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Travel Choice Inertia: The Joint Role of Risk Aversion and Learning

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  • Caspar G. Chorus
  • Benedict G. C. Dellaert

Abstract

This paper shows how travellers that are faced with a series of risky choices become behaviourally inert due to a combination of risk aversion and learning. Our theoretical analyses complement other studies that conceive inertia as resulting from the wish to save cognitive resources. We first present a model of risky travel mode choice. We show that if travellers dislike risk, and part of the quality of travel alternatives is only revealed upon usage, inertia emerges due to a learning-based lock-in effect. We extend our analyses to capture forward-looking behaviour and the provision of travel information. © 2012 LSE and the University of Bath

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  • Caspar G. Chorus & Benedict G. C. Dellaert, 2012. "Travel Choice Inertia: The Joint Role of Risk Aversion and Learning," Journal of Transport Economics and Policy, University of Bath, vol. 46(1), pages 139-155, January.
  • Handle: RePEc:tpe:jtecpo:v:46:y:2012:i:1:p:139-155
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    Cited by:

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    2. Maria Fernanda Guajardo Ortega & Heike Link, 2023. "Estimating Mode Choice Inertia and Price Elasticities after a Price Intervention – Evidence from Three Months of almost Fare-free Public Transport in Germany," Discussion Papers of DIW Berlin 2052, DIW Berlin, German Institute for Economic Research.
    3. de Haas, M.C. & Scheepers, C.E. & Harms, L.W.J. & Kroesen, M., 2018. "Travel pattern transitions: Applying latent transition analysis within the mobility biographies framework," Transportation Research Part A: Policy and Practice, Elsevier, vol. 107(C), pages 140-151.
    4. Yan, Xiang & Zhao, Xilei & Han, Yuan & Hentenryck, Pascal Van & Dillahunt, Tawanna, 2021. "Mobility-on-demand versus fixed-route transit systems: An evaluation of traveler preferences in low-income communities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 481-495.
    5. Qi, Hang & Jia, Ning & Qu, Xiaobo & He, Zhengbing, 2023. "Investigating day-to-day route choices based on multi-scenario laboratory experiments, Part I: Route-dependent attraction and its modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 167(C).
    6. Chen, Kang & Chen, Dongxu & Sun, Xueshan & Yang, Zhongzhen, 2016. "Container Ocean-transportation System Design with the factors of demand fluctuation and choice inertia of shippers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 95(C), pages 267-281.
    7. Xie, Chi & Liu, Zugang, 2014. "On the stochastic network equilibrium with heterogeneous choice inertia," Transportation Research Part B: Methodological, Elsevier, vol. 66(C), pages 90-109.
    8. Sun, Mingmei, 2023. "A day-to-day dynamic model for mixed traffic flow of autonomous vehicles and inertial human-driven vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 173(C).
    9. Hongli Xu & Hai Yang & Jing Zhou & Yafeng Yin, 2017. "A Route Choice Model with Context-Dependent Value of Time," Transportation Science, INFORMS, vol. 51(2), pages 536-548, May.

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    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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