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Bus Drivers’ Behavioral Intention to Comply with Real-Time Control Instructions: An Empirical Study from China

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  • Weiya Chen

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
    Rail Data Research and Application Key Laboratory of Hunan Province, Changsha 410075, China)

  • Ying Chen

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
    Rail Data Research and Application Key Laboratory of Hunan Province, Changsha 410075, China)

  • Yufen Wang

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
    Rail Data Research and Application Key Laboratory of Hunan Province, Changsha 410075, China)

  • Xiaoping Fang

    (School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
    Rail Data Research and Application Key Laboratory of Hunan Province, Changsha 410075, China)

Abstract

Developing intelligent bus control systems is crucial for fostering the sustainability of urban transportation. Control instructions are produced in real time by the bus control system; these are important technical commands to stabilize the order in which buses operate and improve service reliability. Understanding the behavioral intention of bus drivers to comply with these instructions will help improve the effectiveness of intelligent bus control system implementation. We have developed a psychological model that incorporates decomposed variables of the theory of planned behavior (TPB) and other influencing variables to explain the micromechanisms that determine bus drivers’ behavioral intention to comply with real-time control instructions during both peak and off-peak-hour scenarios. A total of 258 responses were obtained and verified for analysis. The results showed that the influential factors in the peak- and off-peak-hour scenarios were not identical. Female drivers had greater off-peak-hour behavior intention to comply than male drivers, and there were significant differences in peak-hour behavior intention among drivers of different ages. In both peak and off-peak-hour scenarios, perceived benefit positively and perceived risk negatively affected behavioral intention. Perceived controllability positively affected behavioral intention only during peak hours. Self-efficacy only negatively affected behavioral intention during off-peak hours. Three antecedent variables (i.e., trust, mental workload, and line infrastructure support) influenced drivers’ behavioral intentions indirectly via the decomposed variables of TPB. These results provide profound insights for the improvement and implementation of real-time control technology for bus services, thereby facilitating the development of smart and sustainable urban public transport systems.

Suggested Citation

  • Weiya Chen & Ying Chen & Yufen Wang & Xiaoping Fang, 2024. "Bus Drivers’ Behavioral Intention to Comply with Real-Time Control Instructions: An Empirical Study from China," Sustainability, MDPI, vol. 16(9), pages 1-23, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:9:p:3623-:d:1383383
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    1. James Flynn & William Burns & C.K. Mertz & Paul Slovic, 1992. "Trust as a Determinant of Opposition to a High‐Level Radioactive Waste Repository: Analysis of a Structural Model," Risk Analysis, John Wiley & Sons, vol. 12(3), pages 417-429, September.
    2. Barbara H. Wixom & Peter A. Todd, 2005. "A Theoretical Integration of User Satisfaction and Technology Acceptance," Information Systems Research, INFORMS, vol. 16(1), pages 85-102, March.
    3. Berrebi, Simon J. & Crudden, Sean Óg & Watkins, Kari E., 2018. "Translating research to practice: Implementing real-time control on high-frequency transit routes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 213-226.
    4. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    5. Nicolás C. Bronfman & Esperanza López Vázquez, 2011. "A Cross‐Cultural Study of Perceived Benefit Versus Risk as Mediators in the Trust‐Acceptance Relationship," Risk Analysis, John Wiley & Sons, vol. 31(12), pages 1919-1934, December.
    6. Bart W. Terwel & Fieke Harinck & Naomi Ellemers & Dancker D. L. Daamen, 2009. "Competence‐Based and Integrity‐Based Trust as Predictors of Acceptance of Carbon Dioxide Capture and Storage (CCS)," Risk Analysis, John Wiley & Sons, vol. 29(8), pages 1129-1140, August.
    7. Rui Jiang & Mao-Bin Hu & Bin Jia & Qing-Song Wu, 2003. "Realistic bus route model considering the capacity of the bus," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 34(3), pages 367-372, August.
    8. Woldeamanuel, Mintesnot & Nguyen, Dang, 2018. "Perceived benefits and concerns of autonomous vehicles: An exploratory study of millennials’ sentiments of an emerging market," Research in Transportation Economics, Elsevier, vol. 71(C), pages 44-53.
    9. Peng Liu & Run Yang & Zhigang Xu, 2019. "Public Acceptance of Fully Automated Driving: Effects of Social Trust and Risk/Benefit Perceptions," Risk Analysis, John Wiley & Sons, vol. 39(2), pages 326-341, February.
    10. Daganzo, Carlos F., 2009. "A headway-based approach to eliminate bus bunching: Systematic analysis and comparisons," Transportation Research Part B: Methodological, Elsevier, vol. 43(10), pages 913-921, December.
    11. Jennifer Dill & Cynthia Mohr & Liang Ma, 2014. "How Can Psychological Theory Help Cities Increase Walking and Bicycling?," Journal of the American Planning Association, Taylor & Francis Journals, vol. 80(1), pages 36-51, January.
    12. LAURENT, Gilles & CHANDON, Pierre & WANSINK, Brian, 2000. "A benefit congruency framework of sales promotion effectiveness," HEC Research Papers Series 698, HEC Paris.
    13. Phillips, William & del Rio, Andrés & Muñoz, Juan Carlos & Delgado, Felipe & Giesen, Ricardo, 2015. "Quantifying the effects of driver non-compliance and communication system failure in the performance of real-time bus control strategies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 463-472.
    14. Chen, Jingxu & Liu, Zhiyuan & Zhu, Senlai & Wang, Wei, 2015. "Design of limited-stop bus service with capacity constraint and stochastic travel time," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 83(C), pages 1-15.
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