The DOI matches its Crossref record; 140 of the 140 references it cites were found in a registry or an index.
Modeling the Psychology of Consumer and Firm Behavior with Behavioral Economics
Abstract
Marketing is an applied science that tries to explain and influence how firms and consumers behave in markets. Marketing models are usually applications of standard economic theories, which rely on strong assumptions of rationality of consumers and firms. Behavioral economics explores the implications of the limits of rationality, with the goal of making economic theories more plausible by explaining and predicting behavior more accurately while maintaining formal power. This article reviews six behavioral economics models that are useful to marketing. Three models generalize standard preference structures to allow for sensitivity to reference points and loss aversion, social preferences toward outcomes of others, and preference for instant gratification. The other three models generalize the concept of game-theoretic equilibrium, allowing decision makers to make mistakes, encounter limits on the depth of strategic thinking, and equilibrate by learning from feedback. The authors also discuss a specific marketing application for each of these six models. The goal of this article is to encourage marketing researchers to apply these models. Doing so will raise technical challenges for modelers and will require thoughtful input from psychologists who study consumer behavior. Consequently, such models could create a common language both for modelers who prize formality and for psychologists who prize realism.
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1 retracted
RETRACTED: Procrastination, Deadlines, and Performance: Self-Control by Precommitment
Ariely, D., & Wertenbroch, K. (2002) · Psychological Science · doi:10.1111/1467-9280.00441 · Cited by 1,266 · cited 1×
“…sophisticate )1ˆ( = ββ , who is fully aware of her time-inconsistency and make decisions that rationally anticipate these problems.17 The sophisticate will seek external self-control devices to commit herself to acting patiently in the future (Ariely and Wertenbroch 2002), but the naïf will not.”
BackgroundRetractedProspect Theory: An Analysis of Decision under Risk
Kahneman, D., & Tversky, A. (1979) · Econometrica · doi:10.2307/1914185 · Cited by 48,524
Prospect theory: An analysis of decision under risk
Kahneman, D., & Tversky, A. (1988) · Decision, Probability and Utility · doi:10.1017/cbo9780511609220.014 · Cited by 32,474
Theory of games and economic behavior
(2019) · 100 Years of Math Milestones · doi:10.1090/mbk/121/32 · Cited by 16,632
Filders, R. (1992) · International Journal of Forecasting · doi:10.1016/0169-2070(92)90130-2 · Cited by 16,165
Advances in prospect theory: Cumulative representation of uncertainty
Tversky, A., & Kahneman, D. (1992) · Journal of Risk and Uncertainty · doi:10.1007/bf00122574 · Cited by 15,467
A Theory of Fairness, Competition, and Cooperation
Fehr, E., & Schmidt, K. M. (1999) · The Quarterly Journal of Economics · doi:10.1162/003355399556151 · Cited by 11,264
(2013) · American Economic Review · doi:10.1257/aer.103.6.i · Cited by 7,220
Loss aversion in riskless choice: A reference-dependent model.
Tversky, A., & Kahneman, D. (1991) · The Quarterly Journal of Economics · doi:10.2307/2937956 · Cited by 6,432
Time Discounting and Time Preference: A Critical Review
Frederick, S., Loewenstein, G. F., & O’Donoghue, T. (2002) · Journal of Economic Literature · doi:10.1257/002205102320161311 · Cited by 6,381
Cited by
Ho, T.-H., & Zhang, J. (2008) · Management Science · doi:10.1287/mnsc.1070.0788 · Cited by 331
Self-citationDoes Customer Demotion Jeopardize Loyalty?
Wagner, T., Hennig-Thurau, T., & Rudolph, T. (2009) · Journal of Marketing · doi:10.1509/jmkg.73.3.069 · Cited by 286
Metadata
- Authors
- Ho, T. H., Lim, N., & Camerer, C. F.
- Venue
- Journal of Marketing Research
- Publisher
- SAGE Publications
- Published
- 2006-08
- Volume
- 43
- Issue
- 3
- Pages
- 307-331
- ISSN
- 0022-2437 (ISSN-L)
- 1547-7193
- OpenAlex
- W1978560443
- Cited by
- 259
- References
- 140
- FWCI
- 6.78
- 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.