Comparison of technology acceptance model, theory of planned behavior, and unified theory of acceptance and use of technology to assess a priori acceptance of fully automated vehicles

Fully automated vehicles (FAVs) are predicted to enter the passenger vehicle market in the near future. Being a new technology, there is significant uncertainty on adoption by users. There is a need for studies on the user acceptance of autonomous vehicles. This study aims to assess user acceptance of FAVs in a middle-income country, Iran, by adopting and comparing three popular user acceptance models: Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB), and Unified Theory of Acceptance and Use of Technology (UTAUT). The data were collected via an online survey of 1381 drivers (with valid driver’s license) from different cities in Iran.The results showed that while 49.4% of participants had never heard of FAVs, the majority of them showed a high intention to use FAVs in the future. All three models successfully explained the behavioral intention to use FAVs. The TPB model was the best performing model to represent acceptance, which explained 70.9% of the variance in behavioral intention with subjective norms as the strongest predictor of the model, followed by attitudes toward FAVs as a significant predictor of intention to use them. The UTAUT model constructs accounted for 69.6% of the variance in intention, followed by the TAM model, which explained 57.6% of the variance in intention to use FAVs.Considering that the study on public perceptions of FAVs in middle-income countries is almost non-existent in the literature, it is expected that the current study will be a benchmarking resource for a comparative study for countries with a similar socio-economic and cultural context as the current study.

• Record URL:
  https://doi.org/10.1016/j.tra.2022.103565
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0965856422003160
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09658564
• Supplemental Notes:
  • © 2022 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Rejali, Sina
  • Aghabayk, Kayvan
  • Esmaeli, Saeed
  • Shiwakoti, Nirajan
• Publication Date: 2023-2

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: 103565
• Serial:
  • Transportation Research Part A: Policy and Practice
  • Volume: 168
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0965-8564
  • Serial URL: http://www.sciencedirect.com/science/journal/09658564

Subject/Index Terms

• TRT Terms: Acceptance; Attitudes; Autonomous vehicles; Behavior; Technology
• Subject Areas: Data and Information Technology; Highways; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01872902
• Record Type: Publication
• Files: TRIS
• Created Date: Feb 10 2023 9:02AM