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Consumer surplus for random regret minimisation models

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  • Thijs Dekker
  • Caspar G. Chorus

Abstract

This paper is the first to develop a measure of consumer surplus for the Random Regret Minimisation (RRM) model. Following a not so well-known approach proposed two decades ago, we measure (changes in) consumer surplus by studying (changes in) observed behaviour, i.e. the choice probability, in response to price (changes). We interpret the choice probability as a well-behaved approximation of the probabilistic demand curve and accordingly measure the consumer surplus as the area underneath this demand curve. The developed welfare measure enables researchers to assign a measure of consumer surplus to specific alternatives in the context of a given choice set. Moreover, we are able to value changes in the non-price attributes of a specific alternative. We illustrate how differences in consumer surplus between random regret and random utility models follow directly from the differences in their behavioural premises.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:teepxx:v:7:y:2018:i:3:p:269-286
    DOI: 10.1080/21606544.2018.1424039
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    Citations

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    Cited by:

    1. Hasnine, Md Sami & Habib, Khandker Nurul, 2020. "Transportation demand management (TDM) and social justice: A case study of differential impacts of TDM strategies on various income groups," Transport Policy, Elsevier, vol. 94(C), pages 1-10.
    2. Geržinič, Nejc & van Cranenburgh, Sander & Cats, Oded & Lancsar, Emily & Chorus, Caspar, 2021. "Estimating decision rule differences between ‘best’ and ‘worst’ choices in a sequential best worst discrete choice experiment," Journal of choice modelling, Elsevier, vol. 41(C).
    3. Luan, Siliang & Yang, Qingfang & Jiang, Zhongtai & Wang, Wei, 2021. "Exploring the impact of COVID-19 on individual's travel mode choice in China," Transport Policy, Elsevier, vol. 106(C), pages 271-280.
    4. John Buckell & Vrinda Vasavada & Sarah Wordsworth & Dean A. Regier & Matthew Quaife, 2022. "Utility maximization versus regret minimization in health choice behavior: Evidence from four datasets," Health Economics, John Wiley & Sons, Ltd., vol. 31(2), pages 363-381, February.
    5. van Wee, Bert & van Cranenburgh, Sander & Maat, Kees, 2019. "Substitutability as a spatial concept to evaluate travel alternatives," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    6. Cai, Zeen & Mo, Dong & Geng, Maosi & Tang, Wei & Chen, Xiqun Michael, 2023. "Integrating ride-sourcing with electric vehicle charging under mixed fleets and differentiated services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 169(C).
    7. van Cranenburgh, Sander & Chorus, Caspar G., 2018. "Does the decision rule matter for large-scale transport models?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 114(PB), pages 338-353.
    8. Hensher, David A., 2019. "Context dependent process heuristics and choice analysis – A note on two interacting themes linked to behavioural realism," Transportation Research Part A: Policy and Practice, Elsevier, vol. 125(C), pages 119-122.
    9. Mai, Nhat Chi, 2022. "Behavioural Economics Assignment: Business Consumer Decision-Making & Consumer Surplus," OSF Preprints 4jrc8, Center for Open Science.
    10. 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.

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