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Random Regret Minimization: An Overview of Model Properties and Empirical Evidence

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  • Caspar Chorus

Abstract

This paper presents an overview of model properties and empirical evidence related to the recently introduced discrete choice paradigm of random regret minimization (RRM). The RRM approach to discrete choice modelling provides an alternative to the conventional, linear-additive random utility maximization (RUM)-based approach which has dominated the field since its inception. Section of Transport and Logistics RRM models postulate that when choosing, decision-makers are concerned with avoiding the situation where one or more non-chosen alternatives perform better than a chosen one in terms of one or more attributes. From this central behavioural premise, semi-compensatory decision-making and choice set composition effects like the compromise effect emerge as RRM model features. Being as parsimonious as RUM's linear-additive multinomial logit model, RRM features logit choice probabilities and is easily estimable using conventional discrete choice software packages. This paper ties together the main insights and results from a number of recent studies that have explored RRM's model properties and empirically tested RRM-based models Delft University of Technology, based on a range of revealed and stated choice data sets. As such, the paper allows for an early assessment of RRM's potential and its limitations as a model of discrete (travel) choice behaviour.

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  • 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.
    • Handle: RePEc:taf:transr:v:32:y:2011:i:1:p:75-92
    DOI: 10.1080/01441647.2011.609947
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    3. Chorus, Caspar G. & de Jong, Gerard C., 2011. "Modeling experienced accessibility for utility-maximizers and regret-minimizers," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1155-1162.
    4. Arentze, Theo & Timmermans, Harry, 2007. "Parametric action decision trees: Incorporating continuous attribute variables into rule-based models of discrete choice," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 772-783, August.
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    6. Caspar G Chorus & Theo A Arentze & Harry J P Timmermans, 2009. "Spatial Choice: A Matter of Utility or Regret?," Environment and Planning B, , vol. 36(3), pages 538-551, June.
    7. Moshe Ben-Akiva & Joffre Swait, 1986. "The Akaike Likelihood Ratio Index," Transportation Science, INFORMS, vol. 20(2), pages 133-136, May.
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    9. John D. Hey & Chris Orme, 2018. "Investigating Generalizations Of Expected Utility Theory Using Experimental Data," World Scientific Book Chapters, in: Experiments in Economics Decision Making and Markets, chapter 3, pages 63-98, World Scientific Publishing Co. Pte. Ltd..
    10. Chorus, Caspar G. & Arentze, Theo A. & Timmermans, Harry J.P., 2008. "A Random Regret-Minimization model of travel choice," Transportation Research Part B: Methodological, Elsevier, vol. 42(1), pages 1-18, January.
    11. Zhang, Junyi & Timmermans, Harry & Borgers, Aloys & Wang, Donggen, 2004. "Modeling traveler choice behavior using the concepts of relative utility and relative interest," Transportation Research Part B: Methodological, Elsevier, vol. 38(3), pages 215-234, March.
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    Cited by:

    1. Aurélien Baillon & Han Bleichrodt & Alessandra Cillo, 2015. "A Tailor-Made Test of Intransitive Choice," Operations Research, INFORMS, vol. 63(1), pages 198-211, February.
    2. Carlo Prato, 2014. "Expanding the applicability of random regret minimization for route choice analysis," Transportation, Springer, vol. 41(2), pages 351-375, March.
    3. Leong, Waiyan & Hensher, David A., 2014. "Relative advantage maximisation as a model of context dependence for binary choice data," Journal of choice modelling, Elsevier, vol. 11(C), pages 30-42.
    4. Haghani, Milad & Sarvi, Majid, 2018. "Hypothetical bias and decision-rule effect in modelling discrete directional choices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 361-388.
    5. 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.
    6. Sunghoon Jang & Soora Rasouli & Harry Timmermans, 2017. "Incorporating psycho-physical mapping into random regret choice models: model specifications and empirical performance assessments," Transportation, Springer, vol. 44(5), pages 999-1019, September.
    7. Mai, Tien & Bastin, Fabian & Frejinger, Emma, 2017. "On the similarities between random regret minimization and mother logit: The case of recursive route choice models," Journal of choice modelling, Elsevier, vol. 23(C), pages 21-33.
    8. 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.
    9. 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.
    10. Haghani, Milad & Sarvi, Majid, 2019. "Laboratory experimentation and simulation of discrete direction choices: Investigating hypothetical bias, decision-rule effect and external validity based on aggregate prediction measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 134-157.
    11. Chorus, Caspar G., 2014. "A Generalized Random Regret Minimization model," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 224-238.
    12. 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.
    13. Caspar Chorus & Michel Bierlaire, 2013. "An empirical comparison of travel choice models that capture preferences for compromise alternatives," Transportation, Springer, vol. 40(3), pages 549-562, May.
    14. Caspar G. Chorus, 2014. "Capturing alternative decision rules in travel choice models: a critical discussion," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 13, pages 290-310, Edward Elgar Publishing.

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