Online Consumers' Switching Behavior: A Buyer-Seller Relationship Perspective
Dahui Li (University of Minnesota Duluth, USA), Glenn J. Browne (Texas Tech University, USA) and James C. Wetherbe (Texas Tech University, USA)
Copyright: © 2009
Limited studies have investigated online consumer loyalty and retention from a relationship orientation in electronic commerce research. It is important to understand the differences in relationship orientations between people who have the propensity to stick to particular web sites (“stayers”) and people who have the propensity to switch to alternative web sites (“switchers”). This study proposes a relationship-based classification schema consisting of five dimensions, i.e., commitment, trust, satisfaction, comparison level of the alternatives, and non-retrievable investment. Data were collected from 299 college students who had experience with e-commerce websites. Using discriminant analysis, we found that stayers and switchers were significantly different along the five research dimensions. Satisfaction with the current website was the most important discriminant factor, followed by trust, commitment, comparison level of alternative websites, and non-retrievable investment in the current website. Implications of the findings for researchers and practitioners are discussed.
Several studies have investigated online switching behaviors. Keaveney and Parthasarathy (2001) found that online consumers’ previous behavioral patterns (e.g., service usage), attitudes (e.g., risk-taking, satisfaction, and involvement), and demographic characteristics (e.g., income and education) were significant discriminating factors between stayers and switchers. In an investigation of the online brokerage industry, Chen and Hitt (2002) found that online consumers’ system usage and the breadth and quality of alternative online service providers were significant in predicting switching behavior. Gupta et al. (2004) found that consumers switching from off-line to online transactions paid attention to channel risk, search effort, and learning effort.