Factors Associated with Adoption Intention of Proton e-MAS: A Multi-Dimensional Analysis of Malaysian Consumers

This paper presented a condensed research framework for examining the factors influencing adoption intention towards Proton e.MAS among current electric vehicle (EV) users in Klang Valley, Malaysia. Although EV registrations and government support had increased, adoption continued to be influenced by practical concerns related to travel distance, driving range, purchase price, charging duration, charging infrastructure, and incentive policies. Existing Malaysian studies had primarily investigated general EV purchase intention, while limited empirical work had focused on Proton e.MAS as a national EV brand and had integrated behavioural, product, and contextual dimensions within a single model. The study was informed by an adapted Theory of Planned Behaviour perspective. Adoption intention served as the dependent variable; travel distance represented the behavioural dimension; driving range, price, and charging time represented the product attributes; and charging infrastructure and incentive policies represented the contextual factors. A quantitative cross-sectional design was employed. Structured questionnaires were distributed through online and offline platforms to 375 EV users aged 18 years and above who held valid driving licences and lived, worked, or regularly travelled within Klang Valley. Purposive sampling, a five-point Likert scale, expert pretesting, and a 30-respondent pilot study were utilised. The data were analysed using SPSS Version 27 through descriptive statistics, reliability analysis, Pearson correlation, and multiple regression. The findings indicated that product and contextual factors positively influenced adoption intention, while the effect of travel distance depended on users’ mobility patterns and perceptions of range adequacy. The study provided practical implications for Proton, charging service providers, and Malaysian policymakers while contributing to the growing body of EV adoption research in an emerging-market context.

Electric Vehicle (EV) Adoption, Purchase Intention, Proton e.MAS, Theory of Planned Behaviour, Travel Distance, Driving Range, Price

1. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. [Google Scholar] [Crossref]

2. Amran, A. N. Q., Ma’aram, A., & Sutopo, W. (2025). The prediction model for electric vehicles adoption rate in Malaysia. Journal of Transport System Engineering, 1–8. [Google Scholar] [Crossref]

3. Buhmann, K. M., Rialp-Criado, J., & Rialp-Criado, A. (2024). Predicting consumer intention to adopt battery electric vehicles: Extending the Theory of Planned Behavior. Sustainability, 16(3), 1284. [Google Scholar] [Crossref]

4. Bujang, M. A., Omar, E. D., Foo, D. H. P., & Hon, Y. K. (2024). Sample size determination for conducting a pilot study to assess reliability of a questionnaire. Restorative Dentistry and Endodontics, 49(1). [Google Scholar] [Crossref]

5. Chen, P., Selamat, M. H., & Lee, S.-N. (2025). The impact of policy incentives on the purchase of electric vehicles by consumers in China’s first-tier cities. Sustainability, 17(12), 5319. [Google Scholar] [Crossref]

6. Fishbein, M., & Ajzen, I. (2010). Predicting and changing behavior. Psychology Press. [Google Scholar] [Crossref]

7. Hair, J. F., Hult, T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (3rd ed.). Sage. [Google Scholar] [Crossref]

8. He, S., Luo, S., & Sun, K. K. (2022). Factors affecting electric vehicle adoption intention: The impact of objective, perceived, and prospective charger accessibility. Journal of Transport and Land Use, 15(1), 779–801. [Google Scholar] [Crossref]

9. Higueras-Castillo, E., Singh, V., Singh, V., & Liébana-Cabanillas, F. (2023). Factors affecting adoption intention of electric vehicle: A cross-cultural study. Environment, Development and Sustainability. [Google Scholar] [Crossref]

10. Holtom, B., Baruch, Y., Aguinis, H., & Ballinger, G. A. (2022). Survey response rates: Trends and a validity assessment framework. Human Relations, 75(8), 1560–1584. [Google Scholar] [Crossref]

11. Hoogland, K., Kurani, K. S., Hardman, S., & Chakraborty, D. (2024). If you build it, will they notice? Public charging density, charging infrastructure awareness, and consideration to purchase an electric vehicle. Transportation Research Interdisciplinary Perspectives, 23, 101007. [Google Scholar] [Crossref]

12. International Energy Agency. (2024). Global EV outlook 2024. IEA. [Google Scholar] [Crossref]

13. Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607–610. [Google Scholar] [Crossref]

14. Krishnan, V. V., & Koshy, B. I. (2021). Evaluating the factors influencing purchase intention of electric vehicles in households owning conventional vehicles. Case Studies on Transport Policy, 9(3). [Google Scholar] [Crossref]

15. Lay, W., Gauhar, V., Castellani, D., & Teoh, J. Y. C. (2023). Tips and pitfalls in using social media platforms for survey dissemination. Société Internationale d’Urologie Journal, 4(2), 118–124. [Google Scholar] [Crossref]

16. Malaysian Green Technology and Climate Change Corporation. (2024). Malaysia on track for EV revolution. [Google Scholar] [Crossref]

17. Malaysian Investment Development Authority. (2025). Powering the future: Accelerating Malaysia’s EV charging revolution for sustainable mobility. [Google Scholar] [Crossref]

18. Mohd Noor, N. A., Muhammad, A., Isa, F. M., Shamsudin, M. F., & Abaidah, T. N. A. T. (2025). The electric vehicle revolution: How consumption values, consumer attitudes, and infrastructure readiness influence the intention to purchase electric vehicles in Malaysia. World Electric Vehicle Journal, 16(10), 556. [Google Scholar] [Crossref]

19. Pamidimukkala, A., Kermanshachi, S., Rosenberger, J. M., & Hladik, G. (2024). Barriers and motivators to the adoption of electric vehicles: A global review. Green Energy and Intelligent Transportation, 3(2), 100153. [Google Scholar] [Crossref]

20. Papageorgiou, S. N. (2022). On correlation coefficients and their interpretation. Journal of Orthodontics, 49(3), 359–361. [Google Scholar] [Crossref]

21. Proton New Energy Technology Sdn. Bhd. (2025). PROTON launches Proton e.MAS 5, Malaysia’s first affordable electric vehicle. [Google Scholar] [Crossref]

22. Siahaan, R., Simamora, N., & Sitindaon, C. (2024). Exploring electric car adoption intent: Role of current travel characteristics among daily car users. Transactions on Transport Sciences, 15(2), 47–53. [Google Scholar] [Crossref]

23. Spencer, N. H., Syrdal, D. S., Coates, M., & Huws, U. (2022). Assessing bias in online surveys using alternative survey modes. Work Organisation, Labour & Globalisation, 16(1). [Google Scholar] [Crossref]

24. Stadtmüller, S., Beuthner, C., & Silber, H. (2021). Mixed-mode surveys. GESIS Survey Guidelines. [Google Scholar] [Crossref]

25. Syed Mansor, H. S., & Anuar, H. S. (2025). Price perception, charging infrastructure and environmental consciousness that influence adoption of electric vehicle: Malaysia perspectives. Journal of Technology and Operations Management, 20(2), 21–37. [Google Scholar] [Crossref]

26. Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). Pearson. [Google Scholar] [Crossref]

27. Tsai, J.-F., Wu, S.-C., Kathinthong, P., Tran, T.-H., & Lin, M.-H. (2024). Electric vehicle adoption barriers in Thailand. Sustainability, 16(4), 1642. [Google Scholar] [Crossref]

28. Umair, M., Hidayat, N. M., Ali, N., Nasir, M., Hakomori, T., & Abdullah, E. (2024). A review of Malaysia’s current state and future in electric vehicles. Journal of Sustainable Development of Energy, Water and Environment Systems, 12(4), 1–35. [Google Scholar] [Crossref]

29. Vafaei-Zadeh, A., Wong, T.-K., Hanifah, H., Teoh, A. P., & Nawaser, K. (2022). Modelling electric vehicle purchase intention among Generation Y consumers in Malaysia. Research in Transportation Business & Management, 43, 100784. [Google Scholar] [Crossref]

30. Wang, J., Huang, C., He, D., & Tu, R. (2023). Range anxiety among battery electric vehicle users: Both distance and waiting time matter. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 67(1). [Google Scholar] [Crossref]

31. Xue, Y., Zhang, Y., Wang, Z., Tian, S., Xiong, Q., & Li, L. Q. (2023). Effects of incentive policies on the purchase intention of electric vehicles in China: Psychosocial value and family ownership. Energy Policy, 181, 113732. [Google Scholar] [Crossref]

32. Yusoff, M. S. B., Arifin, W. N., & Hadie, S. N. H. (2021). ABC of questionnaire development and validation for survey research. Education in Medicine Journal, 13(1), 97–108. [Google Scholar] [Crossref]

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