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New insights on random regret minimization models

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  • van Cranenburgh, Sander
  • Guevara, Cristian Angelo
  • Chorus, Caspar G.

Abstract

This paper develops new methodological insights on Random Regret Minimization (RRM) models. It starts by showing that the classical RRM model is not scale-invariant, and that – as a result – the degree of regret minimization behavior imposed by the classical RRM model depends crucially on the sizes of the estimated taste parameters in combination with the distribution of attribute-values in the data. Motivated by this insight, this paper makes three methodological contributions: (1) it clarifies how the estimated taste parameters and the decision rule are related to one another; (2) it introduces the notion of “profundity of regret”, and presents a formal measure of this concept; and (3) it proposes two new family members of random regret minimization models: the μRRM model, and the Pure-RRM model. These new methodological insights are illustrated by re-analyzing 10 datasets which have been used to compare linear-additive RUM and classical RRM models in recently published papers. Our re-analyses reveal that the degree of regret minimizing behavior imposed by the classical RRM model is generally very limited. This insight explains the small differences in model fit that have previously been reported in the literature between the classical RRM model and the linear-additive RUM model. Furthermore, we find that on 4 out of 10 datasets the μRRM model improves model fit very substantially as compared to the RUM and the classical RRM model.

Suggested Citation

  • van Cranenburgh, Sander & Guevara, Cristian Angelo & Chorus, Caspar G., 2015. "New insights on random regret minimization models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 91-109.
    • Handle: RePEc:eee:transa:v:74:y:2015:i:c:p:91-109
    DOI: 10.1016/j.tra.2015.01.008
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    References listed on IDEAS

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    1. Caspar Chorus, 2011. "Random Regret Minimization: An Overview of Model Properties and Empirical Evidence," Transport Reviews, Taylor & Francis Journals, vol. 32(1), pages 75-92, July.
    2. Mara Thiene & Marco Boeri & Caspar Chorus, 2012. "Random Regret Minimization: Exploration of a New Choice Model for Environmental and Resource Economics," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 51(3), pages 413-429, March.
    3. Chorus, Caspar G., 2012. "Logsums for utility-maximizers and regret-minimizers, and their relation with desirability and satisfaction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(7), pages 1003-1012.
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    7. Chorus, Caspar G. & Koetse, Mark J. & Hoen, Anco, 2013. "Consumer preferences for alternative fuel vehicles: Comparing a utility maximization and a regret minimization model," Energy Policy, Elsevier, vol. 61(C), pages 901-908.
    8. Beck, Matthew J. & Rose, John M. & Hensher, David A., 2013. "Consistently inconsistent: The role of certainty, acceptability and scale in choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 56(C), pages 81-93.
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    10. Hess, Stephane & Stathopoulos, Amanda, 2013. "A mixed random utility — Random regret model linking the choice of decision rule to latent character traits," Journal of choice modelling, Elsevier, vol. 9(C), pages 27-38.
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    13. Thijs Dekker & Caspar G. Chorus, 2018. "Consumer surplus for random regret minimisation models," Journal of Environmental Economics and Policy, Taylor & Francis Journals, vol. 7(3), pages 269-286, July.
    14. Chorus, Caspar G. & Annema, Jan Anne & Mouter, Niek & van Wee, Bert, 2011. "Modeling politicians' preferences for road pricing policies: A regret-based and utilitarian perspective," Transport Policy, Elsevier, vol. 18(6), pages 856-861, November.
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    16. Chorus, Caspar G., 2014. "A Generalized Random Regret Minimization model," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 224-238.
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    18. Denzil G. Fiebig & Michael P. Keane & Jordan Louviere & Nada Wasi, 2010. "The Generalized Multinomial Logit Model: Accounting for Scale and Coefficient Heterogeneity," Marketing Science, INFORMS, vol. 29(3), pages 393-421, 05-06.
    19. Chorus, Caspar & van Cranenburgh, Sander & Dekker, Thijs, 2014. "Random regret minimization for consumer choice modeling: Assessment of empirical evidence," Journal of Business Research, Elsevier, vol. 67(11), pages 2428-2436.
    20. Caspar G. Chorus & John M. Rose, 2013. "Selecting a date: a matter of regret and compromises," Chapters, in: Stephane Hess & Andrew Daly (ed.), Choice Modelling, chapter 11, pages 229-242, Edward Elgar Publishing.
    21. Stephane Hess & John Rose, 2012. "Can scale and coefficient heterogeneity be separated in random coefficients models?," Transportation, Springer, vol. 39(6), pages 1225-1239, November.
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    23. Dekker, Thijs, 2014. "Indifference based value of time measures for Random Regret Minimisation models," Journal of choice modelling, Elsevier, vol. 12(C), pages 10-20.
    24. Boeri, Marco & Longo, Alberto & Grisolía, José M. & Hutchinson, W. George & Kee, Frank, 2013. "The role of regret minimisation in lifestyle choices affecting the risk of coronary heart disease," Journal of Health Economics, Elsevier, vol. 32(1), pages 253-260.
    25. Caspar G Chorus & John M Rose & David A Hensher, 2013. "Regret Minimization or Utility Maximization: It Depends on the Attribute," Environment and Planning B, , vol. 40(1), pages 154-169, February.
    26. C. Angelo Guevara & Caspar G. Chorus & Moshe E. Ben-Akiva, 2016. "Sampling of Alternatives in Random Regret Minimization Models," Transportation Science, INFORMS, vol. 50(1), pages 306-321, February.
    27. Train, Kenneth & Wilson, Wesley W., 2008. "Estimation on stated-preference experiments constructed from revealed-preference choices," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 191-203, March.
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