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Understanding Intention to Use Conditionally Automated Vehicles in Thailand, Based on an Extended Technology Acceptance Model

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  • Phakphum Sakuljao

    (Department of Civil Engineering, Khon Kaen University, 123 Mitrapap Road, Nai Muang Sub-District, Muang District, Khon Kaen 40002, Thailand)

  • Wichuda Satiennam

    (Department of Civil Engineering, Khon Kaen University, 123 Mitrapap Road, Nai Muang Sub-District, Muang District, Khon Kaen 40002, Thailand)

  • Thaned Satiennam

    (Department of Civil Engineering, Khon Kaen University, 123 Mitrapap Road, Nai Muang Sub-District, Muang District, Khon Kaen 40002, Thailand)

  • Nopadon Kronprasert

    (Excellence Center in Infrastructure Technology and Transportation Engineering, Department of Civil Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Sittha Jaensirisak

    (Department of Civil Engineering, Ubon Ratchathani University, 85 Sathonlamark Road, Warin Chamrap District, Ubon Ratchathani 34190, Thailand)

Abstract

Automated vehicles (AVs) provide several advantages in solving issues of road traffic; including enhanced safety, reduced greenhouse gas emissions, and reduced traffic congestion. As AVs are still relatively new developments in developing countries, AV adoption faces challenges from both technological and psychological issues. Therefore, our initial research focus is on identifying the factors that influence the intention to use conditionally automated vehicles (CAVs; SAE Level 3). An extended technology acceptance model (TAM), which includes Trust, Perceived Risks, and Environmental concerns, is proposed as the predictor model in this study. The 299 participants gathered through online surveys in Thailand were examined using the Structural Equation Model (SEM) technique. In this study, Trust was shown to be the strongest predictor of Intention, followed by Perceived Ease of Use, whereas Perceived Usefulness had no impact on intention to use the SAE Level 3. The results of this study will be able to guide the forming of future policies that aim at promoting the use of AVs and helping technology developers create systems to better meet the needs of users in developing nations.

Suggested Citation

  • Phakphum Sakuljao & Wichuda Satiennam & Thaned Satiennam & Nopadon Kronprasert & Sittha Jaensirisak, 2023. "Understanding Intention to Use Conditionally Automated Vehicles in Thailand, Based on an Extended Technology Acceptance Model," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:1868-:d:1040217
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    References listed on IDEAS

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    1. Methawadee Chaisomboon & Sajjakaj Jomnonkwao & Vatanavongs Ratanavaraha, 2020. "Elderly Users’ Satisfaction with Public Transport in Thailand Using Different Importance Performance Analysis Approaches," Sustainability, MDPI, vol. 12(21), pages 1-20, October.
    2. Cunningham, Mitchell L. & Regan, Michael A. & Horberry, Timothy & Weeratunga, Kamal & Dixit, Vinayak, 2019. "Public opinion about automated vehicles in Australia: Results from a large-scale national survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 1-18.
    3. Barclay, Michael J & Smith, Clifford W, Jr, 1995. "The Maturity Structure of Corporate Debt," Journal of Finance, American Finance Association, vol. 50(2), pages 609-631, June.
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