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Danger, Respect, and Indifference: Bike-Sharing Choices in Shanghai and Tokyo using Latent Choice Models

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Listed:
  • Yoo, Sunbin
  • Hong, Sungwan
  • Park, Yeongkyung
  • Okuyama, Akihiro
  • Zhang, Zhaozhe
  • Yoshida, Yoshikuni
  • Managi, Shunsuke

Abstract

While various policy instruments have attempted to raise environmental concerns in the past decades, it is unclear if these concerns are revealed in the consumer choices of our daily life. In this study, we investigate whether environmental concerns drive the choices of modes of transport through the bike-sharing example in Tokyo and Shanghai. We conducted a survey questionnaire to define three types of environmental concerns and quantitatively estimated their effects on bike-sharing choices using the latent class model, considering individual heterogeneity. The results show that environmental concerns affect bike-sharing choices differently for different people. While the fear of natural disasters and/or an indifference towards the environment would be dominant factors in commuting, the willingness to preserve a natural environment shows substantial correlations to bike-sharing when respondents return from weekend shopping. These differences indicate that relevant policies should be effectively implemented to interact with such environmental concerns.

Suggested Citation

  • Yoo, Sunbin & Hong, Sungwan & Park, Yeongkyung & Okuyama, Akihiro & Zhang, Zhaozhe & Yoshida, Yoshikuni & Managi, Shunsuke, 2021. "Danger, Respect, and Indifference: Bike-Sharing Choices in Shanghai and Tokyo using Latent Choice Models," MPRA Paper 108312, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:108312
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    References listed on IDEAS

    as
    1. Zawojska, Ewa & Bartczak, Anna & Czajkowski, Mikołaj, 2019. "Disentangling the effects of policy and payment consequentiality and risk attitudes on stated preferences," Journal of Environmental Economics and Management, Elsevier, vol. 93(C), pages 63-84.
    2. Faghih-Imani, Ahmadreza & Hampshire, Robert & Marla, Lavanya & Eluru, Naveen, 2017. "An empirical analysis of bike sharing usage and rebalancing: Evidence from Barcelona and Seville," Transportation Research Part A: Policy and Practice, Elsevier, vol. 97(C), pages 177-191.
    3. Vredin Johansson, Maria & Heldt, Tobias & Johansson, Per, 2006. "The effects of attitudes and personality traits on mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(6), pages 507-525, July.
    4. Tien Dung Tran & Nicolas Ovtracht & Bruno Faivre D’arcier, 2015. "Modeling Bike Sharing System using Built Environment Factors," Post-Print halshs-01474166, HAL.
    5. Meng, Meng & Rau, Andreas & Mahardhika, Hita, 2018. "Public transport travel time perception: Effects of socioeconomic characteristics, trip characteristics and facility usage," Transportation Research Part A: Policy and Practice, Elsevier, vol. 114(PA), pages 24-37.
    6. Merchán, Daniel & Winkenbach, Matthias & Snoeck, André, 2020. "Quantifying the impact of urban road networks on the efficiency of local trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 135(C), pages 38-62.
    7. Bulte, Erwin & Gerking, Shelby & List, John A. & de Zeeuw, Aart, 2005. "The effect of varying the causes of environmental problems on stated WTP values: evidence from a field study," Journal of Environmental Economics and Management, Elsevier, vol. 49(2), pages 330-342, March.
    8. Stephane Hess & Mark Fowler & Thomas Adler & Aniss Bahreinian, 2012. "A joint model for vehicle type and fuel type choice: evidence from a cross-nested logit study," Transportation, Springer, vol. 39(3), pages 593-625, May.
    9. Bonan, Jacopo & Cattaneo, Cristina & d’Adda, Giovanna & Tavoni, Massimo, 2021. "Can social information programs be more effective? The role of environmental identity for energy conservation," Journal of Environmental Economics and Management, Elsevier, vol. 108(C).
    10. Nordlund, A. & Jansson, J. & Westin, K., 2018. "Acceptability of electric vehicle aimed measures: Effects of norm activation, perceived justice and effectiveness," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 205-213.
    11. Liu, Diyi & Du, Huibin & Southworth, Frank & Ma, Shoufeng, 2017. "The influence of social-psychological factors on the intention to choose low-carbon travel modes in Tianjin, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 105(C), pages 42-53.
    12. Marcel Paulssen & Dirk Temme & Akshay Vij & Joan Walker, 2014. "Values, attitudes and travel behavior: a hierarchical latent variable mixed logit model of travel mode choice," Transportation, Springer, vol. 41(4), pages 873-888, July.
    13. Regue, Robert & Recker, Will, 2014. "Proactive vehicle routing with inferred demand to solve the bikesharing rebalancing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 72(C), pages 192-209.
    14. Qian, Xiaodong & Niemeier, Deb, 2019. "High impact prioritization of bikeshare program investment to improve disadvantaged communities' access to jobs and essential services," Journal of Transport Geography, Elsevier, vol. 76(C), pages 52-70.
    15. Parkes, Stephen D. & Marsden, Greg & Shaheen, Susan A. & Cohen, Adam P., 2013. "Understanding the diffusion of public bikesharing systems: evidence from Europe and North America," Journal of Transport Geography, Elsevier, vol. 31(C), pages 94-103.
    16. Yoo, Sunbin & Kumagai, Junya & Kawabata, Yuta & Keeley, Alexander & Managi, Shunsuke, 2021. "Willingness to Buy and/or Pay Disparity: Evidence from Fully Autonomous Vehicles," MPRA Paper 108882, University Library of Munich, Germany.
    17. Link, Christoph & Strasser, Christoph & Hinterreiter, Michael, 2020. "Free-floating bikesharing in Vienna – A user behaviour analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 135(C), pages 168-182.
    18. Zhang, Yongping & Mi, Zhifu, 2018. "Environmental benefits of bike sharing: A big data-based analysis," Applied Energy, Elsevier, vol. 220(C), pages 296-301.
    19. Cheng, Yung-Hsiang & Chen, Ssu-Yun, 2015. "Perceived accessibility, mobility, and connectivity of public transportation systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 386-403.
    20. Böcker, Lars & Anderson, Ellinor, 2020. "Interest-adoption discrepancies, mechanisms of mediation and socio-spatial inclusiveness in bike-sharing: The case of nine urban regions in Norway," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 266-277.
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    More about this item

    Keywords

    Bike-sharing; shared transportation; demand estimation; latent choice model; latent class; environmental concern;
    All these keywords.

    JEL classification:

    • L62 - Industrial Organization - - Industry Studies: Manufacturing - - - Automobiles; Other Transportation Equipment; Related Parts and Equipment
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • R4 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics

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