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

Weiya Chen (), Ying Chen, Yufen Wang and Xiaoping Fang
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Weiya Chen: School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Ying Chen: School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Yufen Wang: School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
Xiaoping Fang: School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China

Sustainability, 2024, vol. 16, issue 9, 1-23

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.

Keywords: bus real-time control technology; bus drivers’ behavioral intention; technology acceptance; influential factors; empirical study (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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