of frailer older adults. Another confronting lesson learned early in the creation of the panel is that panel members pass away. Specific attention should be paid to communicate in the right way to relatives. 4 Conclusion The plan evaluation revealed different plans to form a representative panel of older adults. However few CLL’s had a strategy to include informal and professional caregivers. Nevertheless the innovations developed in the CLL's will also affect them. Thus, it important to define the target population clearly before the start of the recruitment and to set inclusion and exclusion criteria from the beginning. Most CLL planned a personalized approach for the recruitment, which proved to be successful in earlier research (McHenry et al., 2012; Wilding et al., 2013). Few CLL's had thought about a way to engage the end-users to their panel. The seven step approach used in other domains of panel-based living labs is a valuable guideline for the creation of a panel-based living lab in the domain of innovation in older adult care. Because of the multiple actors a more systematic approach with the concentric circles and a panel matrix was designed, showing the assets and needs while growing as a panel over different projects. The essential function of a panel manager was reaffirmed. Extra attention within this domain should be paid to the existing care relations between care organisations and their clients, the need for filing of the project to the medical ethics committee and the delicate follow up of exit of panel members.


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