Published March 14, 2026
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Extending TAM-UTAUT with Range Anxiety, Charging Infrastructure Access, and FAME-III Policy Awareness as Moderating Constructs
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India’s electric vehicle transition has accelerated sharply since the launch of the FAME-III scheme in 2024, with domestic two-wheeler and passenger car EV sales registering compound annual growth exceeding forty percent; yet aggregate EV penetration as a share of total new vehicle registrations remains below nine percent in even the most progressive states, revealing a pronounced intention-behaviour gap that existing adoption research — dominated by Western samples and pre-infrastructure-buildout contexts — has inadequately explained. This study applies an extended Technology Acceptance Model integrated with Unified Theory of Acceptance and Use of Technology (TAM-UTAUT) constructs to survey data from 1,684 prospective vehicle purchasers across Tier-1, Tier-2, and Tier-3 Indian cities, incorporating range anxiety and charging infrastructure access as contextually salient barriers alongside FAME-III policy awareness as a moderator of the performance expectancy-to-purchase-intention relationship, and finds that the model explains substantially more variance in EV purchase intention than standard TAM formulations, with state-level differences in infrastructure score and policy implementation quality emerging as the primary predictors of gap between expressed intention and projected adoption behaviour.
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2026-03-14India's electric vehicle transition has accelerated sharply since the launch of the FAME-III scheme in 2024, with domestic two-wheeler and passenger car EV sales registering compound annual growth exceeding forty percent; yet aggregate EV penetration as a share of total new vehicle registrations remains below nine percent in even the most progressive states, revealing a pronounced intention-behaviour gap that existing adoption research — dominated by Western samples and pre-infrastructure-buildout contexts — has inadequately explained. This study applies an extended Technology Acceptance Model integrated with Unified Theory of Acceptance and Use of Technology (TAM-UTAUT) constructs to survey data from 1,684 prospective vehicle purchasers across Tier-1, Tier-2, and Tier-3 Indian cities, incorporating range anxiety and charging infrastructure access as contextually salient barriers alongside FAME-III policy awareness as a moderator of the performance expectancy-to-purchase-intention relationship, and finds that the model explains substantially more variance in EV purchase intention than standard TAM formulations, with state-level differences in infrastructure score and policy implementation quality emerging as the primary predictors of gap between expressed intention and projected adoption behaviour.
References
- [1] CEEW. (2024). Consumer Insights on Electric Vehicle Adoption Across Indian Cities. Council on Energy, Environment and Water. [2] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. [3] GoI. (2024). FAME-III Scheme Guidelines. Ministry of Heavy Industries, Government of India. [4] Gupta, R., & Tyagi, A. (2023). EV adoption barriers in emerging markets: A meta-analysis. Renewable and Sustainable Energy Reviews, 187, 113732. [5] IEA. (2025). Global EV Outlook 2025. International Energy Agency. [6] Jaiswal, D., Kant, R., & Priyadarshi, R. (2022). Predicting the adoption of electric vehicles: A conceptual model. Transportation Research Part A, 165, 286-302. [7] Kumar, A., & Mohan, M. (2024). Range anxiety and charging infrastructure: Lessons for Indian EV policy. Energy Policy, 187, 113941. [8] MoP. (2024). Public EV Charging Infrastructure Status Report Q3 2024. Ministry of Power, GoI. [9] Nayak, S., & Dash, A. K. (2023). FAME-II evaluation and prospects for FAME-III: A consumer survey analysis. Economic and Political Weekly, 58(14), 34-41. [10] Ramesh, N., & Gopal, P. (2024). Environmental concern and EV adoption intention in South India. Journal of Cleaner Production, 441, 141052. [11] SMEV. (2024). Annual EV Sales Report 2023-24. Society of Manufacturers of Electric Vehicles. [12] Tandon, U., Kiran, R., & Sah, A. N. (2022). Factors affecting adoption of electric vehicles in India. International Journal of Sustainable Transportation, 16(3), 224-240. [13] Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. [14] Verma, A., & Kumar, P. (2023). Willingness to pay for EVs in Indian urban markets. Transport Policy, 134, 104-115. [15] Wang, S., Fan, J., Zhao, D., et al. (2016). Predicting consumers' intention to adopt hybrid electric vehicles: Using an extended version of the theory of planned behavior model. Transportation, 43, 123-143. [16] Zhao, X., Ke, Y., Zuo, J., et al. (2020). Evaluation of sustainable transport research in 2000–2019. Journal of Cleaner Production, 256, 120404.[1] CEEW. (2024). Consumer Insights on Electric Vehicle Adoption Across Indian Cities. Council on Energy, Environment and Water. [2] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. [3] GoI. (2024). FAME-III Scheme Guidelines. Ministry of Heavy Industries, Government of India. [4] Gupta, R., & Tyagi, A. (2023). EV adoption barriers in emerging markets: A meta-analysis. Renewable and Sustainable Energy Reviews, 187, 113732. [5] IEA. (2025). Global EV Outlook 2025. International Energy Agency. [6] Jaiswal, D., Kant, R., & Priyadarshi, R. (2022). Predicting the adoption of electric vehicles: A conceptual model. Transportation Research Part A, 165, 286-302. [7] Kumar, A., & Mohan, M. (2024). Range anxiety and charging infrastructure: Lessons for Indian EV policy. Energy Policy, 187, 113941. [8] MoP. (2024). Public EV Charging Infrastructure Status Report Q3 2024. Ministry of Power, GoI. [9] Nayak, S., & Dash, A. K. (2023). FAME-II evaluation and prospects for FAME-III: A consumer survey analysis. Economic and Political Weekly, 58(14), 34-41. [10] Ramesh, N., & Gopal, P. (2024). Environmental concern and EV adoption intention in South India. Journal of Cleaner Production, 441, 141052. [11] SMEV. (2024). Annual EV Sales Report 2023-24. Society of Manufacturers of Electric Vehicles. [12] Tandon, U., Kiran, R., & Sah, A. N. (2022). Factors affecting adoption of electric vehicles in India. International Journal of Sustainable Transportation, 16(3), 224-240. [13] Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. [14] Verma, A., & Kumar, P. (2023). Willingness to pay for EVs in Indian urban markets. Transport Policy, 134, 104-115. [15] Wang, S., Fan, J., Zhao, D., et al. (2016). Predicting consumers' intention to adopt hybrid electric vehicles: Using an extended version of the theory of planned behavior model. Transportation, 43, 123-143. [16] Zhao, X., Ke, Y., Zuo, J., et al. (2020). Evaluation of sustainable transport research in 2000–2019. Journal of Cleaner Production, 256, 120404.