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People’s Intentions to Use Shared Autonomous Vehicles: An Extended Theory of Planned Behavior Model

Author

Listed:
  • Wei Luo

    (Beijing Key Laboratory of General Aviation Technology, Beijing University of Civil Engineering and Architecture, Beijing 100044, China)

  • Silong Wei

    (Beijing Key Laboratory of General Aviation Technology, Beijing University of Civil Engineering and Architecture, Beijing 100044, China)

  • Yi Wang

    (School of Civil Engineering, Guangzhou University, Guangzhou 510006, China
    Department of Civil Engineering, Tsinghua University, Beijing 100091, China)

  • Pengpeng Jiao

    (Beijing Key Laboratory of General Aviation Technology, Beijing University of Civil Engineering and Architecture, Beijing 100044, China)

Abstract

With the advancement of technology, sharing and autonomous driving will be the two major themes in the future transportation field, and SAVs (Shared autonomous vehicles) will combine the two things. When SAVs come to market, they will affect the transportation system, so the objective of this paper is to examine people’s intentions to use SAVs and clarify the factors affecting people’s intentions to use SAVs. Due to the application of the theory of planned behavior (TPB) in traffic travel research having important practical significance, this paper used an extended theory of planned behavior model to study people’s intentions to use SAVs. Some important findings are found that the intention to use SAVs is directly affected by attitude, subjective norm, perceived behavior control, barrier, and effects of a public health emergency, and indirectly affected by perceived risk, technical interest, government policy, and environmental awareness. Moreover, perceived behavior control has the mediating effect between government policy and intention to use SAVs, between technical interest and intention to use SAVs, and between subjective norm and intention to use SAVs. According to the influence degree of related influencing factors, the corresponding development recommendations on SAVs development are put forward. The research results of this paper contribute to the subsequent listing of SAVs, promote the further development of intelligent transportation, and provide the scientific basis for future travel policy formulation and traffic planning.

Suggested Citation

  • Wei Luo & Silong Wei & Yi Wang & Pengpeng Jiao, 2023. "People’s Intentions to Use Shared Autonomous Vehicles: An Extended Theory of Planned Behavior Model," Sustainability, MDPI, vol. 15(16), pages 1-17, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:16:p:12455-:d:1218435
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    References listed on IDEAS

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    1. Limin Tan & Changxi Ma & Xuecai Xu & Jin Xu, 2019. "Choice Behavior of Autonomous Vehicles Based on Logistic Models," Sustainability, MDPI, vol. 12(1), pages 1-16, December.
    2. Arto O Salonen & Noora Haavisto, 2019. "Towards Autonomous Transportation. Passengers’ Experiences, Perceptions and Feelings in a Driverless Shuttle Bus in Finland," Sustainability, MDPI, vol. 11(3), pages 1-19, January.
    3. Peng Jing & Hao Huang & Bin Ran & Fengping Zhan & Yuji Shi, 2019. "Exploring the Factors Affecting Mode Choice Intention of Autonomous Vehicle Based on an Extended Theory of Planned Behavior—A Case Study in China," Sustainability, MDPI, vol. 11(4), pages 1-20, February.
    4. Samuel Chng & Sabreena Anowar & Lynette Cheah, 2022. "Understanding Shared Autonomous Vehicle Preferences: A Comparison between Shuttles, Buses, Ridesharing and Taxis," Sustainability, MDPI, vol. 14(20), pages 1-14, October.
    5. 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.
    6. Jiang, Kang & Ling, Feiyang & Feng, Zhongxiang & Wang, Kun & Shao, Cheng, 2017. "Why do drivers continue driving while fatigued? An application of the theory of planned behaviour," Transportation Research Part A: Policy and Practice, Elsevier, vol. 98(C), pages 141-149.
    7. Kum Fai Yuen & Do Thi Khanh Huyen & Xueqin Wang & Guanqiu Qi, 2020. "Factors Influencing the Adoption of Shared Autonomous Vehicles," IJERPH, MDPI, vol. 17(13), pages 1-17, July.
    8. Xuemei Fu & Zhicai Juan, 2017. "Understanding public transit use behavior: integration of the theory of planned behavior and the customer satisfaction theory," Transportation, Springer, vol. 44(5), pages 1021-1042, September.
    9. Longhai Yang & Xiqiao Zhang & Xiaoyan Zhu & Yule Luo & Yi Luo, 2019. "Research on Risky Driving Behavior of Novice Drivers," Sustainability, MDPI, vol. 11(20), pages 1-20, October.
    10. Mohammadhossein Abbasi & Amir Reza Mamdoohi & Grzegorz Sierpiński & Francesco Ciari, 2023. "Usage Intention of Shared Autonomous Vehicles with Dynamic Ride Sharing on Long-Distance Trips," Sustainability, MDPI, vol. 15(2), pages 1-17, January.
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    Cited by:

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    2. Liu, Wenjuan & Liu, Yanfeng, 2025. "Electric vertical takeoff and landing and consumer intention: An empirical test under a theoretical framework," Journal of Air Transport Management, Elsevier, vol. 124(C).

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