Journal of Scholastic Inquiry Business,Volume 5, Issue 1, Fall 2015 by Center for Scholastic Inquiry

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TABLE OF CONTENTS

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Research Manuscripts

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When Consumer Participation is Not Enough: A Classification of Compliance Dependent Services

Lez Trujillo Torres (student), University of Illinois at Chicago Mark J. Hager, Menlo College at Atherton Frances Turner, Menlo College at Atherton Stephanie Dellande, Menlo College at Atherton Latent Variables that Measure Customer Satisfaction

Thomas J. Gogue, Auburn University Marie Kraska, Auburn University Elisha Wohleb, Auburn University Accounting for Intangibles: Does Method of Accounting Matter?

Van Brooks Poole, Mississippi College The Attractiveness of Regions as Sites for Global Value Chain Activities: The Impact of Formal Institutions

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When Consumer Participation is Not Enough: A Classification of Compliance Dependent Services Lez Trujillo Torres (student) University of Illinois at Chicago Mark J. Hager Menlo College at Atherton Frances Turner Menlo College at Atherton Stephanie Dellande Menlo College at Atherton

Abstract This paper presents the results of a pilot study supporting a classification of an important category of services, compliance dependent services (CDS). The results indicate that the perceived consequences of non-compliance by consumers are positively associated with their intent to comply with their role in CDS. Further, the type of CDS moderates the relationship between perceived consequences of non-compliance and intent of compliance. These findings expand the services marketing literature, in regard to CDS, where consumer participation and compliance are both necessary to achieve a successful service outcome. Keywords: consumer participation, consumer compliance behavior

Introduction The consumer has an important role in the service delivery process (Bitner, Faranda, Hubbert, & Zeithaml, 1997; Ostrom et al., 2010; Spanjol et al., 2015). A consumer who wants to lose weight by enrolling in a weight loss program still needs to carry out recommended activities when away from the provider (e.g., use the nutritional label on packages, weigh in daily, measure food portions, eat the recommended types of food, eat the recommended portions of food). Consequently, for better or worse, the consumer has the potential to directly impact the service

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delivery process and outcome. Because of this crucial role, several researchers suggest that customers, who provide resources to the service organization in the form of information or effort, be viewed as “temporary” or "partial employees" of service organizations (see Bowen, 1986; Kelley, Donnelly, & Skinner, 1990; Lovelock & Young, 1979; Mills, Chase, & Margulies 1983). In particular, Kelley et al. (1990) considers employees of a service organization as “internal customers” and consumers of those services as “external employees” of the organization. Yet, the extant literature in services marketing has primarily conceptualized the service delivery process in terms of customer participation as a face-to-face exchange between the service provider and the consumer (Chase, 1978; Lovelock, 1983). As an example, a consumer who wants to lose weight by enrolling in a gym must still do other activities outside the gym in order to meet his or her goal, such as get workout shoes or clothes, exercise between training sessions with a personal training, eat better at home, eat at a restaurant less often, etc. Thus, examining the role of the consumer after the face-to-face exchange between the service provider and the consumer is equally important. The purpose of this paper is to expand the literature in consumer participation and consumer compliance behavior by examining compliance dependent services (CDS) by way of a pilot study. This paper extends the work by Dellande and Gilly (1998) which identified CDS as a distinct type of services (e.g., debt management program, diabetes care, exercise programs, marriage counseling, physical therapy, etc.). Such services typically entail service delivery processes that are of a longer duration, in which the consumer participates in the creation of the service during the provider-consumer face-to-face exchange, and where the consumer must comply with his or her role once away from the provider to ensure positive outcome and satisfaction.

Literature Review

Consumer Participation in Services In services the consumer is, usually, present as the service is created. In contrast, the consumer is rarely, if ever, present in the manufacturing of goods (Bowen, 1986). It is essential

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to understand that the consumer is not only present during the service delivery process, but can impact the outcome. For instance, a patient who conscientiously takes his or her prescribed medication contributes significantly to the improvement of his or her condition. Therefore, it is important that service providers attempt to influence the consumer’s behavior, particularly since the consumer’s involvement in services, in essence, "replaces the work done by the employees of the firm with work done by the consumers" (Bateson, 1989, p. 146). , In that the consumer becomes a temporary employee in the service delivery process of the organization (Kelley et al., 1990). Consumer participation, therefore, is a key identifying characteristic of services (Bowen, 1986) during the face-to-face exchange. Consumer participation has been defined as the consumer’s role in the service delivery process in which the consumer and provider co-produce or co-create the service during the face-to-face exchange (e.g., Humphreys & Grayson, 2008; Ostrom et al., 2010; Prahalad & Ramaswamy, 2004; Spanjol et al., 2015; Lusch & Vargo, 2006). During the co-creation of these services, the consumer contributes information and/or effort. Examples of services in which consumer participation is sufficient are restaurants, in which restaurant patrons’ inform the service provider on how to prepare the meal, or in hair salons where clients’ tell the hair stylists on how to style his or her hair. Furthermore, research on consumer participation has focused primarily on the consumer’s participatory role in service creation during the face-to-face service exchange (Bateson, 1989; Bowen, 1986; Chase, 1978; Kelley et al., 1990; Lovelock & Young, 1979; Mills et al., 1983). For instance, Chase (1978) finds that the degree of consumer participation necessary for a successful outcome is based on the proportion of contact (low, moderate, or high) between the provider and consumer in a service encounter. The literature in consumer participation in services marketing was expanded when Dellande and Gilly (1998) introduced CDS. This study highlights that the existing conceptualization of participation is insufficient for understanding another key consumer role in the service delivery process: consumer compliance. CDS are distinct because they require consumer participation when the consumer is within the service facility and the need of consumer compliance once the consumer is away from the provider.

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Compliance Behavior in Services As previously noted, consumer participation by itself is not enough in the service delivery process in which both consumer participation and consumer compliance are required. Kelman (1961) defines compliance accordingly, Compliance can be said to occur when an individual accepts influence from another person or from a group because he hopes to achieve a favorable reaction from the other. He may be interested in attaining certain specific rewards or in avoiding certain specific punishments that the influencing agent controls. (p. 62) However, while the influencing agent (e.g., doctor or nurse in the health care service context) controls rewards and punishments, such as approval or disapproval, not all of the control is under the agent's influence in CDS. In fact, in weight loss services the compliant individual or consumer has control over what he or she eats and, ultimately, on his or her actual weight outcome. Consumer compliance is critical in a variety of contexts (Guo, Arnould, Gruen, & Tang, 2013; Ostrom et al., 2010). Dellande and Gilly (1998) note that, Vital in CDS is consumer compliance, e.g., in healthcare where patients must comply with doctors’ orders to become well; dieters must comply with nutritionists’ food regimens to lose weight; clients must comply with tax preparers’ instructions to save and organize receipts to minimize tax liability. (p. 2) Similarly, clients must adhere to the auto mechanics recommendation to routinely have basic services done, and patients who have undergone surgery must adhere to postoperative exercises to facilitate recovery (Bowen 1986). Scholars have recognized that consumer compliance is more complicated than simply being required or not required. It can be more or less required at various stages of the service delivery process. Bowen (1986) noted that consumers must often perform (i.e. carry out) certain functions (e.g., gather tax documents) before entering the service firm, as well as after leaving. Additionally, Spanjol et al. (2015) found that consumer adherence behaviors to prolonged and complex health problems, such as cardiovascular diseases, can be determined by the unique circumstances of the customer sphere, specifically the scope (from narrow to wide) and temporal

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aspect (daily to yearly) of the medication adherence. The breath of CDS can be observed in Appendix A where a list of CDS examples is provided. Thus, in CDS, just as in consumer participation, consumer compliance is a key identifying characteristic of the service delivery process; and a crucial one because the consumers are required to perform for themselves and the company to achieve a successful outcome (Bowen 1986). Consequently, consumer compliance performance must be assessed and examined in marketing services research and is useful in the decision making process of providers of CDS. Further, understanding CDS may be useful to other interested parties beyond practitioners (e.g., academics, policy makers, even consumers). To that end, this paper provides a summary of current CDS research and extends that research by presenting a new, expanded classification of CDS.

Compliance Dependent Services Literature Albeit scant, research has been done in the domain of consumer compliance behavior in CDS, e.g., the identification of CDS (Dellande & Gilly, 1998); gaining consumer compliance, (Dellande, Gilly, & Graham, 2004); roles of and communication between the consumer and service provider (Dellande & Taylor, 2004); intrinsic and extrinsic motivators like consumersâ&#x20AC;&#x2122; self-regulatory focus and public commitment (Nyer & Dellande, 2008). Yet, this is a small fraction of the well-established literature on consumer participation. While consumer participation in the delivery of most services is essential to the service delivery process, consumer participation does not consider the consumer's role once away from the provider, a necessary condition of CDS. Figures 1 (and 2 offer greater insight into consumer participation and compliance in services. Specifically, Figure 1, Classification of Consumer Participation in Services, reflects the identification of CDS (Dellande & Gilly, 1998, p.274); while Figure 2, Compliance Dependent Services Model, offers a model of the participation and compliance process (Dellande & Gilly, 1998, p.280). Figure 1 shows a classification scheme which refines previous conceptualizations of consumer participation in services. The matrix indicates that the service delivery process is

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based on whether the nature of consumer participation required is either active or passive, and whether the performance required occurs within or outside of the service firm. The services marketing literature has focused primarily on consumer participation within the service firm (cells 1 and 2), particularly active consumer participation in cell 1. On the other hand, the service marketing literature has not invested much effort on the consumer’s role once outside of the service organization (cells 3 and 4), especially services in cell 3. The terminologies, in Figure 1, “inside factory” and “outside factory,” are based on early literature in services marketing (Bateson, 1989; Bowen, 1986; Chase, 1978; Kelley et al., 1990; Lovelock & Young, 1979; Mills et al., 1983) in which the service delivery process was modeled after the manufacturing of goods. Addressing the service delivery process in this way was a norm until approximately the late 1990s. In Figure 2, service creation for compliance dependent services (CDS) is a two-fold process (Dellande & Gilly, 1998) entailing consumer participation (which occurs while the consumer is within the service firm) and consumer compliance (which occurs once the consumer is away from the service provider). In CDS, the client creates a major portion of the service on his or her own, that is, outside of the supervision of the service provider. The provider may offer the consumer directives on how to perform the service; however, the consumer operates independently in his or her adherence to the directions given by the provider, ultimately impacting service outcomes (Dellande & Nyer, 2013). The model of compliance dependent services, in Figure 2, highlights the ways in which source characteristics influence the acquisition of consumer target attributes necessary for consumer cooperation and the desired outcome in the service delivery process. For the consumer to take part in the service delivery process, the service provider must possess the characteristics expertise and homophily (the tendency people have to connect based on their similarity) with the consumer. In which case, the provider will influence the consumers’ acquisition of the attributes ability, role clarity, and motivation. These variables are necessary for the consumer to perform as expected. Upon participation in the service delivery process and compliance with his or her service delivery role, the model suggests two outcomes. Participation will lead to compliance and satisfaction with the service. Compliance will lead to goal attainment. Consumer goal

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attainment is likely to lead to consumer satisfaction with the outcome of the service delivery process.

A New Classification of Compliance Dependent Services (CDS) As mentioned earlier, the literature relating to compliance dependent services (CDS) is scarce (Nyer & Dellande, 2010), specifically regarding how the consumer needs to participate in the service delivery process during the personal interaction with the provider and then to independently continue to do so over a period of time (Bowen, 1986). This is problematic because failure to comply with the initiation or maintenance of a prescribed regimen is one of today's major unsolved health problems and is beginning to be acknowledged as the most prominent reason for failed therapy (Buckalew, 1991). Petty and Cacioppo (1996) suggest that most of the leading causes of death in the United States, could be greatly reduced if people changed the following risk behaviors – drug abuse, excessive alcohol consumption, lack of an exercise regimen, poor diets, and tobacco use. These behaviors are linked with a lack of compliance with healthful behaviors (Petty & Cacioppo, 1996). Yet, research has not connected all these seemingly different types of CDS into one comprehensive framework that examines compliance in the service delivery process. In addition, research has not addressed the likely outcome of consumer non-compliance with the provider’s directives. Even if non-compliance in certain CDS does not lead to detrimental or ruinous outcomes, it is at least likely to lead to undesirable outcomes. For example, failing to comply with the terms of a loan is likely to lead to consequential (poor) outcomes. As a case in point, nonpayment of a consumer loan can place the consumer further in debt (Li, Mumford, & Tobias, 2012) and lead the consumer into bankruptcy (Skiba & Tobacman, 2009). Thus a classification of CDS is needed given the likely variation in types of CDS. Such a classification system needs to consider both the potential for consequential (poor) or detrimental (ruinous) outcomes when the required regimen is not followed, and the vital role consumers’ play in the service delivery process. Figure 3, “A Classification of CDS,” demonstrates the level of compliance needed (low or high) and the potential outcome of non-compliance (consequential

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or detrimental). For example, in certain CDS, such as education, the level of compliance required when the consumer is away from the provider is high, and not adhering to the requirements will mostly likely lead to consequential outcomes. On the other hand, in other types of CDS, such as tax preparation services, the level of compliance required when the consumer is away from the provider is low, and not adhering to the CDS requirements will most likely lead to detrimental outcomes. The new classification of CDS in Figure 3 entails four cells (low compliance /consequential outcomes, low compliance/detrimental outcomes, high compliance/consequential outcomes, high compliance/detrimental outcomes). Based on this classification, we generated the following pilot study hypotheses: Hypothesis 1: Perceived consequences of non-compliance are positively associated with intent of compliance. Hypothesis 2: The type of Compliance-Dependent Service (CDS) will moderate the relationship between perceived consequences of non-compliance and intent of compliance (see Figure 4, Hypothesized Model).

Methods

Sample To test our hypotheses, we conducted a quantitative pilot study by creating an online survey (see Appendix B) that included two CDS types: auto maintenance (low compliance/consequential outcomes) and tax preparation services (high compliance/detrimental outcomes). Conducting a pilot study at this stage is crucial, because it provides valuable insights (van Teijlingen & Hundley, 2001) for our final framework. The sample was collected through snowball sampling from the researchers networks (N= 91). Respondents were not given monetary incentive to participate and were told that the researchers were attempting to understand adherence to provider directives, and their participation will likely help consumers understand when and why it is beneficial to follow certain provider guidelines. The study sample was 56 (61%) female, 31 (35%) males, and 4 (4%) people who preferred not to disclose

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their gender. Respondents ranged from 18 to 65 years of age, with 53 (53.2%) of all respondents under the age of 34. In addition, 45.7% of respondents were Non-Hispanic Whites, 21.7% were Hispanic/Latino, 15.2% were African American, 9.8% were Asian, and 7.6% selected “other” ethnicity. The majority of respondents (57%) were single never married. Of the 91 respondents, 50 (55.4%) respondents possessed at least a Bachelor’s degree, while 31 (33.7%) of them possessed some college experience or an Associate Degree, and 10 (10.9%) had a high school diploma or some high school. Regarding their employment status, 55 (60.8%) respondents were employed for wages, 28 (30.4%) were students, 3 (3.3%) were self-employed, 3 (3.3%) were retired, 1 (1.1%) was in the military, and only 1 (1.1%) was out of work or looking for work.

Measures Respondents reported responses to questions about auto maintenance and tax preparation compliance and their perceptions of the consequences of noncompliance. The constructs were measured using a 10-point Likert-type scale from 1 (low level) to 10 (high level). Respondents also provided demographic information. To measure intent of compliance with car maintenance directives we created a one-item measurement scale. The item stated, “To successfully maintain a car, to what extent do you need to comply with your mechanic’s or auto shop’s directives on car maintenance.” Three subject matter experts review the question and agree on external validity. Perceived consequences of non-compliance with car maintenance directives was measured using a one-item measurement scale. The item stated, “What is the likely impact of non-compliance with your mechanic’s or auto shop’s directives related to car maintenance?” Three subject matter experts review the question and agree on external validity. To measure Intent of compliance with tax preparation directives, we created a one-item measurement scale. The item stated, “To successfully file your income taxes, to what extent do you need to comply with the tax preparer’s directives?” Three subject matter experts review the question and agree on external validity. Perceived consequences of non-compliance with tax preparation directives was measured with a one-item measurement scale. The item stated, “In your opinion, what is the likely impact

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of non-compliance with the tax preparer’s directives?” Three subject matter experts review the question and agree on external validity. We controlled for variables, such as age, education level, gender, income, and marital status, which may have influenced respondents’ answers.

Results Correlations and descriptive statistics are provided in Table 1, Scale Means, Standard Deviations, and Correlations. To test the relationships between the variables and level of significance, we used a combination of correlation analyses and bootstrapping (Edwards & Lambert, 2007). Bootstrap samples were created by drawing 1000 random samples with replacement from the full sample and constructing a bias-corrected confidence interval (95%). The results indicate that Perceived Consequences of Non-Compliance with Car Maintenance (M = 5.60, SD = 2.09) is positively correlated to Intent of Compliance with Car Maintenance (M = 6.92, SD = 2.14, r = 0.528, p < 0.01). Similarly, the Perceived Consequences of Non-Compliance with Tax Preparation (M = 6.90, SD = 2.60) was found to be positively correlated with Intent of Compliance with Tax Preparation (M = 7.94, SD = 2.74, r = 0.748, p < 0.01). These results support Hypothesis 1 in that respondents associate the perceived consequences of non-compliance as positively associated with intent of compliance, which is not very remarkable in itself. What is surprising is consumers’ intentions of noncompliance even in light of consequential and/or detrimental CDS outcomes. Furthermore, we can see that the type of CDS moderates the strength of the relationship between perceived consequences of non-compliance and intent of compliance. The strength of the relationship between Perceived Consequences of Non-Compliance and Intent of Compliance is higher for Tax Preparation (r = 0.748, p < 0.01) than Car Maintenance (r = 0.528, p < 0.01). This indicates that respondents are able to differentiate between two distinct CDS types, with Tax Preparation being perceived as needing a higher level of compliance and having more detrimental impact; thus providing support for Hypothesis 2.

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Discussion In CDS, there are benefits of compliance. For example, when a consumer complies with his or her role in the service delivery process of CDS, he or she will be more likely to attain the desired outcome (Dellande et al., 2004; Dellande & Nyer, 2013; Nyer & Dellande, 2010; White, Taylor, & Dellande, 2003). As Dellande et al. (2004) demonstrate, compliance leads to goal attainment resulting in consumer satisfaction. However, from Figure 3, we can see that when consumers are noncompliant in the services in cells 1 and 2, the outcome is likely consequential. That is, noncompliance may lead to an undesirable outcome, e.g., a poor performing automobile. When consumers are noncompliant in the services in cells 3 and 4 the outcome will likely be detrimental, i.e. cause irreversible damage, or be ruinous, e.g., a jail sentence for tax evasion. The results of the pilot study indicate that consumers associate the consequences of noncompliance with their intent of compliance. In addition, the type of CDS (i.e. car maintenance, tax preparation) moderates this relationship. These findings suggest there are different types of CDS (as indicated in Figure 3), both in terms of level of compliance and potential outcomes. Future research is needed to investigate CDS across different categories and examine their similarities and differences. Such research is important given that future findings can help service providers facilitate and influence compliance during and after their interaction with consumers. Research in this area is especially important because when consumers are noncompliant they are unlikely to achieve their desired outcomes. Noncompliance may negatively impact consumers in a number of ways. For example, failure to comply with auto maintenance directives can result in a broken car that interrupts a consumer’s daily life (e.g., missed work time), or creates a financial burden with expensive car repairs. Likewise, failure to comply with tax providers’ guidance is also likely to have detrimental financial and legal consequences. Further, economic and social implications are likely in other types of CDS, such as payday loans. Noncompliance with payday loans, which on average are $300, can place the consumer deeper in debt. These loans carry annual percentage rates in excess of 400% (Li et al., 2012), possibly, leading consumers into bankruptcy (Skiba & Tobacman, 2009). Additionally, there are social

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implications with these loans, e.g., the social stigma attached to certain types of loans. As such, borrowers may feel a sense of shame (Elliehausen & Lawrence, 2001). Thus, subsequent studies will need to look closely at the ramifications, e.g., financial or economic, legal, social, even health, of non-compliance in CDS. Because of the important role of consumers in the service delivery process of CDS, it is vital that providers understand ways in which to influence or gain consumer compliance (Dellande et al., 2004). Future research is needed to determine when different role protocols are warranted for their consumers both in terms of participation and compliance. Customized protocols may contribute to increasing consumer role adherence, essential to consistently bringing about successful outcomes. For example, suppose a physical fitness personal trainer had two clients who were extremely different as it relates to their body mass index (BMI). Supposed one has a BMI in the range considered healthy (18.5 - 25.0 kg/m2), the other in the range considered obese (30.0 – 35.0 kg/m2). The physical fitness trainer may need to develop a protocol best suited for each of his clients. From this new classification and pilot study, the recommendation to different providers of CDS is to make certain that their consumers understand the ramifications of noncompliance with the service delivery process. This requires that the provider be mindful of the consumer’s particular situation. Which, likely, will entail customization of the consumer’s role around his or her level of resources. For example, if a health care consumer (patient, in this case) is unable to afford a prescription, to the extent possible, the health care provider can consider an alternative prescription consistent with the patient’s financial means. This recommendation is especially important in CDS with dire consequences when the consumer is non-compliant. Also recommended is that CDS providers make a concerted effort to keep in touch with their consumer; for example, a patient when he or she is away from the health care provider. Doing so is likely to improve compliance with the protocol directives. Another context in which this recommendation is prudent (the provider keeping in contact with the consumer), is in debt management programs. Previous literature has conceptualized consumer participation in the service delivery process in terms of the level of contact between the service provider and consumer as either low, moderate, or high. As this study shows, consumer participation is an important aspect of the

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service delivery process during the face-to-face exchange, but when dealing with CDS, what transpires outside the provider’s sight is perhaps of greater importance to service quality outcome. That is, the impact that the internal process (participation) has on the external process (compliance) may matter most in CDS. As such, this study emphasizes that in CDS, consumer participation is not enough. Author Biographies Lez Trujillo Torres is a doctoral student in Marketing at the University of Illinois at Chicago. Building on her previous work experience, Ms. Trujillo Torres’ research interests relate to value construction and attainment, inequality in the marketplace, pro-social behavior, consumer welfare, and the intersection of marketing and public policy. She received her B.A. in Molecular and Cellular Biology with a concentration in Neurobiology from the University of California, Berkeley and her MBA from the University of Illinois at Chicago. Mark J. Hager is an Associate Professor of Psychology at Menlo College in Atherton, CA. Dr. Hager studies social-psychological influences on faculty teaching and student learning, and future research includes the application of compliance theory to the long term commitment necessary to persist in graduate education. Dr. Hager is a frequent speaker and consultant at national and international venues, including the US Department of Veterans’ Affairs; University of New Mexico Mentoring Institute; the American Educational Research Association; the International Congress of Psychology (Berlin); and the UK Council for Graduate Education. Frances Turner, DBA, is Assistant Professor of Marketing at Menlo College in Atherton, CA. Professional experience in telecommunications, entrepreneurial and non-profit sectors inspire Dr. Turner's research in consumer experience, co-design in mass customization, customer-centricity, relationships between consumer perceived value, satisfaction and loyalty, individual thinking style, and neuromarketing from the consumer’s perspective.

She has

published in Business Leadership Review and Journal of Service Science and presented her research at several international conferences including the World Conference on Mass Customization,

Personalization

and

Co-Creation

(MCPC),

Association

NeuroPsychoEconomics, UK Council for Graduate Education and Association of MBAs.

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Stephanie Dellande, Associate Professor of Marketing, is on the faculty at Menlo College in Atherton, CA (94027) (in Silicon Valley). Dr. Dellande identified and studies a group of services known as compliance dependent services (CDS). Her future research plans are to examine CDS across various socio-economic levels, develop a compliance scale, empirically determine the various categories of CDS, and identify the theory of compliance in CDS. Dr. Dellande has published in top tier academic marketing journals, e.g., the Journal of Marketing (JM), Journal of Retailing (JR), Psychology & Marketing (P&M), and presented her work at national and international conferences. References Andreasen, A. R. (1983). Consumer research in the service sector. In L. Berry, G. L. Shostack, & G. D. Upah (Eds.), Emerging perspectives on Services Marketing (pp. 63-64). Chicago, IL: American Marketing Association. Bateson, J. E. G. (1989). Managing Services Marketing. Chicago, IL: The Dryden Press.

Bowen, D. (1986). Managing customers as human resources in service organizations. Human Resources Management, 25(3), 371-383. doi: 10.1002/hrm.3930250304 Bitner, M. J., Faranda, W. F. T., Hubbert, A. R., & Zeithaml, V. A. (1997). Customer contributions and roles in service delivery. International Journal of Service Industry Management, 8(3), 193-205. BUCKALEW, L. W. (1991). PATIENTS' COMPLIANCE: THE PROBLEM AND DIRECTIONS FOR PSYCHOLOGICAL RESEARCH. PSYCHOLOGICAL REPORTS, 68(1), 348-350. DOI: 10.2466/PR0.1991.68.1.348 Burnier, M. (2006). Medication adherence and persistence as the cornerstone of effective antihypertensive therapy. American Journal of Hypertension, 19(11), 1190-1196. Chase, R. B. (1978). Where does the consumer fit in a service operation? Harvard Business Review, (November-December), 137-142. Cramer, J. A., Roy, A., Burrell, A., Fairchild, C., Fuldeore, M. J., Ollendorf, D. A., & Wong, P. K. (2008). Medication compliance and persistence: Terminology and definitions. Value in Health, 11(1), 44-47.

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Dellande, S., & Gilly, M. C. (1998). Gaining consumer compliance in services. Advances in Services Marketing and Management, 7, 265–92. Dellande, S., Gilly, M. C., & Graham J. L. (2004). Gaining compliance and losing weight: The role of the service provider in health care services. Journal of Marketing, 68(3), 78-91. Dellande, S., & Nyer, P. (2013). Self-regulatory focus: The impact on long-term consumer compliance behavior. Management Research Review, 36(7), 664-673. Dellande S. & Taylor, G. (2004), The role of written provider communication in external client participation. Health Marketing Quarterly, July. Edwards, J. R., & Lambert, L. S. (2007). Methods for integrating moderation and mediation: a general analytical framework using moderated path analysis. Psychological methods, 12(1), 1. Elliehausen, G., & Lawrence, E. C. (2001). Payday advance credit in America: An analysis of customer demand [Monograph]. Credit Research Center, 35, 39-40. Gearing, R. E., Townsend, L., MacKenzie, M., & Charach, A. (2011). Reconceptualizing medication adherence: Six phases of dynamic adherence. Harvard Review of Psychiatry, 19(4), 177-189. Guo, L., Arnould, E. J., Gruen, T. W., & Tang, C. (2013). Socializing to coproduce pathways to consumers’ financial well-being. Journal of Service Research, 16(4), 549-563. Humphreys, A., & Grayson, K. (2008). The intersecting roles of consumer and producer: A critical perspective on co-production, co-creation and presumption. Sociology Compass, 2(3), 1-18. Kelley, S. W., Donnelly, Jr., J. H., & Skinner, S. J. (1990). Consumer participation in service production and delivery. Journal of Retailing, 66(3), 315-335. Kelman, H. C. (1961). Processes of opinion change. Public Opinion Quarterly, 25, 57-78. Li, M., Mumford, K. J., & Tobias, J. L. (2012). A Bayesian analysis of payday loans and their regulation. Journal of Econometrics, 171(2), 205-216. Lovelock, C. H. (1983). Classifying services to gain strategic marketing insights. Journal of Marketing, 47(3), 9-20. Lovelock, C. H., & Young, R. F. (1979). Look to consumers to increase productivity. Harvard Business Review, (May-June), 168-178.

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Lusch, R. F. & Vargo, S. L.(2006). Service-dominant logic: Reactions, reflections, and refinements. Marketing Theory, 6(3), 281–288.  Mills, P. K., Chase, R. B., & Margulies, N. (1983). Motivating the client/employee system as a service production strategy. Academy of Management Review, 8(2), 301-310. Nyer, P., & Dellande, S. (2010). Investigating the role of public commitment as a motivator for weight loss. Psychology & Marketing 27(1), 1-12. Ostrom, A. L., Bitner, M. J., Brown, S. W., Burkhard, K. A., Goul, M., Smith-Daniels, V., Rabinovich, E. (2010). Moving forward and making a difference: Research priorities for the science of service. Journal of Service Research, 13(1), 4-36. Petty, R. E., & Cacioppo, J. T. (1996). Addressing disturbing and disturbed consumer behavior: Is it necessary to change the way we conduct behavioral science? Journal of Marketing Research, 33(1), 1-8. Prahalad, C. K., & Ramaswamy, V. (2004). Co-creating unique value with customers. Strategy & leadership, 32(3), 4-9. Shostack, L. G. (1977). Breaking free from product marketing. Journal of Marketing, 41(2), 7380. doi: 10.2307/1250637 Skiba, P. M. & Tobacman, J. (2009). Do payday loans cause bankruptcy? Vanderbilt Law and Economics Research Paper [No. 11-13]. Spanjol, J., Cui, A. S., Nakata, C., Sharp, L. K., Crawford, S. Y., Xiao, Y., & Watson-Manheim, M. B. (2015). Co-production of prolonged, complex, and negative services an examination of medication adherence in chronically ill individuals. Journal of Service Research, 18(3), 284-302. doi: 10.1177/1094670515583824 Turner, R. J. (2005). The role of pilot studies in reducing risk on projects and programmes. International Journal of Project Management, 23(1) 1, 1–6. White, T., Taylor, G., & Dellande, S. (2003). Extrinsic and intrinsic motivators of consumer participation in compliance dependent services. International Business & Economic Research Journal, 2(11), 101-104. van Teijlingen, E., & Hundley, V. (2001). The importance of pilot studies. Journal of Advanced Nursing, 34(May), 3, 289–295.

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Table 1 Scale Means, Standard Deviations, and Correlations 1. Car Maintenance- Intent of Compliance

Mean

6.92

2.141

.528**

.425**

.320**

5.60

2.086

.528**

.023

.259*

7.64

2.743

.425**

.023

.748**

6.90

2.599

.320**

.259*

.748**

2.Car Maintenance-Perceived Non-Compliance Consequences 3. Tax Preparation- Intent of Compliance 4. Tax PreparationPerceived Non-Compliance Consequences Note. * Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed). n=91.

* Compliance Dependent Services (CDS) Figure 1. Classification of Customer Service Participation in Services (Dellande and Gilly 1998 p 274).

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Figure 2. Compliance Dependent Services Model (Dellande and Gilly 1998) p 280.

Level of Consumer Compliance Required When Away From the Provider Low High 1 2 Consequential Auto maintenance Athletics Counseling Education Dental Care Physical Therapy Exercise Programs Weight Loss Programs Potential Outcomes

Detrimental

3 Prenatal Care Tax Preparation Service

Figure 3. A Classification of Compliance Dependent Services.

4 Certain Medical Conditions Debt Management Program Smoking Cessation Substance Abuse

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Figure 4. Hypothesized Model

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Appendix A Compliance Dependent Services (CDS) Types Compliance Dependent Services (CDS) Athletics Organized sports, e.g., Basketball Auto Maintenance Certain Medical Conditions, e.g., Diabetes Counseling, e.g., Marital Psychological Debt Management Programs (DMP) Dental Care Education Exercise Programs Fitness Postoperative exercise Physical Therapy Prenatal Care Savings Programs, such as, Short-term Savings Programs, e.g., Christmas savings programs Long-term Savings Programs, e.g., Retirement savings programs Smoking Cessation Programs Substance Abuse Programs, such as, Alcohol Drug Tax Preparation Services Weight Loss Programs

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Appendix B Pilot Study Questionnaire We seek to understand adherence to services. Your input is very important. By participating in this survey, you will help us understand when and why it is beneficial for consumers to follow certain guidelines. Your responses are confidential and will only be used for research purposes. In addition, the questionnaire should only take 5-10 minutes to complete. * Required Gender: What is your gender? * o

Male

Female

Prefer not to answer o Age: What is your age? * o

18-24 years old

25-34 years old

35-44 years old

45-54 years old

55-64 years old

65 years old or older o Ethnicity: What is your ethnicity? * o

White

Hispanic or Latino

Black or African American

Native American or American Indian

Asian / Pacific Islander

Other o Marital Status: What is your marital status? * o

Single never married

Married or domestic partnership

Widowed

Divorced

Separated o Education: What is the highest education level that you have achieved? * o

Some high school, no diploma

High school graduate, diploma or the equivalent (for example: GED)

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Some college credit, no degree

Trade/technical/vocational training

Associate degree

Bachelor’s degree

Master’s degree

Professional degree

Doctorate degree o Employment status: Are you currently...? * o

Employed for wages

Self-employed

Out of work and looking for work

Out of work but not currently looking for work

A homemaker

A student

Military

Retired

Unable to work

To successfully maintain a car, to what extent do you need to comply with your mechanic’s or auto shop’s directives on car maintenance? Below, please select the compliance level where 1 is a low level of compliance and 10 is a high level of compliance; * 1

10 High Compliance

Low Compliance

What is the likely impact of non-compliance with your mechanic’s or auto shop’s directives related to car maintenance? Below, please select the likely impact where 1 is Low Impact and 10 is Disastrous Impact; * 1

Low Impact

10 Disastrous Impact

What areas of your life would be impacted by not having a well-maintained car? Select all that apply; * o

No impact

Financial

Social

Educational

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Health

Legal

Other

To successfully file your income taxes, to what extent do you need to comply with the tax preparer’s directives? Below, please select the level of compliance where 1 is a low level of compliance and 10 is a high level of compliance; * 1

10 High Compliance

Low Compliance

In your opinion, what is the likely impact of non-compliance with the tax preparer’s directives? Below, please select the likely impact where 1 is Low Impact and 10 is Disastrous Impact; * 1

Low Impact

10 Disastrous Impact

What areas of your life would be impacted by not filing taxes? Select all that apply; * o

No impact

Financial

Social

Educational

Health

Legal

Other o Please indicate if these statements apply to you; * o

I do not use a mechanic or auto shop to maintain my car

I do not use a tax preparer to file taxes

These statements do not apply to me

Optional: Please provide any additional insights that you have about adhering to auto care and tax directives. Optional: Please provide any additional insights that you have about the questionnaire. Thank You!

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Latent Variables that Measure Customer Satisfaction Thomas J. Gogue Auburn University Marie Kraska Auburn University Elisha Wohleb Auburn University

Abstract The focus of this study was customer satisfaction in a large bar/restaurant in the Midwestern region of the United States that served food, as well as drinks. The sample for this study was 597 individuals who patronize the bar and returned anonymous paper/pencil survey forms. The survey form sought customer responses to 22 items that addressed features of a food and drink place. The intent of the study was to identify the underlying structure of the 22 survey items. Results of the study revealed three factors (Responsiveness, Reliability, and Tangibles) that explained 63.9% of the variance in overall customer satisfaction with bar and restaurant services. These findings imply that business owners and managers may build stronger businesses and create customer loyalty by delivering the kinds of services desired by individuals who patronize large bar/restaurant establishments. Furthermore, these findings can be extended to smaller food and drink businesses. Keywords: Factor analysis, Latent variables, Customer satisfaction, Bar/nightclub

Introduction Service quality is a major concern for all consumers. Service quality in a bar or restaurant implies various customer expectations related to features such as environment,

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friendliness, cleanliness, and hours of operation. Characteristics of effective service and ways to assess quality of services are described in the literature. The topic for this research is an investigation of the kinds of features that lead to consumer satisfaction within a large bar/restaurant setting that serves food, as well as drinks. The topic is based on the paucity of empirical research on the expectations and satisfaction of consumers in a bar/restaurant setting. Customer satisfaction is a fundamental indicator of a firm’s performance due to its links to behavioral and economic consequences beneficial to the firm (Anderson, Fornell, & Rust, 1997). In order to identify the kinds of features that indicate customer satisfaction, the following research question was formulated for this study: What is the underlying factor structure for 22 variables (items) that address customer satisfaction in a bar/restaurant setting? Knowledge of broadly stated variables that are required for customer satisfaction when customers frequent a bar or restaurant to socialize with drink and/or food may be helpful to bar/restaurant owners and managers. The intent of this research is to inform business people employed in a bar/restaurant establishment about the features of services and products that may attract new customers and retain returning customers.

Literature Review

Service Quality Services have four unique characteristics which distinguish them from tangible goods: intangible, perishable, variable, and inseparable (McDaniel, Hair, & Lamb, 2012). This view on the four characteristics has been criticized by some authors in recent literature on the basis that the characteristics stated are not applicable to all service sectors (Afthinos, Theodorakis, & Nassis, 2005). Focusing too heavily on these characteristics can result in overlooking the consumer’s role in the delivery of the service (Afthinos et al., 2005). A key feature of the services is inseparability, as it clearly highlights consumer-employee interactions as a vital part of the production and consumption of the service (Chelladurai & Chang, 2000). Firms dealing with tangible goods are able to measure quality by the number of defects produced; organizations, such as bars, are unable to do this as instead they need to measure the services

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provided (Chelladurai & Chang, 2000). However, bars potentially do have a “defect” that could be measured – the number of mixed drinks made incorrectly. According to customers, in heavy service industries such as restaurants and bars, the importance of customer service and service quality is 60:40 when compared to the product. In product-focused industries, the ratio is 25:75 when customer service and service quality are compared to the product (St. Clair, 2014). The following four quantifiable costs are associated with poor service quality (1) loss of all future revenues from that customer and every referral not received, (2) redundant cost of replacing a lost customer rather than gaining a new one (advertising, promotion, sales and marketing expenses), (3) loss of employee morale from dealing with unhappy customers, and (4) further decline in customer service from discontented employees (St. Clair, 2014). In addition, benefits associated with optimal or superior service quality are (1) increased revenues and referrals, (2) improved reputation, (3) lower sales, marketing, and operating expenses, (4) increased time to focus on new products, services, and customers, (5) increased bottom line, and (6) sustainability of a business (St. Clair, 2014). One of the most important advances in business thinking is “the recognition that people, in their purchase decision-making, respond to more than simply the tangible product or service being offered” (Kotler, 1973, p. 48). This way of thinking explains why in today’s business world, particularly in the service industries, increased attention is being paid not only to pricing and merchandise, but also to the provision of a pleasant and exciting, when possible, shopping atmosphere (Turley & Milliman, 2000). This attention may be even more amplified in the hospitality industry. As products are highly intangible in nature (Kotler, 1973), customers often experience a service organization’s facilities and infer service quality from tangible cues in the physical environment (Bitner, 1992). Hospitality service providers strive to ensure that every single detail of the physical atmosphere contributes to the customers’ overall satisfaction (Heung & Gu, 2012). Service quality and customer satisfaction are considered to be the most important outcomes of all marketing activities in a market-oriented firm (Kandampully & Suhartanto, 2000). The obvious need for satisfying the firm’s customer is to expand the business, gain a higher market share, and acquire repeat and referral business, all of which lead to improved profitability (Barsky, 1992). A future behavioral intention is the probability that a customer will

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perform some behavior in the future (Canny & Hidayat, 2012). Perceptions that exceed a customer’s expectations result in a state of satisfaction, leading to a positive attitude towards the product or service, and influencing positive future behavioral intentions (Carpenter, 2008). However, based on the performance-based approach, other scholars have asserted that customer satisfaction incorporates cognitive judgments and affective reactions during consumption (Mano & Oliver, 1993). Some researchers argue that satisfaction includes an evaluation of the consumption emotions elicited by using or consuming a product or service (Westbrook, 1987). Also, customer satisfaction is considered as the degree of pleasantness or unpleasantness, which suggests that satisfaction reflects the impact of the performance of a customer’s emotional state (Rosenberg, 1960).

Measuring Services One way of measuring services provided is to ask customers to give feedback through customer service satisfaction surveys. A variety of past studies have been conducted to assess service quality. Much of the initial work in developing a model to assess service quality came from Parasuraman, Zeithaml and Berry (1985), who noted that discrepancies of service quality existed between the perceptions of organizational management and customers. When the experience is less than the expected experience, less-than-satisfactory service quality is implied. After two stages of validation, the SERVQUAL scale, which includes five dimensions of service quality, was adapted from a model consisting of 10 dimensions (Parasuraman, Zeithaml, & Berry, 1988). Cronin and Taylor (1992) proposed a model that would measure customer expectations and provide evidence that customers assess service quality in terms of performance minus expectations. In addition, Cronin and Taylor suggested that an effective service model should focus on the outcomes of the service encounter, not on the process of service delivery. Finally, a service model should include dimensions or features that are universal. Many scholars agree that service quality can be measured in two major dimensions. The first dimension addresses what the service delivers. This dimension is referred to as outcome quality or technical quality. The second dimension focuses on how the service is delivered or the process that the customer went through to get the service outcome. This is referred to as process

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quality or functional quality (Parasuraman et al., 1985). Gronroos and Shostack (1983) interchanged the phrase service quality with service process quality. Both phrases are used to represent the total service comprised of process and outcome. Likewise, service quality is used to refer to the totality of the process quality and the outcome quality. Another approach to creating measures for customer satisfaction is to identify both antecedents to, and consequences of, satisfaction (Ha & Jang, 2010). Marketing researchers have examined perceived value as an antecedent of satisfaction (Babin, Darden, & Griffin, 1994). In particular, a strong link between hedonic/utilitarian values and satisfaction has been identified, suggesting that both values have a positive effect on customer satisfaction (Babin et al., 1994). Hedonic value is related to revisit-intention because perceiving value through emotions and affective experiences can be antecedents of approach or avoidance behavior (Donovan & Rossiter, 1982). Utilitarian value is also related to revisit-intention. Customers who have previous experiences that they perceive as highly valuable in terms of efficient and economical aspects will be more likely to have revisit-intentions (Swinyard, 1993). In the service industry, word-of-mouth is one of the most powerful forms of communication (Ha & Jang, 2010). Customers seek information. During the information-seeking process, customers often view word-of-mouth information as more reliable because it is a third-party’s opinion based on firsthand experience (Ha & Jang, 2010). Previous research has suggested that word-ofmouth is a consequence of customers’ emotional responses to consumption experiences (Swan & Oliver, 1989). The more customers value the affective aspects of a dining or drinking experience, the more likely they will spread positive word-of-mouth comments about the experience.

Methodology

Purpose of this Research The purpose of this study was to identify underlying latent variables among 22 manifest variables on the Customer Service Survey (CSS). The CSS was developed by the researchers for this study. A basic assumption of this study was that relationships among the 22 items on the

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scale would reveal underlying factors for the total scale. In turn, the underlying factors would indicate the types of variables important to customers in a bar/restaurant environment.

Design of the Study This was an exploratory study that used a survey research design. The researchers developed a questionnaire that consisted of 22 items based on a review of relevant research and literature related to customer satisfaction, service quality, and measures of customer satisfaction. The items were judged by the researchers to be representative of a broad perspective of customer satisfaction. An eight-member panel of experts including a manager of a bar that offered nightly shows, a manager of a bar and restaurant, two bartenders who worked in a gay bar, and four customers who had frequented a bar in the past six months reviewed the questionnaire and provided input for revisions to provide content and face validity of the survey instrument. Quantitative validity measures accuracy (Huck, Cormier, & Bounds, 1974). Validity is the underlying soundness of an instrument signaling sufficiency that the instrument measures what it is purported to measure.

Content Validity Content validity answers the question, does the instrument measure what it is supposed to measure, and whether the instrument is appropriate, clear, relevant, meaningful, and important to the studied subject (Huck et al., 1974). The panel of experts was asked to critique and offer insight about the instrument. Individuals on the panel of experts had over 80 combined years of experience in the bar industry. They have been owners, managers, or customers in bars for more than 10 years. Panel members had experience in every aspect of the operations of bars as well as knowledge of the customer base of the bar. The expert panel confirmed the content validity of the instrument.

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Face Validity Face validity is the overall appearance of an instrument. Face validity of the instrument was established using input from three members of the panel of experts (bar manager and two customers) and a research methodologist. These individuals reviewed the instrument for ease of administration and comfort for the respondents. Amount of white space, size and type of print, categories of questions, and time to complete the instrument were evaluated with positive results.

Setting for the Study The location for this research was chosen for its convenience and accessibility to the researchers. The setting is classified as a show bar located in a large city in the mid-western region of the United States. Even though the bar is known as a gay bar, lesbian, bisexual, transgender, and straight customers also patronize the bar. This bar has been in operation for more than 10 years and is known as the most popular bar in the city. The bar is open seven days a week, 365 days a year from noon until 3:00 A.M.

Participants in the Study Participants in the study were individuals who were in the bar as customers during the time of the study and who agreed to complete the survey form. The total sample was comprised of 597 customers. There were 298 males and 299 females who completed the survey. Age groups for the participants ranged from the 20’s to 50 and older, with 251 in the 20’s age group, 210 in the 30’s age group, 101 in the 40’s age group, and 33 who were in the 50 plus age group. The education level of participants ranged from 19 who had some high school to 192 who were high school graduates to 168 who held an associate degree to 190 who held a college degree to 28 who held a post- baccalaureate degree. Six individuals reported that they were Asian, 109 reported their ethnicity as African American, 45 reported being Hispanic, 3 reported being Native American, 371 identified themselves as Caucasian, and 39 said they were Bi-Racial. The majority of participants (375) identified themselves as gay (homosexual); 111 identified

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themselves as bi-sexual; and 107 identified themselves as straight (heterosexual). The large percent (63%) of homosexuals was to be expected, since the site for this study was known as a gay bar. Most of the participants (540) patronized the bar one or more times per week. Only 57 reported as being first-time customers.

Data Collection Procedures Permission was secured from the owner manager of the bar located in the mid-western region of the United States and the Institutional Review Board at Auburn University to conduct the study. In all cases, the data collected were anonymous. A pen and paper questionnaire consisting of 46 items was distributed by the researchers and returned anonymously to a drop box by customers. Part 3 of the questionnaire asked questions about satisfaction with services. Each item asked participants to indicate their level of agreement or disagreement on a 5-point Likert-type scale. The survey forms were distributed to the patrons over a 10-day period in March 2012. Survey forms were distributed randomly to visitors during the “cocktail” shift (noon to 8:00 P.M.) and during the “night” shift (8:00 P.M. to 3:00 A.M.) during the 10-day period. All questionnaires were numbered consecutively for data entry into an SPSS data editor.

Data Analysis The research question was stated as follows: What is the latent variable structure of the 22 items on the Customer Service Satisfaction Scale? Exploratory factor analysis procedures were used to identify the underlying structure for measures on the 22 items on the CSS questionnaire. Each item on the questionnaire was treated as a variable. The variables were as follows: (1) equipment, (2) interior, (3) employee appearance, (4) physical facilities appearance, (5) promise, (6) sympathetic, (7) dependable, (8) timely, (9) recovers from problems, (10) service information (11) prompt service, (12) helpful, (13) prompt response, (14) trust, (15) safe, (16) polite, (17) employees well-trained, (18) individual attention, (19) no personal attention, (20) do not know customer needs, (21) customer best interests, and (22) operating hours.

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Results/Findings A total of 2,100 surveys were distributed: 1,364 were returned to the drop box and 597 complete and usable for the study. Based on the number of usable surveys, the response rate was 44%. All usable survey data were coded and entered into an IBM SPSS version 22 spreadsheet for analysis. The mean scores and standard deviations for each of the items on the survey form are listed in Table 1 by factor. Item 22 (operating hours) had the highest mean score (4.72) and the smallest standard deviation (.72) on the scale. It is apparent that customers liked the fact that the gay bar is open many hours throughout a 24-hour period. Item 10 (service information) had the smallest mean score (3.91) and a fairly large standard deviation (1.06). Customers either already knew when services would be offered or that aspect of the bar was not as important to them as other aspects.

Construct Validity Construct validity is a theoretical modeling of attributes and characteristics under scrutiny by the researcher (Clark, Riley, Wilkie, & Wood, 1998). For self-reporting instruments, construct validity assesses the meaningfulness of the test score to validate the usefulness of the instrument. Construct validity for the 22 items was established using item inter-item correlations and factor analysis. Results of the inter-correlations supported the constructs identified in the factor analysis. For example, the inter-correlations revealed that items within the same factor generally yielded a higher correlation with one another than items not included in that factor. For instance, Item 12 and Item 18, both within the Responsiveness factor, showed a correlation of 0.72; Item 7 and Item 8, both within the Reliability factor, showed a correlation of 0.71; and Item 1 and Item 2, both within the Tangibles factor, showed a correlation of 0.67. Furthermore, Item 1, a Tangible factor, and Item 18, a Responsiveness factor, showed a correlation of 0.24; Item 7, a Reliability factor and Item 3, a Tangible factor, showed a correlation of 0.21; and Item 11, a Responsiveness factor, and Item 1, a Tangible factor, showed a correlation of 0.19.

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Reliability Quantitative reliability is defined as the consistency of a measure (Huck et al., 1974). The ability of solutions to reach valid reliability scores indicates that the measure itself, not chance, explains the results. Reliable research instruments allow for future research to be consistently measured using the same factors and different results can be reliably attributed to differences in the sample and not to the instrument itself. Reliability for the entire scale and individual factors was established using Cronbach’s Alpha. The acceptable range of values for Cronbach’s Alpha is 0.70 to 100 (Huck et al., 1974). The reliability coefficient was very high for the entire scale; Cronbach’s Alpha was 0.94. The reliability coefficient was also very high for the Reliability and Responsiveness factors; Cronbach’s Alpha was 0.93 and 0.89 respectively. The reliability coefficient was lower for the Tangibles factor, however, still within the acceptable range; Cronbach’s Alpha was 0.76.

Factor Structure Extensive methodological literature addresses the optimal number of factors to retain. The Kaiser criterion of computing eigenvalues for the correlation matrix is the best known procedure for determining number of factors to retain (Fabrigar, MacCallum, Wegener, & Strahan, 1999). The number of eigenvalues equal to or greater than one may be used as the number of factors to retain. The unrotated and variamax rotated procedures revealed that three factors had eigenvalues greater than 1.0. The first factor accounted for 45.39% of the variance; the second factor accounted for 12.77% of the variance; and the third factor accounted for 5.23% of the variance. These three factors explained 63.39% of the total variance in the original variables. There were 72 (31.0%) non-redundant residuals with absolute values greater than 0.05, suggesting that the factors that were extracted may not work well in representing the original data. However, the amount of variance accounted for the number of factors with eigenvalues >1, and the scree plot all suggested that three factors should be retained, as illustrated in Figure 1.

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Efforts to improve the model by decreasing the eigenvalues to 0.98 (a fourth factor had an eigenvalue of 0.987) and forcing a four-factor solution did not improve the model. The fourfactor solution accounted for 67.88% of the total variance, a scree plot showing that three factors should be retained, one-factor loading on a single variable, and 75 (32.0%) non-redundant residuals with absolute values greater than 0.05. Examination of the factors revealed that eight variables loaded on factor 1, nine variables loaded on factor 2, five variables loaded on factor 3, and only one variable loaded on factor 4. Since some confusion existed around factor loadings in terms of one variable loading on its own factor and the discrepancy between the extracted sums of squared loadings (variance accounted for) and the scree plot, the researcher performed factor analysis on the variables again to retain three factors using varimax rotation. The threefactor varimax rotated solution produced excellent loadings (>0.71) on 10 of the variables to very good loadings (>0.60) on eight of the variables, and less than desirable on (<0.591) on the remaining four variables. The highest loading was 0.879 on one variable; the lowest loading was 0.485 on one variable. The scree plot showed clearly that a three-factor solution was appropriate for the data. In addition, a comparison of the four-factor solution and the three-factor solution revealed that variables were loading on the same factors for both solutions. Consequently, the researcher chose the three-factor solution as the model of choice to identify the underlying structure of the data. A reference variable was arbitrarily selected to represent each of the factors. Eight variables loaded on Factor 1. Item 11 on the CSS (You do not receive prompt service from employees.) was selected as the reference variable for the Responsiveness factor. Nine variables loaded on Factor 2. Item 7 (dependable) was selected as the reference variable for the Reliability factor, and five variables loaded on Factor 3. Item 4 (The appearance of the physical facilities is in keeping with the type of services provided.) was selected as the Tangibles factor. The rotated factor matrix and observed factor loadings are shown in Table 2.

Discussion This study presented an exploratory factor analysis to uncover the underlying structure of the 22 items on a Customer Service Satisfaction questionnaire. The study included research and

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related literature on customer satisfaction with service and products in a bar/restaurant. Results of the factor analysis yielded three factors showing that customers desire responsiveness to their needs, reliability of the staff and trust that acceptable services and products will be delivered, and tangibles, such as a visually appealing interior and staff. Findings from this study suggest that all consumers desire a friendly environment with timely service and a quality product. These expectations within a bar/restaurant establishment may be important to other kinds of businesses, such as retail stores and service agencies. This study is timely and beneficial to business owners and manages as individuals continue to patronize bar/restaurant establishments as a form of social interaction and personal satisfaction. Although this research was limited to a hospitality industry, marketers of all products could benefit from additional empirical studies. Future research may be conducted to replicate these results and investigate the kinds of features that customers value in a bar/restaurant environment. This type of study could be expanded to assess satisfaction of individuals in other environments, such as Catholic bingo halls, full-service gas stations, fast-food establishments, and retail specialty (art, gifts, cards, etc.) Another future research study could assess service satisfaction of cigarette smokers and nonsmokers in an establishment that does not ban smoking indoors. As competition grows in the business sectors, it behooves owners and managers to know their customers so that acceptable services and products will be delivered. Author Biographies Jason Gogue is owner of Gogue and Company, Auctioneers and Realtors, LLC. He holds a Ph.D. in Hotel and Restaurant Management, with emphasis in research and statistics from Auburn University and a Masterâ&#x20AC;&#x2122;s degree in Business Administration from Auburn University-Montgomery. Dr. Gogue has been a business consultant to several different state agencies, including Alabama Department of Finance, Alabama Department of Corrections, and Alabama Department of Education. His research interests are in management strategies, customer satisfaction, and services that include recreation, tourism, and bar and restaurant service.

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Marie Kraska is a Distinguished Professor in the Department of Educational Foundations, Leadership, and Technology in the College of Education at Auburn University. She holds a Ph.D. in technical (research and statistics) studies, from the University of Missouri, a Master's degree in Probability and Statistics from Auburn University, and a Master of Science degree in research and statistics from the University of Wisconsin-Stout. Her experience includes teaching applied statistics and directing research. Her research interests are applications of statistical procedures to theoretical concepts and modeling latent variables related to values, student retention, special populations, rehabilitation clients and services. Elisha C. Wohleb is an Associate Clinical Professor at Auburn University in the Business/Marketing Education program. She has a PhD in Career and Technical Education. Her research interests include mobile technology, social media, web 2.0, and integrating technology into the classroom. Dr. Wohleb is the Editor of the Business Teacher Education Journal and is the currently serving as the Vice President of the Southern Business Education Association. References Afthinos, Y., Theodorakis, N. D., & Nassis, P. (2005). Customers’ expectations of service in Greek fitness centers: Gender, age, type of sport center, and motivation differences. Managing Service Quality, 15(3), 245-258. Anderson, E. W., Fornell, C., & Rust, R. T. (1997). Customer satisfaction, productivity, and profitability: Differences between goods and services. Marketing Science, 16(2), 129145. Babin, B. J., Darden, W. P., & Griffin, M. (1994). Work and/or fun: Measuring hedonic and utilitarian shopping value. Journal of Consumer Research, 644-656. Barsky, J. D. (1992, February). Customer satisfaction in the hotel industry: Measurement and meaning. Journal of Hospitality and Tourism Research, 16(1), 51-73. Bitner, M. J. (1992, April). Servicescapes: The impact of physical surroundings on customers and employees. Journal of Marketing, 56(2), 57-71. Canny, I., & Hidayat, N. (2012). The influence of service quality and tourist satisfaction on future behavioral intentions: The case study of Borobudur Temple as a UNESCO World

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Culture Heritage Destination. International Proceedings of Economics Development & Research, 50, 89-97. Carpenter, J. M. (2008, September). Consumer shopping value, satisfaction and loyalty in discount retailing. Journal of Retailing and Consumer Services, 15(5), 358-363. Chelladurai, P., & Chang, K. (2000). Targets and standards of quality in sport services. Sport Management Review, 3(1), 1-22. Clark, M. A., Riley, M. J., Wilkie, E., & Wood, R. C. (1998). Researching and writing dissertations in hospitality and tourism. New York City, NY: International Thomson Business Press. Cronin, J. J., & Taylor, S. A. (1992, July). Measuring service quality: A reexamination and extension. Journal of Marketing, 56, 55-68. Donovan, R. J., & Rossiter, J. R. (1982). Store atmosphere: An environmental psychology approach. Journal of Retailing, 58(1), 34-57. Fabrigar, L. R., MacCallum, R. C., Wegener, D. T., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272-299. Gronroos, C., & Shostack, G. L. (1983). Strategic management and marketing in the service sector. Cambridge, MA: Marketing Science Institute. Ha, J., & Jang, S. (2010). Perceived values, satisfaction, and behavioral intentions: The role of familiarity in Korean restaurants. International Journal of Hospitality Management, 29, 2-13. Heung, V. C., & Gu, T. (2012). Influence of restaurant atmospherics on patron satisfaction and behavioral intentions. International Journal of Hospitality Management, 31, 1167-1177. Huck, S. W., Cormier, W. H., & Bounds, W. G. (1974). Reading statistics and research. New York City, NY: Harper & Row. Kandampully, J., & Suhartanto, D. (2000). Customer loyalty in the hotel industry: the role of customer satisfaction and image. International Journal of Contemporary Hospitality Management, 12(6), 346-351. Kotler, P. (1973). Atmospherics as a marketing tool. Journal of Retailing, 49(4), 48-64.

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Mano, H., & Oliver, R. L. (1993, December). Assessing the dimensionality and structure of the consumption experience: Evaluation, feeling, and satisfaction. Journal of Consumer Research, 20, 451-466. McDaniel, C., Hair, J. F., & Lamb, C. W. (2012). Introduction to marketing (12th ed.). Independence, KY: South-Western College Publishing. Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49(4), 41-50. Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 1240. Rosenberg, M. J. (1960). An analysis of affective-cognitive consistency. In C. I. Hovland, W. J. McGuire, R. P. Abelson, & J. Brehm (Eds.), Attitude organization and change (pp. 1564). New Haven, CT: Yale University Press. St. Clair, K. (2014, February 20). The value of quality customer service. Retrieved July 1, 2014, from Small Business Samaritans.com: http://www.smallbusinesssamaritans.com/thevalue-of-quality-customer-service Swan, J. E., & Oliver, R. E. (1989). Postpurchase communications by consumers. Journal of Retailing, 65(4), 516-533. Swinyard, W. R. (1993). The effects of mood, involvement, and quality of store experience on shopping intentions. Journal of Consumer Research, 20, 271-281. Turley, L. W., & Milliman, R. E. (2000, August). Atmospheric effects on shopping behavior: A review of the experimental evidence. Journal of Business Research, 49(2), 193-211. Westbrook, R. A. (1987). Product/consumption-based affective responses and postpurchase processes. Journal of Marketing Research, 258-270.

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Tables and Figures Table 1 Item Mean Scores, Standard Deviation, Skewness, and Kurtosis Item

Item Description

No.

Mean

Standard

Score

Deviation

Up-to-date equipment

4.33

0.93

Interior is visually appealing

4.24

0.95

Employees are well dressed and appear neat

3.95

1.07

4.16

0.88

4.21

0.88

4.24

0.94

4. 5. 6.

Appearance of the physical facilities is in keeping with the type of services provided When promises to do something by a certain time, it does so When you have problems, is sympathetic and reassuring

Dependable

4.34

0.78

Provides its services at the time it promises to do so

4.27

0.86

When you have a problem, recovers adequately

4.21

0.95

3.91

1.06

4.05

1.09

4.17

1.12

4.15

1.16

10. 11. 12. 13.

Does not tell customers exactly when services will be performed (reverse coded) You do not receive prompt service from employees (reverse coded) Employees are not always willing to help customers (reverse coded) Employees are too busy to respond to customer requests promptly (reverse coded)

14.

You can trust the employees

4.45

0.86

15.

You feel safe in your transactions with employees

4.46

0.78

16.

Employees are polite

4.22

0.95

17.

It appears that employees are well trained

4.32

0.92

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18. 19. 20. 21. 22.

Does not give you individual attention (reverse coded) Employees do not give you personal attention (reverse coded) Employees do not know what your needs are (reverse coded) Does not have your best interests at heart (reverse coded) Does have great operating hours

3.96

1.13

4.14

1.12

4.09

1.10

4.18

1.10

4.72

0.72

Table 2 Rotated Factors and Their Corresponding Variables with Loadings Factor

Factor 1: Responsiveness Item 19.

Employees do not give you personal attention

0.879

Item 18.

Does not give you individual attention

0.858

Item 12.

Employees are not always willing to help customers

0.842

Item 13.

Employees are too busy to respond to customer requests promptly

0.816

Item 11.

You do not receive prompt service from employees

0.811

Item 20.

Employees do not know what your needs are

0.794

Item 10. Item 21.

Does not tell customers exactly when services will be performed Does not have your best interests at heart

0.680 0.678

Factor 2: Reliability Item 7.

Dependable

0.830

Item 8.

Provides its services at the time it promises to do so

0.781

Item 9.

When you have a problem, recovers adequately

0.748

Item 15.

You feel safe in your transactions with employees

0.710

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Item 6.

When you have problems, sympathetic and reassuring

0.687

Item 17.

It appears that employees are well trained

0.651

Item 14.

You can trust the employees

0.601

Item 5.

When promises to do something by a certain time, it does so

0.595

Item 16.

Employees are polite

0.485

Factor 3: Tangibles Item 2.

Interior is visually appealing

0.683

Item 1.

Up-to-date equipment

0.616

Item 22.

Does keep great operating hours

0.591

Item 4. Item 3.

The appearance of the physical facilities is in keeping with the type of services provided Employees are well dressed and appear neat

0.541 0.535

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Figure 1. Scree plot showing a three-component solution.

Scree Plot

Eigenvalue

0 1

9 10 11 12 13 14 15 16 17 18 19 20 21 22

Component Number

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Accounting for Intangibles: Does Method of Accounting Matter? V. Brooks Poole Mississippi College Abstract The purpose of this study was to determine if method of accounting for intangible-related transactions matters. One hundred four subjects were asked to determine the effect on future earnings of a company with internal research and development expenditures. In one scenario, the company capitalizes the intangibles as is allowed under International Financial Reporting Standards. In the other scenario, the research and development expenditures were expensed as required by US GAAP. Results indicate that users’ perceptions of value of intangibles were affected by how those intangibles are reported. Large expenditures were deemed more valuable by users when capitalized versus small expenditures. Based on the outcome of the experiment, it appears that users’ perceptions of the benefit of intangible expenditures can be influenced by the accounting treatment, even though the expenditures should have the same impact on future earnings. Keywords: Expenditures, accounting intangible-related transactions, reporting, market reaction

Introduction The goal of this study is to understand the market’s reaction to differences in reporting intangible-related transactions. Intangible-related transactions are often accounted for differently, depending on the set of accounting principles followed by the company engaging in such activity. For example, companies adhering to US Generally Accepted Accounting Principles (GAAP) account for research and development costs as an expense; however, development costs are often accounted for as an asset by companies prescribing to International Financial Reporting Standards (IFRS). The primary question of interest in this study is whether

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the market is efficient in understanding that these transactions are identical in nature even though they are accounted for differently to adhere to particular reporting requirements. A secondary question of interest in this study is whether any perceived differences in the intangible expenditures based on accounting treatment are affected by the size of the expenditure. In other words, does size of an intangible-related transaction affect investors’ perceptions of its benefit on future earnings when the intangible is expensed versus capitalized?

Background and Hypotheses Development Intangible assets are identifiable (separable) non-monetary sources of probable future economic benefits to an entity that lack physical substance, have been acquired or developed internally from identifiable costs, have finite life, have market value apart from the entity, and are owned or controlled by the firm as a result of a past transaction or event. The ratio of intangible assets relative to tangible capital assets has nearly flip-flopped from 1929 to 1990. In 1929, the ratio of intangible assets to tangible assets was 30:70; in 1990, the ratio was 63:37 (Canibano, Garcia-Ayuso, & Sanchez, 2000). Segelod (1998) researched the change of companies’ assets in Sweden for the years 1964, 1977, 1990, and 1993. The results show that companies are investing more and more in intangibles and that guidance is needed by management to determine how to account for such investments, particularly those internally developed intangibles expected to provide future value to the company, which are expensed as opposed to capitalized in accordance with financial reporting requirements. The primary choices for accounting for an intangible per Financial Accounting Standards Board’s (FASB’s) Statement of Financial Accounting Standards (SFAS) 141, “Business Combinations,” and SFAS 142, “Goodwill and Other Intangible Assets,” are as follows: 1) an asset without amortization, 2) an asset with annual impairment testing, 3) an asset with systematic amortization, and 4) an expense (Financial Accounting Standards Board, 2001a, 2001b). Basically, US standards mandate that externally acquired intangibles be capitalized, while internally generated intangibles are to be expensed. Externally acquired intangibles with finite lives are to be amortized over the shorter of their economic or legal life. Those externally acquired intangible assets with an indefinite life are not to be amortized but rather checked

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annually for impairment. An intangible is said to have become impaired when its carrying value (book value) exceeds its fair market value. To adhere to the conservatism principle of accounting, when such impairment occurs the intangible is written down to its fair market value with a corresponding charge to the income statement. While it is the norm in the US to expense internally generated intangibles, the American Institute of Certified Public Accountants (AICPA) has been responsive in the past to recognize that some internally generated intangibles should be presented on the face of the balance sheet. The AICPA’s Statement of Position (SOP) 93-7 mandates that direct-response advertising that can be expected to result in benefits in future periods be capitalized as an intangible asset, given the benefits are measurable and a company makes certain disclosures. Such direct-response advertising is to be amortized, on a cost-pool-by-cost-pool basis, over the estimated time of benefit (Flesher, Hopskins, & Thompson, 2002). Therefore it is not unreasonable to think that the FASB would allow other internally generated intangibles with potential future value to be capitalized. The International Accounting Standards Board (IASB) hopes to create a framework that will establish international agreement on how to account for intangibles. By definition a company’s assets are its resources with potential future value. Since intangible assets lack physical existence, measuring their potential value is not easy and is quite subjective. The major reason that internally generated intangibles have not been treated the same as externally acquired intangibles is because internally generated intangibles are extremely difficult to value. Arriving at relevant and reliable figures can be problematic (Radebaugh, Gray, & Black, 2006). International Accounting Standards related to accounting for intangible expenditures are principles-based, relative to rules-based US GAAP. The IASB attempts to create standards that will account for these expenditures in a manner that most appropriately reflects the underlying nature of such transactions. Rather than mandating that these expenditures be accounted for in a certain manner depending on how the transaction arose (internally or externally), the IASB attempts to create standards in such a way that if the expenditure has future value, it is accounted for as an asset; if it does not, it should be expensed. International Accounting Standards (IAS) 38 (IAS, 2004b) mandates that identifiable intangibles be capitalized if they have probable future benefit to the company and the costs of the intangible can be measured reliably. If such

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recognition criteria cannot be met, IAS 38 (2004b) requires that the expenditure be expensed when it is incurred. This treatment applies to both externally acquired and internally generated intangibles. Companies adhering to IFRS must classify intangible assets based on their lives—assets with indefinite or finite lives. Those with finite lives are amortized over their useful lives. Those with indefinite lives are checked annually to determine if their lives are still indefinite and to determine if they have become impaired. Assets that become impaired are written down to net realizable value. However, if such impairment reverses, those intangibles may be written back up, unlike intangibles tested annually for impairment under US GAAP (IAS, 2004a). IAS 38 offers specific guidance for how to treat certain intangible-related expenditures. Like US GAAP, IASB mandates all research costs be expensed. However, development costs may be capitalized if they meet the recognition requirements described above. The purpose of this paper is to test whether developing international consensus on how to account for intangible-related transactions is necessary. Arguably, the method of accounting for intangibles may not matter. If two countries account for the same intangible-related transaction differently and the market is efficient, the market’s reaction to such transaction will be the same. As long as a company discloses information about its intangibles and how they were accounted for, share prices will not differ as accounting treatment of intangible-related transactions differs in efficient markets (Radebaugh et al., 2006). This study is motivated and warranted due to the current increased talk of a need for international consensus on accounting for intangibles (Radebaugh et al., 2006). Further, it is important to investigate whether users understand and account for differences in US GAAP and IFRS given that the Securities and Exchange Commission is contemplating allowing U.S. companies and foreign registrants to file using IFRS (Securities Exchange Commission, 2007). Existing literature finds that market does value reported intangibles. Disclosed intangibles, while consistently undervalued compared to tangible assets, are valued positively (Choi, Kwon, & Lobo, 2000). Lev (1999) conducted an archival investigation of intangibles including research and development, goodwill, and brands. He found the market values intangibles regardless whether they are treated as an asset on the balance sheet or an expense on the income statement. Regardless of the treatment of the intangible-related transaction, the

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market is efficient to recognize the underlying nature of the transaction and positively values the intangible as long as the information is disclosed (as an asset or as an expense). Knowing that GAAP does not allow internally created intangibles to be capitalized, the market recognizes that potential future value flows from a transaction that is expensed simply in order to align with GAAP. Hirschey (1982), Hirschey and Weygandt (1985), Cockburn and Griliches (1988), and Hall (1993) all researched the market’s reaction to companies’ disclosed research and development expenditures. Each find that the market positively values such expenditures. Even though the research and development expenditures are expensed on the financial statements to align with GAAP, the market recognizes such expenditures as assets with potential future value (Ballester, Garcia-Ayuoso, & Livnat, 2003). Sougiannis (1994) created an earnings model showing that research and development expenditures increase future income and a stock valuation model to show the market indeed does value such expenditures. Studies by Woolridge (1988) and Chan, Martin, and Kensinger (1990) find that the market also reacts to companies that announce their research and development expenditures. Bublitz and Ettredge (1989) find positive abnormal returns when the market becomes aware of unexpected research and development expenditures of a company. The expenditures, regardless how they are treated for financial reporting purposes, are viewed as investments and are expected to benefit the companies engaging in research and development investments, per the market’s reaction. Research also shows that users of financial information understand GAAP reporting requirements, and hence recognize that many intangibles never reach the financial statements (Barth, Kasznik, & McNichols, 2001). Since stakeholders positively value information about investments in intangibles, many companies voluntarily disclose information beyond the requirements of GAAP. Entwistle (1999) finds that the amount of disclosure a company makes about its intangible expenditures depends on what management wants the market to know, implying that management realizes that the market and analysts value disclosures about its intangibles. Gelb (2000) finds analysts give higher ratings for supplementary disclosure to companies with higher investments in research and development and advertising than to those which have fewer expenditures on intangibles. The supplemental disclosure is provided by

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companies because the financial statements alone are insufficient in communicating information about intangible-related transactions. Several countries’ GAAP facilitate more disclosure of intangibles than US GAAP. Prior to adopting IFRS, both Australia and the United Kingdom allowed internally generated intangibles to be capitalized. Goodwin and Ahmed (2006) and Abrahams and Sidhu (1998) found that the Australian market values the disclosure of internally generated intangibles. Those firms that capitalized internally developed intangibles are viewed more favorably by the market than those firms that expensed such expenditures (Smith, Percy, & Richardson, 2001). Alford, Jones, Leftwich, & Zmijewski (1993) find that Australian and the United Kingdom’s financial statements are just as useful and informative, if not more, than US financial statements. They note that Australian and UK financial statements are often more informative due to the fact that they provide more disclosure, specifically about intangibles. Investors use information reported on these countries’ financial statements about internally generated intangibles when evaluating companies’ earnings potential (Godfrey & Koh, 2001). As additional updated information about internally generated assets is disclosed, the market reacts favorably to the release of new information. Barth and Clinch (1998) found that Australian companies that updated the value of their intangibles were treated favorably by the market. Studies of British companies have found similar results to those of Australian companies. As Australian GAAP allowed the capitalization of internally generated intangibles, the United Kingdom did as well (prior to the adoption of IFRS). Mather and Peasnell (1991) find that British companies that disclosed internally generated brand names by capitalizing them reaped positive benefits in the market. Barth, Clement, Foster, and Kanznik (1998) and Kallapur and Kwan (2004) find that the disclosure of internally developed brand names by British companies provides valuable information to the market. The problem associated with communicating information about internally generated intangibles is the difficulty of valuing them. However, they are nonetheless valuable and should be disclosed in the financial statements (Amir & Lev, 1996). Even though the value of the brands and other internally generated intangibles is somewhat subjective, the market appreciates the disclosure of internally generated brands and recognizes that their values are subjective and non-exact. Arguably, companies that are not

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disclosing their brand names (such as US companies and companies following IFRS) are not communicating valuable information to stakeholders. Wyatt (2005) finds that US financial statements may have substantially less value than they could because internally generated intangibles are not reported on financial statements, as required by GAAP reporting requirements. Limiting managements' choices to record intangible assets tends to reduce, rather than improve, the quality of the balance sheet and investors' information set. Luft and Shields (2001) find that the accounting method of intangible-related transactions does affect users of financial statements. If stakeholders are told the intangiblerelated transaction was expensed, they underestimate the value of the expenditure on future periods’ earnings. However, if the exact same transaction is capitalized, future profits are predicted more accurately. Their study finds through experimentation that when investors predict future profits using information on intangible expenditures, expensing (versus capitalizing) the expenditures significantly reduces the accuracy, consistency, consensus, and self-insight of profit predictions. Therefore, based on these two behavioral experiments, not only do stakeholders need disclosure of intangibles in the financial statements, but the intangible needs to be accounted for as an asset and thus capitalized. The results of these various aforementioned studies on intangibles yield conflicting findings. Results for Lev (1999) indicate that the (US) market is efficient in understanding intangible-related transactions regardless if they are expensed or capitalized. Luft and Shield’s (2001) findings indicate that stakeholders’ assessments of companies’ financial statements are impacted by the method of accounting of intangible-related transactions. Investors’ assessments of the transactions depend on whether they are capitalized or expensed. Results of other studies mentioned above indicate that other countries’ GAAP, such as the UK’s and Australia’s, provide for more informative financial reporting relative to US GAAP (Alford et al., 1993; Mather & Peasnell, 1991). Prior to their adoption of IFRS, companies in these countries were allowed to disclose internally generated intangibles as assets. These mixed results indicate that future research is needed to understand how accounting treatment affects users’ assessments of the value of intangible expenditures. It is obvious why the IASB has had such difficulty in adopting acceptable international accounting standards on accounting for intangibles.

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One major area that cannot seem to get reconciled between the US and IFRS is accounting for research and development costs. Per US GAAP, all research and development expenditures flow through the income statement as an expense when incurred. FASB argues that such requirement is a conservative, practical method of accounting for research and development which insures consistency in practice and comparability among accompanies (Millan, 2005). FASB also postulates that the accounting method of such R&D expenditures makes little longrun difference from an income statement approach. Arguably, the amount of R&D that would be expensed on the income statement would be approximately the same each accounting period, regardless whether standards mandate immediate expensing or capitalization followed by amortization. Most companies engaging in R&D continue such activities in subsequent years (Millan, 2005). Conversely, while all expenditures related to research must be immediately expensed, IFRS allows the expenditures for development costs to be capitalized on the balance sheet as intangible assets if specific criteria are met. The cost is then amortized on a straight-line basis over the expected useful lives of the products for which they were incurred. The main difference between IFRS and US GAAP is that IFRS recognizes that sometimes a business is able to identify development expenditures that fulfill the requirements to be recognized as an intangible asset. From the perspective of IAS 38, such intangible assets should not be accounted for any differently than those acquired externally. If, however, the expenditure does not meet the criteria for asset recognition, such expenditure should be recognized as an expense and may never be recognized as an asset. The treatment of in-process research and development acquired through business combination is also accounted for differently under US GAAP and IFRS. US GAAP mandates that the portion of the purchase price attributable to in-process R&D be written off as expense immediately, while IFRS 38 mandates that such costs be recognized as a separate asset from goodwill or any other asset. While the IASB and FASB both pledge to make IFRS and GAAP as compatible as possible, such convergence on accounting for R&D expenditures does not seem promising in the near future. Since neither organization is willing to compromise on this issue, attempts for convergence on this issue have been temporarily suspended (Millan, 2005). According to the efficient market hypothesis, all publicly available information is quickly incorporated into stock share prices. The prices of traded assets (i.e. shares of stock) reflect all

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known information about the company and what investors project for the company’s future (Fama, 1970, 1991; Lev, 1999). If the efficient capital market hypothesis is true, the method of accounting for intangibles is irrelevant. Whether an intangible is expensed or capitalized with or without amortization, or capitalized and checked annually for impairment, will not affect the investors’ understanding of the true economic underlying of the intangible-related transactions; as long as disclosure about the intangibles and how they were accounted for are fully made. If the market is efficient, it will realize and understand the nature of the intangible-related transactions regardless of the accounting treatment of such transactions. However, Luft and Shields (2001) find that the accuracy of predicting future profits of a company is influenced by how transactions are accounted for. Based on Luft and Shields (2001), Hypothesis 1 of the paper is that the market is inefficient in recognizing that two transactions are identical in nature if they are accounted for differently. The first hypothesis of interest in this study is as follows: H1: Ceteris paribus, the market’s reaction to two identical intangible-related transactions will differ as accounting treatment of such transaction differs. If the market is inefficient with respect to intangible assets, the IASB should resume efforts to find consensus of accounting method for intangible-related expenditures. If, however, the results of this study indicate that the market is efficient, the IASB should focus its efforts on mandatory disclosure of intangible-related transactions as opposed to method of accounting for intangibles. The second issue tested in this experiment is whether the size of intangible expenditure affects investors’ perception of its benefit, based on whether the expenditure is expensed versus capitalized. Arguably, a small expenditure may be assessed by investors the same way no expenditure will be perceived. To effectively manipulate the amount of the expenditure, size in this study is manipulated based on the assumption of materiality from other studies. Materiality is not a simple calculation. Rather, it is a determination of what will affect the knowledgeable investors’ decisions given a specific set of circumstances related to the fair presentation of a company’s financial statements and disclosures concerning existing or future debt and equity instruments. According to SFAS 34 (Financial Accounting Standards Board, 1979), interest of certain assets must be capitalized only if the effects of capitalization are deemed material. Jordan and Clark (2004) find that when defining materiality for capitalizing

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interest, 4 to 5% or less of operating income is considered immaterial. Thus capitalizing or expensing expenditures of immaterial amounts of interest should not affect stakeholders’ analyses of financial statements. However, interest amounting to more than 5% of income should be capitalized in order to align with SFAS 34. The “5% rule” remains the fundamental basis for working materiality estimates. Because a qualitative analysis of determining materiality is very complex, almost everyone—including CPAs—uses quantitative estimates to identify potential materiality issues (Vorhies, 2005). Therefore to manipulate size in this study, a large expenditure is defined as an amount greater than 5% of net income; a small expenditure is defined as an amount less than 5% of net income. Large expenditures are expected to have a greater (positive or negative) influence on investors than small expenditures. The second hypothesis of interest in this study is as follows: H2: Ceteris paribus, the market’s reaction to two identical intangible-related transactions will differ as size of the expenditure differs, given the amount of such transaction is fully disclosed. The third hypothesis of this study is derived from the interaction of the two aforementioned hypotheses. Arguably, as postulated in Hypothesis 2, as level (amount) of an intangible expenditure differs, investors’ perception of the benefits of such expenditure may differ. The third question of interest is whether investors perceive a large or small intangiblerelated expenditure more favorably when it is accounted for in a particular manner—capitalized or expensed. In other words, will investors’ perceptions of future benefits of intangible-related expenditures depend on both method of accounting and size of the expenditure in combination? The third hypothesis of interest in this study is as follows: H3: Ceteris paribus, the market’s reaction to two identical intangible-related transactions accounted for differently will differ as size of the expenditure differs, given the accounting treatment and size of such transaction is fully disclosed.

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Methodology

Subjects In order to test the hypotheses of the study, a behavioral experiment was conducted. One hundred four upper-level undergraduate and masters-level accounting students of a state university in the United States serve as the subjects of this experiment conducted in June 2007. Studies show that MBA students who have completed a financial statement analysis course are able to acquire and use financial information in a similar manner to nonprofessional investors when making investment-related judgments and decisions (Elliott, Hodge, & Kennedy, 2007). All subjects in this study are upper-level or master’s-level accounting, and as such are appropriate proxies for nonprofessional investors. Twenty-eight subjects participated in the capitalize/large expenditure manipulation group; 24 subjects comprise the capitalize/small expenditure group; 24 subjects make up the expense/large expenditure group; and 24 subjects participated in the expense/small expenditure manipulation. Ideally, 26 subjects would comprise each group, giving each manipulation group the same number of subjects. However, since data was collected at various times, unequal group sizes occurred. Creating unequal group sizes is not intentional; however, results are not skewed by the slight difference in group sizes.

Instrument Subjects were randomly assigned one of four versions of the instruments located in the appendix of this paper. They were asked to determine the benefit of an intangible-related expenditure after reading a narrative describing the intangible-related activities of a company. Pro-forma financial statements accompany the instrument to assist subjects in their analysis. Since convergence of US GAAP and IFRS related to R&D expenditures (specifically development costs) has been difficult and remains unresolved, the intangible development costs was chosen as the intangible of the experiment.

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The US and UK companies described in this experiment are automobile manufactures. Both companies are described identically as heavily engaging in research and development related to improving the development of their hybrid automobiles. The idea to use an automobile manufacturing company stems from an actual automobile manufacturer’s 2006 annual report. DaimlerChrysler, a German-based international company, informs its stakeholders of the divergence between US GAAP and IFRS on accounting for development costs, as described in the related literature section of this paper. This experiment decribes automobile manufacturing companies engaging in research and incurring development costs. The method of accounting for development cost and the dollar amount of the expenditure are the manipulations of this behavioral experiment. To manipulate accounting method, the instrument used to conduct this experiment describes a US company and UK company. The UK currently reports financial statements in accordance with IFRS. In accordance with IFRS, the UK company described in the instrument capitalizes these expenditures. Accordingly, these expenditures are placed on the balance sheet as intangible assets. These expenditures in no way affect the current year’s net income of the company engaging in the internal development activities. Adhering to US GAAP, the US company expenses these expenditures, reducing current year’s net income. Accordingly, these expenditures did not ever show up on the balance sheet as an asset. However, management of the US company chooses to disclose within the notes of the financial statements that these expenses relate to the internal expenditures related to development costs arriving from research. Two versions of the experiment were created for each of the countries represented in order to test Hypothesis 2 of the study. The level of research and development activities of each of the two companies described is varied. In accordance with the 5% rule of materiality described previously, one company’s intangible-related expenditures is less than 5% of net income, while the other company’s transactions total more than 5% of current year’s net income. The US company’s net income is reduced by either 4.6%, a small amount, or by 81.5%, a large amount. Accordingly, the UK company capitalizes the intangible-related transaction by one of the two same dollar amounts. After reading about the company and its development activities, and after analyzing the company’s financial statements, subjects are asked two questions relating to whether such expenditures will be beneficial to the company in future years.

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Pilot Test Prior to conducting the actual experiment, a pilot test was administered to ensure that subjects would understand the experiment. The 24 participants of the pilot study were drawn from an undergraduate accounting course at a state university in June 2007. Upon completion of the pilot test, the subjects participated in a discussion forum. They indicated that the experiment was comprehensible and quite self-explanatory. The results of the pilot study were almost identical to those of the actual experiment, which are described in the following section of this paper.

Statistical Methods To test the hypotheses of interest of this study, the experiment was designed as a 2X2 between subjects experiment, with two levels of accounting treatment of an intangible-related transaction crossed with two levels of size of the intangible-related transaction. By manipulating only accounting treatment and size of the intangible-related expenditure, these two variables can be analyzed to determine if they affect subjects’ perception on the intangible’s future benefit. Factorial Analysis of Variance (ANOVA) was applied to the data collected in the experiment. Factorial ANOVA applied to the data collected from the 104 subjects’ responses to the experiment described above determines whether accounting treatment, size, and/or the interaction of accounting treatment and size are significant indicators of subjects’ responses, and thus account for the variance of investors’ perceptions of intangible-related expenditures’ benefit on future earnings. The independent variable accounting treatment was coded one (1) for IFRS treatment and two (2) for GAAP treatment. The independent variable size was coded one (1) for a large expenditure; small expenditures are coded two (2). The dependent variable in this study was the subjects’ perceived benefit of a company’s intangible-related expenditures. Two questions were asked in the experiment to capture these perceptions. Responses to questions 1 and 2 of the experiment were treated as the dependent variables. Question 1 asked subjects to indicate on a scale of 1 to 10, how beneficial the intangible-related expenditure (asset or expense) will be on future earnings, with 1 representing not beneficial and 10 representing very

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beneficial. The second question asked subjects how likely they would be to invest in the company engaging in the intangible-related expenditures described in the instrument. The scale for this question also ranges from 1 to 10, with 1 representing not likely to invest and 10 representing very likely to invest.

Results

Overall ANOVA Results The average scores to the dependent variables, which represents investorsâ&#x20AC;&#x2122; perceived future benefit of the intangible-related expenditures, are the best predicted values of the dependent variable, given a particular accounting treatment and size of the intangible-related expenditure. Questions 1 and 2 of the experiment are on a 10-point scale. The average responses to each of the questions is greater than 5.5, with the only exception being the Capitalize/Small group for question 2 with an average response of 5.0, indicating that the expenditures are perceived to have positive benefits on future earnings. This finding aligns with the research addressed earlier, indicating that both capitalized and expensed research and development costs are viewed favorably by the market (Ballester et al., 2003; Cockburn & Griliches, 1998; Hall, 1993; Hirschey, 1982; Hirschey & Weygandt, 1985). However, the degree of perceived benefit varies significantly as method of accounting and size of the expenditure vary. As shown in Table 1, each of the overall ANOVA models is statistically significant at the p<0.01 level; the F statistic for each overall model ranges from 6.177 to 7.618, depending on which variable is treated as the dependent variable. The variance accounted for (adjusted R2) by these regression equations ranges from 13.1% to 16.2%.

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Table 1 ANOVA models DV:Q1

DV:Q2

Adj R2=0.131

Adj R2=0.162

Sum of

F-stat

Squares

Sum of

F-stat

Squares

Model

36.568

6.177***

54.462

7.618***

Method

6.309

3.197*

2.572

1.079

Size

11.693

5.925**

18.726

7.858***

Interaction

19.788

10.027***

34.111

14.314***

Note. ***p-value<0.01; **p-value <0.05; *p-value <0.10

Accounting Method Hypothesis 1 of the study suggests that investors’ responses will differ as accounting treatment of the intangible-related transactions differs. The independent variable method is marginally significant when Q1 is treated as the dependent variable. The F-statistic for the independent variable accounting method is 3.197 and 1.079 when Q1 and Q2 respectively are treated as the dependent variable. The variable is significant at the p-value < 0.10 level when Q1 is considered the dependent variable. Thus, Hypothesis 1 is not rejected. Method of accounting significantly accounts for the variance in investors’ responses. The marginally statistically significant independent variable method indicates that investors will not perceive the benefit of a company engaging in identical intangible-related transactions the same if they are accounted for differently.

Size Hypothesis 2 of the study suggests investors’ responses will differ as size of the intangible-related transactions differs. The independent variable size is statistically significant in

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each of the ANOVA models, indicating that Hypothesis 2 should not be rejected. The F-statistic for this variable is 5.925 and 7.858 when Q1 and Q2 respectively are treated as the dependent variable. Each of these F-statistics has a p-value < 0.05. Thus, size (or amount) of a company’s intangible-related transactions significantly accounts for the variance in investors’ responses. As size of the expenditure varies, investors’ expected benefit from the expenditure varies. The statistically significant independent variable size indicates that investors do not perceive that the future effects on income from engaging in intangible-related transactions of small size to be the same effects as those transactions of a large size.

Interaction Variable (MethodXSize) Hypothesis 3 postulates that the combination of accounting treatment and size of an intangible-related expenditure affects investors’ perception of its future benefit. The interaction of these two independent variables method and size is found significant in each ANOVA model. The F-statistic for the interaction variable is 10.027 and 14.314 when Q1 and Q2 respectively are treated as the dependent variable. Each of these F-statistics has a p-value < 0.01. Investors’ perception of the expenditure’s benefit depends upon the condition of the other independent variables in the regression equation. Investors’ expected benefit of the expenditure does not depend solely on the method of accounting for the expenditure or the size of the expenditure, but rather on the combination of the two. Thus, Hypothesis 3 is not rejected. Alone, the marginally statistically significant independent variable method indicates that investors will not perceive the benefit of a company engaging in identical intangible-related transactions the same if they are accounted for differently. Also, considered alone, the statistically significant independent variable size indicates that investors do not perceive that the future effects on income from engaging in intangible-related transactions of small size to be the same effects as those transactions of large size. However, neither of these statistically significant variables alone truly reveals how investors perceive a company’s intangible-related expenditures. It is the interaction variable that offers the most meaningful information to the international accounting world. The statistically significant interaction variable found in each of the predicted regression equations indicates that

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an investor’s perception of the benefit of an expenditure for intangibles does not depend merely on how it is accounted for or the size of it, but rather on the combination of the two. The findings of this study indicate that how investors perceive the future benefits of an intangible-related expenditure depends not only on how the expenditure is accounted for, but also on the size of the expenditure. While the substance of these transactions is identical, their perceived benefits on future earnings may be quite different. The ANOVA results indicate that the variable accounting treatment is not statistically significant at the p < 0.05 level when Q1 or Q2 is treated as the dependent variable. This variable accounting treatment is however significant at the p < 0.10 level when Q1 is treated as the dependent variable. The independent variable size is significant at the p < 0.05 level when Q1 is treated as the dependent variable and at the p < 0.01 level when Q2 is treated as the dependent variable. However, these findings are somewhat meaningless since the interaction of accounting treatment and size is found significant. The interaction term accounting treatment X size is significant at the p < 0.01 level regardless whether Q1 or Q2 is treated as the dependent variable. This finding indicates that an investor’s perception of the benefit of an expenditure for intangibles does not depend merely on how the expenditure is accounted for, or the size of the expenditure, but rather on the combination of the accounting treatment and size of the expenditure.

Pairwise Comparisons In order to further understand the meaning of the statistically significant interaction term of the ANOVAs, pairwise comparisons of manipulated groups were conducted, revealing exactly where differences among groups exist. Simple t-tests reveal differences among the following four groups: IFRS treatment of a large expenditure, IFRS treatment of a small expenditure, GAAP treatment of a large expenditure, and GAAP treatment of a small expenditure. A statistical difference exists between groups that treat the expenditure as an asset (IFRS treatment). A large expenditure accounted for as an asset is perceived significantly more beneficial than a small expenditure that is accounted for as an asset. However, an expenditure that is accounted for as an expense (GAAP treatment) is not perceived differently based on size.

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The perceived benefit of a large versus small expense does not statistically differ. In other words, a large amount expensed for development is perceived no more beneficial by investors than a small development cost that is expensed. However, if this expenditure has been capitalized, the large expenditure would have been perceived more beneficial than the small expenditure. While these expenditures are identical in nature, their perceived benefits differ as size and accounting treatment of the expenditures differs. Investors do not perceive the future benefits of a large expense differently than the future benefits of a large asset. Both are perceived to have positive benefits on future earnings. Based on this finding, if a company has large development cost expenditures, investors will perceive the future benefit of these expenditures in the same manner, regardless of accounting treatment. However, small expenditures are viewed differently by investors based on accounting treatment. A small expense is perceived to be more beneficial relative to a small asset. Perhaps, investors perceive a small asset as insignificant when comparing it to the other assets and total assets of a company. This combination of IFRS treatment and small size is the only group perceived by investors as having a somewhat negative effect on the company; it is this group that has a mean score of less than 5.5. Although the small expenditures are identical in nature, because they are accounted for differently, investors perceive their future benefits differently. These pairwise comparisons reveal that investors often perceive identical transactions differently depending on how they are accounted for. It is the combination of accounting treatment and size of the expenditure that accounts for how investors perceive the future benefit of expenditures. If multinational companies’ financial statements are going to be comparable, convergence is needed so that all companies will be accounting for these expenditures in a manner that reflects the true underlying nature of these transactions.

Conclusion The purpose of this study is to determine if method of accounting for intangible-related transactions matters. Different countries have conflicting acceptable ways of accounting for intangible expenditures. With the international marketplace becoming more united, the IASB strives to create standards that will establish international accounting consensus. If company’s

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financials are going to be compared internationally, arguably they need to be in the same financial language. If different countries are accounting for transactions differently, comparability is hindered. Conversely, according to the efficient market hypothesis, if two transactions are identical but they are accounted for differently, investors will be efficient in understanding the substance of the transaction as long as full disclosure of the transaction is made. Therefore, the first question posed in this study is whether method of accounting of intangible-related transactions influences investors’ perceived benefit of the expenditure. A second question of interest is whether a large expenditure is perceived by investors to have the same benefits as a small expenditure. The results of factorial ANOVA indicate that investors’ perceptions of value of intangible-related expenditures are affected by the method of accounting, even when full disclosure of the nature of the transaction is made. Their perceptions of the benefits of an expenditure are influenced by the accounting treatment of the expenditure. When an expenditure reduces net income, a large expenditure is perceived no differently than a small expenditure. However, when an expenditure is capitalized, investors perceive a large expenditure to have a more beneficial effect on future earnings relative to a small expenditure. When companies are engaging in large intangible-related expenditure, accounting method does not influence investors’ perceptions of future benefit of the expenditures. However, if the company has small intangible-related expenditures, accounting treatment significantly influences investors’ perception of their benefits. Even if the substance of intangible-related expenditures is identical, investors are influenced by the accounting method of the expenditure when analyzing its expected benefit on future earnings. It is the combination of both size and accounting treatment of the expenditure that determines investors’ perceived benefit on companies’ intangible-related expenditures. Therefore the IASB needs to resume efforts on developing international consensus on how to properly account for intangible-related expenditures, specifically development costs. A limitation of this paper relates to the fact that different markets have different levels of efficiency. When developing international consensus of standards, the IASB must recognize that not all markets will have the same level of efficiency in incorporating all publicly available information into stock prices. Although different markets (UK and US) were used in the

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experiment, all the subjects are US citizens and part of the US marketplace. Future research could employ subjects from different markets to investigate whether results differ. A future research idea stemming from this research is to determine empirically through an archival study if these expenditures related to development costs do have potential future value and should therefore be capitalized, or if their benefits are exhausted upon incurrence and should therefore be expensed. The results of our study indicate that investors view these expenditures—material or immaterial and capitalized or expensed—positively, and anticipate future benefits to flow from them. However, the degree of benefit differs as accounting method and size of the expenditure differ. Future archival studies could investigate the actual market’s reaction to these expenditures as well as attempt to capture if future benefits actually flow into subsequent periods as a result of these expenditures. Another future research idea is to test whether the deductibility for tax purposes of expensed intangibles influences how companies account for their intangibles. The primary motivator for railroads to begin accounting for depreciation expense was its deductibility for tax purposes. In Japan, currently the majority of companies immediately write off goodwill arising from consolidation against current earnings in order to get a deduction for tax purposes. A tax effect may be influencing factor in how companies account for intangibles. Given the option to do so and holding all other factors constant, companies with high taxable income seem more prone to expense intangibles relative to companies with little or no taxable income. However, a great disparity between financial accounting and tax accounting exists. Therefore, merely because GAAP allowed the capitalization of certain intangibles, the IRS would not automatically mandate similar capitalization. Author Biography V. Brooks Poole, CPA, CIA, is an instructor of financial accounting and taxation at Mississippi College in Clinton, MS. His research focus is practitioner-geared topics in taxation and international financial accounting. Specific areas of research interest include estate taxation and planning, federal and state income tax planning, international convergence, and ethics in financial accounting.

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References Abrahams, T. , & Sidhu, B. K. (1998). The role of R&D capitalization in firm valuation and performance measurement. Australian Journal of Management, 23(2), 169-183. Alford, A., Jones, J., Leftwich, R., & Zmijewski, M. (1993). The relative informativeness of accounting disclosures in different countries. Journal of Accounting Research, 31, 183223 Amir, E., & Lev, B. (1996). Value-relevance of nonfinancial information: The wireless communications industry. Journal of Accounting and Economics, 22, 3-10. Ballester, M., Garcia-Ayuoso, M., & Livnat, J. (2003). The economic value of the R&D intangible asset. European Accounting Review, 12(4), 605-633. Barth, M., Clement, M., Foster, G., & Kanznik, R. (1998). Brand values and capital market valuation. Review of Accounting Studies, 3(1-2), 41-68. Barth, M., & Clinch, G. (1998). Revalued financial, tangible, and intangible assets: Associations with share prices and non-market-based value estimates. Journal of Accounting Research, 36, 199-247. Barth, M., Kasznik, R., & McNichols, M. (2001). Analysts coverage and intangible assets. Journal of Accounting Research, 39(1), 1-34. Bublitz, B., & Ettredge, M. (1989). The information in discretionary outlays: Advertising, research, and development. The Accounting Review, 64, 108-124. Canibano, L., Garcia-Ayuso, M., & Sanchez, P. (2000). Accounting for intangibles: A literature review. Journal of Accounting Literature, 19, 102-103. Chan, S., Martin, J., & Kensinger, J. (1990). Corporate research and development expenditures and share value. Journal of Financial Economics, 26, 255-276. Choi, W., Kwon, S., & Lobo, G. (2000). Market valuation of intangible assets. Journal of Business Research, 49(1), 35-45. Cockburn, I., & Griliches, Z. (1988). Industry effects and appropriability measures in the stock market’s value of R&D and patents. American Economic Review, 78, 419-423. Daimler Chrysler. (2006). Interactive annual report: Transition to International Financial Reporting Standards (IFRS). Retrieved from

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International Accounting Standards Board. (2004a). International accounting standard 36: Impairment of assets. London, UK: Author. International Accounting Standards Board. (2004b). International accounting standard 38: Intangible assets. London, UK: Author. Jordan, C. E., & Clark, S. J. (2004). Capitalizing interest: What does “material” mean? Journal of Corporate Accounting and Finance, 16, 59-64. Kallapur, S., & Kwan, S. Y. S. (2004). The value relevance and reliability of brand assets recognized by U.K. firms. The Accounting Review, 79(1), 151-172. Lev, B. (1999). R&D and capital markets. Journal of Applied Corporate Finance, 11(4), 21-35. Luft, J. L., & Shields, M. D. (2001). Why does fixation persist? Experimental evidence on the judgment performance of expensing intangibles. The Accounting Review, 76(4), 561-587. Mather, P. R., & Peasnell, K. V. (1991). An examination of the economic circumstances surrounding decisions to capitalize brands. British Journal of Management, 2(3), 151164. Millan, M. A. (2005). Accounting for research and development costs: A comparison of U.S. and international standards. Review of Business, 26(2). Radebaugh, L. H., Gray, S. J., & Black, E. L. (2006). International accounting and multinational enterprises (6th ed.). Chichester, UK: Wiley. Securities and Exchange Commission. (2007). Concept release on allowing U.S. issuers to prepare financial statements in accordance with international financial reporting standards (Release No. 33-8831). Retrieved from https://www.sec.gov/rules/concept/2007/33-8831a.pdf Segelod, E. (1998). Capital budgeting in a fast-changing world. Long Range Planning, 31(4), 529-541. Smith, D. T., Percy, M., & Richardson, G. (2001). Discretionary capitalization of R&D: Evidence on the usefulness in an Australian and Canadian context. Advances in International Accounting, 14, 15-46. Sougiannis, T. (1994). The accounting based valuations of corporate R&D. The Accounting Review, 69(1), 44-68.

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Vorhies, J. B. (2005). The New Importance of Materiality. Journal Of Accountancy, 199(5), 5359. Woolridge, R. (1988). Competitive decline and corporate restructuring: Is a myopic stock market to blame? Journal of Applied Corporate Finance, 1(1), 26-36. Wyatt, A. (2005). Accounting recognition of intangible assets: Theory and evidence on economic determinants. The Accounting Review, 80(3), 967-1003.

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The Attractiveness of Regions as Sites for Global Value Chain Activities: The Impact of Formal Institutions Olumide Ijose Governors State University Anthony Andrews Governors State University

Abstract This paper examines the effect of institutional attractiveness on Global Value Chain (GVC) location decisions. We hypothesize that GVC activity is in part determined by the attractiveness of the formal institutions of countries in a regional classification. We test our hypothesis using data on 26 advanced economies, 17 emerging economies, and 33 Sub-Sahara Africa economies. We used a panel data approach with data covering 8 years and estimated a Random Effect Maximal Likelihood model for each region. Our results support the perspective that regional classifications with more attractive institutions have a greater share of global GVC activity. Keywords: global value chains (GVC); institutional quality; institutional attractiveness; regional abstraction; global business; institutional theory

Introduction This study examines the relationship between the institutional quality of a country and its attractiveness for global value chain (GVC) activities. Firms create value through activities performed in value chains, and over the last 25 years, the practice of outsourcing value chain activities to foreign suppliers has become widespread (Beugelsdijk, Petersen, & Pedersen, 2009; Kotabe & Mudambi, 2009; Coucke & Sleuwaegen, 2008). However, the capacity to engage in value creation, as well as the exploitability of available resources and capabilities, vary by country and are a function of country-level differences in institutional quality. Success in

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optimizing the resources and capabilities available in other countries, can impact a multinational enterprise’s (MNE) transaction costs and competitive advantage in product and consumer markets, through scale economies, shorter learning curves, scope economies, improved differentiation and innovation capabilities, increased ability to adopt and diffuse new learning across the enterprise and to partners, speedier introduction of new products and services, and greater latitude to focus on core capabilities (Hätönen & Eriksson, 2009; ). As such, a firm’s decisions on the dispersal of its value chain activities to take advantage of the best locations and modes, is a critical aspect of strategy implementation that carry significant benefits (Kedia & Mukherjee, 2009). MNE value chain activities have received growing attention from academic researchers examining the forces, reasons, and drivers underlying global value chain location decisions, variations in organizing and governing global value chains, and the outcomes of global value chain activities. In a meta-study of prior publications, Schmeisser (2013) found that the typical empirical study on MNE value chain activities was based on a co-evolutionary perspective that emphasized the multi-directional effects of firm level resources and institutional factors. For example, Chung and Yeaple (2008) found that agglomeration, the clustering of economic activities, had a positive effect on the attractiveness of a location, as the abundance of knowledge helps to ameliorate research and development costs, while Nachum and Zaheer (2005) concluded that information intensity and efficiency seeking are causal factors associated GVC attractiveness. Significantly, though Schmeisser’s (2013) rigorous meta-study identified several theoretical works based on institutional theory, it found just one research effort predicated on it Lewin, Massini, and Peeters (2009), which revealed a trend towards the global sourcing of science and engineering human capital (normative dimension), in innovation intensive industries. As such, significant empirical work is required to test the theory and help us better understand the role institutions at the country level play in attracting MNE value chain activities. Using data on the trade in intermediate goods, we examine, at the global level, the relationship between a country’s institutional quality and its value chain activities. We focus on intermediate goods trade as indicators of GVC formation because fragmented production processes, parts, components and partly manufactured sub-assemblies, have to cross national borders before final goods are assembled (Arndt & Kierzkowski, 2001) and also because of the

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availability of rich international data on intermediate goods trade (Sturgeon & Gereffi, 2009). Applying insights from Henisz and Williamson (1999), we contend that a MNE’s perception of a country’s institutional quality is a proxy for anticipated transaction costs and degree of uncertainty in siting GVC activities in a location, as institutions define the rules of the game for operating in an economy (North, 1990). In essence, the quality of institutional frameworks helps MNE’s understand the transaction costs, such as the potential for opportunism, present in a country (Brouthers, 2002). Thus, institutional frameworks increase certainty by detailing the rules of the game as they are related to political uncertainty (Delios & Henisz, 2000), property rights (Djankov, Glaeser, La Porta, Lopez-de-Silanes, & Shleifer, 2003), the relationship between regulatory rules, legal norms and transaction costs (La Porta, Lopez-de-Silanes, Shleifer, & Vishny, 1998) and the nature of the institutional distance between the home country and host country institutions (Kostova, 1999; Kostova & Roth, 2002). In addition, we apply insights from Peng (2011), that when formal institutions are not well defined, are unclear or fail, informal institutions define the rules of the game. We argue that these implied transaction costs are related to uncertainties associated with the ability of a country’s formal and informal institutions to adequately support value chain activities. Building on insights from institutional theory, we examine the role of institutional constraints in determining the attractiveness of a country’s institutional framework for GVC activities. We employ a measure of institutional quality that captures the effect of formal institutions on a country’s institutional quality and attractiveness. We believe that it is a country’s institutional framework that leads to the perception of its attractiveness to GVC activities. This study contributes to the existing literature in four ways. Empirical studies examining the relationship between institutions and GVC location decisions are rare, though there is a rich body of theoretical literature on the relationship (Gereffi, Humphrey, & Sturgeon, 2005; Kshetri, 2007; Kshetri & Dholakia, 2009). In addition, there is empirical evidence on the relationship between institutions and economic outcomes that suggests that institution quality is a source of comparative advantage (e.g. La Porta et al., 1997, 1998; Acemoglu, Johnson, & Robinson, 2001, 2002). We extend this insight in this paper, and in our analysis, by using a comprehensive measure of the Fraser Institute’s Economic Freedom Index as a proxy for the

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quality of market-facing formal institutions. Any attempt to model institutional differences into an empirical analysis necessarily requires specifying the type of institutions to model. In this paper, we focus on formal institutions that affect business relationships between two economic parties (Acemoglu & Johnson, 2003) and their effect on GVC location decisions. Second, and to the best of our knowledge, our study is the first that employs a conceptual framework with empirical data that extends the analysis of how institutional quality impacts global value chains to the developing countries in Sub-Saharan Africa. Research evidence suggests that the North has better institutions than those of the South (e.g. La Porta et al., 1997, 1998; Acemoglu et al., 2001, 2002) but the extent to which differences in institutional quality affects GVC activities has never been empirically examined for emerging and Sub-Saharan economies in the South. The importance of Sub-Saharan Africa within the global economy lies in its factor endowments: a large and diversified natural resource base, a growing population, and a large land mass, all of which are supportive of MNE GVC activity. The study examines the extent to which institutional quality is a barrier to leveraging the region’s comparative advantages in attracting greater inflows of MNE GVC activity. Third, we use a unique dataset of the trade in intermediate goods that covers a broad range of products, including food and beverages, industrial supplies, fuel and lubricants, capital goods, and parts and accessories of transport equipment. The dataset provides this information for most countries of the world, enabling us to conduct a detailed and rigorous empirical analysis of our hypotheses. We limit our analysis to intermediate and not final goods, because value added in the transition from primary to intermediate goods is more likely to be globally dispersed than for final goods. This level of abstraction also supports the development of policy implications that are applicable to a broader range of countries, including frontier economies that are the source of many primary goods, but are deficient in value adding capability. We employ panel data for 76 countries (26 advanced countries, 17 emerging economies, and 33 Sub-Saharan African countries) for the period from 2002 to 2009 (8 years). We hypothesize that institutional quality has a positive impact on a country’s attractiveness at a GVC location. Specifically, we argue that institutional quality is determined by a set of variables that cut across economies. We hypothesize that the relationship between institutional quality and GVC activities will be strongest in advanced economies and weakest for less advanced

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economies, including those in Sub-Saharan Africa. In essence, we predict (expect) that crosssectional variations exist in the relationship between the quality of institutional frameworks and the extent of GVC activities by region. The remainder of the paper is structured as follows. The literature review presents the theoretical discussion around institutional quality, institutional theory, and GVC location decisions. The methodology section, discusses the statistical methodology and the data used to estimate our model. We report empirical results in the results and discussion section, and end with a summary of the findings and the conclusions emanating from them.

Literature Review The competitiveness of a business is directly related to its ability to control operating costs and to increasing the value that customers perceive in its products. Firms with a global presence have the opportunity to manage their value creation activities by implementing a global value chain strategy. In keeping with the theory of international trade, on the relationship between differences in factor costs and comparative advantage (Porter, 1990), such firms are able to leverage location economies to gain cost and/or differentiation advantages by performing a value creation activity at the optimal location for it. Global firms consider a range of factors in making location decisions. In determining the quality or attractiveness of a location’s institutions, firms typically assess its political, economic (including trade barriers), legal risks, and where relevant, transportation costs. In essence, firms consider the attractiveness of the basic and advanced factors available in a location in making such decisions. Ultimately, firms hope to attain a strategic position on their industry’s efficiency frontier that lowers their cost structure and increases the perceived value of their products, allowing them to build a sustainable competitive advantage relative to firms that locate their value creating activities in one location. The literature clearly demonstrates the link between increasing competitive pressures and the adoption of a global value chain strategy (Buckley & Hashai, 2004; Reich, 1991). At the macro level, institutional quality is function of a country’s rules of the game for doing business. Institutions include a wide range of social structures that provide the arena in

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which economic exchanges occur. Formal institutions are underpinned by a regulatory pillar, and include political systems and the political risk of changes that may adversely affect business operations; legal systems that determine the legal right to use an economic property for business purposes; the manner in which rules, regulations, and laws relating to physical property, contracts, and intangible intellectual property are enacted and enforced; and economic systems that determine the ownership of factors of production, the role of markets and the rules for managing an economy (Peng, 2011). Insights from the political science literature suggest that policy reforms to improve a country’s institutions are often difficult to implement because they result in winners and losers (Alesina, Ardagana, & Trebbi, 2006; Haggard & Kaufman, 1992). In addition, Acemoglu and Robinson (2008), determined that the leadership in countries that are unattractive for GVC activity often have de facto political power, and are generally more likely to repress rather than encourage reforms, and that reforms to improve institutional environments are undertaken only when there is a general consensus on the necessity of reform (Armijo & Faucher, 2002). Though institutional transitions, and thus the rules of the games and modes of exchange, can and do occur (for example China’s transition from a centrally planned to a market oriented economy), they happen slowly, have uncertain outcomes, and are thus not expected to be a significant shortrun drivers of MNE location decisions (Peng, 2003). Given an environment of uncertainty and transaction costs, MNEs consider their perception of the institutional quality on such costs in making GVC location decisions. In essence, the higher the quality of a country’s institutional framework, the higher its comparative arrangement! The literature demonstrates that 1) poor contract protection, and 2) protection of intellectual property rights, and investor rights, are a disincentive to GVC location because they create uncertainty in the manner in which frictions between contracting parties are resolved. These, in turn, lead to rigid labor markets, high tariffs, which serve to reduce labor productivity while introducing high levels of inflation and exchange rate volatility, and create uncertainty about the cost of doing business. Thus, institutions can impact market distortions the more imperfect a country’s institutional framework is, regardless of the ability to move GVC activities to a different location. Institutional quality can enhance or constrain the gains a MNE expects to receive from offshoring and diversifying its GVC activities to take advantage of global

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differences in factors, access to key markets, and in leveraging its strategy for competitive advantage.

Institutional Theory Proponents of institutional theory offer an explanation of how macro-level institutions are created. Early research in institutional theory posited that over time isomorphic pressures in organizational fields create macro level structural conformity that determines a country’s business system (Friedland & Alford, 1991). In order for isomorphic pressure to gain legitimacy, the diffusion of business models, practices, and structures within and across organizational fields must converge over time to create a distinct and observable identity defined by common norms and behavior patterns (Dimaggio & Powell, 1983, 1991; Meyer & Rowan, 1977). Once established, a country’s business system determines whether a country is advantageous or disadvantageous to GVC location. Moreover, institutional frameworks increase certainty by clarifying the rules of the game for firms seeking to perform GVC activities in a foreign country. We subscribe to the general contention that in the quest for competitive advantage, MNEs have the latitude to make GVC location decisions aimed at opportunistically exploiting country differences in market-facing institutions (Dicken, 2003; Kotabe & Murray, 2004). In essence, diversity of institutional systems among countries gives MNEs the ability to pick and choose where to best locate their GVC activities, taking advantage of country-level institutional differences and influences.

Formal Institutions Though there is no singular institutional approach in the literature, there is widespread agreement in the literature that an institutional effect on human behavior and decision making exists. The seminal study in the area focused on how organizations become institutions by becoming infused with values that are beyond the technical prescriptions of an organization’s tasks and activities (Selznick, 1949, 1957). In the 1970s, the “new institutional literature” focused on how organizations are influenced by institutions which resulted in a significant

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amount of research activity. The research stream identified three distinct institutional forces – coercion, imitation, and normative - that affect behavior through the process of isomorphism (DiMaggio & Powell, 1983, 1991). Tenets of new institutional theory have since been widely utilized to deepen our understanding of the external contextual forces that influence technological innovation, knowledge management, and organizational change (Avgerou, 2001; Barley, 1986; Meyer, Brooks, & Goes, 1990). In essence, by positing that institutions determine the rules of doing business in a location, institution theory suggests that the attractiveness of a country’s institutional framework is a determinant of GVC activity. A second approach sought to understand and explain how and why institutional quality differs among countries. For example Chong and Zanforlin (2000) and La Porta et al. (2000), found that the type of legal system in a country is an important determinant of institutional quality, while Islam and Montenegro (2002) found that trade openness is significantly related to institutional quality. De Groot, Linders, Rietveld, & Subramanian (2004) studied the effects of institutions on trade flows and observed a significantly positive relationship between the quality of a country’s formal institutions and trade flows. While North (1990), Kedia and Mukherji, (2009), Dunning, (1998, 1999), and Porter, (1994, 1998) contend that a country’s institutional quality is a product of the attractiveness of its legal, economic, and political environment. Thus, institutional quality is acknowledged as a critical determinant of trade and development. However, we note that the relationship between formal institutions and GVC activities has yet to be examined. Based on insights from the related literature, we contend that formal rules of the game create the institutional quality that is a key consideration in making decisions related to GVC activity. Institutional quality is a good indicator of the attractiveness of a country as a location for GVC activities, because institutional quality can be impartially observed and measured (Slesman, Baharumshahm, & Wohar, 2015). Consequently, we- posit that as pressure to reduce costs and to optimize competitive advantages increases along with advancing globalization of markets, institutional quality will become even more central in making GVC location decisions. In addition, prior research suggests that institutional attractiveness creates winners and losers and that it is reasonable to expect GVC activities to be highest in economies with more attractive arrangements (Buchanan, Le, & Rishi, 2012; Hill, 2015; Lim, 2014). As such, we posit that by

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determining the attractiveness of the rules of the game in individual countries, institutional quality has a direct impact on transaction costs and opportunism, and by logical extension, to the ability of a MNE to deliver value to its customers. We contend that the generalized insights and findings in the literature will operate differently in different countries and different regions of the world. In essence, we expect the quality of institutions to differ based on the unobserved individual effects of historical and contemporary factors, i.e. the error component of the estimated models. For instance, informal institutions have been found to be associated with a country’s institutional attractiveness. Institutional issues are then at the heart of the development process (Perkins, Radelet, & Lindauer, 2012). By aggregating data from the individual country to the regional level, we overlooked differentials that could be examined at the country level. This is a necessary sacrifice in order to examine impacts at the more interesting regional level. As such, in addition to testing the generalized hypothesis below, we hypothesized the direction of each variable at the regional level (see Table 1). Hypothesis: The attractiveness of an economy’s formal institutions is associated with the likelihood of attracting the GVC activities of MNEs. As indicated above, we expect the directional effects of the variables to operate differently in Advanced, Emerging, and Sub-Saharan economies. Stronger governance and institutions help improve the locational choices for investment by reducing risk and increasing profitability; in other words, institutions matter (Alence, 2004; Williamson, 1998). Table1 describes the relationship between formal and informal variables with respect to GVC activities in the locational decisions by MNEs.

Methodology Building on the preceding discussion, our model includes three different types of variables: Global Value Chain (GVC) activity, variables on formal institutions, and control variables. Data were collected from individual countries and then aggregated into groups of

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countries (see Table 2). To measure GVC activities, we utilize data from the United Nations Commodity Trade (UN Comtrade) database, which provides detailed information on international shipments of capital, intermediate, and consumption goods. We proxy GVC activity using intermediate goods; that is, goods used in the production of a final good, because trade in these goods are indicative of GVC activity (Sturgeon, Levy, Brown, Jensen, & Weil, 2006). The UN Comtrade database provides standardized annual, monthly, and quarterly statistics on the import of intermediate goods by country of origin. These data are reported by the importing country and identifies the country of origin of the imported intermediate good, making it a good proxy for international comparisons of GVC value added activity. Since we do not distinguish between customized intermediaries, that is, goods used in the manufacture of one or a few final products and generic intermediaries, following Sturgeon and Gereffi (2009), our approach addresses products used in the production of a wide variety of goods. For institutional variables, we incorporate data from Frasier Institute’s Economic Freedom Index (FEI) as a proxy for the quality of formal institutions. These data, which are available at five-year intervals from 1970 – 2000, and a yearly basis afterwards, provide comprehensive measures of five sub-indices that measure critical country-specific institutional arrangements: 1) expenditure and tax reforms; 2) property and legal reforms; 3) trade reforms; 4) reforms related to access to sound money; and 5) labor, business, and credit reforms. Each of the five sub-indices is based on data for 35 objective indicators measuring the quality of formal institutions for that particular sub-index. These data were used to derive values for qualitative variable sub-indices, whose values ranged from 0 to 10, with 10 representing most favorable for the particular measure. The five sub-indices were then averaged to derive a summary index for each country. A summary final index was then developed that provided a ranking on a scale from 0 (not free) to 10 (totally free) in which the higher value represents a higher degree of institutional presence (or efficiency). In essence, a value of zero (0) denotes the absence of formal institutional arrangements and reduces the attractiveness of an economy, while a value of 10 denotes the presence of high-quality formal institutions that contribute to an economy being open and attractive for foreign direct investment, as well as localized in-country investment.

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The Data and Descriptives We analyzed a panel dataset containing 77 countries, aggregated into three groupings of countries over the years 2002 – 2009. There are several reasons for focusing on this time period. First, our analysis requires data on the characteristics of institutions in the various countries, and these data are readily available for this time horizon. Second, our time horizon for these data begin after 1999 when China initiated its “Go Global” strategy, enabling the UN Comtrade data to capture GVC activities in China. The model is estimated separately for each of three groups (or regimes) of countries: Advanced Economies (outside Sub Saharan Africa and Emerging economies), Emerging Economies (Below Advanced Economies and outside Sub-Saharan economies but including South Africa), and Sub-Saharan Economies (economies in Sub-Saharan Africa, excluding South Africa). This arrangement allows for the estimation of each regime with respect to the interaction of the institutional factors on the determination of indigenous GVC activity. Further, definitions of Emerging and Advanced economies follow designations provided by the International Monetary Fund (IMF), in its World Economic Outlook (WEO), which states, [t]he criteria used by WEO for classifying the global economy into advanced economies and emerging market and developing economies are (1) the size of per capita income levels, (2) the degree of export diversification (oil exporters that have high per capita GDP are not classified as advanced because 70% of its exports are oil and thus, do not satisfy the degree of export diversification in element 2), and (3) the degree of internationalization of their financial systems. (International Monetary Fund, 2012, p. 177) Additional data from various sources were used in estimating models for each of the three groups of countries. Intermediate value added data was collected from the UN Commodity Trade dataset, data on GDP per capita and population are from the World Bank Database, data on educational attainment came from the UNESCO Institute of Statistics, while formal institutional data, was collected from the Fraser Freedom Index. A sample of 26 Advanced Economies (AE), 17 Emerging Economies (EM), and 34 Sub-Saharan Economies (SSA) are employed in our analysis. Again, the time horizon for the analysis is 2002 – 2009, or 8 years.

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Annual data on real GDP, GDP per capita, and Intermediate Goods are converted to US dollars based on 2000 constant prices. Descriptive Statistics are presented in Table 3. It is of particular interest to note that the mean responses for intermediate goods for advanced and emerging economies are very similar, and represent about 1.3 times that of SSA economies’ GVC activity. Impartiality of courts is approximately twice that for advanced economies than those of emerging and SSA economies. The volatility of inflation presents a similar pattern. As would be expected, mean responses of institutional variables in EM and SSA economies are substantially lower than those in advanced economies. For example, the court system in advanced economies is almost 1.75 times more impartial than those in EM and SSA economies, about 1.3 times more effective in the structure of their business regulations, and 1.5 times more effective in assisting business start-up. A critical factor, and one that stands out the most, is mean years of education, where AE’s are almost 2.5 times those of both emerging and SSA economies. Thus, the gap in human capital (investment in educational attainment) is a factor affecting both the productivity potential and wage levels in emerging and SSA economies (Devarajan, Easterly, & Pack, 2003). Given these disadvantages, it is important to see that increasing institutional attractiveness is a critical factor in off-setting the disadvantages just described.

The Model Although country of origin with respect to attractiveness for GVC activity is not well documented with respect to institutional variables, the attractiveness of a country’s location by multinational corporations is based on the a favorable image of a country’s institutional arrangements. In other words, favorable institutional arrangements are a signal to multinational corporations and firms to locate and extend value added to production processes that can produce above normal profits. Ultimately, economies “succeed in particular industries because their home environment is forward-looking, dynamic, and challenging” (Porter, 1998, p. 155). Our research considers the impact of institutional arrangements as critical in attracting firms to extend value-added in a country's competitive advantage area(s).

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We focus on the effect of determinants of institutional quality on an international business outcome namely, GVC activity. The central implication of our model is that differences in institutional quality affects locational attractiveness for GVC activity, and while there is no consensus on the specificity of institutional determinants, we add to the literature with respect to our consideration and choice of variables. We therefore specify the standard semi-log linear form in which the model is estimated for the 2002 - 2009 period by: ivai,j = αi,j + x’I,j ßi,k + Z’i,m γi, k+1-m + εi,t

Eq. 3.1

where the dependent variable IVA is an indicator of global value chain activity (intermediate value added); x’I,j , is a matrix of formal institutional variables; and Z, a matrix of control variables, where i refers to region (i = 1,2, 3), and t, refers to time (t = 2000 – 2008). The intercept term, αi,j , is randomly distributed, that is: αi,j = αi + ui

Eq.3.2

Our model is a semi-log function given as: ln(iva) = ß0 +

ß1 impcourtsi,j + ß2 stdinflationi,j

ß5 busregi,j

ß6 startbusi,j

ß9 ln(gdpcapi,j)

ß7 taxintrdi,j

ß10 edmeanyrsi,j

ei,j

ß3 stdtariffi,j +

ß4 minwagei,j

ß8 ln(popi,j) Eq. 3.3

Where iva is intermediate value added, impcourts is impartial courts, stdinflation is the standard deviation (or volatility) of inflation, stdtariff is the standard deviation of tariffs, minwage is the minimum wage, busreg is business regulations, stratbiz is the ease of starting a business, tasntrd is taxes on trade, logPOP is the log of population, edmeanyrs is the mean years of education, and ei,j is the i.i.d. error term. The parameters of independent logarithmic variables represent elasticities. We include a matrix of control variables (Z), the vector of which includes other potential determinants of GVC activity, which we obtain from the extant literature on the subject. That is, we control for population based on the standard premise - the larger a country’s population, the greater the implicit pressure to create stable institutions. Indeed, the political science literature has demonstrated that country size is a robust predictor of civil war and political repression (Hegre & Sambanis, 2006; Landman, 2005). To measure the impact of educational attainment, we include the mean number of years of education attained in each country for each regime, as

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levels of education have been shown to be related to institutional attractiveness (Hanushek & Wöβmann, 2007). The model thus consists of three sets of data: Advanced Economies (AE), Emerging Economies (EM), and Sub-Saharan African economies (SSA). Statistically, we can estimate a Random Effects, a Between Effects or a Fixed Effects model. These data do not include explanatory variables that are fixed over time, such as race, and as such the Between Effects model is not applicable (Ashley, 2012; Baltagi, 2013). However, if the errors are generally heteroskedastic and/or serially correlated across t, a more general estimator of the variancecovariance matrix can be used. Thus, Generalized Least Squares (GLS) estimation of the Random Effects is presented in Eq. (3.1). Under GLS regression, the variance-covariance matrix depends only on two parameters,

  and   , regardless the size of the number of observations (Wooldridge, 2002). In addition, the Random Effect Maximal Likelihood can be more efficient under the homogeneity and stationarity assumptions if  i, j is random. As a result of a series of robust diagnostic tests, the Hausman test and the Breusch and Pagan Lagrangian multiplier test for random effects, we assessed the hypothesis using the efficient Random Effects test (Hisao, 2014).

Results and Discussion We estimate Eq. 3.1, a purely contemporaneous formulation, using linear panel data models to test the Hypotheses. Our models use variables that include institutional and macrolevel variables in their specification. We model three regimes of country classifications (Advanced, Emerging, and Sub-Saharan economies) separately and examined the independent effects of each regime’s impact on their intermediate value-added. Table 4 presents the results for Advanced Economies (AE), Emerging Economies (EM), and Sub-Saharan Africa (SSA) countries in our sample. Our results provide support for the institution based view that the attractiveness of institutional frameworks is a determinant of GVC activity, as firms consider institutional quality in making GVC location decisions (Cantwell, Dunning, & Lundan, 2010; Kim & Prescott, 2005).

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Estimation signs were as expected with respect to AE’s with the exception of the minimum wage where the magnitudes of some of the parameters are small. In addition, only four variables were significant: inflation, population, GDP per capita, and mean years of education. For EM economies, we find all parameter signs are as expected, with the exception of the volatility of inflation and taxes on trade. Level of significance for variables 10% and below are inflation, ease of starting a business, minimum wage, population, and GDP per capita. Similarly, results for Sub-Sahara Africa (SSA) economies are of the predicted directions, again illustrating the relationship between institutional attractiveness and GVC activity. However, only the effects of population size and GDP per capita are statistically significant. An examination of the results follows: Result one. The legal system has a positive effect on GVC activity in Advanced Economies and Emerging Economies. However, the impartiality of the legal system in the period under review had a negative effect in Sub-Saharan Africa. This finding suggests that greater protection of property rights and intellectual property, fairer contract enforcement, and more transparent, fair, and reliable adjudication of disputes between contracting parties, e.g. partnerships, will result in increasing attractiveness for international business (La Porta et al., 1998). Since many of the SSA economies rank low on other indices of impartiality, such as the widely regarded Transparency International Corruption Perception Index we expect impartial courts to have a greater positive impact than on advanced economies in comparable areas of production. The data thus supports this hypothesis in each region with respect to the direction of signs, though the magnitude of change is small in each of them and is not significant in any. Result two. The volatility of inflation is expected to have a negative impact in advanced countries, where buyer demand can be expected to be more sensitive to price increases. We expect moderate inflation to have a positive effect on GVC activity in Emerging and Sub-Sahara Africa economies, as increasing prices is indicative of a business environment that is supportive of higher margins. In essence, we posit that as long as the magnitude of change is small, in Emerging and Sub-Saharan Africa economies, higher inflation suggests 1) improved returns to higher labor productivity, product quality and reliability, and 2) a growing economy. The data

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supports this hypothesis in each region. The effect of volatile inflation is significant at the 5% level for Advanced Emerging Economies and at the 10% level for Emerging Economies. Result three. Tariffs are expected to have a negative effect on GVC activity (De Santis, Mercuri, & Vicarelli, 2003). This is supported in advanced economies but not in emerging and SSA economies. The results are not significant in any region. The insignificant results indicate that the standard deviation of tariffs, which measures the volatility in tariff rates, may not be a determinant of GVC activity. In order for us to verify this, we need to examine the means, medians, and ranges of these standard deviations. In addition, we might want to look at these standard deviations in terms of quartiles or quintiles. For example, if tariffs are consistently high or low, this implies very little volatility and that this small volatility may not be a determinant of value added. On the other hand, if the volatility of taxes on trade is high, it may be a determinant of value added. In other words, we have to understand what the standard deviation is actually measuring. That is, what are the characteristics of the volatility of the measures? From what we observe in the results, Advanced Economies have the lowest volatility of taxes on trade with a coefficient of 5.6%, whereas Emerging Economiesâ&#x20AC;&#x2122; coefficient is 12.7%, and that for SSA Economies is a negative 25%. Both Emerging and SSA economies have higher volatility rates relative to the Advanced economies; however, the negative sign of SSA economies may be due to the fact that such an abnormally high volatility induces strongly inverse expectations as to expectations about taxes on trade; thereby, acting as a deterrent for locating in countries with such institutional characteristics. Result four. Minimum wages are expected to have a negative effect in advanced economies and a positive effect in the other two regions. In advanced economies, higher minimum wages suggest pressure to shift from manufacturing lower margin intermediate goods to higher margin final products and into services. However, the result for advanced economies was in the opposite direction and may reflect higher productivity negating the effect of higher minimum wages. For example, Card and Krueger (1994) in their study of the fast food industry in the states of New Jersey and Pennsylvania found no effect of an increase in the minimum wage on employment. More recently, Schmitt (2013), reviews research since 2000 and

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concludes that “the cost shock of the minimum wage is small relative to most firms' overall costs and only modest relative to the wages paid to low-wage workers” (p. 24). In addition, employers have many other channels of adjustment rather than focusing on wage increases; for example employers can reduce working hours, non-wage benefits, or training. Employers can also shift the composition toward higher skilled workers, cut pay to more highly paid workers, take action to increase worker productivity (from reorganizing production to increasing training), increase prices to consumers, or simply accept a smaller profit margin. Workers may also respond to the higher wage by working harder on the job. But, probably the most important channel of adjustment is through reductions in labor turnover, which yield significant cost savings to employers. In emerging and SSA economies, a lower minimum wage, is expected to have a positive effect on GVC activity, as it signals the possibility of a lower cost structure. As hypothesized, the effect of small, but incrementally higher, minimum wages is positive for Emerging and SubSahara Africa economies, though it is only significant for Emerging Economy’s. This finding substantiates the results of previous studies in the literature, since the type of manufacturing based GVC activity in these regions tend to be low to semi-skilled and labor intensive. Result five. Increasing regulation of business activity is expected to have a negative effect on GVC activity (Borrmann, Busse, & Neuhaus, 2006). Even though this is supported by the results, the statistics are not significant. However, the finding does elicit a few comments and suggests a need for further investigation into the relationship between business regulation and attractiveness as a destination for GVC activity. The magnitude of the relationship is quite large in Advanced Economies and in Sub-Sahara Africa, and lowest in Emerging Economies. In Sub-Sahara Africa, we posit that the level of bureaucracy is tied to bureaucratic corruption activity whereby officials demand a bribe for reviewing and signing off on paperwork. In Advanced Economy, we posit that increased regulation is a function of efforts to protect the environment, to protect consumers, to guard against tort based legal exposure, and to ensure that businesses compete on a level playing field. We also consider that the lower level of regulation in Emerging Economy may be a deliberate strategy aimed at reducing the cost of doing business.

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Result six. Following the insights of Capelleras, Mole, Greene, & Storey (2008), the ease of starting a business is expected to have a positive effect on GVC activity. The hypothesis is supported in each region and is strongly significant in Emerging and Sub-Saharan Africa economies. The finding is supported by recent research and confirms the policy goal of making the process of starting a new business efficient and effective. This finding is perhaps more important for countries in the SSA region that have the most procedures for starting new businesses and more bottlenecks in the process. Such countries may need to make the regulatory processes involved more efficient. These include factors such as the number of days required to incorporate a business, the time it takes to connect electricity, Internet, telephone, and water services and having to pay a bribe (Corcoran & Gillanders, 2015; Munemo, 2015). Result seven. Surprisingly, taxes on international trade had a negative effect only in Advanced Economies and none of the coefficients were significant. The direction may however be due to the structure of particular markets. Since cost structures are higher in the markets in Advanced Economies, it stands to reason that higher taxes might be a disincentive to lower skill requirement GVC activities. For Emerging and Sub-Saharan Africa economies, we theorize that cost structures are such that higher taxes on international trade may not create significant disincentive to GVC activity. We also consider that in support of the Infant Industry Argument, higher taxes may be a deliberate barrier established by policy makers to protect export oriented GVC activities. In addition, if overall cost structures render a good relatively inelastic, the impact of higher taxes may be insignificant, which could be the case since there may be no close substitutes available; the tax is seen as part of the price and higher taxes may continue to elicit a positive effect on GVC activity, up to a threshold undetermined in this research. Result eight. The effect of population size is in the hypothesized direction and is extremely significant and positive in all regions (see Sethi, Guisinger, & Berg, 2003). We contend that population is indicative of the size of a labor market and signals the possibility of generating positive economies of scale, experience, and learning effects, since the production of intermediate goods is labor intensive, even in world-class size, capital intensive factories. This finding suggests that countries with larger populations are likely to be the most attractive for

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GVC activities, everything being equal. However, the study did not examine the population level at which attractiveness is enhanced, also everything being equal, and this is a topic that may be worthy of further research. In essence, to what extent does China, with a population that is over one billion, have a competitive advantage in attracting GVC activities, relative to a country like Nigeria (with a population that is estimated at over 150 million), assuming that other indicators of their institutional attractiveness are roughly similar. Result nine. Increased purchasing power, as measured by GDP per capita, is expected to have a positive effect on GVC activity. Income size suggests the level of effective demand for final products and thus increased downstream demand for intermediate (GVC) inputs. The effect is in the hypothesized direction and is extremely significant and positive in all regions. The finding suggests that domestic demand for intermediate goods is positively related to domestic purchasing power. This could be an important finding because it is indicative of a capability to produce for domestic consumption that may serve to shield a country from the full effects of negative global economic conditions. The research did not explore this effect at different income levels, and did not account for a country that may elect to execute an export oriented strategy regardless of relative domestic purchasing power. It also did not account for the extent to which domestic consumption of domestically produced intermediate value added goods can insulate a country from the negative effects of downswings in the global economy, and indeed, from the magnitude of such downturns. Result ten. Increased years of schooling is expected to have a negative effect on GVC activity in advanced economies, because the returns to schooling are expected to be higher in advanced manufacturing and value added services, and not in the production of intermediate goods on this region. Similarly we expect increases in schooling to have a negative impact on GVC activity in Emerging Economies, though we expect the effect to be much smaller than for Advanced Economies. This is because we expect the substitution effect of moving from producing lower value added intermediate goods to producing finished products and services to be at a much lower stage in Emerging Economies, relative to Advanced Economies. The coefficients supported both directions and were strongly significant for Advanced Economies.

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We contend that the insignificant findings for Emerging Economies may be indicative of the beginning of a shift towards producing finished products. The expectation of a positive relationship between educational attainment and GVC activity was supported for Sub-Saharan Africa economies. However, the coefficient was not significant suggesting that the current stock of human capital were not deemed determinants of Intermediate Value Added activity in these economies.

Summary and Conclusions Our results using a balanced data set add to the research on GVC analysis and with the inclusion of differentiated regional comparisons, add to the research stream. More importantly, by including data on Sub-Saharan economies, an additional research stream is identified. Though the effects of some of the coefficients are small, they are typically in the hypothesized direction! That we cannot be conclusive on the direct impact of the institutions studied, suggests a need to conduct confirmatory research in future years (especially in the case of Sub-Saharan Africa), when the availability of additional data points can be expected to further support the identification of structural/institutional constraints to GVC activity. Our understanding will likewise be enriched by an estimation of the role of the informal environment (political systems and societal culture), as well as a deeper analysis of effect of corruption and legal systems; especially the nature of property rights, the enforcement of contracts, and the protection of intellectual property. Though suitable variables are available in databases such as the World Bank’s Doing Business, the data does not begin to systematically include sub-Saharan Africa economies until the late 2000’s, and as such, do not provide enough data points at this time for a significant empirical analysis. In essence our study represents an examination of fairly static conditions; their underpinnings need to be further explored to provide a comprehensive picture and a richer predictive capacity.

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Author Biographies Dr. Olumide Ijose is an Associate Professor of Management and MBA Program Coordinator at Governors State University, where teaches graduate and undergraduate courses in International Business, International Business Strategy and Strategic Management. He has published in the areas of knowledge management, cross-cultural issues, and strategic human resource management. His current research interests are in global value chain location and governance models, multinational corporations in the extractive and natural resource sectors, and the role of public private partnerships in economic development. Dr. Anthony Andrews is an Associate Professor of Economics and Director of the International Business and Global Trade Research Institute at Governors State University, where he teaches graduate and undergraduate courses in Managerial Economics. He has published in the areas of Development Economics and Economic Growth. His current research interests are unemployment, church growth, and location theory. References Acemoglu, D., & Johnson, S. (2003). Unbundling Institutions. Unpublished manuscript, Cambridge, MA: Massachusetts Institute of Technology. Acemoglu, D., Johnson, S., & Robinson, J. (2001). Colonial origins of comparative development: An empirical investigation. American Economic Review, 91, 1369–1401. Acemoglu, D., Johnson, S., & Robinson, J. (2002). Reversal of fortune: Geography and institutions in the making of the modern world income distribution. Quarterly Journal of Economics, 117, 1231–94. Acemoglu, D., & Robinson, J. (2008). Paths of economic and political development. In B. Weingast & D. Wittman (Eds.), Handbook of political economy. Oxford, UK: Oxford University Press. Alence, R. (2004). Political institutions and developmental governance in Sub-Saharan Africa. The Journal of Modern African Studies, 42(2), 163-187.

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Alesina, A., Ardagana, S., & Trebbi, F. (2006). Who adjusts and when? The political economy of reforms (IMF Staff Papers 53). Washington, DC: The International Monetary Fund. Arndt, S., & Kierzkowski, H. (Eds.). (2001). Fragmentation: New production patterns in the world economy. Oxford, UK: Oxford University Press. Armijo, L. E., & Faucher, P. (2002). ‘We have a consensus’: explaining political support for market reforms in Latin America. Latin American Politics and Society, 44(2), 1-40. Ashley, R. A. (2012). Fundamentals of applied econometrics. Danvers, MA: Wiley. Avgerou, C. (2001). The significance of context in information systems and organizational change. Information System Journal, 11, 43-63. Baltagi, D. (2013). Econometric analysis of panel data. West Sussex, UK: Wiley. Barley, S. R. (1986). Technology as an occasion for structuring: Evidence from observations of CT scanners and the social order of radiology departments. Administrative Science Quarterly, 31, 78-108. Beugelsdijk, S., Pedersen, T., & Petersen, B. (2009). Is there a trend towards global value chain specialization? — An examination of cross border sales of US foreign affiliates. Journal of International Management, 15(2), 126-141. Borrmann, A., Busse, M., & Neuhaus, S. (2006). Institutional quality and the gains from trade. Kyklos, 59(3), 345-368. Brouthers, K. D. (2002). Institutional, cultural and transaction cost influences on entry mode choice and performance. Journal of International Business Studies, 33(2), 203-221. Buchanan, B. G., Le, Q. V., & Rishi, M. (2012). Foreign direct investment and institutional quality: Some empirical evidence. International Review of Financial Analysis, 21, 81-89. Buckley, P.J., & Hashai, N. (2004). A global systems view of firm boundaries. Journal of International Business Studies, 35(1), 33-50. Cantwell, J., Dunning, C., & Lundan, S. (2010). An evolutionary approach to understanding international business activity. Journal of International Business Studies, 41, 567-586. Capelleras, J., Mole, K. F., Greene, F. J., & Storey, D. J. (2008). Do more heavily regulated economies have poorer performing new ventures? Evidence from Britain and Spain. Journal of International Business Studies, 39, 688-704.

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Card, D., & Krueger, A. B. (1994). Minimum wages and employment: A case study of the fastfood industry in New Jersey and Pennsylvania. American Economic Review, 84(4), 77293. Chong, A., & Zanforlin, L. (2000). Law tradition and institutional quality: Some empirical evidence. Journal of International Development, 12(8), 1057-1068. Chung, W., & Yeaple, S. (2008). International knowledge sourcing: Evidence from US firms expanding abroad. Strategic Management Journal, 29(11), 1207-1224. Corcoran, A., & Gillanders, R. (2015). Foreign direct investment and the ease of doing business. Review of World Economics, 1, 103-126. Coucke, K., & Sleuwaegen, L. (2008). Offshoring as a survival strategy: Evidence from manufacturing firms in Belgium. Journal of International Business Studies, 39(8), 12611277. de Groot, L. F., Linders, G., Rietveld, P., & Subramanian, U. (2004). The institutional determinants of bilateral trade patterns. Kyklos, 57(1), 103-123. Delios, A., & Henisz, W. J. (2000). Japanese firms' investment strategies in emerging economies. Academy of Management Journal, 43(3), 305-323. De Santis, R., Mercuri, M. C., & Vicarelli, C. (2003). Taxes and location of foreign direct investment: An empirical analysis for the European Union countries. Economia, Società e Istituzioni, 15(1). Devarajan, S., Easterly, W. R., & Pack, H. (2003). “Low investment is not the constraint on African development,” Economic Development and Cultural Change, 51(3), 547-71. Djankov, S., Glaeser, E., La Porta, R., Lopez-de-Silanes, F., & Shleifer, A. (2003). The new comparative economics. Journal of Comparative Economics, 31(4), 595-619. Dicken, P. (2003). Global shift (4th ed). London, UK: Sage. DiMaggio, P., & Powell, W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48, 147– 160. DiMaggio, P., & Powell, W. (Eds.). (1991).The iron cage revisited: institutional isomorphism and collective rationality in organizational fields. The new institutionalism in organizational theory. Princeton, NJ: Princeton University Press.

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Dunning, J. (1998). Location and the multinational enterprise: A neglected factor. Journal of International Business Studies, 29(1), 45-66. Dunning, J. (1999). Globalization and the theory of MNE activity. In N. Hood & S. Young (Eds.), The globalization of multinational enterprise activity (pp. 45-65). London, UK: Macmillan. Gereffi, G., Humphrey, J., & Sturgeon, T. (2005). The governance of global value chains. Review of International Political Economy, 12(1), 78-104. Friedland, R., & Alford, R. R. (1991). Bringing society back in: Symbols, practices, and institutional contradictions. In W. W. Powell & P. J. DiMaggio (Eds.), The new institutionalism in organizational analysis (pp. 232–263). Chicago, IL: University of Chicago Press. Haggard, S., & Kaufman, R. R. (1992). The politics of adjustment. Princeton, NJ: Princeton University Press. Hanushek, E. A., & Wöβmann, L. (2007). The role of education in economic growth (World Bank Policy Research Working Paper No. 4122). Washington, DC: The World Bank. Hätönen, J., & Eriksson, T. (2009). 30+ years of research and practice of outsourcing – Exploring the past and anticipating the future. Journal of International Management, 15(2), 142-155. Henisz, W. J., & Williamson, O. E. (1999). Comparative economic organization - Within and between countries. Business and Politics, 1(3), 261-277. Hegre, H., & Sambanis, N. (2006). Sensitivity analysis of empirical results on civil war onset. The Journal of Conflict Resolution,50(4), 508-535. Hill, C. (2015). International business: Competing in the global market place. New York, NY: McGraw Hill Education. Hodgson, G. (2006). What are institutions? Journal of Economic Issues, 40(1), 1-25. Hisao, C. (2014). Analysis of panel data. New York, NY: Cambridge University Press. International Monetary Fund. (2012). World Economic Outlook: Statistical Appendix. Washington, DC: Author. Islam, R., & Montenegro, C. (2002). What determines the quality of institutions?” (Working Paper No. 2764). Washington, DC: World Bank Policy Research.

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Kedia, B. L., & Mukherjee, D. (2009). Understanding offshoring: A research framework based on disintegration, location and externalization advantages. Journal of World Business, 44(3), 250-261. Kim, B., & Prescott, J. (2005). Deregulatory forms, variations in the speed of governance adaptation, and firm performance. Academy of Management Review, 30, 414-425. Kotabe, M., & Mudambi, R. (2009). Global sources and value creation: Opportunities and challenges. Journal of International Management, 15(2), 121-125. Kotabe, M., & Murray, J. Y. (2004). Global sourcing strategy and competitive advantage. Industrial Marketing Management, 33, 7-14. Kostova, T. (1999). Transnational transfer of strategic organizational practices: A contextual perspective. Academy of Management Review, 24(2), 308-324. Kostova, T., & Roth, K. (2002). Adoption of an organizational practice by subsidiaries of multinational corporations: Institutional and relational effects. Academy of Management Journal, 45(1), 215-233. Kshetri, N. (2007). Institutional factors affecting offshore business process and information technology outsourcing. Journal of International Management, 13(1), 38–56. Kshetri, N., & Dholakia, N. (2009). Professional and trade associations in a nascent and formative sector of a developing economy: A case study of the NASSCOM effect on the Indian offshoring industry. Journal of International Management, 15(2), 225–239. Lahiri, S., & Kedia, B. L. (2011). Co-evolution of institutional and organizational factors in explaining offshore outsourcing. International Business Review, 20(3), 252–263. Landman, T. (2005). The political science of human rights. British Journal of Political Science, 35(3), 549-572. La Porta, R., Lopez-de-Silanes, F., Shleifer, A., & Vishny, R. (1997). Legal determinants of external finance. Journal of Finance, 52, 1131–1150. La Porta, R., Lopez-de-Silanes, F., Shleifer, A., & Vishny, R. W. (1998). Law and finance. Journal of Political Economy, 106, 1113-1155. La Porta, R., Lopez-de-Silanes, F., Shleifer, A., & Vishny, R. (2000). The quality of government. Journal of Law Economics and Organizations, 15(1), 222-279.

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Lim, J. J. (2014). Institutional and structural determinants of investment worldwide. Journal of Macroeconomics, 41, 160-177. Lewin, A. Y., Massini, S., & Peeters, C. (2009). Why are companies offshoring innovation? The emerging global race for talent. Journal of International Business Studies, 40, 901-925. Meyer, A. D., Brooks, J. R., & Goes, J. B. (1990). Environmental jolts and industry revolutions: Organizational responses to discontinuous change. Strategic Management Journal, 11, 93-110. Meyer, J. W., & Rowan, B. (1977). Institutionalized organizations: Formal structure as myth and ceremony. American Journal of Sociology, 83, 340–363. Munemo, J. (2015). Foreign direct investment, business start-up regulations and entrepreneurship in Africa. Economics Bulletin, 35(1). Nachum, L., & Zaheer, S. (2005). The persistence of distance? The impact of technology on MNE motivations for foreign investment. Strategic Management Journal, 26(8), 747767. North, D. C. (1990). Institutions, institutional change, and economic performance. Cambridge, UK: Cambridge University Press. Peng, M. (1998). Law and finance. Journal of Political Economy, 106(6), 1113–55. Peng, M. (2001). How entrepreneurs create wealth in transition economies. Academy of Management Review, 15, 95-108. Peng, M. (2003). Institutional transitions and strategic choices. Academy of Management Review, 28, 275-296. Peng, M. (2011). Global business. Mason, OH: South Western. Perkins, D. H., Radelet, S., & Lindauer, D. L. (2012). Economics of development. New York, NY: Norton Publishers. Poe, S. C., Tata, C. N., & Keith, L. C. (1999). Repression of the human rights to personal integrity revisited: A global cross-national study covering the years 1976-1993. International Studies Quarterly, 43(2), 291-313. Porter, M. (1990). The competitive advantage of nations. New York, NY: Free Press. Porter, M. (1994). The role of location in competition. Journal of Economics of Business, 1(1), 35-39.

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Porter, M. (1998). The Adam Smith address: Location, clusters and the ‘new’ micro-economics of competition. Business Economics, 33(1), 7-13. Reich, R. B. (1991). The work of nations. New York, NY: Alfred A. Knopf. Schmeisser, B. (2013). A systematic review of literature on offshoring of value chain activities. Journal of International Management, 19(4), 390-406. Schmitt, J. (2013). Why does the minimum wage have no discernible effect on employment? Washington, DC: Center for Economic and Policy Research. Scott, R. W. (2001). Institutions and organizations. Thousand Oaks, CA: Sage. Selznick, P. (1949). TVA and the grass roots. Berkeley, CA: University of California Press. Selznick, P. (1957). Leadership in administration. New York, NY: Harper & Row. Sethi, D., Guisinger, S. E., & Berg, D. M. (2003). Trends in foreign direct investment flows: A theoretical and empirical analysis. Journal of International Business Studies, 34, 315326. Slesman, L., Baharumshahm, A. Z., & Wohar, M. E. (2015). Capital inflows and economic growth: Does the role of institutions matter? International Journal of Finance & Economics, 20(3), 253-275. Sturgeon, T., & Gereffi, G. (2009). Measuring success in the global economy: Technological learning, industrial upgrading, and business function outsourcing in Global Value Chains. Transnational Corporations, 18(2), 1-35. Sturgeon, T., Levy, F., Brown, C., Jensen, B., & Weil, D. (2006). Why we can't measure the economic effects of services offshoring: The data gaps and how to fill them (Working paper No. 06-006). Cambridge, MA: MIT Industrial Performance Center. Williamson, O. (1998) “Institutions matter.” American economic review: Papers and proceedings of the one hundred and tenth annual meeting of the American Economic Association, 8(2),75-79. Wooldridge, J. M. (2002). Econometric analysis of cross section and panel data. Cambridge, MA: The MIT Press.

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Tables Table 1 Direction of Coefficient – Hypothesis VARIABLE Formal Variables IMPCOURTS SDINFLATION logGDPCAP STDTARRIFS MINWAGE BUSREG STARTBIZ TAXINTRD Control Variables logPOP EDMEANYRS

INSTITUTION

ADVANCED ECONOMIES

EMERGING ECONOMIES

SSA ECONOMIES

Legal Economic Economic Economic Economic Regulatory Regulatory Regulatory

Positive effect Negative effect Positive effect Negative effect Negative effect Negative effect Positive effect Negative effect

Positive effect Positive effect Positive effect Negative effect Positive effect Negative effect Positive effect Negative effect

Positive effect Negative effect

Positive effect Positive effect

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Table 2 Countries in the study Obs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

Advanced Australia Austria Belgium Canada Czech Republic Denmark Finland France Germany Greece Ireland Israel Italy Japan Korea, South Netherlands New Zealand Norway Portugal Singapore Spain Sweden Switzerland Taiwan United Kingdom United States

N = 26; t = 8 N*t = 208

Emerging Argentina Brazil Chile China Hungary India Indonesia Malaysia Mexico Philippines Poland Romania Russia South Africa Thailand Turkey Vietnam

N = 17; t = 8 N*t = 136

SSA Angola Benin Botswana Burkina Faso Burundi Cameroon Central Africa Republic Chad Congo, Democratic Republic Congo, Republic of Cote d’Ivoire Ethiopia Gabon Ghana Guinea-Bissau Kenya Lesotho Madagascar Malawi Mail Mauritania Mozambique Namibia Niger Nigeria Rwanda Senegal Sierra Leone Tanzania Togo Uganda Zambia Zimbabwe N = 33; t = 8 N*t = 264

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Table 3 Descriptive Statistics Variable Log of Intermediate Goods Impartial Courts Std. Dev. of Inflation Std. Dev. Of Tariffs Minimum Wage Business Regulation Start a Business Taxes on Int’l Trade Log of Population Log of GDP Per Capita Education Index

Advanced Obs Mean

Std Dev

Emerging Obs Mean 24.40

Std Dev 0.94

Sub-Saharan Africa Obs Mean Std Dev 207 19.20 2.23

207

24.94

1.22

136

208 208 205 208 208 208 208 200 200 125

6.74 9.54 6.05 7.46 6.73 9.21 8.27 16.66 10.03 10.91

1.61 0.44 2.48 2.41 0.72 0.66 0.94 1.19 0.41 1.33

135 135 135 136 135 136 135 136 136 85

4.45 8.27 5.16 6.43 5.30 8.27 7.19 18.19 7.90 7.93

1.43 1.87 2.24 2.44 0.87 1.18 1.09 1.30 0.82 1.93

256 256 244 267 221 267 256 272 272 170

3.92 7.32 6.08 5.97 5.07 6.39 6.25 16.11 6.03 4.28

1.13 2.67 1.67 3.06 0.89 2.01 1.14 1.16 0.95 2.02

Table 4 RE-GLS Estimation Variable Impartial Courts Std. Dev. of Inflation Std. Dev. Of Tariffs Minimum Wage Business Regulation Start a Business Taxes on Int’l Trade Log of Population Log of GDP Per Capita Education Index Countries Time dummies R-squared Hausman test

Advanced Coef. P (z) 1.38 0.169 -2.20 0.028** 0.27 0.786 1.05 0.293 -1.38 0.169 0.43 0.669 -0.09 0.931 10.83 0.000*** 3.35 0.001*** -3.04 0.002*** 26 Yes 0.661 3.87 (0.4240

Emerging Coef. P (z) 0.85 0.398 1.79 0.073* 0.29 0.771 1.99 0.047* -0.39 0.694 1.88 0.060* 1.33 0.184 10.14 0.000*** 6.57 0.000*** -1.06 0.287 17 Yes 0.704 4.77 (0.311)

Sub-Saharan Africa Coef. P (z) -1.38 0.169 0.48 0.628 -1.50 0.135 1.03 0.303 -0.59 0.558 1.55 0.122 0.85 0.397 6.13 0.000*** 4.61 0.000*** 0.61 0.545 33 Yes 0.472 5.76 (0.218)

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Table 5 Sources of Data Variable logINTERMGDS IMPCOURTS SDINFLATION STDTARRIFS MINWAGE BUSREG STARTBIZ TAXINTTRD logPOP logGDPCAP EDINDEX

Description Log of Intermediate Goods Impartial Courts Standard deviation of inflation Standard deviation of tariffs Minimum wage Business regulation Starting a business Tax on international trade Count of total population (logged) Per capita GDP (logged)in US$ 2000 constant prices Education Index

Data Source United Nations Commodity Trade Database Fraser Economic Freedom Index Fraser Economic Freedom Index Fraser Economic Freedom Index Fraser Economic Freedom Index Fraser Economic Freedom Index Fraser Economic Freedom Index Fraser Economic Freedom Index World Bank World Bank UNESCO Institute of Statistics

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When Consumer Participation is Not Enough: A Classification of Compliance Dependent Services Lez Trujillo Torres (student), University of Illinois at Chicago Mark J. Hager, Menlo College at Atherton Frances Turner, Menlo College at Atherton Stephanie Dellande, Menlo College at Atherton

Latent Variables that Measure Customer Satisfaction Thomas J. Gogue, Auburn University Marie Kraska, Auburn University Elisha Wohleb, Auburn University

Accounting for Intangibles: Does Method of Accounting Matter? V. Brooks Poole Mississippi College

The Attractiveness of Regions as Sites for Global Value Chain Activities: The Impact of Formal Institutions Olumide Ijose, Governors State University Anthony Andrews, Governors State University

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