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Author:

Li, Zhen-Long (Li, Zhen-Long.) | Xing, Guan-Yang (Xing, Guan-Yang.) | Li, Jia (Li, Jia.) | Zhao, Xiao-Hua (Zhao, Xiao-Hua.) | Zhang, Jing-Si (Zhang, Jing-Si.)

Indexed by:

EI Scopus

Abstract:

The cooperative vehicle infrastructure system (CVIS) has been regarded as an advanced technology and a research focus in the field of intelligent transportation. Countries worldwide are committed to the research and development, testing, demonstration applications, and utility evaluation of CVIS. However, the service object of CVIS is the driver; therefore, it is of great importance to study the driver's subjective acceptance of CVIS and its influencing factors before CVIS is officially applied. The basic technology acceptance model (TAM) was used as the theoretical framework in this study. Using the four basic variables (perceived usefulness, perceived ease of use, attitude, and intention), as well as four extended variables (quality of warning service, distraction perception, personal innovation, and trustworthiness), an extended TAM was used to analyze the driver's subjective acceptance of CVIS and its influencing factors. First, an online CVIS questionnaire was sent to 392 drivers. Second, Cronbach's α and confirmatory factor analysis were used to inspect the reliability and validity of the questionnaire. Finally, path analysis was used to explore the driver's acceptance of CVIS and its influencing factors. The results show that the relationship among the basic TAM variables is consistent with the basic model assumptions. The quality of the CVIS warning service indirectly affects usage intentions through perceived usefulness, perceived ease of use, and attitude. The driver's distracted perception of CVIS has no negative effect on his attitude and usage intention. The driver's personal innovation not only directly affects the usage intention, but also indirectly influences usage intention through attitude. The driver's trust in CVIS is a direct influencing factor of usage intention, and indirectly affects usage intention through other variables. The results contribute to understanding the driver's acceptance of CVIS and its influencing factors and provide theoretical support for the design of CVIS. © 2021, Editorial Department of China Journal of Highway and Transport. All right reserved.

Keyword:

Reliability analysis Regression analysis Factor analysis Highway engineering Quality control Surveys

Author Community:

  • [ 1 ] [Li, Zhen-Long]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Xing, Guan-Yang]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Li, Jia]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Zhao, Xiao-Hua]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Zhang, Jing-Si]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing; 100124, China

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Source :

China Journal of Highway and Transport

ISSN: 1001-7372

Year: 2021

Issue: 7

Volume: 34

Page: 188-200

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 9

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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