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.
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We also examined the possibility that demands for reparation and retaliatory behaviors were higher-order constructs formed by (instead of reflected in) their respective first-order constructs. To do so, we performed two multiple indicators of multiple causes (MIMIC) models by following the procedures of Diamantapoulos and Winklhofer (2001). Both models indicated that the expected first-order constructs were valid and significant components of the higher constructs (all p’s < 0.05). The details of this procedure are available from the first author.
The only exception was procedural fairness for which a lesser but still acceptable value was obtained for the average variance extracted. Nevertheless, the scale was not modified because it has been previously validated.
We performed a similar regression analysis using relationship exit as dependent variable. This constructs was composed of three items including “I stopped flying with the airline” (α = 0.67; AVE = 0.51). In this regression, dissatisfaction (β = 0.216; p < 0.01) and failure severity (β = 0.172; p < 0.05) were significant predictors. Although betrayal had a significant impact (β = 0.159; p < 0.05), its effect was less pronounced compared to those observed for retaliatory behaviors and demands for reparation. Anger had no significant effect (β = −0.046; p < 0.57).
We performed additional regression analyses that included anger and dissatisfaction as control variables. Although the effects of anger were significant (all p’s < 0.001) and those of dissatisfaction close to significant (all p’s < 0.06), the three-way interactions remain significant (all p’s < 0.05), and the pattern of interaction supporting the “love becomes hate” effect remains unchanged. These two control variables are not reported in Table 3 because their inclusion was not theoretically justified.
We also performed mediational analyses that examined the role of betrayal in the relationships “fairness violation → retaliatory behaviors, or demands for reparation.” Following the procedures recommended by Baron and Kenny (1986), we found that the effects of “DF × PF” and “DF × IF” on the two fairness restoration mechanisms were fully mediated by perceived betrayal. The details of this analysis are available from the first author.
We tested the “love becomes hate” hypothesis with anger and dissatisfaction (instead of betrayal) as dependent variables. In contrast to the model with betrayal, none of the three-way interactions achieved significance for anger (all p’s > 0.07) or dissatisfaction (all p’s > 0.24).
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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.
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Grégoire, Y., Fisher, R.J. Customer betrayal and retaliation: when your best customers become your worst enemies. J. of the Acad. Mark. Sci. 36, 247–261 (2008). https://doi.org/10.1007/s11747-007-0054-0
- Customer retaliation
- Customer betrayal
- Justice theory
- Customer relationship
- Service failure and recovery
- Moderated regression analyses