The rapid growth of e-commerce reflects its compelling advantages such as enhanced market outreach, lower cost structure, greater flexibility, broader product lines, greater convenience, and faster transactions. The evolution is foreshadowed by the growing popularity of online environments in which millions of people interact with one another. However, e-commerce also comes with its own set of challenges. Competitors are only a few mouse clicks away. Currently, an agreement seems to favor better customer service and its consequent effect on e-satisfaction and repurchase, even though low price and web presence were believed to be the drivers of success in nascent days of e-commerce. Especially, e-satisfaction is not only the primary driver of online consumers’ continuous behavior (Bhattacherjee, 2001b, Cenfetelli et al., 2005, Hsu et al., 2006, Lin et al., 2005 and Thong et al., 2006), but also the key to building and retaining a loyal base of long-term customers (Evanschitzky, Iyer, Hesse, & Ahlert, 2004).
Recently, the exploration of e-satisfaction has gained increasing importance in the IS and marketing disciplines (e.g. Anderson and Srinivasan, 2003, Bhattacherjee, 2001b, Evanschitzky et al., 2004, Hsu, 2008, Lin et al., 2005, McKinney et al., 2002 and Szymanski and Hise, 2000). Drawing from user satisfaction and technology acceptance, IS researchers have investigated e-satisfaction. From the user satisfaction perspective, Molla and Licker (2001) and Mckinney et al. (2002) have investigated the constructs for the process by which e-satisfaction is formed based on the DeLone and McLean IS success model (DeLone & McLean, 1992). The instrument for measuring web customer satisfaction has been developed and validated (Wang and Tang, 2004 and Wang et al., 2001). From the technology acceptance perspective, IS researchers have explored e-satisfaction as an antecedent to continuous intention of e-commerce services (Bhattacherjee, 2001a, Bhattacherjee, 2001b, Cenfetelli et al., 2005, Hsu and Chiu, 2004, Hsu et al., 2006, Lin et al., 2005 and Thong et al., 2006). In marketing fields, antecedents to e-satisfaction and its consequent effects have also been examined in a variety of resources (Anderson and Srinivasan, 2003, Balasubramanian et al., 2003, Bansal et al., 2004, Cao et al., 2003, 2004, Evanschitzky et al., 2004, Luarn and Lin, 2003, Szymanski and Hise, 2000, Yang and Fang, 2004, Yang and Peterson, 2004 and Yen and Gwinner, 2003). Among these studies, Anderson and Srinivasan (2003), and Yang and Peterson (2004) have explored the conditions under which the effect of e-satisfaction on e-loyalty may vary.
Although much progress has been made for the exploration of e-satisfaction from these two disciplines, the following two issues have not been explored rigorously. First, in the IS discipline, based on the model by Spreng et al., 1996 and McKinney et al., 2002 posit that e-satisfaction has two antecedents – website information satisfaction and its system satisfaction. However, their study fails to include service quality delivered by a website, or e-service quality, because it focuses on the information search phase only. In the marketing discipline, based on the service quality and satisfaction literature (Cronin and Taylor, 1992, Parasuraman et al., 1988 and Spreng and Mackoy, 1996), it has been demonstrated that e-service quality is a key antecedent to e-satisfaction (Janda et al., 2002 and Wolfinbarger and Gilly, 2003). Yet, few studies have explored these three antecedents to e-satisfaction simultaneously and possible relationships among them. Second, perhaps more important, few studies have investigated the condition under which the formation of online consumers’ e-satisfaction and repurchase may vary. In view of the significance of the computer interface for the consumer-business relationship in the context of e-commerce, it is important to explore how computer-related individual differences such as computer self-efficacy and computer anxiety serve as these moderators. Despite the importance of such an insight, few studies have been investigated toward this direction.
To fill this knowledge void, this paper attempts to explore the key antecedents to e-satisfaction and the moderating effects of computer self-efficacy and computer anxiety on the possible relationships among them. While computer self-efficacy represents one’s belief about his or her ability to use computers in diverse situations, computer anxiety is associated with negative attitudes toward use of computers (Venkatesh, 2000). Within the context of innovation diffusion research, computer self-efficacy and computer anxiety represent well-established dynamic, situation-specific individual differences (Thatcher & Perrewe, 2002). These individual differences reflect malleable inclinations that influence responses to stimuli. These two constructs are potentially critical to connecting website information and system satisfaction found in IS with e-satisfaction and other antecedents found in marketing because they can play an important role in affecting customers’ responses to a retail-oriented website.
For the above exploration, we employ the theory of reasoned action (TRA) (Ajzen & Fishbein, 1980), and synthesize past research on service quality and satisfaction in marketing and self-efficacy and anxiety in social psychology. This paper can help managers understand online customers’ e-satisfaction formation and repurchase behavior, and retain long-terms customers.
The rest of the paper is organized as follows. Research on the moderating effects of individual differences toward online consumer behavior is reviewed in the next section. The conceptual model is then developed. The method used to test the hypotheses and the results of the data analysis are then presented. In the ensuing section, the contributions and implications are summarized. The final section summarizes the results of the paper.
