Corresponding Author

Heng Tang

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Consumer social interaction is one of the most influential factors affecting people’s consumption-related decision making (Y. Chen, Wang, & Xie, 2011). When making product choice, particularly, consumers apt to follow the action of the crowd in many circumstances (Bonabeau, 2004). Referred to as herding in literature, such behavior-based social influence among market participants has long been studied (Banerjee, 1992; Hirshleifer & Hong Teoh, 2003; Raafat, Chater, & Frith, 2009). With the rise of online social platforms, other people’s actions are getting increasingly more observable, as consumers usually share with each other their product-related use experiences, opinions, and purchase decisions (Liu, Brass, Lu, & Chen, 2015). As such, behaviorbased social influence plays a critical role in shaping and affecting consumers’ choice (Duan, Gu, & Whinston, 2009). Meanwhile, research on herd behavior has grown significantly and continues to grow. Empirical research examines herd behavior in a wide range of contexts, including online purchase (C. M. K. Cheung, Xiao, & Liu, 2014; Huang & Chen, 2006), technology adoption (Sun, 2013; Walden & Browne, 2009), online auction (Simonsohn & Ariely, 2008), contribution to open source projects (Oh & Jeon, 2007), etc. While it is generally held that no single reason can explain the behavioral convergence of consumers, literature in economics, marketing, and IS (information systems) disciplines primarily highlight two utility-based mechanisms behind herding (Bikhchandani, Hirshleifer, & Welch, 1992; Y.-F. Chen, 2008; Duan et al., 2009; Huang & Chen, 2006; Langley, Hoeve, Ortt, Pals, & van der Vecht, 2014; Zhang & Liu, 2012). These mechanisms are informational cascades (i.e., ignore one’s own information and make a choice based on other’s choice due to uncertainty when making decision, see (Bikhchandani et al., 1992) and positive network externalities (i.e., additional users of a good increase the value of that good, (Kauffman, McAndrews, & Wang, 2000). Despite a wealth of literature on herd behavior, there has been little work discusses the convergent behavior occurs among customers who are already the patrons of certain brands. This setting is unique in that, available choices in the market (i.e., current brand vs. alternatives) are not in the same position from the standpoint of consumers. Empirical studies do show that the popularity of a brand, per se, positively impacts its customers’ loyalty (Raj, 1985) and favorable cost-benefit evaluation (Deval, Mantel, Kardes, & Posavac, 2013; He & Oppewal, 2018; Li, 2004). These key components, in turn, encourage the existing customers of the brand continue their patronage (Aaker, 2009). By this process, a product’s popularity establishes a hinderance to its customers’ attrition by cementing brand-customer relationship (Aaker, 2009). However, it remains uncertain how and to what extent that customers’ continuance intention (as opposed to migrating to alternative brands) is affected by the crowd’s choice. Note: in some occasions, indeed, brand popularity is negatively associated with one’s brand choice. Need for uniqueness (Tian, Bearden, & Hunter, 2001) and negative network externalities (Hellofs & Jacobson, 1999) are two common mechanisms. The former occurs primarily in the market of self-expressive products, such as luxury goods, apparels, and the like (Steinhart, Kamins, Mazursky, & Noy, 2014); whereas a typical context of the latter is that the quality of certain services being worsen off due to high service popularity (Hellofs & Jacobson, 1999). Obviously, the understanding of brand patrons’ behavioral convergence has significant implications on both theory and managerial practice. However, none of the aforementioned utility-based mechanisms of herding (i.e., informational cascades and positive network externalities) provides a satisfactory explanation in this context. One reason for this theoretical lacuna is related to the implicit assumption in the herding literature (i.e., available choices in the market are of the same position), which is not the case in the research context of business retention/switching. A second reason deals with the overwhelming emphasis on the economic utility as the underlying mechanisms. As pointed out by Bikhchandani et al. (1992), herding could also be induced by noneconomic factors, such as the decision-maker’s conformity with others (Jones, 1984), avoiding sanctions due to disobedience (Bendor & Mookherjee, 1987), and so on. Building upon the prior research on customer retention, we introduce customer commitment — the key construct in business relationship literature, into the understanding of brand patrons’ behavioral convergence. It is widely held that commitment plays the central role in people’s persistence of behavior (Newman & Sabherwal, 1996). Particularly, customer commitment involves not only the state of mind that binds a customer with the present business relationship (Kelley & Davis, 1994), but also the structural conditions that prevent her from making a change (Becker, 1960). Therefore, we contend that the perspective of commitment offers an integrative understanding of the behavioral convergence induced by both psychological and utility-based mechanisms. This research adopts the three-component commitment model (TCM) — a widely used conceptualization of commitment (Meyer, Stanley, Herscovitch, & Topolnytsky, 2002). According to TCM, people choose to maintain the current business relationship Tang The 18th International Conference on Electronic Business, Guilin, China, December 2-6, 2018 822 because they feel they want to (affective commitment), ought to (normative commitment), or need to (calculative commitment) (Meyer, Allen, & Smith, 1993). By introducing TCM into the study of herding phenomenon, this research takes a holistic and novel view for understanding the interplay between product popularity and consumers’ continuance. In particular, we ask, how do affective commitment, normative commitment, and calculative commitment mediate the effects of product popularity on customers intention of brand continuance? In this research, we attempt to answer the research question in the settings of virtual communities of consumption (VCC), which are online groups explicitly centered on consumption-related interests (De Valck, 2005). VCCs provide plentiful of informative cues about brands’ relative popularity and consumers’ choices (C. M. K. Cheung et al., 2014), hence constitute an ideal research environment of our study. This study potentially contributes to the literature at the following perspectives. First, despite the voluminous research on herding, it remains uncertain how group mimicking behavior affect customer retention or migration. The current research adds to the literature by expanding research on herding to a domain in which, to the best of our knowledge, very little scholarly effort has been devoted. Second and more importantly, this research theorizes and empirically tests the central role of commitment components underlying the herd behavior of brand patrons. This perspective provides insights into an alternative mechanism of how herding takes effect in the context of customer migration, thus adds to both the herding and customer retention literature. In addition, our exploration of the heterogeneous roles of various popularity cues in customer retention sheds lights on marketing practice about the most effective way to retain patrons and attract potential customers.

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