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An Integrated Choice and Latent Variable Model to Explore the Influence of Attitudinal and Perceptual Factors on Shared Mobility Choices and Their Value of Time Estimation

Author

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  • Weibo Li

    (University College London, UCL Energy Institute, WC1H 0NN, London, United Kingdom)

  • Maria Kamargianni

    (University College London, UCL Energy Institute, WC1H 0NN, London, United Kingdom)

Abstract

This work studies how the usage of shared mobility services could be influenced by latent factors. An integrated choice and latent variable model is adopted to explore the effects of three attitudinal and perceptual factors on bike- and car-sharing choices while simultaneously investigating the causes associated with each of the latent variables. A group of Chinese commuters’ stated preference mode choice data are collected. It is found that the probability to choose bike-sharing could be positively affected by “willingness to be a green traveler” and “satisfaction with cycling environment,” and car-sharing choice is positively correlated with “advocacy of car-sharing service.” By taking into account the interaction effects between the latent variables and travel time of the two services, a significant difference is discovered on the estimated value of travel time savings (VTTS) compared with other more restrictive model specifications. The finding highlights the importance to derive different VTTS for travelers with differentiated attitudes and perceptions as the tastes toward travel time spent could vary substantially. In other words, there would be different trade-off preferences across attitudinal groups, according to which transport service operators could customize their strategies on prices and levels of service offered.

Suggested Citation

  • Weibo Li & Maria Kamargianni, 2020. "An Integrated Choice and Latent Variable Model to Explore the Influence of Attitudinal and Perceptual Factors on Shared Mobility Choices and Their Value of Time Estimation," Transportation Science, INFORMS, vol. 54(1), pages 62-83, January.
    • Handle: RePEc:inm:ortrsc:v:54:y:2020:i:1:p:62-83
    DOI: 10.1287/trsc.2019.0933
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    4. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
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    6. Lahoz, Lorena Torres & Pereira, Francisco Camara & Sfeir, Georges & Arkoudi, Ioanna & Monteiro, Mayara Moraes & Azevedo, Carlos Lima, 2023. "Attitudes and Latent Class Choice Models using Machine Learning," Journal of choice modelling, Elsevier, vol. 49(C).
    7. Iogansen, Xiatian & Wang, Kailai & Bunch, David & Matson, Grant & Circella, Giovanni, 2023. "Deciphering the factors associated with adoption of alternative fuel vehicles in California: An investigation of latent attitudes, socio-demographics, and neighborhood effects," Transportation Research Part A: Policy and Practice, Elsevier, vol. 168(C).
    8. Lorena Torres Lahoz & Francisco Camara Pereira & Georges Sfeir & Ioanna Arkoudi & Mayara Moraes Monteiro & Carlos Lima Azevedo, 2023. "Attitudes and Latent Class Choice Models using Machine learning," Papers 2302.09871, arXiv.org.
    9. Bansal, Prateek & Kumar, Rajeev Ranjan & Raj, Alok & Dubey, Subodh & Graham, Daniel J., 2021. "Willingness to pay and attitudinal preferences of Indian consumers for electric vehicles," Energy Economics, Elsevier, vol. 100(C).
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