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

Sustainability (Switzerland), ISSN: 2071-1050, Vol: 15, Issue: 3
2023
  • 5
    Citations
  • 0
    Usage
  • 25
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    5
  • Captures
    25
  • Mentions
    1
    • News Mentions
      1
      • News
        1

Most Recent News

Reports Outline Technology Study Findings from Khon Kaen University (Understanding Intention to Use Conditionally Automated Vehicles in Thailand, Based on an Extended Technology Acceptance Model)

2023 FEB 20 (NewsRx) -- By a News Reporter-Staff News Editor at Tech Daily News -- Fresh data on technology are presented in a new

Article Description

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.

Bibliographic Details

Phakphum Sakuljao; Wichuda Satiennam; Thaned Satiennam; Nopadon Kronprasert; Sittha Jaensirisak

MDPI AG

Computer Science; Social Sciences; Energy; Environmental Science

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