The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Regret: A Model of Its Antecedents and Consequences in Consumer Decision Making
Open accessAbstract
The article develops a model of regret and tests it via four studies. Study 1 develops a multi-item measure of regret and distinguishes it from satisfaction. It also shows that, while satisfaction directly influences both repurchase and complaint intentions, regret directly influences only repurchase intentions, and its effect on complaint intentions is fully mediated via satisfaction. Study 2 examines the antecedents and moderators of regret. It shows that regret is experienced even in the absence of information on a better-forgone outcome. Furthermore, the moderating effect of three situation-specific characteristics (outcome valence, status quo preservation, and reversibility of the outcome) is examined. Studies 3 and 4 examine the cognitive process underlying the experiencing of regret in the absence of information on a better-forgone outcome. Generation of counterfactuals is identified as the cognitive mechanism that engenders regret. Results show that counterfactuals are most likely to be generated when the chosen outcome is negative and not the status quo.
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“Tsiros and Mittal (2000) define regret as one's realization that the choice one considered suitable and made under pressure was actually mistaken.”
BackgroundZhao, H., Wang, X., & Jiang, L. (2021) · Journal of Business Research · doi:10.1016/j.jbusres.2020.10.067 · Cited by 52
Metadata
- Authors
- Tsiros, M., & Mittal, V.
- Venue
- Journal of Consumer Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2000-03
- Volume
- 26
- Issue
- 4
- Pages
- 401-417
- ISSN
- 0093-5301 (ISSN-L)
- 1537-5277
- OpenAlex
- W1967154531
- Cited by
- 604
- References
- 7
- FWCI
- 4.20
- Type
- journal article
- Language
- en
- Open access
- green
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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.
