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Influence of Psychological and Socioeconomic Factors on Purchase Likelihood for Autonomous Vehicles: A Hybrid Choice Modeling Approach

Author

Listed:
  • Yunyi Liang

    (School of Traffic & Transportation Engineering, Central South University, Changsha 410075, China)

  • Jinjun Tang

    (School of Traffic & Transportation Engineering, Central South University, Changsha 410075, China)

  • Zhizhou Wu

    (College of Transportation Engineering, Tongji University, Shanghai 201804, China
    School of Business, Xinjiang University, Urumqi 830091, China)

  • Mei Jia

    (School of Business, Xinjiang University, Urumqi 830091, China)

Abstract

This study looks into how psychological and socioeconomic factors interact to affect people’s propensity to purchase autonomous vehicles (AVs). Inspired by the Technology Acceptance Model, six psychological variables—social influence, convenience, perceived utility, perceived ease of use, perceived risk, and usage attitude—are proposed. Twenty-two measurement variables are introduced because it is difficult to measure these latent factors directly. To understand the link between the latent variables and calculate their factor scores, a structural equation model is created. The latent variables, along with observable socioeconomic attributes, are included as explanatory variables in a mixed logit model to estimate the purchase likelihood for AVs on different levels. A stated preference survey is conducted for data collection. We obtained 302 effective samples. The experiment results demonstrate that perceived usefulness has the most significant positive impact on purchase likelihood, followed by social influence and perceived ease of use. However, perceived risk has a significant negative impact on the purchase likelihood. Individuals with less driving experience and those without a motor vehicle driving license are more inclined to adopt autonomous vehicles. Additionally, there is a substantial correlation between the frequency of car use and the propensity to support the deployment of autonomous vehicles.

Suggested Citation

  • Yunyi Liang & Jinjun Tang & Zhizhou Wu & Mei Jia, 2023. "Influence of Psychological and Socioeconomic Factors on Purchase Likelihood for Autonomous Vehicles: A Hybrid Choice Modeling Approach," Sustainability, MDPI, vol. 15(21), pages 1-21, October.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:21:p:15452-:d:1270816
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    References listed on IDEAS

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    1. Md. Mokhlesur Rahman & Jean-Claude Thill, 2023. "What Drives People’s Willingness to Adopt Autonomous Vehicles? A Review of Internal and External Factors," Sustainability, MDPI, vol. 15(15), pages 1-29, July.
    2. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    3. Bhat, Chandra R. & Castelar, Saul, 2002. "A unified mixed logit framework for modeling revealed and stated preferences: formulation and application to congestion pricing analysis in the San Francisco Bay area," Transportation Research Part B: Methodological, Elsevier, vol. 36(7), pages 593-616, August.
    4. Webb, Jeremy & Wilson, Clevo & Kularatne, Thamarasi, 2019. "Will people accept shared autonomous electric vehicles? A survey before and after receipt of the costs and benefits," Economic Analysis and Policy, Elsevier, vol. 61(C), pages 118-135.
    5. Gurumurthy, Krishna Murthy & Kockelman, Kara M., 2020. "Modeling Americans’ autonomous vehicle preferences: A focus on dynamic ride-sharing, privacy & long-distance mode choices," Technological Forecasting and Social Change, Elsevier, vol. 150(C).
    6. John Rose & Michiel Bliemer, 2013. "Sample size requirements for stated choice experiments," Transportation, Springer, vol. 40(5), pages 1021-1041, September.
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