본문 바로가기
KERD
논문KCI 등재

Determining Behavioral Intention of Logistic and Distribution Firms to Use Electric Vehicles in Thailand

2

조회

0

다운로드

0

인용

0

참고문헌

키워드

초록

Purpose: Electric vehicle (EV) technology started in 2015 in Thailand. The Thai Government has indicated that 30% of all cars produced in Thailand by 2025 will be EVs. Using EVs in Thailand will reduce road pollution and increase energy efficiency, especially in major cities. Hence, the adoption of EVs in the country has been promoted. This study pointed out that social influence, facilitating conditions, perceived enjoyment, environmental concern, attitude, and perceived behavioral control are key factors affecting the behavioral intention to adopt EVs among logistic and distribution firms in Thailand. Research design, data, and methodology: 500 top management, middle management and purchasing managers of logistic and distribution firms in Thailand are surveyed. The study employed judgmental, convenience, and snowball sampling. Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM) are the main statistical tools for data analysis. Results: The results show that all determinants impact customers’ willingness to adopt EVs, except perceived enjoyment and environmental control. Conclusions: The study proposes to promote the incentives by decreasing electricity prices and endorsing EVs purchase to accelerate the adoption of EVs in Thailand. Therefore, future policies should focus on behavioral intention toward EVs amongst logistic and distribution firms for enhancing the future of mobility in Thailand.

Abstract

Purpose: Electric vehicle (EV) technology started in 2015 in Thailand. The Thai Government has indicated that 30% of all cars produced in Thailand by 2025 will be EVs. Using EVs in Thailand will reduce road pollution and increase energy efficiency, especially in major cities. Hence, the adoption of EVs in the country has been promoted. This study pointed out that social influence, facilitating conditions, perceived enjoyment, environmental concern, attitude, and perceived behavioral control are key factors affecting the behavioral intention to adopt EVs among logistic and distribution firms in Thailand. Research design, data, and methodology: 500 top management, middle management and purchasing managers of logistic and distribution firms in Thailand are surveyed. The study employed judgmental, convenience, and snowball sampling. Confirmatory Factor Analysis (CFA) and Structural Equation Model (SEM) are the main statistical tools for data analysis. Results: The results show that all determinants impact customers’ willingness to adopt EVs, except perceived enjoyment and environmental control. Conclusions: The study proposes to promote the incentives by decreasing electricity prices and endorsing EVs purchase to accelerate the adoption of EVs in Thailand. Therefore, future policies should focus on behavioral intention toward EVs amongst logistic and distribution firms for enhancing the future of mobility in Thailand.

참고문헌 (48)

  1. Ajzen, I., "The theory of planned behavior", Organizational Behavior and Human Decision Processes, 50(2), pp.179~211 (1991)[DOI]
  2. Ali, I., "Insights on electric vehicle adoption : Does attitude play a mediating role?", Innovative Marketing, 18(1), pp.104~116 (2022)[DOI]
  3. Alomari, M. M., "Analysis of Energy Conservation Behavior at the Kuwaiti Academic Buildings", International Journal of Energy Economics and Policy, 11(1), pp.219~232 (2020)[DOI]
  4. Anable, J., "Complacent Car Addicts or Aspiring Environmentalists? Identifying travel behaviour segments using attitude theory", Transport Policy, 12(1), pp.65~78 (2005)[DOI]
  5. Casey, T., "Predicting uptake of technology innovations in online family dispute resolution services : An application and extension of the UTAUT", Computers in Human Behavior, 28(6), pp.2034~2045 (2012)[DOI]
  6. Dash, A., "Determinants of EVs adoption : A study on green behavior of consumers", Smart and Sustainable Built Environment, 10(1), pp.125~137 (2021)[DOI]
  7. Davis, F. D., "User acceptance of computer technology : A comparison of two theoretical models", Management Science, 35(8), pp.982~1003 (1989)[DOI]
  8. Dunlap, R. E., "Encyclopedia of Psychological Assessment", pp.364~369 (2003), Sage
  9. Eagly, A. H., "The advantages of an inclusive definition of attitude", Social Cognition, 25(5), pp.582~602 (2007)[DOI]
  10. Fleury, S., "What drives corporate carsharing acceptance? A French case study", Transportation Research Part F : Traffic Psychology and Behaviour, 45, pp.218~227 (2017)[DOI]
  11. Fornell, C., "Evaluating structural equation models with unobservable variables and measurement error", Journal of Marketing Research, 18(1), pp.39~50 (1981)[DOI]
  12. Hair, J. F., "A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)" (2017), Sage Publications Inc
  13. Kester, J., "Policy mechanisms to accelerate electric vehicle adoption : A qualitative review from the Nordic region", Renewable and Sustainable Energy Reviews, 94, pp.719~731 (2018)[DOI]
  14. Khazaei, H., "Electric Vehicles and Factors That Influencing Their Adoption Moderating Effects of Driving Experience and Voluntariness of Use (Conceptual Framework)", IOSR Journal of Business and Management(IOSR-JBM), 18(12), pp.60~65 (2016)[DOI]
  15. Khurana, A., "A Study on the Adoption of Electric Vehicles in India : The Mediating Role of Attitude", Vision, 24(1), pp.23~34 (2020)[DOI]
  16. Kline, R. B., "Principles and practice of structural equation modeling" (1998), Guilford Press
  17. Kline, R. B., "Principles and practice of structural equation modeling" (2005), Guilford Press
  18. Kline, R. B., "Principles and practices of structural equation modeling" (2011), The Guilford Press
  19. Klöckner, C. A., "Positive and negative spillover effects from electric car purchase to car use", Transportation Research Part D : Transport and Environment, 21, pp.32~38 (2013)[DOI]
  20. Kongklaew, C., "Barriers to Electric Vehicle Adoption in Thailand", Sustainability, 13, pp.1~14 (2021)[DOI]
  21. Kraft, P., "Perceived Difficulty in the Theory of Planned Behaviour : Perceived Behavioural Control or Affective Attitude", British Journal of Social Psychology, 44(3), pp.479~496 (2005)[DOI]
  22. Lai, I., "Factors Influencing the Behavioural Intention towards Full Electric Vehicles : An Empirical Study in Macau", Sustainability, 7(9), pp.12564~12585 (2015)[DOI]
  23. Liao, C. -H., "The roles of perceived enjoyment and price perception in determining acceptance of multimedia-on-demand", International Journal of Business and Information, 3(1), pp.27~52 (2008)[DOI]
  24. MacCallum, R. C., "Power Analysis and Determination of Sample Size for Covariance Structure Modeling", Psychological Methods, 1(2), pp.130~149 (1996)[DOI]
  25. Madigan, R., "What influences the decision to use automated public transport? Using UTAUT to understand public acceptance of automated road transport systems", Transportation Research Part F : Traffic Psychology and Behaviour, 50, pp.55~64 (2017)[DOI]
  26. Mahmoud, M., "Measuring the influence of bus service quality on the perception of users", Transport Plan Technology, 39(3), pp.284~299 (2016)[DOI]
  27. Mohamed, M., "Identifying and characterizing potential electric vehicle adopters in Canada : A two-stage modelling approach", Transport Policy, 52, pp.100~112 (2016)[DOI]
  28. Nguyen, Q. N., "Applying the Theory of Planned Behavior to Analyze Household EnergySaving Behavior", International Journal of Energy Economics and Policy, 12(5), pp.287~293 (2022)[DOI]
  29. Nunnally, J. C., "The Assessment of Reliability", Psychometric Theory, 3, pp.248~292 (1994)
  30. Ozaki, R., "Going hybrid : An analysis of consumer purchase motivations", Energy Policy, 39(5), pp.2217~2227 (2011)[DOI]
  31. Razak, M. I. M., "Intention to Purchase Hybrid Cars in Malaysia: An overview", International Journal of Economics, Commerce and Management, 2(10), pp.1~13 (2014)
  32. Rogers, E. M., "Diffusion of Innovations Theory" (2003), Free Press
  33. Sierzchula, W., "The influence of financial incentives and other socio-economic factors on electric vehicle adoption", Energy Policy, 68, pp.183~194 (2014)[DOI]
  34. Steiger, J. H., "Understanding the limitations of global fit assessment in structural equation modeling", Personality and Individual Differences, 42(5), pp.893~898 (2007)[DOI]
  35. Studenmund, A. H., "Using Econometrics: A Practical Guide" (1992), Harper Collins
  36. Tabachnick, B. G., "Using Multivariate Statistics" (2007), Allyn and Bacon
  37. Thananusak, T., "The development of electric vehicle charging stations in Thailand : Policies, players, and key issues(2015–2020)", World Electric Vehicle Journal, 12(1), pp.2~30 (2021)[DOI]
  38. Tran, V., "Travelers’ Acceptance of Electric Carsharing Systems in Developing Countries : The Case of China", Sustainability, 11(19), pp.1~22 (2019)[DOI]
  39. Venkatesh, V., "User Acceptance of Information Technology : Toward a Unified View", MIS Quarterly, 27(3), pp.425~478 (2003)[DOI]
  40. Venkatesh, V., "Consumer Acceptance and Use of Information Technology : Extending the Unified Theory of Acceptance and Use of Technology", MIS Quarterly, 36(1), pp.157~178 (2012)[DOI]
  41. Wang, N., "Research on Consumers’ Use Willingness and Opinions of Electric Vehicle Sharing : An Empirical Study in Shanghai", Sustainability, 8(1), pp.1~18 (2015)[DOI]
  42. Wang, S., "Predicting consumers’ intention to adopt hybrid electric vehicles : using an extended version of the theory of planned behavior model", Transportation, 43(1), pp.123~143 (2014)[DOI]
  43. Wang, S., "The impact of policy measures on consumer intention to adopt electric vehicles : Evidence from China", Transportation Research Part A : Policy and Practice, 105, pp.14~26 (2017)[DOI]
  44. West, R. F., "Cognitive sophistication does not attenuate the bias blind spot", Journal of Personality and Social Psychology, 103(3), pp.506~519 (2012)[DOI]
  45. Xie, H., "The Effect of Behavioral Intention to Use Hybrid Education : A Case of Chinese Undergraduate Students", AUGSB E-JOURNAL, 15(2), pp.159~168 (2022)[DOI]
  46. Yadav, R., "Young Consumers’ Intention towards Buying Green Products in a Developing Nation : Extending the Theory of Planned Behavior", Journal of Cleaner Production, 135, pp.732~739 (2016)[DOI]
  47. Yan, Q., "Research on Real Purchasing Behavior Analysis of Electric Cars in Beijing Based on Structural Equation Modeling and Multinomial Logit Model", Sustainability, 11(20), pp.5870~ (2019)[DOI]
  48. Yegin, T., "Analysis of Consumers’ Electric Vehicle Purchase Intentions : An Expansion of the Theory of Planned Behavior", Sustainability, 14, pp.12091~ (2022)[DOI]

관련 논문AI추천

이 간행물의 다른 논문 (11건)