E-Customer Loyalty

E-Customer Loyalty

Alvin Y.C. Yeo, Michael K.M. Chiam
Copyright: © 2006 |Pages: 6
DOI: 10.4018/978-1-59140-799-7.ch055
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Abstract

Increasingly, businesses are beginning to understand the profit potential of loyal customers (Oliver, 1999). Marketers endowed with such consumers can expect repeat patronage to remain high until competitors can find a way to: (1) close the gap in attitude among brands, (2) increase the differentiation of their own brand, or (3) encourage spurious loyalty from consumers (Dick & Basu, 1994). Loyalty leads to higher retention. According to one study, a 5% increase in customer retention rates increases profits by 25% to 95% (Reicheld & Schefter, 2000). It is thus heartening to note that “one of the most exciting and successful uses of [the Internet] … may be the Internet’s role in building customer loyalty and maximizing sales to your existing customers” (Griffin, 1996, p. 50). Given its relative importance in cyberspace, it is surprising that relatively little has been done in conceptualizing and validating e-loyalty models (Luarn & Lin, 2003). Parasuraman and Grewal (2000) argue for more research pertaining to the influence of technology on customer responses, such as perceived value and customer loyalty. Besides customer trust, our study also incorporates two constructs—corporate image and perceived value—that have been poorly explored in online environments despite their recognized importance in off-line contexts. Consequently, a primary objective of this article is to discuss the impact of three constructs (i.e., customer trust, corporate image, and perceived value) on e-loyalty in a business-to-consumer (B2C) e-commerce context. In doing so, our model is expected to offer useful suggestions on how to manage customer trust, corporate image, and perceived value as online loyalty management tools. This article is generally divided into three sections. The first section will discuss the constructs of interest and clarify what they mean. In the second section, we will propose hypotheses explaining these relationships. And in the final section, we introduce actionable strategies for online loyalty management based on the proposed framework.

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