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Modeling dynamic travel mode choices using cumulative prospect theory

Author

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  • Zhou, Yuyang
  • Wang, Peiyu
  • Zheng, Shuyan
  • Zhao, Minhe
  • Lam, William H.K.
  • Chen, Anthony
  • Sze, N.N.
  • Chen, Yanyan

Abstract

Travelers’ mode choice behavior is jointly influenced by their attributes, such as personal income, vehicle ownership, and travel purpose, and external factors, such as the built environment and traffic state. The mode chosen by a traveler before a trip may change during the trip due to uncertainties associated with transportation systems. A cumulative prospect theory-based dynamic mode choice model that describes the changes in decisions at different travel stages is proposed to investigate the within-trip mode-shifting behavior during daily travel. The journey duration or travel time of a trip is divided into a series of stages, which includes the access or connection time (i.e., the time required for the traveler to reach the station or vehicle), waiting time, in-vehicle time, and parking time. The generalized travel cost includes the expense cost, time cost, and penalty cost. The penalty cost is expressed as a negative exponential function with respect to the punctuality satisfaction rating. A novel method is proposed for calculating the mode choice possibility in terms of the changes in travel cost during a trip, in which the psychological weights at different stages are reflected by the ratio of the actual travel time to the expected travel time. Data from a journey survey involving 637 respondents in Beijing were used to test the model. The results of a random parameter logit model reveal the main influencing factors of each travel mode, and show that economic strategies can influence the mode choice of 77.94% of travelers. The dynamic mode choice model predicted the pre-trip mode and mode shift with accuracies of 90.05% and 67.86%, respectively, both of which are higher than those of the expected utility theory-based model. Moreover, the results show that mode-shifting behaviors during a trip generally occur in public transit mode and/or active travel mode. The study results demonstrate the dynamic characteristic and quantitative change in mode choice behavior in multi-mode daily travel and are beneficial for the study of travel behavior in relation to the traffic environment.

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  • Zhou, Yuyang & Wang, Peiyu & Zheng, Shuyan & Zhao, Minhe & Lam, William H.K. & Chen, Anthony & Sze, N.N. & Chen, Yanyan, 2024. "Modeling dynamic travel mode choices using cumulative prospect theory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
  • Handle: RePEc:eee:transa:v:179:y:2024:i:c:s0965856423003580
    DOI: 10.1016/j.tra.2023.103938
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    as
    1. Xu, Hongli & Lou, Yingyan & Yin, Yafeng & Zhou, Jing, 2011. "A prospect-based user equilibrium model with endogenous reference points and its application in congestion pricing," Transportation Research Part B: Methodological, Elsevier, vol. 45(2), pages 311-328, February.
    2. Mohring, Herbert, 1972. "Optimization and Scale Economies in Urban Bus Transportation," American Economic Review, American Economic Association, vol. 62(4), pages 591-604, September.
    3. Schwanen, Tim & Ettema, Dick, 2009. "Coping with unreliable transportation when collecting children: Examining parents' behavior with cumulative prospect theory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(5), pages 511-525, June.
    4. Fan, Yingling & Guthrie, Andrew & Levinson, David, 2016. "Waiting time perceptions at transit stops and stations: Effects of basic amenities, gender, and security," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 251-264.
    5. André de Palma & Pierre Hansen & Martine Labbé, 1990. "Commuters' Paths with Penalties for Early or Late Arrival Time," Transportation Science, INFORMS, vol. 24(4), pages 276-286, November.
    6. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    7. Ye, Runing & De Vos, Jonas & Ma, Liang, 2020. "Analysing the association of dissonance between actual and ideal commute time and commute satisfaction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 47-60.
    8. Cats, Oded & West, Jens & Eliasson, Jonas, 2016. "A dynamic stochastic model for evaluating congestion and crowding effects in transit systems," Transportation Research Part B: Methodological, Elsevier, vol. 89(C), pages 43-57.
    9. Vasudevan, N. & Gore, Ninad & Zope, Rupali & Arkatkar, Shriniwas & Joshi, Gaurang, 2021. "Determining mode shift elasticity based on household income and travel cost," Research in Transportation Economics, Elsevier, vol. 85(C).
    10. Chakroborty, Partha & Pinjari, Abdul Rawoof & Meena, Jayant & Gandhi, Avinash, 2021. "A Psychophysical Ordered Response Model of Time Perception and Service Quality: Application to Level of Service Analysis at Toll Plazas," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 44-64.
    11. Jou, Rong-Chang & Chen, Ke-Hong, 2013. "An application of cumulative prospect theory to freeway drivers’ route choice behaviours," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 123-131.
    12. El-Geneidy, Ahmed & Levinson, David & Diab, Ehab & Boisjoly, Genevieve & Verbich, David & Loong, Charis, 2016. "The cost of equity: Assessing transit accessibility and social disparity using total travel cost," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 302-316.
    13. Geng, Jichao & Long, Ruyin & Chen, Hong, 2016. "Impact of information intervention on travel mode choice of urban residents with different goal frames: A controlled trial in Xuzhou, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 134-147.
    14. de Moraes Ramos, Giselle & Daamen, Winnie & Hoogendoorn, Serge, 2013. "Modelling travellers' heterogeneous route choice behaviour as prospect maximizers," Journal of choice modelling, Elsevier, vol. 6(C), pages 17-33.
    15. Abdullah, Muhammad & Ali, Nazam & Hussain, Syed Arif & Aslam, Atif Bilal & Javid, Muhammad Ashraf, 2021. "Measuring changes in travel behavior pattern due to COVID-19 in a developing country: A case study of Pakistan," Transport Policy, Elsevier, vol. 108(C), pages 21-33.
    16. Du, Fangye & Mao, Liang & Wang, Jiaoe, 2021. "Determinants of travel mode choice for seeking healthcare: A comparison between elderly and non-elderly patients," Journal of Transport Geography, Elsevier, vol. 92(C).
    17. Ha, Jaehyun & Lee, Sugie & Ko, Joonho, 2020. "Unraveling the impact of travel time, cost, and transit burdens on commute mode choice for different income and age groups," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 147-166.
    18. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    19. Wiktor Adamowicz & Sarah Jennings & Alison Coyne, 1989. "A Sequential Choice Alternative to the Travel Cost Model," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 37(4), pages 1305-1305, December.
    20. Li, Yongling & Geertman, Stan & Hooimeijer, Pieter & Lin, Yanliu & Yang, Haoran, 2021. "Do migrants and locals differ in commuting behavior? A case study of Xiamen, China," Transport Policy, Elsevier, vol. 108(C), pages 1-10.
    21. Xiong, Siqin & Yuan, Yi & Yao, Jia & Bai, Bo & Ma, Xiaoming, 2023. "Exploring consumer preferences for electric vehicles based on the random coefficient logit model," Energy, Elsevier, vol. 263(PA).
    22. Andani, I Gusti Ayu & La Paix Puello, Lissy & Geurs, Karst, 2021. "Modelling effects of changes in travel time and costs of toll road usage on choices for residential location, route and travel mode across population segments in the Jakarta-Bandung region, Indonesia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 81-102.
    23. Mao, Zidan & Ettema, Dick & Dijst, Martin, 2016. "Commuting trip satisfaction in Beijing: Exploring the influence of multimodal behavior and modal flexibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 592-603.
    24. Das, Sanhita & Boruah, Alice & Banerjee, Arunabha & Raoniar, Rahul & Nama, Suresh & Maurya, Akhilesh Kumar, 2021. "Impact of COVID-19: A radical modal shift from public to private transport mode," Transport Policy, Elsevier, vol. 109(C), pages 1-11.
    25. Mohammadzadeh, Mohsen, 2020. "Exploring tertiary students' travel mode choices in Auckland: Insights and policy implications," Journal of Transport Geography, Elsevier, vol. 87(C).
    26. McConnell, Kenneth E., 1985. "The economics of outdoor recreation," Handbook of Natural Resource and Energy Economics, in: A. V. Kneese† & J. L. Sweeney (ed.), Handbook of Natural Resource and Energy Economics, edition 1, volume 2, chapter 15, pages 677-722, Elsevier.
    27. Small, Kenneth A, 1982. "The Scheduling of Consumer Activities: Work Trips," American Economic Review, American Economic Association, vol. 72(3), pages 467-479, June.
    28. Wardman, Mark, 2004. "Public transport values of time," Transport Policy, Elsevier, vol. 11(4), pages 363-377, October.
    29. Geng, Kexin & Wang, Yacan & Cherchi, Elisabetta & Guarda, Pablo, 2023. "Commuter departure time choice behavior under congestion charge: Analysis based on cumulative prospect theory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 168(C).
    30. Hess, Stephane & Orr, Shepley & Sheldon, Rob, 2012. "Consistency and fungibility of monetary valuations in transport: An empirical analysis of framing and mental accounting effects," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1507-1516.
    31. Leng, Jun-qiang & Zhai, Jing & Li, Qian-wen & Zhao, Lin, 2018. "Construction of road network vulnerability evaluation index based on general travel cost," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 493(C), pages 421-429.
    32. Gao, Yanan & Rasouli, Soora & Timmermans, Harry & Wang, Yuanqing, 2018. "Trip stage satisfaction of public transport users: A reference-based model incorporating trip attributes, perceived service quality, psychological disposition and difference tolerance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 759-775.
    33. Shahadat Hossain, Md & Rahman Fatmi, Mahmudur, 2022. "Modeling individuals’ preferences towards different levels of vehicle autonomy: A random parameter rank-ordered logit model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 163(C), pages 88-99.
    34. Kroesen, Maarten, 2014. "Modeling the behavioral determinants of travel behavior: An application of latent transition analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 65(C), pages 56-67.
    35. Lai, Xinjun & Lam, William H.K. & Su, Junbiao & Fu, Hui, 2019. "Modelling intra-household interactions in time-use and activity patterns of retired and dual-earner couples," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 172-194.
    36. Li, Yaping & Guo, Yuntao & Lu, Jian & Peeta, Srinivas, 2019. "Impacts of congestion pricing and reward strategies on automobile travelers’ morning commute mode shift decisions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 125(C), pages 72-88.
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