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Latent variables and route choice behavior

Author

Listed:
  • Carlo Giacomo Prato

    (Department of Transport - DTU - Danmarks Tekniske Universitet = Technical University of Denmark)

  • Shlomo Bekhor

    (Faculty of Civil and Environmental Engineering - Technion - Israel Institute of Technology [Haifa])

  • Cristina Pronello

    (LET - Laboratoire d'économie des transports - UL2 - Université Lumière - Lyon 2 - ENTPE - École Nationale des Travaux Publics de l'État - CNRS - Centre National de la Recherche Scientifique, Dipartimento di Idraulica Trasporti e Infrastrutture Civili - Polito - Politecnico di Torino = Polytechnic of Turin)

Abstract

In the last decade, a broad array of disciplines has shown a general interest in enhancing discrete choice models by considering the incorporation of psychological factors affecting decision making. This paper provides insight into the comprehension of the determinants of route choice behavior by proposing and estimating a hybrid model that integrates latent variable and route choice models. Data contain information about latent variable indicators and chosen routes of travelers driving regularly from home to work in an urban network. Choice sets include alternative routes generated with a branch and bound algorithm. A hybrid model consists of measurement equations, which relate latent variables to measurement indicators and utilities to choice indicators, and structural equations, which link travelers' observable characteristics to latent variables and explanatory variables to utilities. Estimation results illustrate that considering latent variables (i.e., memory, habit, familiarity, spatial ability, time saving skills) alongside traditional variables (e.g., travel time, distance, congestion level) enriches the comprehension of route choice behavior.

Suggested Citation

  • Carlo Giacomo Prato & Shlomo Bekhor & Cristina Pronello, 2012. "Latent variables and route choice behavior," Post-Print halshs-00733464, HAL.
    • Handle: RePEc:hal:journl:halshs-00733464
    DOI: 10.1007/s11116-011-9344-y
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    Citations

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    Cited by:

    1. Bartosz Bursa & Markus Mailer & Kay W. Axhausen, 2022. "Intra-destination travel behavior of alpine tourists: a literature review on choice determinants and the survey work," Transportation, Springer, vol. 49(5), pages 1465-1516, October.
    2. Junghan Baek & Keemin Sohn, 2016. "An investigation into passenger preference for express trains during peak hours," Transportation, Springer, vol. 43(4), pages 623-641, July.
    3. Kim, Hyunmi & Kwon, Sohee & Wu, Seung Kook & Sohn, Keemin, 2014. "Why do passengers choose a specific car of a metro train during the morning peak hours?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 61(C), pages 249-258.
    4. Chorus, Caspar G. & Kroesen, Maarten, 2014. "On the (im-)possibility of deriving transport policy implications from hybrid choice models," Transport Policy, Elsevier, vol. 36(C), pages 217-222.
    5. Keemin Sohn, 2017. "An Expectation-Maximization Algorithm to Estimate the Integrated Choice and Latent Variable Model," Transportation Science, INFORMS, vol. 51(3), pages 946-967, August.
    6. Carlo Prato, 2014. "Expanding the applicability of random regret minimization for route choice analysis," Transportation, Springer, vol. 41(2), pages 351-375, March.
    7. Manley, E.J. & Addison, J.D. & Cheng, T., 2015. "Shortest path or anchor-based route choice: a large-scale empirical analysis of minicab routing in London," Journal of Transport Geography, Elsevier, vol. 43(C), pages 123-139.
    8. Balbontin, Camila & Hensher, David A. & Beck, Matthew J., 2022. "Advanced modelling of commuter choice model and work from home during COVID-19 restrictions in Australia," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 162(C).
    9. Benedict G. C. Dellaert & Joffre Swait & Wiktor L. Vic Adamowicz & Theo A. Arentze & Elizabeth E. Bruch & Elisabetta Cherchi & Caspar Chorus & Bas Donkers & Fred M. Feinberg & A. A. J. Marley & Linda , 2018. "Individuals’ Decisions in the Presence of Multiple Goals," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 51-64, March.
      • Dellaert, B.G.C. & Swait, J. & Adamowicz, W.L. & Arentze, T.A. & Bruch, E.E. & Cherchi, E. & Chorus, C.G. & Donkers, A.C.D. & Feinberg, F.M. & Marley, A.A.J. & Salisbury, L.C., 2017. "Individuals' Decisions in the Presence of Multiple Goals," ERIM Report Series Research in Management ERS-2017-007-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    10. Weckström, Christoffer & Mladenović, Miloš N. & Kujala, Rainer & Saramäki, Jari, 2021. "Navigability assessment of large-scale redesigns in nine public transport networks: Open timetable data approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 212-229.
    11. Joseph F. Hair & Christian M. Ringle & Siegfried P. Gudergan & Andreas Fischer & Christian Nitzl & Con Menictas, 2019. "Partial least squares structural equation modeling-based discrete choice modeling: an illustration in modeling retailer choice," Business Research, Springer;German Academic Association for Business Research, vol. 12(1), pages 115-142, April.
    12. Thorhauge, Mikkel & Swait, Joffre & Cherchi, Elisabetta, 2020. "The habit-driven life: Accounting for inertia in departure time choices for commuting trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 272-289.
    13. Gustavo García-Melero & Rubén Sainz-González & Pablo Coto-Millán & Alejandra Valencia-Vásquez, 2021. "Sustainable Mobility Policy Analysis Using Hybrid Choice Models: Is It the Right Choice?," Sustainability, MDPI, vol. 13(5), pages 1-16, March.
    14. Kim, Seheon & Rasouli, Soora, 2022. "The influence of latent lifestyle on acceptance of Mobility-as-a-Service (MaaS): A hierarchical latent variable and latent class approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 304-319.
    15. Bhat, Chandra R. & Dubey, Subodh K. & Nagel, Kai, 2015. "Introducing non-normality of latent psychological constructs in choice modeling with an application to bicyclist route choice," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 341-363.
    16. Kim, Jinhee & Rasouli, Soora & Timmermans, Harry, 2014. "Expanding scope of hybrid choice models allowing for mixture of social influences and latent attitudes: Application to intended purchase of electric cars," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 71-85.
    17. Hamzeh Alizadeh & Bilal Farooq & Catherine Morency & Nicolas Saunier, 2018. "On the role of bridges as anchor points in route choice modeling," Transportation, Springer, vol. 45(5), pages 1181-1206, September.
    18. Ciyun Lin & Kang Wang & Dayong Wu & Bowen Gong, 2020. "Research on Residents’ Travel Behavior under Sudden Fire Disaster Based on Prospect Theory," Sustainability, MDPI, vol. 12(2), pages 1-21, January.
    19. Ikki Kim & Hyoung-Chul Kim & Dong-Jeong Seo & Jung In Kim, 2020. "Calibration of a transit route choice model using revealed population data of smartcard in a multimodal transit network," Transportation, Springer, vol. 47(5), pages 2179-2202, October.
    20. Manley, Ed & Cheng, Tao, 2018. "Exploring the role of spatial cognition in predicting urban traffic flow through agent-based modelling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 109(C), pages 14-23.
    21. Balogh, Péter & Török, Áron & Czine, Péter & Horváth, Péter, 2020. "A fogyasztói magatartás elemzése feltételes választási modellekkel - a mangalicakolbász példáján [Analysing consumer behaviour with conditional choice models, with Mangalica sausage as an example]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(5), pages 474-494.
    22. Hess, Stephane & Spitz, Greg & Bradley, Mark & Coogan, Matt, 2018. "Analysis of mode choice for intercity travel: Application of a hybrid choice model to two distinct US corridors," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 547-567.
    23. Dalumpines, Ron & Scott, Darren M., 2017. "Determinants of route choice behavior: A comparison of shop versus work trips using the Potential Path Area - Gateway (PPAG) algorithm and Path-Size Logit," Journal of Transport Geography, Elsevier, vol. 59(C), pages 59-68.

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