CUSTOMER-FIRM RELATIONSHIPS: WORKING TWO SIDES OF THE STORY By Praneet Randhawa A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Business Administration—Doctor of Philosophy 2014 ABSTRACT CUSTOMER-FIRM RELATIONSHIPS: WORKING TWO SIDES OF THE STORY By Praneet Randhawa This dissertation, using a two essay format, focuses on two separate, but related, facets of the customer-firm relationships. The first essay advances current research on relationship marketing, by examining the role of innovation in generating continuous value for current customers while building relationships with new customers. Specifically, I complement current models of relationship marketing, by accounting for the need for firms to continually differentiate their offerings to provide continual value to the relationship. This advancement addresses calls in the literature to both identify missing mediators that connect relationship investments to firm performance. In addition, I identify variables (e.g., managerial risk taking) that moderate the relationship between relational investment and service innovation. The second essay integrates research on customer-brand relationships and consumer propensity to purchase counterfeit luxury products. This study explores the non-price motivations that lead consumers to consider buying counterfeit luxury products. The arguments are built on the literatures of self-brand connection and consumer personality traits. ii Copyright by PRANEET RANDHAWA iii To The Four Strong Pillars of My Life: Ramesh Randhawa (Mama), Raghbir S. Randhawa (Papa), Aman Randhawa (Brother) And Jimish Gandhi (The Best Husband) This Would Have Not Been Possible Without You All. Love You All. iv ACKNOWLEDGEMENTS My Ph.D. experience has been a life-transforming journey. A journey that not only transformed me into a better human being but also helped me build strong relationships with great mentors and friends without whom this journey would have not ended on a happy note. I feel very fortunate to have many wonderful people in my life that I would like to express my sincere THANKS for all the big and little things they did in helping me get through the program. First and foremost, I would like to express my deepest gratitude to my dear mentor, Dr. Ronald F. Cichy, for his unwavering support and faith in me. It was his vision that helped me embark on the path of pursuing a doctorate. He has been my guarding ANGEL- a true angel who made sure I was always given the best possible opportunities and support. I am forever indebted to him for giving me opportunities that forever transformed my life. THANK YOU! Next, I would like to express my sincere THANKS to my dissertation co-chairs, Drs. Roger J. Calantone and Clay. M. Voorhees. They have been truly great mentors to me. I have learned so much from both of them that I will carry all the learning for the rest of my academic career. I would like to specially express my THANKS to my mentor, Dr. Clay M. Voorhees, for his extraordinary patience in dealing with my endless email queries and pounding on his office door. Many things would have not been possible without your support and guidance, Clay. THANK YOU! I would also like to THANK my committee member, Dr. Tom Page for his guidance through the dissertation phase, and the wonderful department sectaries, Jamie Lyon, Sheila v Mead, and Marlena Vertrees for their amazing support throughout the program. I greatly appreciate all their help. Last and more importantly, I would like to THANK many friends who have taught me to appreciate life. My dear friends and colleagues, Hannah S. Lee and ChangSeob Yeo, deserve a special mention. They stood by me in my happy and sad times. I would have not made it through many phases of the Ph.D. program without their support and affection. I found great friends in them and would forever cherish our times together. I would also like to THANK my friends, Meenal Rana, Chitra Dabas, Tereza Dean, MiRan Kim and Julie Tkach, who always encouraged me to do my best and think like a true scholar. THANK YOU! vi TABLE OF CONTENTS LIST OF TABLES ......................................................................................................................... ix LIST OF FIGURES .........................................................................................................................x GENERAL INTRODUCTION ........................................................................................................1 ESSAY ONE: THE ROLE OF SERVICE INNNOVATION IN RELATIONSHIP MARKETING..................................................................................................................................5 CONCEPTUAL BACKGROUND ..............................................................................................7 HYPOTHESES DEVELOPMENT ...........................................................................................10 Relationship Investment, Perceived Innovation Capability and Customer Outcomes ........10 Perceived Innovation Capability and Commitment ............................................................12 Risk Taking and Perceived Innovation Capability ..............................................................13 Interaction Orientation and Perceived Innovation Capability .............................................15 METHOD ..................................................................................................................................18 Sample and Data Collection.................................................................................................18 Construct Measures ..............................................................................................................20 ANALYSIS AND RESULTS ...................................................................................................20 Measurement Analysis .........................................................................................................20 Assessment of Common Method Bias .................................................................................23 Analytical Approach and Results.........................................................................................24 Probing the Cross Level Interaction ....................................................................................29 DISCUSSION ............................................................................................................................32 Theoretical and Managerial Implications ............................................................................32 Limitations and Directions for Future Research ..................................................................35 ESSAY TWO: THE PURSUIT OF COUNTERFEITED LUXURY: AN EXAMINATION OF THE NEGATIVE SIDE EFFECTS OF CLOSE CONSUMER-BRAND CONNECTIONS .......37 CONCEPTUAL BACKGROUND ..........................................................................................38 HYPOTHESES DEVELOPMENT .........................................................................................41 The Effect of Self Brand Connection...................................................................................41 The Effects of Value Consciousness, Impulsive Buying and Openness to Experience ......42 Interactive Effects ................................................................................................................45 METHOD ................................................................................................................................47 Sample and Data Collection.................................................................................................47 Construct Measures ..............................................................................................................48 ANALYSIS AND RESULTS ....................................................................................................50 Measurement Analysis .........................................................................................................50 Assessment of Common Method Bias .................................................................................52 Analytical Approach and Results.........................................................................................52 Probing the Interactions .......................................................................................................56 DISCUSSION ............................................................................................................................58 Theoretical Implications .......................................................................................................58 vii Managerial Implications ......................................................................................................60 Authenticating Brand Purchases ................................................................................60 Creating a Shopping Confidante ................................................................................61 Limitations and Directions for Future Research ..................................................................62 REFERENCES ..........................................................................................................................63 viii LIST OF TABLES Table 1.1: Construct Correlations, Reliabilities and Descriptive Statistic ....................................20 Table 1.2: Measures and Factor Loadings .....................................................................................22 Table 1.3: Summary of Results ......................................................................................................26 Table 1.4: Assessment of Research Hypotheses ............................................................................31 Table 2.1: Construct Descriptive Statistic, Correlations, and Covariances ...................................49 Table 2.2: Measures, Factor Loadings, and Composite Reliabilities ............................................51 Table 2.3: Assessment of Research Hypotheses ............................................................................54 ix LIST OF FIGURES Figure 1.1: Conceptual Model .......................................................................................................17 Figure 1.2: Graphical Interpretation of Cross Level Interaction....................................................30 Figure 2.1: Conceptual Model .......................................................................................................41 Figure 2.2: Graphical Interpretation of The Moderation Effects on Self-Brand Connection ........57 x GENERAL INTRODUCTION Firm’s ability to leverage relationships with customers is key to sustaining their competitive advantage in the marketplace (Hogan, Lemon, and Rust 2002; Mithas, Krishnan, and Fornell 2005). The general consensus is whether a customer builds relationship with the firm or with one of the brands of the firm; both forms of relationship building must lead to beneficial outcomes for the firm. Yet, it’s highly likely that customer-firm relationship building may or may not reap the benefits that the firm wishes to receive. In this dissertation, I set out to examine both sides to relationship building. In my first essay, I examine how service firms can benefit from building long-term relationships with their customers. In the second essay, I examine how customer-firm relationships may lead to unfavorable outcomes for the firm. Essay 2 specifically examines the underlying motivations that may lead consumers to consider buying counterfeit luxury products. In essay 1, I examine the role of service innovation in the relationship marketing literature. Managing relationship with customers has been proposed as a critical strategic initiative that helps firms to develop, maintain, and leverage relationships with customers (Kumar, Sunder, and Ramaseshan 2011; Reinartz and Kumar 2003). But the question how management of relationship improves firm performance has still not been fully addressed in the literature (Krasnikov, Jayachandran, and Kumar 2009; Kumar 2008). One potentially effective strategy that helps firms build stronger customer relationship is to align firm offerings with their needs and wants (Gruner and Homburg 2000; Im and Workman 2004; Joshi and Sharma 2004). Although the importance of innovation has been well demonstrated in the manufacturing and technology sectors, its importance in the service sector has not been fully explored (Chesbrough 2005; Bitner, Ostrom and Morgan 2008). 1 Relationship marketing has emerged as one of the leading business strategies for the firms to differentiate themselves from their competitors and to increase their firm performance. I propose service innovation as the underlying mechanism that not only helps in explaining the impact of relationship investment on firm performance but also helps in explaining consumers’ commitment to the relationship with the firm. I test the proposed model in the private club industry; in the private club industry there is an exceptional emphasis on building relationship with its customers, called members, as they embody frequent service encounters and long-term relationships with memberships spanning generations in families. (Cichy, Cha and Kim 2009). Club’s membership is generally referred to as its “lifeblood” (Fornaro 2003) because the club operations are always centered on its members. Many clubs are either fully or partly owned by their members, which increase the magnitude of the importance of relationship building for the club managers as well as the pressure of providing the best offerings to meet and exceed member expectations. Overall this essay makes the following two important contributions to the marketing literature. First, this essay advances both the literatures of relationship marketing and innovation by demonstrating that both RM and innovation are complementary systems of thinking and practice. Specifically, I complement current models of relationship marketing by accounting for the need for firms to continually differentiate their offerings to provide continual value to the relationship. This advancement addresses calls not only in the RM literature to identify missing underlying mechanisms that connect relationship investments to firm performance, but also in service innovation literature to build models that demonstrate how service managers can embrace innovation. Second, I advance a step further and identify conditions under which the relationship between of RM and service innovation can be altered. 2 In essay 2, I examine how customer-brand relationships may lead consumers to buy luxury counterfeit products. Consumers form interpersonal relationships with the brands that they know and/or use (Fournier 1998). Consumer-brand relationships are considered as a reflection of a consumer’s identity (Escalas and Bettman 2005). Consumers have the freedom to build relationship with any brand they like and for as long as they want. However, consumer’s tendency to build relationships with brands does not always lead to favorable outcomes for brand owners. I posit that purchasing of counterfeit products is an unfavorable outcome of customerbrand relationship. Counterfeit goods refer to products that are low-priced, illegal, and lower quality that are imitation of goods that have high brand value (Lai and Zaichkowsky 1999). Luxury counterfeit products are posing a major problem to not only the brands that get counterfeited but also impact the economy of the nations through tax evasion and job losses. Research to date is split on the motivations for buying counterfeit luxury products. Some researchers argue that consumers buy counterfeit luxury products because they are driven by social motivations (Han, Nunes, and Dreze 2010; Wilcox, Kim, and Sen 2009), while others argue that consumer buy counterfeit because they can’t afford the original version of the product (Poddar et al. 2011; Turunen, and Laaksonen 2011). Hence, there are many contradictory findings and unanswered questions that still remain (Penz, Schlegelmilch and Stottinger 2009; Staake, Thiesse and Fleisch, 2009; Wilcox, Kim and Sen 2009). In this essay, I set out to explore whether consumers’ demand for counterfeit luxury products hinges on their need to construct their self-concept. If so, then to what extent do personality traits impact the willingness? It can be largely argued that consumer-brand relationships do not necessarily always lead to positive outcomes, even if firms do not do anything to harm their own brand or their customers. It is consumers’ high vulnerability to reflect personal identities that may lead them to 3 consider buying lower-priced, counterfeit-versions of branded luxury products. The results reveal that consumer’s self-brand connection is positively related to their willingness to purchase counterfeit products. This effect is amplified when consumers are value-conscious and reduced when consumers are more open to new experiences. Ultimately, the results of this essay extend prior studies on counterfeit purchase behavior by demonstrating that, in addition to social and economic motivations, the consumer’s connection to the brand and their personality traits also play an important role in driving their willingness to purchase counterfeit products. 4 ESSAY ONE: THE ROLE OF SERVICE INNOVATION IN RELATIONSHIP MARKETING Building relationships with customers is critical for firm success (Bolton 1998; Reinartz, Thomas and Kumar 2005). One potentially effective strategy that helps firms build stronger customer relationship is to align firm offerings with their needs and wants (Gruner and Homburg 2000; Im and Workman 2004; Joshi and Sharma 2004). Although the importance of innovation has been well demonstrated in the manufacturing and technology sectors, its importance in the service sector has not been fully explored (Chesbrough 2005; Bitner, Ostrom and Morgan 2008). Particularly, there are very few models in the services field that demonstrate how service managers can operationalize a service innovation strategy and leverage it to foster relationships with customers. This reality is startling given that fact that we are operating in an increasingly service-based economy (Lusch et al. 2007). Moreover, according to recent findings of Moorman’s survey of Chief Marketing Officers (CMO) (2011), service customers consider innovativeness and building relationships more important than brand and quality. This suggests that service customers expect their service providers to embrace the culture of innovation and focus on building relationships with them. This suggests that both researchers and service managers need to heed customer expectations and dive deeper to understand how service firms can embrace a culture of innovation while nurturing relationships. I suggest that much can be learned about service firms’ innovation capabilities by leveraging the relationship marketing (RM) literature. Christopher, Payne and Ballantyne (1991, p.7) state that, “relationship marketing is concerned with both the act of making the offer different and its evaluation by customer over time.” For a long time, trust and commitment have been considered as the main mediating mechanisms between relationship marketing and superior 5 firm performance (Moorman, Zaltman and Despande 1992; Morgan and Hunt 1994; Sirdeshmukh, Singh and Sabol 2002). However, a meta-analysis conducted by Palmatier et al. (2006), found that the RM model is missing one or more important mediating mechanisms that researchers need to understand in order to fully appreciate the impact of RM on firm performance. I argue that one probable cause behind such a finding is the narrow focus of RM on customer evaluation aspect and a lost focus on the aspect of differentiating offerings, a sort of marketing myopia. The definition of RM proposed by Christopher, Payne and Ballantyne (1991) suggests that a firm’s relationship initiatives are successful if the firm is able to continuously generate value for the customer by differentiating their offerings. Given the importance of both RM and innovation for firm’s sustained competitive advantage, research integrating these two literature streams will be of great significance to the development of the field of marketing. Thus, the main focus of this study is to integrate the literatures of RM and innovation to explore whether innovation is one of the missing links between relationship investment and firm performance. By doing this, I will contribute significantly to further knowledge and application of both of RM and innovation. To investigate our research question, I use a nested data collected from the private club industry. The private club industry comprises of golf clubs, country clubs, yacht clubs, social clubs, and athletic clubs. The private club industry is an ideal setting to examine this research question because there is an exceptional emphasis on relationship building with its customers, called members, as they embody frequent service encounters and long-term relationships with memberships spanning generations in families, and additionally it is an institution where the relationship is declared between and by both parties. 6 Overall this study makes the following two important contributions to the marketing literature. First, this study advances both the literatures of relationship marketing and innovation by demonstrating that both RM and innovation are complementary systems of thinking and practice. Specifically, I complement current models of relationship marketing by accounting for the need for firms to continually differentiate their offerings to provide continual value to the relationship. This advancement addresses calls not only in the RM literature to identify missing underlying mechanisms that connect relationship investments to firm performance, but also in service innovation literature to build models that demonstrate how service managers can embrace innovation. Second, I advance a step further and identify conditions under which the relationship between of RM and service innovation can be altered. In the sections that follow, I begin by describing the conceptual backgrounds on innovation and relationship marketing and then propose hypotheses. Last, I very briefly discuss the research context, results and managerial implications. CONCEPTUAL BACKGROUND RM is considered as one of the successful mantras for helping firms to build close and lasting relationships with their customers; it emphasizes that firms should have a long-term focus towards building relationships with customers rather than a short-term transaction oriented focus (Berry 1983; Dwyer, Schurr and Oh 1987; Gronroos 1990; Hunt and Morgan 1994; and Palmatier et al. 2006). The customer is at the center of all conceptualizations of RM, and a firm’s survival and success depends on the relationship between the firm and its customers (Bendapudi and Berry 1997). Building relationships are especially critical for service firms where employees are actively involved in shaping service experiences for their customers, and where customers 7 benefit from forming relationships with their service provider. Additionally, they are important because services are intangible, inconsistent, nonperishable, and hard to evaluate prior to use, and often require coproduction (Zeithaml, Parasuraman and Berry 1985). These complexities associated with services make building relationships with customers a critical aspect of firm success. The fundamental purpose of an exchange relationship is to connect the customer’s need with the seller’s (or firm’s) offerings. Customers choose firms that provide them with the highest benefits (Johnson and Selnes 2004). According to Kotler and Armstrong (2004), achieving organizational goals depends on understanding targeted customers’ need and wants. Gruen states, “Relationship marketers consider value creation a fundamental concept upon which strategic competitive advantage is built,” (1997, p. 34). Many researchers imply innovation when they refer to value creation (e.g., Raphael and Zott (2001); Prahalad and Ramaswamy (2004); Tsai and Ghoshal (1998)). Innovation to date remains one of the most important topics in business research. It has been widely recognized as an important source of competitive advantage for firms (Dierickx and Cool 1989; Damanpour 1991; Tushman and O’Reilly 1996; Dess and Picken 2000). There is a wide agreement among researchers that firms’ innovativeness is among the most critical aspects of firm’s survival and prosperity (Rubera and Kirca 2012). Innovativeness is defined as, “product benefits that are unique to a given product and are perceived as meaningful by the customer” (Sethi, Smith and Park 2001, p.73), hence it is a form of a capability. According to this definition, success of any form of innovation rests in the hands of the customer who determines the value of the offering. No surprise that Hauser, Tellis and Griffin (2006) suggest that the first step of developing a successful innovation depends on understanding the needs of the customer, 8 and then accordingly developing new products/services to meet those needs. Innovation has been described as the next big thing in the service industry (Jana 2007). Many developed nations have undergone a dramatic shift towards service economies, with services now representing about 80% of U.S. gross domestic product (Libai, Muller and Peres 2009). However, despite this dramatic shift, service innovation is still one of the poorly understood phenomena (Libai, Muller and Peres 2009). Parvatiyar and Sheth (2000) argue that relationship marketing research is still in its preliminary stage and there is no consensus on what relationship marketing constitutes. Relationship marketing has been mostly associated with customer retention rather than with customer attraction (Berry 1983; Gronoos 1994; Morang and Hunt 1994). Research shows that as customers’ duration with the firm increases, the volume of purchase increases, the customer becomes less price sensitive, the customer engages in greater word-of-mouth communication, and the customer relationship maintenance cost decreases (Heskett, Sasser and Schlesigner 1997). However, most research to date has emphasized the importance of relationship building from customer satisfaction perspective whereas preliminary research shows that a customer’s future continuation with a firm not only rests on its current level of satisfaction but also with the future expectations of benefits from a service relationship (Lemon, White and Winer 2002). The authors argue that customer retention models only focus on the current and past levels of customer experience in order to conceptualize customer’s decision to continue relationship with the firm, and have ignored customer’s future-orientation. I argue that in order for service firms to fulfill the future expectations of their customer base, innovation is the engine that helps firms to sustain their firm’s long-term competitive advantage by continuously providing value to their current customers. I further argue that innovation in services will not only help firms to retain 9 their current customers, but will also help in attracting potential customers through greater wordof-mouth by the current customers. However, most firms in service industry do not formally and strategically plan their new service development process, and at the same time do not develop new services frequently. Rather, they heavily rely on understanding customer needs in order to better serve them. Despite the close proximity of the firm with their customers, there is still limited evidence as to how can service firms innovate in order to retain and attract customers. Without a better understanding of how and when service firms can effectively innovate, managers will continue to struggle to fight customer retention and attraction problems. HYPOTHESES DEVELOPMENT My conceptual model proposes innovation capability as an additional mechanism in the traditional RM model where the effects of RM on customer and firm performance outcomes are mediated by trust and commitment (Moorman, Zaltman and Deshpandé 1992; Morgan and Hunt 1994; Palmatier et al. 2006). Although, I do not formally hypothesize the mediating effects related to trust and commitment, I do test them in my model. Relationship Investment, Perceived Innovation Capability and Customer Outcomes Relationship investment refers to the efforts, resources, and time invested by the seller for building stronger and long-term relationships with their customers (Ganesan 1994; Palmatier et al. 2006). Most research in relationship investment literature to date investigates the psychological outcomes produced by seller’s investment towards a relationship. These psychological outcomes are trust (Ganesan 1994), gratitude (Palmatier et al. 2009), relationship quality (De Wulf, Odekerten-Schroder and Iacobucci 2001), dependence, and commitment 10 (Ganesan 1994). It has relied largely on the theoretical principles of transaction cost analysis, which suggest that relationship investments make the customer more dependent on the firm, and raises the cost of switching to competitors. This is because by switching to competitors, the customer may lose the relationship investment benefits it is receiving from its current firm. However, reliance on a single theoretical perspective has been considered too restrictive (Weits and Jap 1995; Bendapuddi and Berry 1997) and paying too much attention to the psychological outcomes of relationship investment leads to a lesser exploration of other potential outcomes. I posit that relationship investments for building strong and long-term relationships with customers not only lead to the psychological outcomes of commitment, trust, or reciprocity but also lead to other outcomes, such as customer’s high perception of firm’s innovation capability. My contention is based on the findings that customers want to receive benefits from the provider that delivers value above and beyond the delivery of the core product and service (Gwinner, Gremler and Bitner, 1998). According to Sheth and Parvatiyar (2005), customers seek variety and novelty in their choice process, and when they are satiated due to lack of new choices, they may intentionally exit a relationship. Given that novelty is identified as a critical aspect of innovativeness (Crawford and di Benedetto 2003). I argue that relationship investments bring the customer and the firm closer each other. This closeness between the customer and firms has two benefits: (1) it allows the firm to gain an in-depth understanding of the needs and wants of their customers, hence enhances the possibility of generating new ideas and approaches to meet those needs and wants (Cambra-Fierro et al. 2011), and (2) it allows the customer to know and better understand their firm and its abilities. Additionally, building close relationships with customers helps the firm understand and determine what characteristics of the products/services offered by the firm are highly valued by 11 the customer. However, ascertaining the exact value is difficult; thoroughly understanding the process consumers use to evaluate the value of products/service will help firms to deliver its products/services in a successful fashion (Gordon et al. 1993). I further argue that this close relationship and an in-depth understanding of customer needs and wants via relationship investment can also be used as a tool for extracting unmet customer needs (Urban and Hauser 2004). Urban and Hauser argue that by “listening in” to customer needs, the firms can discover new opportunities based on amalgamation of customer needs. Hence, firms that invest in building relationships with their customers should be able to provide better value proposition such that it increases customers’ perception of firm’s innovation capability. Furthermore, previous research validates that customer perception of a firm’s innovation capability is related to positive attitudinal and behavioral outcomes (Chun and Davies 2006; Szymanski, Kroff and Troy 2006; Schreier, Fuchs and Dahl 2012). Therefore, I posit that converting customer needs into products (processes, services) should also lead to positive outcomes associated with the customers, such as positive word-of-mouth, willingness to recommend, and future purchase intention. Hence, I propose the following hypotheses: H1. There is a positive relationship between relationship investment and perceived innovation capability. H2. There is a positive relationship between perceived innovation capability and customer outcomes. Perceived Innovation Capability and Commitment Commitment is broadly defined as the will to maintain an enduring relationship between two parties (Moorman, Zaltman and Deshpande 1992). The importance of commitment is considered vital for service firms because for most services the customer is often the part of the 12 production and delivery process (Kelley and Davis 1994). Additionally, Berry and Parasuraman (1991, p.139) argued that in services relationship marketing, “relationships are built on the foundation of mutual commitment.” In another study Parasuraman, Berry and Zeithaml (1991, p. 44) argued that "firms that do not provide the service core that customers are buying-a correctly repaired automobile, for example-fail their customers in the most direct way." Similarly, other research shows that in order to maintain a long-term relationship with a customer, firms must continuously revive their value proposition from keeping the customer too defect (See Bolton, Kannan and Bramlett 2000; Verhoef 2003). Together, the findings to date suggest that a customer’s willingness to sustain the relationship with a firm is greatly driven by the benefits received. Hence, it can be argued that firms that keep their value proposition fresh by offering new and improved products and services have a higher probability of having committed customers. Therefore, I posit that when customers’ perception of a firm’s innovation capability is high, their commitment to stay in a relationship with the firm will also be high. Hence, the following hypothesis is proposed: H3. There is a positive relationship between perceived innovation capability and commitment. Next, I address a set of firm level boundary conditions that may impact the effect of customer’s perception of relationship investment on perceived innovation capability. I specifically propose two moderating variables (1) interaction orientation and (2) risk taking. The direct and interacting effect of these variables on perceived innovation capability, and the relationship between relationship investment and perceived innovation capability may hold important functional implications for managers. Risk Taking and Perceived Innovation Capability 13 The general consensus in the firm risk literature is that when firm performance is below (above) target, firms tend to be risk taking (averse) (see e.g., Bromiley 1991; Fiegenbaum and Thomas 1988; Miller and Chen 2004). Risk is considered inherent to innovation (Hauser, Tellis and Griffin 2006), which suggest that risk-taking behavior is positively associated with a firm’s innovativeness. Firms operate in a complex environment, where decision-making involves a certain level of uncertainty because it is difficult for managers to decipher every signal stemming from the environment (March and Olson 1975). Firms form a sense of their environment through social interactions; the patterns of these social interactions help the organization understand the external and internal environment, which becomes the basis for managerial decision-making (Gilley, Walters and Olson 2002). Additionally, Lehman and Hahn (2013, p. 852) argue that the framework of attention model that focuses on understanding firm’s risk seeking behaviors is driven by the, “feedback about performance, and the nature of this relationship depends on the focus of organizational attention. Attention can be focused on one of three objectives: reaching performance targets, avoiding threats, or experimenting with excess resources.” I maintain that in a service setting, managers’ organizational attention is mostly focused toward avoiding threats in the form of unhappy customers. Since the customer is closely involved in the service production and consumption episode, managers receive or sense customer feedback on a regular basis and thus have opportunities to create happy customers. Therefore, I posit that managers’ social interactions with customers allow them to understand not only customer expectations, but also service performance. Hence, managers who are risk seeking are better positioned to address and meet the needs of the customers by offering them better value propositions. In the process, they not only increase customers’ perception of firms’ innovation capability, but also enhance the efforts of building strong and close relationship with customers. In other words, I argue that 14 managers’ risk-taking behavior has a dual effect. It allows managers to better cater to the needs of the customers by offering new and improved offerings, and also allows the risk-seeking managers to enhance the benefits from its relational investment efforts in increasing customers’ perceptions of firm abilities. Thus, I propose the following hypotheses: H4a: There is a positive relationship between a manager’s risk taking and a customer’s perceived innovation capability. H4b: The positive relationship between relationship investment and perceived innovation capability will be moderated by risk taking such that the relationship will be stronger when a manager’s risk taking is higher than when it is lower. Interaction Orientation and Perceived Innovation Capability Frequent interaction with customers has been considered beneficial for the firm (Crosby, Evans and Cowles 1990; Doney and Cannon 1997; Ramani and Verma 2008). Effective management of customer interactions is considered as a vital source for sustaining competitive advantage (Rayport and Laworski 2005). Additionally, research shows that frequent interactions with customers can be a critical source of innovation (Freeman 1968; von Hipple 1976; Rothwell 1994 and Foss, Laursen and Pedersen 2011). The interactions with the customers are considered to help the firm build a close social bond with the customer, which fosters free flow of information about customer needs and wants (Doney and Cannon 1997; Srinivasan, Anderson and Ponnavolu 2002). It is also aids in sharing customer information about customer likes and dislikes regarding the current products/services offered by the firm. This open flow of information from the customer to the firm is considered to act as a great source for improving products and services. However, this can also act as a fatal strategy (Christensen 1997). Blindly and extensively interacting with customers can lead to failures in the form of bad investments in 15 new products/services (Christensen 1997). Many researchers (e.g., Christensen and Bower 1996; Christensen 1997; Frosch 1996; and Macdonald 1995) have argued that for firms to truly develop an innovative product/service they need to maintain distance from the customers because the customers themselves are not fully aware of their needs, and instead have a myopic outlook toward understanding their own needs and wants. Frequent interactions with a customer causes an overflow of information that may lead to both over analysis of customer needs and difficulty in strategically organizing the information gathered to leverage for firm success (Etienne, MacDermott and Snyder 2002). Additionally, frequent interactions with customers increase customer expectations, which might be hard to fulfill and hence might negatively affect a customer’s overall perception of a firm’s innovation capabilities. I argue that frequent interaction with customers acts as a double-edged sword. It not only reduces a firm’s capability to innovate in the eyes of their customers, but it may also impede in effectively transforming relational investment efforts to innovation capability in the eyes of the customer. Customers like to be heard, but when firms are unable to fulfill the expectations of their customers, it is bound to fire back. Therefore, I hypothesize the following: H5a: There is a negative relationship between a manager’s interaction orientation and a customer’s perceived Innovation capability. H5b: The positive relationship between relationship investment and perceived innovation capability will be moderated by interaction orientation such that the relationship will be weaker when a manager’s interaction orientation is higher than when it is lower. 16 Figure 1.1: Conceptual Model Level 2 Risk Taking (+) Interaction Orientation (-) Level 1 Relationship Investment Perceived Innovation Capability Commitment Customer Outcomes* Trust Controls *Customer Outcomes • Word of Mouth • Willingness to Recommend • Future Purchase Intention 17 METHOD Sample and Data Collection The data was based on a survey of private club managers and their members located across the United States. The private club industry is an ideal set-up to study this research problem because this industry has an exceptional emphasis on building relationships with its members, as contextually they embody frequent service encounters and very long-term relationships with memberships spanning generations in families. (Cichy, Cha and Kim 2009). A club’s membership is generally referred to as its “lifeblood” (Fornaro 2003) because club operations are always member focused. Few establishments across the service industry enjoy both the close and the long-term relationship with their customers, as does the private club industry. Many clubs are fully or partly owned by their members, which magnifies the critical importance of relationship building for club managers, as well as increases the pressure to provide services and product offerings that meet and frequently exceed member expectations. Like most service firms, private clubs also heavily rely on understanding customer needs to better serve them. Yet, most clubs do not formally research their members and strategically plan their new service/product development process, and rarely develop new services. The importance of proactively responding to changes in members’ needs is even more critical now, as most private clubs across North America are facing shorter wait lists, a decline in overall membership, and ultimately reduced profits. This contraction among existing membership bases is complicated by the emergence of new clubs on the scene, which has placed increased pressure on maintaining members in a volatile and competitive environment (Barrows and Ridout 2010). Therefore, due to the importance of relationship building with club members 18 and the need to revamp their value proposition, managers in the private club industry have much to learn from the integration of relationship marketing and innovation literatures. Data were mainly collected via a web-based questionnaire that was mailed out to all the members of Club Managers Association of America (CMAA). To encourage club managers to participate in the study, an invitation email was sent directly from one of the top executives of the CMAA. Only 1,384 managers in the CMAA database accessed the initial email request. Two weeks later, a reminder email was sent to those who did not respond initially to the survey. A total of 386 responses were collected with a 29% response rate. In our initial survey to the managers, we asked managers if they were interested in participating in a follow up study with their members. Out of the 386 responses, 120 managers agreed to participate in the follow up study. In the second phase of the study, which immediately followed the first phase, member survey was carried out. Merging the manager and member data resulted in a data set containing 48 matched responses between managers and their members with a total member sample of 1594, representing 40% of the response rate. In terms of the demographics of the respondents, 76% of the managers were a part of golf/country clubs, 4% from athletic clubs, 6% from yacht clubs, 4% from city clubs, and 10% were from other types of clubs, such as social clubs. In the sample, 83% of the clubs were member-owned, 9% were corporate-owned, and 8% having other type of ownership. The average length of a relationship held by a member in our sample as reported by the manager is 16 years. The average number of years a manager has been with their individual club is 16 years, and the average number of years of club industry experience was 20 years. The managers provided risk taking and interaction orientation measures while the members provided relationship investment, perceived innovation capability, trust, commitment, and outcomes measures. 19 Construct Measures All of the constructs were instituted with established measures from the literature. Unless specifically indicated, items were measured using a five-point Likert scale (1= strongly disagree to 5= strongly agree). Firm age, firm size, R & D investment, and type of club ownership were included as controls in the models for capturing any additional effects. Club ownership is defined as whether the club is fully owned by its members or by a corporation. This construct was included to control for any biased opinions that may impact member’s rating of member-owned club’s ability to innovate. Refer to Table 1 for descriptive statistics, correlation and reliabilities. Table 1.1: Construct Correlations, Reliabilities and Descriptive Statistic Constructs 1. Interaction Orientation 2. Risk Taking 3. Future Purchase Intention 4. Word-of-Mouth 5. Innovation 6. Trust 7. Commitment 8. Relationship Investment 9. Willingness to Recommend M SD α ρ 1 .82 .14 -.10 -.10 -.19 .06 -.13 -.02 -.10 2 .02 .82 -.05 .03 .11 .18 -.05 -.09 .02 3 .01 .00 .53 .60 .38 .38 .60 .45 .50 4 .01 .00 .36 .70 .50 .53 .63 .51 .78 5 .04 .01 .14 .25 .91 .50 .50 .54 .58 6 .00 .03 .14 .28 .25 .94 .51 .54 .59 7 .02 .00 .36 .40 .25 .26 .74 .60 .69 8 .00 .01 .20 .26 .29 .29 .36 .89 .60 9 .01 .00 .25 .60 .34 .35 .48 .36 - 4.72 .49 .93 .93 2.96 1.11 .90 .93 3.36 1.08 .69 .69 4.27 .88 .87 .88 3.37 1.10 .97 .97 4.21 .85 .98 .98 4.04 .86 .88 .89 3.76 1.07 .96 .96 9.40 2.15 - All correlations are significant at .05 level. Notes: α = Cronbach’s index of internal consistency reliability, ρ = Bagozzi’s (1980) composite reliability index, and AVE = Fornell and Larcker’s (1981) index of the average variance extracted by the construct. Correlations are given below the diagonal, AVE at the diagonal and squared correlations above the diagonal. ANALYSIS AND RESULTS Measurement Analysis A confirmatory factor analysis checked the discriminant and convergent validities of each latent variable to determine model fit and construct reliability. The analysis indicates a good fit 20 for the independent variables used in the model (CFI = .97, SRMR = .044, RMSEA = .069 and χ2(1727.50) = 203, p = 0.00) based on the guidance provided by Bagozzi and Yi (2012). The resulting measures together with individual item reliabilities and loadings are reported in Table 2 and demonstrate that all standardized loadings for items of reflective measures are large and significant (range: 0.72 to 0.98), indicating support of convergent validity. Internal consistency of reflective measures is denoted by construct reliability estimates (Fornell and Larcker 1981). Table 1 reveals that all constructs have reliability estimates well above the accepted level of 0.7 with the exception of future purchase intention, which is at the borderline with reliability of .69. These reliabilities reasonably further confirm both the unidimensionality and convergent validity of the constructs. Discriminant validity was established by first examining the interconstruct correlations, which were all significantly smaller than 1.0 (Bagozzi, Yi and Phillips 1991). The squared correlations were compared with average variance explained (AVE) by each latent variable. In all cases, the squared correlations were smaller than the AVE with the exception of the squared correlation between future purchase intentions and word-of-mouth, which is greater than the AVE of future purchase intention. Since future purchase intention and word-of-mouth are dependent variables, and the model fit did not improve after treating both the constructs as one construct (χ2(2096.36) = 210, CFI = .963 and RMSEA = .075), they are treated as separate variables in the model. Therefore, adequately confirming discriminant validity (Fornell and Larcker 1981). 21 Table 1.2: Measures and Factor Loadings Source Brady, Voorhees, and Brusco (2012); Foss, Laursen, and Pedersen (2011) Miller (1987) Palmatier et al. (2009) Constructs Level 2 Interaction Orientation • How often do you make casual conversation with the members at your club? • How frequently do you touch base with your members? • How regularly do you chat with the members at your club? (1 = never to 5 = all the time) Risk Taking • In our club there is a strong tendency toward low-risk projects (with normal and certain rates of return)… ……………..In our club there is a strong tendency for high-risk projects (with chances of very high return). • Due to the nature of the environment in our club, it is best to explore things gradually via timid, incremental behavior…………….In our club bold, wide-ranging acts are viewed as useful and common practice. • In our club we prefer to play it safe………………..In our club, we are willing to take risks. Level 1 Relationship Investment • The managers at my club worked hard to strengthen our relationship. • The managers at my club made significant investments in building a relationship with me. • The managers at my club devoted time and effort to our relationship. Perceived Innovation capability Schreier, Fuchs What do you think about your club’s ability to innovate? and Dhal I think my club's ability to innovate: (2012) • Not very high…………….Very high • Not very strong…………..Very strong • Not excellent……………..Excellent 22 Construct Loading λ .954 .898 .864 .951 .792 .972 .886 .976 .969 .958 .973 .935 Table 1.2 (cont’d) Source Palmatier et al. (2009) Palmatier et al. (2009) Brady, Voorhees and Brusco (2011) Net Promoter’s Score and System Constructs Commitment • I am willing to go the extra mile to work with my club. • I have a desire to maintain my relationship with my club. • I view the relationship with my club as a long-term partnership. Trust • I have trust in my club. • My club is trustworthy. • My club gives me a feeling of trust. Dependent Variables Word-of-Mouth • I recommend visiting my club to friends. • I say good things about my club to others. • I encourage friends and relatives to become members at my club. Construct Loading λ Willingness to Recommend • How likely are you to recommend your club to a colleague or friend? Future Purchase Intention • I would consider upgrading my membership to Garbarino and premier membership. Johnson (1999) • I would consider using more facilities and services provided by my club. Note: N.A. = not applicable. .732 .910 .920 .971 .982 .958 .867 .840 .808 N/A .719 .736 Assessment of Common Method Bias Both the independent and dependent variables at level 1 came from the same source, raising the concern of common method bias (Podsakoff et al. 2003). Two separate tests assess the presence of common method bias. First, the CFA-based version of Harmon`s one-factor test (McFarlin and Sweeney 1992; Sanchez and Brock 1996) was employed and results for this test specification were substantially worse than those from the original specification of the measurement model (χ2 (15980.759) =135, CFI = 0.487, RMSEA = 0.273, and SRMR = 0.116), 23 indicating minimal likelihood of common method bias. Second, Lindell and Whitney`s (2001) marker variable assessment technique was employed. This technique involves assessing the impact of a variable, which is theoretically uncorrelated with the variables in the study, on the correlations among the independent and dependent variables. After partialling out the marker variable, the significance level of all the bivariate correlations remained unchanged. Thus, the convergent assessment results of two tests suggest that the risk of common method bias is minimal. Analytical Approach and Results The problem is, per se, multilevel and thus, given the multilevel nature of the dataset some of the data could vary in some systematic or clustered manner across the 48 clubs, consequently violating the independence assumption. Therefore, it is important to test for the appropriateness of multilevel analysis. The first step toward determining the need for multilevel analysis begins by examining the amount of variance residing within and between units to serve as a basis for additional analyses. First, an intercepts only model with perceived innovation capability as an outcome variable was assessed. The analysis indicated that 75% of the variance is explained by between level variables and 32% variance is explained by within level variable. Additionally, the intra-class correlation coefficient (ICC) and corresponding design effect also determines the presence of group-level variance (Duncan et al. 1997). The ICC (.06) associated with perceived innovation capability and thus the design effect (2.93 with given an average cluster size of 33.19) suggests a multilevel structure should be investigated (Muthen and Satorra 1995). Therefore, I employed multilevel structural equation modeling using maximum likelihood estimation in Mplus version 7.0 (Mplus is considered as an advanced application of structural equation modeling for analyzing a nested data). 24 Next, I estimated a series of models to examine linear as well as interactive effects for the a priori hypotheses (Mathieu and Taylor 2006). I first estimated a baseline model with only level 1 variables, and then estimated a second model where the linear effects of risk taking and interaction orientation (level 2) were examined on perceived innovation capability. Last, I estimated a model where the cross level effects of risk taking and interaction orientation (level 2) were examined on the random slope of the relationship between relationship investment and perceived innovation capability (level 1). Since the fit indices are not available with the numerical integration in Mplus, a log likelihood difference test was employed to compare the fit of the selected models. In comparing the different models, I find that the level 1 and 2 main effects model clearly dominates, in terms of fit, than the level 1 only effects model. Additionally, I find that the level 1 and 2 main effects model also demonstrates as a better fitting model than the interactive model. Although, the interactive model has a significant interaction effect as discussed in the following subsection and is a marginally (p < .10) better fitting model than the level 1 and 2 main effects model. Table 3 presents the results of the models tested. 25 Table 1.3: Summary of Results Relationships Relationship Investment to Perceived Innovation Capability Relationship Investment to Trust Relationship Investment to Commitment Trust to Commitment Perceived Innovation Capability to Commitment Risk Taking to Perceived Innovation Capability Interaction Orientation to Perceived Innovation Capability Risk Taking X Relationship Investment to Perceived Innovation Capability Interaction Orientation X Relationship Investment to Perceived Innovation Capability Perceived Innovation Capability to Wordof-Mouth Perceived Innovation Capability to Willingness to Recommend Perceived Innovation Capability to Future Purchase Intention Commitment to Word-of-Mouth Commitment to Willingness to Recommend Commitment to Future Purchase Intention Trust to Word-of-Mouth Trust to Willingness to Recommend Trust to Future Purchase Intention Controls Club Ownership to Word-of-Mouth R & D Investment to Word-of-Mouth Firm Size to Word-of-Mouth Firm Age to Word-of-Mouth Type of Club Ownership to Future Purchase Intention R & D Investment to Future Purchase Intention Model 1 Model 2 Model 3 Customer Searching Test for Effects for Omitted Level 2 (Level 1 Effects Interactive Only) (Levels 1 Effects and 2) .662*** .662*** n.s. R R R .500*** .289*** .162*** .110*** .499*** .287*** .171*** .105*** .500*** .288*** .171*** .105*** - .260*** .193*** - -.354*** -.317*** - - .079** - - n.s. .116*** .114*** .114*** .476*** .476*** .476*** .056** .065*** .064*** R R .226*** 1.416*** .446*** 1.412*** .446*** 1.413 *** R R R R .642*** .447*** .707*** .107*** .636*** .228*** .714*** .105*** .637*** .228*** .714*** .104*** .082** n.s. n.s. n.s. .166*** n.s. .059** n.s. n.s. .144*** n.s. .058** n.s. n.s. .144*** n.s. n.s. n.s. 26 Table 1.3 (cont’d) Relationships Model 1 Customer Effects (Level 1 Only) Model 2 Model 3 Searching Test for for Omitted Level 2 Effects Interactive (Levels 1 Effects and 2) n.s. n.s. n.s. n.s. n.s. n.s. Firm Size to Future Purchase Intention n.s. Firm Age to Future Purchase Intention n.s. Type of Club Ownership to Willingness .261*** to Recommend R & D Investment to Willingness to n.s. .179*** .176*** Recommend Firm Size to Willingness to Recommend n.s. n.s. n.s. Firm Age to Willingness to Recommend .003** n.s. n.s. 84 107 112 Number of Free Parameters -34554.684 -34671.662 -34667.019 Log-Likelihood Base 233.96** 9.29* 2LL 1593 1593 1593 N 48 48 48 Clusters ***p < .01; ** p < .05; *p< .10; n.s. = not significant; R = replication of prior effects. The key set of hypotheses, representing net new findings in the empirical literature are that perceived innovation capability drive both commitment and customer outcomes. Then commitment additionally drives customer outcomes. This multiplex of mediating constructs well represents the complex interplay, within the full nomological net, that results in a deeper and more complete understanding of customer orientation in a service setting. Additional variance explained by level 2 constructs of risk taking and interaction orientation. Risk taking has a contingent effect on the relationship between relationship investment and perceived innovation capability representing a nuanced view of the level 1 relationship. In terms of specifically reviewing hypotheses, the results across the hypothesized linear effects model involving both level 1 and 2 variables show that relationship investment has a positive and significant effect on perceived innovation capability (H1: γ = .662; p< .01). Next, 27 the results show that perceived innovation capability has a positive and significant effect on commitment (H3: γ = .105; p< .01). The results also indicate that perceived innovation capability has a positive and significant effect on all the outcome variables. Specifically, perceived innovation capability has a direct and significant effect on word-of-mouth (H2a: γ = .114; p< .01), willingness to recommend (H2b: γ = .476; p< .01), and future purchase intention (H2c: γ = .065; p< .01). In testing for the main effects of risk taking and interaction orientation on perceived innovation capability, results show that both constructs have significant effects on perceived innovation capability. Risk taking has a positive and significant effect on perceived innovation capability (H4a: γ = .260; p< .01), and interaction orientation has a negative and significant effect on perceived innovation capability (H5a: γ = -.354; p< .01). Next, the interactive effects between relationship investment and both the level 2 variables on perceived innovation capability were examined. The cross-level interaction model is generally referred to as the slopes as outcomes model. To assist with the interpretation of crosslevel interactions, independent variables (relationship investment, risk taking and interaction orientation) were standardized with higher values suggesting greater amount of each variable. Based on the suggestion of Bauer and Curran (2005), level 2 variables (risk taking and interaction orientation) grand mean centered and level 1 variable (relationship investment) was group mean centered for ease of interpretation of the results. The interaction results suggest that risk taking has a positive and significant effect on the relationship between relationship investment and perceived innovation capability (H4b: γ = .079; p< .05). This result suggests that managers who are risk seeking get a higher return from relationship investment than those managers who are risk averse. Next, I examined the interactive effect of interaction orientation and found that the effect is insignificant (H5b: γ = 28 .022; p>.05). Hence, failing to confirm the effect of interaction orientation on the relationship between relationship investment and perceived innovation capability. As mentioned in the theory section, I did not formally hypothesize the relationships among relationship investment, commitment, and trust, but these relationships were tested in the models. The results associated with these effects are presented in Table 3. Probing the Cross Level Interaction To improve the interpretation of the significant cross level interaction, the interaction effect was graphed by plotting the means resulting from a univariate analysis. Risk taking and relationship investment variables were split at the median to create two groups of high and low, and then using perceived innovation capability as the outcome an analysis of variance test was conducted. The result shows that manager’s ability to take risk is more crucial to increase customers’ perception of firm’s ability to innovate when customers’ perception of firm’s relationship investment is lower than when it is higher. In fact, result shows that when customer’s perception of relationship investment is high, manager’s risk taking ability does not matter in terms of impacting customer’s perception of firm’s innovation capability. In sum, all the hypotheses are supported with the exception of cross-level interaction associated with interaction orientation. Please refer to table 4 for summary of hypotheses assessment. 29 Figure 1.2. Graphical Interpretation of Cross Level Interaction 3.7 3.5 3.3 Risk Avoidance 3.1 Risk Seeking 2.9 2.7 Low Relationship Investment High Relationship Investment 30 Table 1.4: Assessment of Research Hypotheses Hypotheses Main Effects H1 H2 H3 H4a H5a Relationships Assessment There is a positive relationship between relationship investment and perceived innovation capability. There is a positive relationship between perceived innovation capability and customer outcomes. There is a positive relationship between perceived innovation capability and commitment. There is a positive relationship between a manager’s risk taking and a customer’s perceived innovation capability. There is a negative relationship between a manager’s interaction orientation and a customer’s perceived Innovation capability. Supported Supported Supported Supported Supported Cross Level Interaction Effects H4b H5b The positive relationship between relationship investment and perceived innovation capability will be moderated by risk taking such that the relationship will be stronger when a manager’s risk taking is higher than when it is lower. The positive relationship between relationship investment and perceived innovation capability will be moderated by interaction orientation such that the relationship will be weaker when a manager’s interaction orientation is higher than when it is lower. 31 Supported Not Supported DISCUSSION In this study, I set out to understand how the fields of relationship marketing and innovation tie together, and to build a model that demonstrates how service managers, in particular, can embrace a culture of innovation. Given that service managers are very relational in their mindset when dealing with customers, exploring the relationship marketing literature seemed to be a natural fit for building our understanding on how to inculcate a culture of innovation. Despite the known importance of services to the world economy and the United States in particular, understanding of how service firms can be innovative is still sparse. The findings primarily exhibit that for service firms to have long-term and successful relationships with their current customers and recruit new customers, they need to continuously differentiate their products and services. Managers who only focus on the psychological outcomes such as trust and commitment associated with relational investments may not be able to fully reap the performance benefits. The results of this study hold important implications for managers and theory development. Below, I first describe the theoretical and managerial implications of the study followed by opportunities for future research. Theoretical and Managerial Implications This study makes three important contributions in the marketing literature. First, this study addresses the call made by Palmatier and colleagues (2006), who found in their meta-analysis that the relationship marketing literature is missing some underlying mechanisms to help explain the impact of relationship investment on firm performance. I address that call by introducing the variable of innovation. The results show that as a customer’s perception of relationship investment increases; it also increases their level of perception of a firm’s innovation capability. The argument for this finding is centered on the idea that when managers invest resources in 32 building relationships with customers, they not only build close and strong connections with them, but also in the process understand their needs and wants better. It is this understanding of these needs and wants that allows the firm to alter their value proposition in such a way that it has a positive effect on a customer’s perception of a firm’s ability to innovate. Second, this study extends the service innovation literature by empirically demonstrating how service managers can embrace the culture of innovation while fostering relationship with customers. As mentioned earlier that service managers are very relational in their approach toward customer management. This finding is an important step toward developing our understanding of how managers can to reap more benefits from their relational investments, and provide better value to their customers. The above two findings support the main premise of this study, i.e., relational investment reaps benefits beyond emotional connections. Firms operate in a volatile market environment that requires continuous assessment of firm offerings that leads to the attraction and retention of customers (Christensen 1997). The concept of relationship marketing is centered on getting and keeping customers by providing them with the best value proposition (Gruen 1997), thus reinforces that the findings have significant implications for both theory and practice. These findings also support the existing trends in marketing that (1) greater emphasis on one-to-one marketing, and (2) improving marketing investments (Palmatier, Gopalakrishna and Hosuton 2006). Third, I take a step forward in understanding firm boundary conditions that have a direct and interactive effect with relationship investment on perceived innovation capability. These conditions help managers understand how they can effectively leverage the impact of relationship investments in a customer’s perception of a firm’s innovation capability. The results 33 show that a manager’s interaction orientation and risk taking abilities have an affect on creating a customer’s perception of firm’s innovation capabilities. While risk taking increases perceived innovation capability, interaction orientation has a deterring effect. Both of these findings make unique contributions to the field of marketing. First, implications of a manager’s risk taking ability have been sparsely understood in the services literature (Murray 1991). Second, we contribute to the topic of customer proximity in innovation projects by demonstrating that regular and frequent interactions with customers have a high likelihood to fire back. It is important for firms to establish emotional connections with their customers, but they must maintain a balance in how frequently they interact with them so that they can effectively cater to their needs rather than getting lost in the overload of customer feedback. Below, we describe our two key firm boundary conditions in detail. A manager’s ability to take risk has important implications for creating a customer’s impression of a firm’s ability to innovate. Managers who are risk seeking are able to better address the needs of the customers and hence increase a customer’s perception of innovation capability. Likewise, a manager’s risk taking abilities allow for them to increase the impact of relational investment on perceived innovation capability. This shows that it is important for a firm to hire talent with risk taking abilities, and inculcate a culture of risk taking if it wishes to increase its impression in the eyes of the customers. Managers who are risk seekers have a high proclivity toward trying new ideas, which increases the return of a manager’s relational investment such that managers not only build stronger and longer-term relationships with the customers, but also extract information in the process that helps in engaging in new opportunities associated with building new products/services. Risk taking allows firms to experiment with new ideas generated based on customer feedback. Given that firms operate in volatile environments, 34 firms that embrace risk taking will be able to make faster and effective decisions in unpredictable or unfamiliar environments. Unlike the positive effects of risk taking, interaction orientation has negative effect on improving perceived innovation capability. This finding has important implications for the innovation literature where the involvement of customer in the innovation product is a topic of debate. The finding suggests that too frequent interactions with customers lead to an overload of information that is not only but also leads to over-analysis of customer problems leading to creation of solutions that do not successfully adopt. Hence, it is important that the firms train their managers and staff to maintain a balance in the frequency of their interactions with the managers so they do not end up increasing customer expectations that are hard to be fulfilled, and lead to the lowering of a customer’s expectations from the firm offerings. All three contributions make significant contributions to the field of marketing. In particular, this study demonstrates that the fields of innovation and relationship marketing are complementary systems of thinking, and much can be learned by integrating them together. Limitations and Directions for Future Research Although this study offers many insights for understanding the role of innovation in relationship marketing, this research has limitations that open avenues for future research. First, although I study the research questions in a nested set-up, the findings have limitation in terms of describing the true cause and effect between and among variables. Future research must replicate the same model with a longitudinal dataset to understand if the results hold. Second, since we are among the first few studies that empirically demonstrate a model of service innovation, we focused on understanding customer’s perception of firm’s innovation capability. Although, we think this is an acceptable approach as customer is the king in a service setting. However, I 35 believe that it would be fruitful for future research to measure innovation capability from an objective perspective and test whether the results hold. Third, since most of relationship marketing research has focused on a Business-to-Business (B2B) set-up, it important that the model is replicated in a B2B set-up to understand whether synergies related to innovation take place. Fourth, since we only focused on one segment of the service industry, the generalizability of our results is limited. It would be worthwhile for future research to examine this problem using multiple service sectors. 36 ESSAY TWO: THE PURSUIT OF COUNTERFEITED LUXURY: AN EXAMINATION OF THE NEGATIVE SIDE EFFECTS OF CLOSE CONSUMER-BRAND CONNECTIONS Counterfeiting of brand name goods has increased by more than 10,000 percent in the past two decades and costs U.S. manufacturers over $200 billion annually (International AntiCounterfeiting Coalition 2012). Counterfeit goods, comprising any illegal impersonation of branded goods, are growing in popularity (particularly for luxury brands) due to the relative ease of manufacturing and the spike in consumer demand. Despite the fact that counterfeit products represent one of the single biggest environmental threats facing luxury brand manufacturers, academic research focused on improving our understanding of what factors drive consumer demand for these products is still in its infancy (Staake, Thiesse and Fleisch 2009). Specifically, initial investigations into consumer evaluations of counterfeits have demonstrated that social (Han, Nunes and Dreze 2010; Wilcox, Kim and Sen 2009) and financial motivations (Poddar, Foreman, Banerjee and Ellen 2012; Turunen and Laaksonen 2011) impact consumers’ propensity to purchase counterfeits. While these studies provide a basis for our understanding, more research is needed on what internal factors, unique to the consumer, may drive them to purchase counterfeit products regardless of their social groups or income (Penz, Schlegelmilch and Stottinger 2009; Staake, Thiesse and Fleisch 2009; Wilcox, Kim and Sen 2009). By extending research in this space, focusing on individual motivations for purchasing counterfeit products, an improved understanding into this complex decision-making process can be developed. This study inspects whether consumers’ demand for counterfeit luxury products hinges on their need to construct their self-concept. If so, then to what extent do personality traits impact 37 the brand relationships? It can be largely argued that consumer-brand relationships do not necessarily always lead to positive outcomes, even if firms do not do anything to harm their own brand or their customers. It is consumers’ high vulnerability to reflect personal identities that may lead them to consider buying lower-priced, counterfeit-versions of branded luxury products. The results reveal that consumer’s self-brand connection is positively related to their willingness to purchase counterfeit products. This effect is amplified when consumers are value-conscious and reduced when consumers are more open to new experiences. Ultimately, the results of the research extend prior studies on counterfeit purchase behavior by demonstrating that, in addition to social and economic motivations, the consumer’s connection to the brand and their personality traits also play an important role in driving their willingness to purchase counterfeit products. In the following sections, we review the literature on counterfeiting luxury products, develop hypotheses, describe the research design and analysis, present results. Followed by discussion of the research implications. CONCEPTUAL BACKGROUND To effectively curb manufacturing and sale of counterfeit products, it is critical to fully understand the mechanisms that entice consumers to seek and buy such products. As long as there is demand for counterfeit products by the consumers, the manufacturers of counterfeit products will always find a way to get the product to the customers. From a consumer’s perspective, counterfeiting can be either deceptive or non-deceptive (Grossman and Shapiro 1988). Deceptive counterfeiting occurs when a consumer buys a product thinking that it is the original product having the value of the original and worth the money asked by the seller. Non- 38 deceptive counterfeiting, on the other hand, occurs when consumers knowingly buy a product that they know is an imitation of a highly-valued brand. Non-deceptive counterfeiting is mostly prevalent in the luxury goods market (Nia and Zaichkowsky 2000), whereas deceptive counterfeiting is prevalent in the drugs, automobile parts, and electronic goods markets (Grossman and Shapiro 1988). According to Gentry, Putrevu and Shultz (2006), over the course of time the quality of counterfeit products has increased so dramatically that consumers cannot truly judge fakes and even customs inspectors need high-tech tools to detect fakes. There are two leading reasons for improvement in the quality of counterfeit products: (1) the trend of outsourcing of manufacturing to countries with poor intellectual property protection laws; this outsourcing has opened doors for counterfeiters to get information on product specifications, intricate design details and molds, as well as packaging sourced from the same suppliers as the original (Parloff 2006; Wilcox, Kim and Sen 2009). These product specifications help counterfeiters to develop a product that looks identical to the original product, but is usually quite inferior in quality to the original product, and (2) the wide-spread use of internet and ecommerce websites, which have opened a whole new platform for forgers to sell their products (Phillips, 2005). This increased access of counterfeit products to consumers has made counterfeiting an even more lucrative business model to pursue. Due to the increased quality of counterfeit products, Bosworth (2006) suggests using counterfeiting as a continuum of deception, rather than treating it as dichotomous because counterfeit products are available in varying degrees of imitation. Research to date on counterfeit products has attributed counterfeit consumption proliferation to a combination of the following three reasons (Eisend and Schuchert-Güler 2006): consumer price affordability and/or product feature preferences (e.g., Albers-Miller 1999; 39 Cordell, Wongtada and Kieschnick 1996), social and cultural influence (e.g., Chakraborty, Allen and Bristol 1996; Lai and Zaichkowsky 1999; Leisen and Nill 2001; Han, Nunes and Dreze 2010; Hoe, Hogg and Hart 2004; Wilcox, Kim and Sen 2009), and consumer socioeconomic status (e.g., Bloch, Bush and Campbell 1993; Cheung and Prendergast 2006; Chuchinprakarn 2003). Because of this, it can be hypothesized that the resolution to understand consumers’ affinity toward counterfeit products is a subtle combination of these influences according to contextual and situational pressures on individual consumers (Warshaw 1980). Considerable potential remains in an examination of how consumers’ need to create self-concept can come to center on obtaining and using counterfeit products. Humans are motivated to carry dishonest acts in order make a tradeoff between the expected external benefits and the costs associated with such acts (Allingham and Sandmo 1972; Mazar, Amir and Ariely 2008). Our argument follows on a similar logic, namely, consumers buy counterfeit products to create a balance between creating their self-concept and paying lower prices for high value brands; as well as the positive affect of each. This study focuses on non-deceptive counterfeiting luxury product purchases, where consumers are aware that they are buying an imitated version of high-brand value product. In the next section, arguments will be developed to support the hypotheses. 40 Figure 2.1: Conceptual Model Consumer Personality Traits 1) Value Consciousness (+) 2) Impulsive Buying (+) 3) Openness to Experience (-) Willingness to Buy Counterfeit Products Self-Brand Connection (+) Covariates HYPOTHESES DEVELOPMENT The Effect of Self-Brand Connection Brands have the ability to both influence customer purchase decisions and shape consumer identities (Aaker 1997; Escalas and Bettman 2005; Richins 1994). Material possessions in the form of luxury brands help consumers satisfy different psychological needs such as creating and communicating their self-concept (Belk 1988; Escalas and Bettman 2005; Sirgy 1982). This association with brands to create a self-concept is referred to as self-brand connections (Escalas and Bettman 2003). Consumers adopt different techniques, such as conforming to social norms, flattery, selfpromotion, projecting consistency between beliefs and behaviors (Escalas and Bettman 2003; Fiske and Taylor 1991), or acting dishonestly (Mazar, Amir and Ariely 2008) to accomplish the objective of signaling and shaping identities. Among the different techniques used by the customers, acting dishonestly for signaling identities is an intriguing consumer behavior 41 phenomenon with strong implications for counterfeit consumer behavior. Mazar, Amir and Ariely (2008, p. 633) argue that customers “behave dishonestly enough to profit but honestly enough to delude themselves of their own integrity. A little bit of dishonesty gives a taste of profit without spoiling a positive self-view.” This suggests that some customers deliberately carry out dishonest acts with the aim of maximizing their return while reducing the investment cost, and in the process do not question their self-concept. Deliberate dishonest acts in retailing, such as wardrobing (the act of purchasing, using and then returning the used clothing or accessories), cost U.S. retailers $16 billion annually (Speights and Hilinski 2005), and consumers do not consider acts like wardrobing to be unethical or immoral (Rosenbaum, Kuntze and Wooldridge 2011). In a similar vein, it is contended that some consumers that make brands an integral part of their self do not necessarily buy the original products, but instead buy fake versions of their favorite brands. These consumers act a dishonestly by buying fake products to signal the desired image of the self to others. Furthermore, it can be argued that many consumers are tempted to buy counterfeit products because, according to them, the act of buying counterfeit products falls within the boundaries of acceptable dishonestly and allows them to unbundle the status and quality attributes of a high status brand without paying the high price (Grossman and Shapiro 1988). Therefore, the following hypothesis can be made: H1: Self-brand connection is positively associated with the willingness to buy counterfeit products. The Effects of Value Consciousness, Impulsive Buying and Openness to Experience Value consciousness is defined as a concern for price keeping in mind the quality received (Lichtenstein, Ridgway and Netemeyer 1993). A consumer’s perceived value of a product is considered to be an influential driver of their purchase decision. Research shows that 42 when consumers find better value in a product compared to other product options, their intention to buy that product increases (Dodds, Monroe and Grewal 1991). Value-conscious consumers seek immense pleasure in finding products that provide greater value at lower prices. This experience provides them with a feeling of being a “smart shopper” (Lichenstein, Ridgway and Netemeyer 1993). By the same token, we argue that when consumers encounter counterfeit products that seem to provide high value at low price, their tendency to buy such a product increases. Our argument shadows Lichtenstein, Netemeyer and Burton’s (1990, p. 56) reasoning that, “for most people price and quality are the most salient ‘give and get’ components,” and in any given purchase situation where consumers find the salient “give and take” component, their willingness to purchase the product will be high. Therefore, the following is hypothesized: H2: Value-consciousness is positively associated with willingness to buy counterfeit products. Impulsive buying behavior is a widely-known phenomenon in the United States. According to Kacen and Lee (2002, p. 163), it is defined as, “a sudden, compelling, hedonically complex purchasing behavior in which the rapidity of the impulse purchase decision process precludes thoughtful, deliberate consideration of all information and choice alternatives.” Impulsive buying behavior is often associated with negative traits and outcomes such as immaturity, financial problems, and lower self-esteem (Zhang and Shrum 2009). Consumer impulsivity is argued to arise from the tendency to overvalue benefits and undervalue long-term effects (Ramanathan and Menon 2006). According to Stern (1962), impulse buying is largely dependent on resources such as money, time, and physical and mental effort, with money exerting the most direct impact on the purchase decision. If a consumer gets easy access to a product where the expenditure of money, time, and the effort of physically and mentally 43 planning and locating the product is low, then the likelihood of an impulse purchase is greater (Stern 1962). For the reasons presented above, it can be argued that when consumers with impulsive buying traits encounter counterfeit products, the probability of buying such a product may be high. They may find that the counterfeit product provides high utility at low price, thus making the customer fall prey to the purchase situation. Hence, it is hypothesized, H3: Impulsive buying behavior is positively associated with willingness to buy counterfeit products. Openness to experience refers to a person who is curious, creative, original and imaginative, finds novel solutions, and enjoys new experiences (Costa and McCrae 1992, McCrae 1987). According to Costa and McCrae (1992), open individuals are highly motivated to find new and diverse experiences. These individuals are always actively seeking situations that expose them to unfamiliar conditions that help them find novel experiences. Additionally, in another study, McCrae and Costa (1997) claim that open individuals have absorptive capability of combining and integrating new and unrelated information. These characteristics not only allow open individuals to find novel solutions, but also allow them to make better decisions when they are exposed to unfamiliar situations. Thus, it is argued that customers who are open to experiencing new and novel situations will be highly likely to engage in a counterfeiting shopping experience, but their probability to actually buy the product will be low. We base our argument on the fact that engaging in a counterfeit shopping experience provides novel and unique experiences that satisfies the curious nature of such a customer at no cost. However, purchasing and using counterfeit products does not provide novel or creative experiences, rather purchasing such products runs counter to their true self of being authentic and original. Thus, the following is expected: 44 H4: Openness to experiences is negatively associated with willingness to buy counterfeit products Interactive Effects The next set of hypotheses involves two-way interactions between consumer-brand connection and consumer personality trait constructs. Prior research indicates the importance of the interaction between value consciousness and brand preferences (Monroe 1979). According to Monroe (1979), the best purchase decision is the one where the brand provides the highest ratio of quality to price for the product category. This suggests that when value-conscious consumers encounter a counterfeit product of a brand they think provides value and embodies their selfconcept, their willingness to buy the product will be high. There are two reasons for expecting such an interaction. First, consumers who deliberately buy counterfeit products buy them because of the brand image associated with the product. Branded counterfeit products help consumers achieve two separate objectives: (1) it gives some consumers the opportunity to create a unique identity by using a brand that helps them separate from others, and (2) it allows some customers to assimilate with a group they desire (Wilcox, Kim and Sen 2009). This objective is achieved by showing what the brand means rather than how the counterfeit product performs (Penz and Stottinger 2005). Branded counterfeit products are considered to provide the prestige without paying the high price. Second, evidence shows that there are consumers who buy counterfeit products because of the value the product provides in terms of the price-quality ratio rather than just merely acquiring a brand (Geiger-Oneto, Gelb, Walker and Hess 2012). Keeping these two reasons in consideration, the following is hypothesized: H5: The combined effect (i.e., interaction effect) of self-brand connection and value consciousness will be positively associated with willingness to buy counterfeit products. 45 Impulsive consumption has been associated with a conflict between the desire to consume and the ability to resist it (Hoch and Loewenstein 1991). This conflict upsurges in situations where processing resources, such as time and money, are limited, thus enticing consumers to give in to their impulses. Moreover, prior research shows that a consumer’s need to build their self-concept is linked to impulsive buying tendencies (Zhang and Shrum 2009), and these tendencies are higher for hedonic things such as branded products (Ramanathan and Menon 2006). These findings suggest that when an impulsive buyer finds a brand that is associated with their self-concept, their propensity to buy such a product may increase. This may also suggest that when a consumer with an impulsive buying behavior encounters a branded counterfeit product that personifies their self, their willingness to buy the product may increase. Therefore, the following hypothesis is proposed: H6: The combined effect (i.e., interaction effect) of self-brand connection and impulsive buying will be positively associated with willingness to buy counterfeit products. McCrae’s (1996) extensive review on openness to experience shows that the openness element of personality is associated with different social outcomes. He argues that openness is a fundamental way of approaching life that impacts both internal experience and social relationships and behaviors. This implies that openness to experience may play a role in building self-concept. As previously argued, an open consumer may be highly motivated to engage in counterfeit shopping experiences, but might not be willing to engage in the actual product purchasing. In a similar vein, it is also argued that open consumers, who use brands to create their self-concept by building self-brand connections, will have a lower tendency to buy counterfeit products. Our premise is in line with previous findings that open consumers tend to be loyal toward the brands they like (Matzler, Bidmon, Grabner-Krauter 2006; Lin 2010). 46 Additionally, research shows that consumer personality interacts with brand personality because it provides a vehicle for self-expression (Fournier 1998; Sirgy, Johar, Samli and Claiborne 1991). In sum, this implies that engaging in branded counterfeit product purchase may not only lead to a clash with the true self, but may also induce a feeling of disloyalty toward the preferred brands. Thus, the following is hypothesized: METHOD Sample and Data Collection Respondents were recruited via Amazon’s Mechanical Turk’s service. Mechanical Turk is gaining popularity as a source for collecting data. It is considered to provide slightly more demographically diverse sample compared to the traditional Internet or typical American college student samples. The data obtained are considered to be at least as reliable as those gathered via the traditional data collection methods (Buhrmester, Kwang and Gosling 2011). For our particular data collection, 296 consumers provided complete data that was suitable for analysis. Fifty-two percent of the sample was male and the average age was 35 years. In terms of race/ethnicity, 86% of the respondents were Caucasian, 5% African-American, 3% Hispanic, 4% Asian, 1.3% Native American, and 0.7% reported their race/ethnicity as “other.” After agreeing to participate in the research study, respondents were directed to the survey instrument. The first question on the survey captured the respondents’ gender and was used to direct each respondent to a gender-specific product type scenario. Specifically, men were directed to one of three product scenarios: (1) men’s watch (Rolex), (2) men’s belt (Gucci), or (3) men’s wallet (Louis Vuitton) and women were directed to one of the three product scenario: (1) women’s watch (Rolex), (2) women’s belt (Gucci), or (3) women’s handbag (Louis Vuitton). 47 The brands for each of these products were selected based on the results of a pre-test to ensure that consumer familiarity with each was sufficiently high. Once they were assigned to one of the preceding product categories, respondents were shown pictures of the counterfeit product along with the asking price. The respondents were informed that the products in the pictures are fake and their quality is poor as compared to the original product. We also provided the participants with a price comparison to the original product. The pictures and the price of the counterfeit product were taken from a website that claimed to be selling high quality replica at cheap prices. Once the respondents viewed the photos they were asked to respond to a set of questions by bearing in mind both the product and brand type shown. At last, they were asked to respond a set of questions about impulsive buying, openness to experience, and demographics. Construct Measures The independent variables predicted to impact willingness to buy counterfeit products are brand-self connection, impulsive buying, value consciousness, and openness to experience. In addition to the independent variables, we included perceived level of affordability of the original product, prior fake product experience, propensity to buy original and authentic products, age, gender, and product types as control variables. Table 1 shows the descriptive statistics, correlation and covariance matrices for all the variables used in the analysis. 48 Table 2.1. Construct Descriptive Statistic, Correlations, and Covariances Construct 1 2 3 4 5 6 7 8 9 10 11 12 1. Willingness to Buy Counterfeit Products .67 .38 .21 .01 .05 .18 -.12 -.27 -1.10 -.02 -.00 .81 2. Value Consciousness .68 .24 .08 .05 .07 .18 -.06 -.28 -.31 .06 -.03 .74 3. Brand Connection .46 .27 .26 .06 .03 .20 -.08 .15 -.51 .03 -.01 .79 4. Impulsive Buying .23 .09 .32 -.01 -.02 .08 -.07 -.06 -.91 -.04 -.00 .74 5. Openness to Experience .01 .07 .10 -.02 .00 .04 -.00 .11 .28 .02 .00 .72 6. Gender .09 .15 .07 -.05 .01 -.05 .01 -.03 1.05 .01 -.00 N/A 7. Affordability .15 .15 .18 .07 .04 -.03 -.03 .08 -.02 -.01 -.02 N/A 8. Prior Fake Product Experience -.24 -.12 -.20 -.14 -.00 .06 -.06 .12 .47 .01 .00 N/A 9. Authentic Products -.30 -.29 .18 -.07 .15 -.06 .07 .25 -.13 .01 .02 N/A 10. Age -.10 -.03 -.05 -.09 .03 .19 -.00 .09 -.01 -.08 -.37 N/A 11. Watch Dummy -.04 .13 .01 -.08 .07 .04 -.02 .03 .03 -.02 -.11 N/A 12. Purse Dummy -.00 -.06 -.01 -.01 .00 -.01 -.04 .01 .04 -.07 -.50 N/A Mean 2.16 2.86 1.94 2.34 3.35 1.48 1.84 1.61 3.75 35.07 SD 1.06 1.03 .93 .91 .77 .50 1.23 .49 .95 11.00 Note: Correlations are provided below the diagonal, covariances are provided above the diagonal, and the square roots of AVEs are provided at the diagonal. N/A = Not Applicable as construct measured by single item. All correlations are significant at .05 level. 49 Where possible, all established measures were used using a 5-point Likert-type scale. Table 2 provides complete detail on measures. ANALYSIS AND RESULTS Measurement Analysis Based on guidance provided by Bagozzi and Yi (2012), we conducted a comprehensive confirmatory factor analysis that included all constructs in the research model in order to check the discriminant and convergent validities of the variables to determine model fit and construct reliability. The resulting measures together with individual item reliabilities and loadings are reported in Table 2 and demonstrate that all standardized loadings for items of reflective measures are large and significant (range: 0.62 to 0.93), in support of convergent validity. Internal consistency of reflective measures is denoted by construct reliability estimates (Fornell and Larcker 1981). Table 2 reveals that all constructs have reliability estimates well above the accepted level of 0.7, thus further reasonably confirming the unidimensionality and convergent validity of the constructs. Discriminant validity was established by first examining the interconstruct correlations, which were all significantly smaller than 1.0 (Bagozzi, Yi and Phillips 1991). The squared average variance extracted (AVE) for each construct was then compared with the correlations. In all cases, the squared AVE was larger than the correlations, therefore adequately confirming discriminant validity (Fornell and Larcker 1981). See Table 1 for the comparison. The analysis indicates a good fit for the independent variables used in the model (CFI = .98, SRMR = .04, RMSEA = .04 and χ2(220) = 354, p = 0.00). 50 Table 2.2: Measures, Factor Loadings, and Composite Reliabilities Source Escalas and Bettman (2003) ; Rindfleisch et al. (2009) Constructs Antecedents Self-Brand Connection • The luxury brand reflects who I am. • I can identify with the luxury brand. • I feel a personal connection to the luxury brand. • I (can) use this luxury brand to communicate who I am to other people. • I consider this luxury brand to be “me.” Loadings λ AVE C.R. .77 .94 .68 .91 .63 .92 .63 .83 .90 .86 .91 .85 .88 Moderators Doods, Monroe and Grewal (1999) Rook and Fisher (1995) Mowen and Spears (1999); Brown et al. (2002) Doods, Monroe and Grewal (1999) Value Consciousness • This product is a (1 = very poor value for money to 5= very high value for money). • At the price shown, the product is (1 = very uneconomical to 5 = very economical). • The product is considered to be a good buy • This product appears to be a bargain. • This price shown for the product is (1 = very unacceptable to 5 = very acceptable). Impulsive Buying • I often buy things spontaneously. • "Just do it" describes the way I buy things. • "I see it, I buy it" describes me. • "Buy now, think about it later" describes me. • I buy things according to how I feel at the moment. • Sometimes I am a bit reckless about what I buy. Openness to Experience How often you experience the following: (1 = never to 5 = always) • Frequently feel highly creative. • Imaginative. • Feel more original than others. Dependent Variable Willingness to Buy Counterfeit Products • The likelihood of purchasing this product (1 = very low to 5 = very high). • The probability that I would consider buying the product (1 = very low to 5 = very high). • I intent to buy this product. • At this price shown, I would consider buying the product. 51 .87 .73 .86 .80 .85 .83 .92 .88 .82 .76 .74 .88 .86 .62 .82 .92 .89 .93 .87 .95 Assessment of Common Method Bias Cross-sectional surveys where both the independent and dependent variables came from the same source are susceptible to common method bias (Podsakoff et al. 2003). Thus, we conducted two separate tests to assess the presence of common method bias. First, we employed a CFA-based version of Harmon`s one-factor test (McFarlin and Sweeney 1992; Sanchez and Brock 1996). Results for this model were quite poor and substantially worse than those from the proposed measurement model (chi-square goodness-of-fit index of 4702 with 495 degrees of freedom; CFI = 0.340, RMSEA = 0.170, and SRMR = 0.172), indicating that common method bias is minimal. Second, Lindell and Whitney`s (2001) marker variable assessment technique was employed. This technique involves assessing the impact of a variable, which is theoretically uncorrelated with the variables in the study, on the correlations among the independent and dependent variables. After partialing out the marker variable, the significance level of all the bivariate correlations remained unchanged. Thus, the assessment of two tests suggests that the risk of common method bias is minimal. Analytical Approach and Results To estimate the paths among the constructs and thereby test the propositions advanced, we used structural equations modeling approach (Anderson and Gerbing 1982) using EQS version 6.1. This approach allows accounting for measurement error and simultaneously estimating all direct and interaction effects in the conceptual model. Specifically, we estimated a model based on Ping’s (1995; 2007) approach for modeling latent variables interactions. Using this approach, three interaction variables were created that accounted for the interaction between self-brand connection and consumer personality traits. In addition to these interaction effects, the direct effects of the four exogenous variables on 52 willingness to buy counterfeit products were also estimated. The structural model was estimated simultaneously with the measurement model using raw data as an input. The overall fit of the data to the hypothesized model was done using Maximum Likelihood, and the resulting fit was satisfactory (χ2 = 595, df = 400; CFI = 0.98; SRMR = .03; RMSEA = 0.04). The standardized coefficients and significance levels for the moderated structural equation model are reported in Table 2.3. 53 Table 2.3: Assessment of Research Hypotheses Hypotheses Relationships CS Assessment Self-Concept H1 Self-brand connection is positively associated with the willingness to buy counterfeit products. .29*** Supported .54*** .09** n.s. Supported Supported Not Supported .18*** Supported Consumer Personality Traits H2 H3 H4 Value-consciousness is positively associated with willingness to buy counterfeit products. Impulsive buying behavior is positively associated with willingness to buy counterfeit products. Openness to experience is negatively associated with willingness to buy counterfeit products. Interaction/Moderation Effects H5 The combined effect (i.e., interaction effect) of self-brand connection and value consciousness will be positively associated with willingness to buy counterfeit products. H6 The combined effect (i.e., interaction effect) of self-brand connection and impulsive buying will be positively associated with willingness to buy counterfeit products The effect of self-brand connection on willingness to buy counterfeit products will be diminished as openness to experience increases. H7 n.s. -.12** Covariates Affordability of Original Product Prior Fake Product Experience Propensity to Buy Authentic Products Age Gender Product Types: Watch Dummy Purse Dummy Note: CS = Completely Standardized Path Coefficient: **p < .05, ***p < .01, n.s. = not significant. 54 n.s. n.s. -.15*** -.07** n.s. -.11** n.s. Not Supported Supported To assess H1 – H7, we examined the sign and significance of the coefficients for the interaction terms and the baseline direct effects. Overall, the independent variables explained 65 percent of the variance in willingness to buy counterfeit products. More detailed results are reported in Table 3 and provide strong support for the direct effects of self-brand connection (β = .29, p < 0.01) on willingness to buy counterfeit products, providing support for H1. Additionally, we find strong support for the direct effects of value consciousness (β = 0.54, p < 0.01) and impulsive buying (β = 0.09, p < 0.05) on willingness to buy counterfeit product, hence confirming H2 and H3. Unfortunately, our model does not provide support for the direct effect of openness to experience on willingness to buy counterfeit products (β = -0.02, p > 0.05). Therefore, no support was found for H4. With respect to the interaction results, the interaction between self-brand connection and value consciousness on willingness to buy counterfeit products is significant (β = 0.18, p < 0.01), supporting H5. Further, the interactions between self-brand connection and impulsive buying (β = -.06, p > 0.05) on willingness to buy counterfeit products is not significant. This means that H6 is not supported. We also tested the interaction effects between self-brand connection and openness to experience. The examination of the coefficients reveals that in support of H8 (β = -.12 p < 0.05). However, it is important to note here that since the direct effect of openness to experience on willingness to buy counterfeit products is not significant, openness to experience acts as a doubly exogenous variable that diminishes the effects of self-brand connection on willing to buy counterfeit product. This means that the effects of self-brand connection on willingness are stronger when openness to experience is low, than when it is high. 55 Lastly, we also tested the effects of a few control variables. Of all the controls included, we find that consumer’s propensity to buy authentic and original products has a negative and significant effect on willingness to buy counterfeit products. Further, we find age has a negative and significant effect on willingness to buy, which indicates that younger consumers are more susceptible to buying counterfeit products than the older consumers. We also find that the effect of prior fake experience has a negative effect on willingness to buy, although the effect is nonsignificant but worth bringing to light. Lastly, we find that watch product category has a negative and significant effect on the willingness to buy counterfeit product. This may suggest that consumers may not have faith in a counterfeit product that involves difficulty in predicting the performance quality. Probing the Interactions To improve our understanding of the significant interaction and moderating effects, we conducted simple slopes tests and plotted the interactions graphically (see Figures 2 and 3). These plots were created by adapting the procedure described in Aiken and West (1991), using standardized path coefficients (Cortina, Chen and Dunlap 2001). With respect to the effect proposed in H5, simple slopes test revealed that self-brand connection only had positive and significant effect on willingness to purchase counterfeit products when value consciousness was high. Thus, for consumers who are not concerned with price, developing strong brand connections doesn’t make them more likely to purchase fake goods. For H7, the results also supported the proposed directionality as at low levels of openness to new experience, self-brand connection had a significant impact on willingness to purchase counterfeits. However, the effect was significant at both high and low levels of openness to experience, but the effect was stronger at lower levels than at higher levels of openness to experience. 56 Figure 2.2. Graphical Interpretation of The Moderation Effects on Self-Brand Connection A. Value Consciousness Low Value Consciousness High Value Consciousness Willingness to Buy 3.5 3 2.5 2 1.5 1 Low Self-Brand Connection High Self-Brand Connection B. Openness to Experience Low Openness to Experience High Openness to Experience Willingness to Buy 3.5 3 2.5 2 1.5 1 Low Self-Brand Connection 57 High Self-Brand Connection DISCUSSION This study attempts to analyze the underlying consumer psyche for buying branded counterfeit products. It specifically examined how building brand connections and certain personality traits affect consumer weakness for buying counterfeit products. The overall results of the study show support for the claim that consumer-brand connections increase the willingness to buy counterfeit products. This research challenges the current assumption in the literature that shows consumer-brand relationship lead to universally positive developments for brands. The study takes a step further to understand under what conditions these effects are either enhanced or diminished by certain consumer personality traits. The results hold important implications for both managers and scholarly research, which are described in detail in the following subsections. Theoretical Implications The research makes three important contributions to the literature. First, a unique contribution to the growing literature of consumer-brand relationship is made. Previous research to date has primarily explored the bright side of the formation of consumer-brand relationship (Batra, Ahuvia and Bagozzi 2012; Escalas and Bettman 2003; Escalas and Bettman 2005). The research is the first to explore the “dark side” of consumer-brand relationship. The primary finding is that consumers’ need to buy counterfeit product is driven by their desire to create selfconcept. This research, of course, is not meant to claim that every consumer who builds a relationship with a brand to create self-concept gets lured to buy counterfeit products. Rather, the result claims that the susceptibility to consider buying counterfeit products increases for consumers who build interpersonal connections with luxury brands. This finding is in line with the findings of Mazar, Amir and Ariely (2008) that consumers have a tendency to strike a 58 balance between driving some financial benefit and behaving dishonestly without damaging their self-concept. Second, most research to date has focused on the formation of consumer-brand relationship. This research, along with Swaminathan, Page and Gurhan-Canli (2007), and Cheng, White and Chaplin (2012), is among the first few to explore the outcomes associated with selfbrand connection. Although the other two studies look at the outcome associated with original brand evaluation, this study focused on testing whether considering buying counterfeit product centers on consumer’s need to form their self-concept. Third, the research provides conditions under which the strength of the relationship between the consumer-brand relationship dimensions and willingness to buy counterfeit product varies. These results will help researchers understand consumer dynamics from a different perspective than has been previously explored in both the consumer-brand relationship and counterfeit product literatures. The results show that a consumer with both high self-brand connection and high value consciousness has relatively higher propensity to buy counterfeit products. However, intriguing conditions are found under which the effects of self-brand connection on willingness to buy counterfeit products are diminished. Consumers that are high on openness to experience are less likely to buy counterfeit products even if they are high on self-brand connection. This finding suggests that researchers have much to learn by understanding consumers’ need to be original and find novel solutions to their needs. This finding contributes to the literature on openness to experience, which is labeled as one of the fundamental elements of personality, but with limited understanding in the literature (McCrae 1996; Woo et al. 2013). 59 Managerial Implications The results of this research offer several managerial implications for brand managers and their salespeople. A concerted combined effort by brand managers and their salespeople can help create intangible propositions that signal exclusivity, heritage, and customer relationship orientation that will be difficult to be counterfeited. The rise in fake fashion is attributed to consumers’ changing attitude toward, “buy now, throw away tomorrow” (Huffington Post 2013). This suggests that brands need to offer much more than the tangible product in order to stop customers from buying fake products. In the section below, a few key areas for opportunities for both brand managers and salespeople are highlighted. Authenticating Brand Purchases As expected, it is found that self-brand connection has strong and significant influence on consumer’s willingness to buy counterfeit products. This suggests that individuals with a high need to create a unique personal identity are willing to go as far as buying a counterfeit product to fulfill their objective. This finding suggests that marketing managers need to create a brand image that conveys a message of exclusivity that can only be experienced by the use of the original product, and no product replacement can bring the same level of exclusivity. The brand managers can effectively accomplish this objective by closely working with salespeople who can reinforce the concept of exclusivity by creating loyalty initiatives that provide special privileges to the shoppers. For example, giving shoppers the ability to put products on hold for more than a week, extended return policy, and/or special assistance provided to make the shopping experience more effective and memorable. In instances where simply developing the image cannot curtail interest in counterfeits, the brands could find new, creative ways to socially authenticate purchases for their customers. Because, counterfeiters have become so skilled in 60 replicating the actual products, brands need to provide authentication via means that are completely internal to their ecosystem. One opportunity along these lines could be public validation of a branded purchase via social media. Specifically, upon purchase of a branded item or registration of the product, the consumer could be sent a congratulatory note to their accounts via social media outlets from the official accounts of the brand or in collaboration with retailers. This would not only allow the brand to provide the consumer with further validation of their purchase in a media that is easily shared with their friends, but also help the retailer to attract customers to its store. Creating a Shopping Confidante Many salespeople focus on building relationships with their customers by making house calls, texting photos of the product, friending customers on Facebook, and giving in-store and online product advice (The Wall Street Journal 2013). These strategies will allow the salespeople to not only woo customers, but can also be used to curb counterfeit product purchases. Salespeople can leverage these findings to better profile customers for effective results in building both customer behavioral and attitudinal loyalties. One of the results in our study shows that open customers are less likely to buy counterfeit products because such products do not allow consumers to express their true self to others. While it would be difficult for salespeople to identify these consumers for a targeted marketing campaign, salespeople can leverage this finding when working closely with customers to increase connections. Specifically, consumers’ relationships with brands are becoming increasingly more about the overall experience with a brand and less about the simple product offering. As a result, brands could strive to offer consumers a unique, value-added brand experience at their retail outlets that could not be replicated by counterfeit manufacturers. By simply reminding consumers that they should do the 61 right thing to support the brand as part of these branded experiences, they could change this negative behavior (Mazar, Amir and Ariely 2008). Limitations and Directions for Future Research These findings open opportunities for researchers to study how consumer-brand relationship dimensions may lead to other unfavorable outcomes for brands. This study, while offering many insights, has some limitations or rather opportunities for future research, as well. First, the consumers were shown pictures of the product rather than the actual products. Since there is high potential for consumers to act differently in an actual shopping situation, future research must be done to observe or create actual shopping experiences. Second, the study could not capture how a customer will behave when they buy these products online and with money back guarantee. With the growth of e-commerce, most of the counterfeit products are being sold online. 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