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Cited by 978

The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.

When Customer Love Turns into Lasting Hate: The Effects of Relationship Strength and Time on Customer Revenge and Avoidance

Grégoire, Yany, Tripp, Thomas M., Legoux, Renaud·2009·Journal of Marketing

Abstract

This article explores the effects of time and relationship strength on the evolution of customer revenge and avoidance in online public complaining contexts. First, the authors examine whether online complainers hold a grudge—in terms of revenge and avoidance desires—over time. They find that time affects the two desires differently: Although revenge decreases over time, avoidance increases over time, indicating that customers indeed hold a grudge. Second, the authors examine the moderation effect of a strong relationship on how customers hold this grudge. They find that firms' best customers have the longest unfavorable reactions (i.e., a longitudinal love-becomes-hate effect). Specifically, over time, the revenge of strong-relationship customers decreases more slowly and their avoidance increases more rapidly than that of weak-relationship customers. Third, the authors explore a solution to attenuate this damaging effect—namely, the firm offering an apology and compensation after the online complaint. Overall, they find that strong-relationship customers are more amenable to any level of recovery attempt. The authors test the first two issues with a longitudinal survey and the third issue with a follow-up experiment.

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Metadata

Authors
Grégoire, Y., Tripp, T. M., & Legoux, R.
Venue
Journal of Marketing
Published
2009-11
Volume
73
Issue
6
Pages
18-32
ISSN
  • 0022-2429 (ISSN-L)
  • 1547-7185
OpenAlex
W2180761394
Cited by
978
References
17
FWCI
31.23
Type
journal article
Language
en
Open access
closed

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.