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Why to buy or why not to buy? - Revealing the inherent mechanism and the psychological impacts on the behavior of purchasing automated vehicles

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  • Gu, Yingfan
  • Wang, Song
  • Li, Zhixia
  • Zhang, Guohui
  • Ai, Chengbo
  • Li, Pengfei

Abstract

This paper reveals the mechanism of how different personal variables interactively impact the purchasing behaviors for automated vehicles (AVs). Data is collected from a state-wide public survey study. The structural equation model-based path analysis is employed to reveal the variables' interrelationship. A hierarchical model is used to quantitatively understand the willingness to pay extra money for different automations levels. The revealed internal relationships between variables facilitate understanding why the variables impact an individual's purchasing behavior. The results show that rural residents are less likely to purchase an AV due to their lower income and familiarity levels compared to urban residents. Highly educated individuals who drive more frequently are more likely to pay for an AV because they demonstrate a higher ability to afford one. Safety concerns remain the primary factor influencing purchasing behavior. This study contributes to the literature by revealing internal heterogeneity and the psychological effects that influence purchasing behaviors for AVs, as well as the willingness to pay extra for each level of automation. The results are expected to be beneficial for government policymakers, vehicle manufacturers, and organizational stakeholders in devising long-term policies.

Suggested Citation

  • Gu, Yingfan & Wang, Song & Li, Zhixia & Zhang, Guohui & Ai, Chengbo & Li, Pengfei, 2025. "Why to buy or why not to buy? - Revealing the inherent mechanism and the psychological impacts on the behavior of purchasing automated vehicles," Research in Transportation Economics, Elsevier, vol. 109(C).
    • Handle: RePEc:eee:retrec:v:109:y:2025:i:c:s0739885924001112
    DOI: 10.1016/j.retrec.2024.101516
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    More about this item

    Keywords

    Willingness to purchase; SEM-based path analysis; Hierarchical model; Policy recommendation; Automated vehicles;
    All these keywords.

    JEL classification:

    • L91 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Transportation: General
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning

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