Customer betrayal and retaliation: when your best customers become your worst enemies
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After a service failure and a poor recovery, what leads loyal customers to try to punish a firm even if there is no material gain for doing so? We propose and test a justice-based model that incorporates perceived betrayal as the means to understand customer retaliation and the “love becomes hate” effect. The results suggest that betrayal is a key motivational force that leads customers to restore fairness by all means possible, including retaliation. In contrast to the majority of findings in the service literature, we propose and find that relationship quality has unfavorable effects on a customer’s response to a service recovery. As a relationship gains in strength, a violation of the fairness norm was found to have a stronger effect on the sense of betrayal experienced by customers. The model was tested on a national sample of airline passengers who complained to a consumer agency after an unsuccessful recovery.
KeywordsCustomer retaliation Customer betrayal Justice theory Customer relationship Survey Service failure and recovery Moderated regression analyses
The authors gratefully acknowledge support for this research from the Social Sciences and Humanities Council of Canada, the Quebec Government “Fonds pour la formation de chercheurs et l’aide à la recherche,” the Richard Ivey School of Business, and the Canadian Transportation Agency. They also would like to thank Richard Elgar, Allison Johnson, Jean Johnson, Kelly Martin, Dave Sprott, Tom Tripp, and the PhD students from the course Marketing Theory (WSU) for their constructive suggestions on earlier versions of this manuscript.
- Aiken, L. S., & West S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury Park, CA: Sage.Google Scholar
- Bardhi, F., Price, L. L., & Arnould, E. J. (2005). Extreme service failures. Working paper, University of Nebraska.Google Scholar
- Bentler, P. M., & Cho, C.-P. (1988). Practical issues in structural modeling. In J. S. Long (Ed.), Common problems/proper solutions: Avoiding error in quantitative research (pp. 161–192). Newbury Park, CA: Sage.Google Scholar
- Blau, P. (1962). Exchange and power in social life. New York: Wiley.Google Scholar
- Cohen, J., Cohen, P., West, S. G., & West, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd Ed.). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
- Customer Care M&C. (2005). First results of the 2005 national customer rage study. Available at: http://www.customercaremc.com.
- Heskett, J. L., Sasser Jr., W. E., & Schlesinger, L. A. (1997). The service profit chain: How leading companies link profit to loyalty, satisfaction, and value. New York: Free Press.Google Scholar
- Huefner, J. C., Parry, B. L., Payne, C. R., Otto, S. D., Huff, S. C., Swenson, M. J., et al. (2002). Consumer retaliation: Confirmation and extension. Journal of Consumer Satisfaction, Dissatisfaction and Complaining Behavior, 15, 114–127.Google Scholar
- Lyons, D. (2005). Attack of the blogs. Forbes, 176, 128 (November).Google Scholar
- Oliver, R. L. (1996). Satisfaction: A behavioral perspective on the consumer. New York: McGraw-Hill.Google Scholar
- Singh, J. (1990). A typology of consumer dissatisfaction response styles. Journal of Retailing, 66, 57–99 (Spring).Google Scholar
- The Economist (2006). The blog in the corporate machine. The Economist, 378, 66 (February 11).Google Scholar
- Yahoo! (2007). Consumer advocacy and information in the Yahoo! directory. Available at: http://dir.yahoo.com/Society_and_Culture/Issues_and_Causes/Consumer_Advocacy_and_Information.