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Public Acceptance of Driverless Buses in China: An Empirical Analysis Based on an Extended UTAUT Model

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  • Jian Chen
  • Rui Li
  • Mi Gan
  • Zhiyan Fu
  • Fatao Yuan

Abstract

Driverless buses are expected to play a vital role in the future, and better public acceptance will provide a social foundation for its development. In this study, two new variables, personal innovativeness (PI) and perceived risk (PR), were incorporated into the integrated technology acceptance model (UTAUT, unified theory of acceptance and use of technology) to construct an extended model, which was then applied to explore the influencing factors for the public acceptance of driverless buses. The quality of this extended model was verified through survey data collected in Chongqing, China. The structural equation modeling (SEM) method was adopted to quantitatively describe the impact of each factor on acceptance intention (AI) as well as the mutual influence relationships between the factors. The moderating effects of demographic attributes (gender, age, and education level) on each factor in the model were also analyzed. The results showed that PI and PR are the most critical factors that affect the public’s acceptance intention; effort expectancy (EE), performance expectancy (PE), social influence (SI), and facilitating condition (FC) can also determine the acceptance intention to a certain extent; gender, age, and education level have exhibited significantly different moderating effects on the influencing factors. The explanatory power of the current research model for acceptance intention has reached 48%. This study has confirmed the applicability of the extended UTAUT model to the research of driverless bus acceptance and the research outcomes can serve as a reference basis for improving the service quality of driverless buses in China.

Suggested Citation

  • Jian Chen & Rui Li & Mi Gan & Zhiyan Fu & Fatao Yuan, 2020. "Public Acceptance of Driverless Buses in China: An Empirical Analysis Based on an Extended UTAUT Model," Discrete Dynamics in Nature and Society, Hindawi, vol. 2020, pages 1-13, November.
    • Handle: RePEc:hin:jnddns:4318182
    DOI: 10.1155/2020/4318182
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    Cited by:

    1. Naihui Wang & Yulong Pei & Hao Fu, 2022. "Public Acceptance of Last-Mile Shuttle Bus Services with Automation and Electrification in Cold-Climate Environments," Sustainability, MDPI, vol. 14(21), pages 1-16, November.
    2. Koh, Le Yi & Yuen, Kum Fai, 2023. "Public acceptance of autonomous vehicles: Examining the joint influence of perceived vehicle performance and intelligent in-vehicle interaction quality," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    3. Li, Dun & Huang, Youlin & Qian, Lixian, 2022. "Potential adoption of robotaxi service: The roles of perceived benefits to multiple stakeholders and environmental awareness," Transport Policy, Elsevier, vol. 126(C), pages 120-135.
    4. Singha Chaveesuk & Wornchanok Chaiyasoonthorn & Nayika Kamales & Zdzislawa Dacko-Pikiewicz & Wiesław Liszewski & Bilal Khalid, 2023. "Evaluating the Determinants of Consumer Adoption of Autonomous Vehicles in Thailand—An Extended UTAUT Model," Energies, MDPI, vol. 16(2), pages 1-22, January.
    5. Haider Ali Abbasi & Satirenjit Kaur Johl & Zullina Bt Hussain Shaari & Wajiha Moughal & Muhammad Mazhar & Muhammad Ali Musarat & Waqas Rafiq & Asaad Salam Farooqi & Alexey Borovkov, 2021. "Consumer Motivation by Using Unified Theory of Acceptance and Use of Technology towards Electric Vehicles," Sustainability, MDPI, vol. 13(21), pages 1-22, November.
    6. Jaeyoung Lee & Farrukh Baig & Mir Aftab Hussain Talpur & Sajan Shaikh, 2021. "Public Intentions to Purchase Electric Vehicles in Pakistan," Sustainability, MDPI, vol. 13(10), pages 1-18, May.
    7. Kriswardhana, Willy & Esztergár-Kiss, Domokos, 2023. "Exploring the aspects of MaaS adoption based on college students’ preferences," Transport Policy, Elsevier, vol. 136(C), pages 113-125.
    8. Naihui Wang & Yulong Pei & Yi-Jia Wang, 2022. "Antecedents in Determining Users’ Acceptance of Electric Shuttle Bus Services," Mathematics, MDPI, vol. 10(16), pages 1-19, August.
    9. Tiansheng Xia & Xiaowu Lin & Yongqing Sun & Tingting Liu, 2023. "An Empirical Study of the Factors Influencing Users’ Intention to Use Automotive AR-HUD," Sustainability, MDPI, vol. 15(6), pages 1-15, March.
    10. Yan, Yingying & Zhong, Shiquan & Tian, Junfang & Li, Tong, 2022. "Continuance intention of autonomous buses: An empirical analysis based on passenger experience," Transport Policy, Elsevier, vol. 126(C), pages 85-95.
    11. van 't Veer, Renske & Annema, Jan Anne & Araghi, Yashar & Homem de Almeida Correia, Gonçalo & van Wee, Bert, 2023. "Mobility-as-a-Service (MaaS): A latent class cluster analysis to identify Dutch vehicle owners’ use intention," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).

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