DETERMINANTS OF ELECTRIC VEHICLE ADOPTION AMONG YOUNG ADULTS: AN EXTENDED TECHNOLOGY ACCEPTANCE MODEL APPROACH USING PLS-SEM
This study investigates the determinants of EV adoption among young adults in Bilaspur, Chhattisgarh, using data from 120 college students. The research model integrates the Technology Acceptance Model (TAM) with contextual factors such as awareness, environmental concern, social influence, charging infrastructure, and cost barriers. Data were collected through a structured questionnaire using a five-point Likert scale and analyzed using PLS-SEM.
The findings reveal that perceived ease of use and perceived usefulness significantly influence attitude toward EVs, which in turn positively affects purchase intention. Additionally, perceived usefulness directly impacts purchase intention. However, awareness, environmental concern, social influence, and cost barriers were not significant predictors of attitude, while charging infrastructure showed only marginal influence. These results suggest that young adults in Bilaspur prioritize practical usability and perceived benefits of EVs over environmental or social motivations. The study offers valuable insights for policymakers, educational institutions, and EV manufacturers to design targeted strategies that enhance usability, improve perceived benefits, and address infrastructure concerns to encourage EV adoption among youth in emerging urban contexts.
Jain, H. (2026). Determinants Of Electric Vehicle Adoption Among Young Adults: An Extended Technology Acceptance Model Approach using PLS-SEM. International Journal of Science, Strategic Management and Technology, 02(03). https://doi.org/10.55041/ijsmt.v2i3.016
Jain, Harsh. "Determinants Of Electric Vehicle Adoption Among Young Adults: An Extended Technology Acceptance Model Approach using PLS-SEM." International Journal of Science, Strategic Management and Technology, vol. 02, no. 03, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i3.016.
Jain, Harsh. "Determinants Of Electric Vehicle Adoption Among Young Adults: An Extended Technology Acceptance Model Approach using PLS-SEM." International Journal of Science, Strategic Management and Technology 02, no. 03 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i3.016.
2.Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
3.Dhankhar, S., Pateer, S., Sandhu, V., & Kaur, H. (2024). Barriers to electric vehicle adoption in India: A comparative review and future growth prospects. European Economic Letters, 14(3), 2007–2015.
4.Dunlap, R. E., Van Liere, K. D., Mertig, A. G., & Jones, R. E. (2000). Measuring endorsement of the new ecological paradigm: A revised NEP scale. Journal of Social Issues, 56(3), 425–442.
5.Egbue, O., & Long, S. (2012). Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions. Energy Policy, 48, 717–729.
6.Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Sage Publications.
7.India’s electric vehicle journey. (n.d.). Drishti IAS. https://www.drishtiias.com/daily-updates/daily-news-editorials/india-s-electric-vehicle-journey
8.Jansson, J., Nordlund, A., & Westin, K. (2011). Examining drivers of sustainable consumption: The influence of norms and attitudes on electric vehicle adoption. Journal of Cleaner Production, 19(17–18), 2058–2065.
9.Mehta, H., Rathod, L., Shah, F., Bhatt, A., Machhvara, J., Chauhan, R., & Maseleno, A. (2024). Perceptions of electric vehicle adoption among young adults in Ahmedabad: Exploring influences and implications. Global Journal of Innovative Economic Studies, 1(4), 202–212.
10.Moons, I., & De Pelsmacker, P. (2012). Emotions as determinants of electric car usage intention. Journal of Marketing Management, 28(3–4), 195–237