Confirmatory Factors of Battery Electric Vehicle Technology Acceptance Model (BEVTAM) of Thai Consumers - Chomchark, Pannathadh; Ngamjarussrivichai, Pichit (Science and Engineering Connect, 2024)
Background and Objectives: The popularity of electric vehicles around the world is rapidly growing. The use of electric vehicles is also becoming popular in Thailand. Nevertheless, there are still obstacles from such factors as limited driving distance per charge, lack of confidence in the technology and safety of electric vehicles as well as inadequate knowledge of and understanding of electric vehicles. The objectives of the present research were to analyze confirmatory factors of the battery electric vehicle technology acceptance model (BEVTAM) and to prioritize such factors. Methodology: Questionnaires were used to gather the data from 440 Thai consumers aged between 25-65 years who were the target group to buy battery electric vehicles (BEV) during 2022-2025. Data were analyzed in terms of the mean, standard deviation, chi-square, degree of freedom, p-value, root mean square error of approximation (RMSEA), standardized root mean square residual (SRMR), goodness of fit index (GFI), adjusted goodness of fit index (AGFI) and comparative fit index (CFI). Main Results: It is possible to rank 6 elements involved in the battery electric vehicle technology acceptance by their importance of the elements from the highest to the lowest as follows: 1) Perceived Ease of Use (PEU), 2) Perceived Usefulness (PCU), 3) Perceived Security Risk (PSR), 4) Perceived Trust (PCT), 5) Perceived Compatibility (PCC) and 6) Perceived Financial Resources (PFR). The component weights were 0.98, 0.90, 0.88, 0.85, 0.85 and 0.76, respectively. The proposed Battery Electric Vehicle Technology Acceptance Model (BEVTAM) represents a new finding as all available previous researches focused only on the components of technology acceptance models; BEVTAM had never been used in research studies in the context of battery electric vehicle technology before, especially in Thailand. Conclusions: The 6-dimension electric vehicle technology acceptance measure represents a component of technology acceptance measurement in the context of BEV electric vehicles in Thailand. The results are consistent with the empirical data. Practical Application: The obtained results provide primary information that can be used to formulate a framework for manufacturers and distributors of battery electric vehicles to improve the technology to be more stable. Such improvement includes the development of an intelligent system that can help drivers operate their vehicles more efficiently and safely. Software that responds to modern usage should also be developed, along with a battery technology that is efficient for long-term use and allows for longer driving distance per charge. Faster chargeability also deserves attention. Such developments would give consumers more confidence in the use of battery-electric vehicles.