Applying the Unified Theory of Acceptance and Use of Technology to Analyze the Adoption of Battery Electric Vehicles in Nepal
Main Article Content
Abstract
Aim/Purpose: This study examined factors influencing battery electric vehicle (BEV) adoption in Kathmandu, Nepal, where transitioning from combustion engines to BEVs could advance sustainable transportation and renewable energy growth. Using the extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, Price Value, and Government Incentives were analyzed. It also explored how Environmental Concerns mediate Purchase Intention and Usage Behavior, linking intent to actual BEV utilization. The findings aim to inform policies accelerating Nepal’s green mobility transition.
Background: With its abundant hydropower resources, Nepal has a unique opportunity to shift toward green mobility and reduce dependence on imported fossil fuels. Despite the increased use of BEVs, there has been limited research on purchase intention factors that significantly impact consumer adoption. This study provides actionable insights for policymakers, manufacturers, and marketers to encourage BEV adoption. This research examined the impact of performance expectancy, effort expectancy, social influence, and facilitating conditions alongside additional constructs such as hedonic motivation, environmental concerns, price value, and government incentives on the purchase intention and subsequent use behavior of BEVs in Nepal.
Methodology: A quantitative research approach was employed in this study to analyze the constructs of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). This study focused on vehicle owners aged 18 and above who were interested in purchasing BEVs in Kathmandu, Nepal. The data were collected through a structured questionnaire using a purposive stratified random sampling method. A sample size of 400 respondents was targeted; however, 572 surveys were distributed to enhance reliability, yielding 536 valid responses. Data collection took place between May and June 2024 through online surveys and self-administered questionnaires distributed across various digital platforms. The survey questionnaire included three sections: demographic data (e.g., gender, age, income, education), consumer behavior, and BEV adoption constructs (Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Condition, Hedonic Motivation, Government Incentives, Environmental Concerns, and Price Value), which were measured on a five-point Likert scale. Descriptive statistics (mean, median, mode) and frequency distributions were used to summarize key variables and demographic trends. This study used a partial least squares structural equation modeling (PLS-SEM) analysis tool to determine factors direct and indirect effects on BEV adoption intention in Kathmandu, Nepal.
Findings: The study revealed that purchase intention significantly and directly affected the use behavior of BEVs in Nepal. The UTAUTS constructs, such as Effort Expectancy, Hedonic Motivation, Price Value, Government Incentives, and Facilitating Conditions, significantly impacted the purchase intention of BEV in Kathmandu, Nepal, leading to use behavior. This indicated that purchase intention was a strong predictor of usage behavior. However, Performance Expectancy, Social Influence, and Environmental Concerns did not have a significant impact, suggesting that consumers prioritized affordability and practical considerations over perceived vehicle performance. These findings indicate that in the Nepalese context, consumers' decisions are more driven by practical benefits and individual preferences rather than performance expectations or social pressures. This divergence from typical UTAUT2 outcomes indicates that Nepalese consumers prioritize immediate and tangible benefits over perceived performance and societal influences. Environmental Concerns, while relevant, did not emerge as a primary factor influencing purchase intentions, which may reflect the current state of environmental awareness and prioritization among Nepalese consumers.
Contribution/Impact on Society: This study provides theoretical insights into BEV adoption by demonstrating that facilitating conditions have a positive influence on adoption intention. By empirically validating this relationship, the findings of the study demonstrated the UTAUT2 framework’s applicability to BEV adoption. These findings underscore the essential role of supportive infrastructures, such as charging networks and governmental incentives, in reducing adoption barriers and enhancing consumer willingness to adopt BEVs. This study equips decision-makers with the necessary tools to foster a more sustainable and electrically driven transportation ecosystem in Kathmandu, paving the way toward a cleaner and more livable urban environment.
Recommendations: The adoption of BEVs in Nepal offers wide-ranging benefits. For policymakers, the study provides insights to guide evidence-based decisions, including incentives, infrastructure, and regulatory frameworks. Industry stakeholders can better understand consumer preferences and adoption barriers, informing strategies for product development and market positioning. Environmental organizations can use these findings to advocate for policies that promote emissions reduction and sustainable transport. Consumers gain awareness of BEVs' economic and environmental benefits, empowering informed choices. Academically, the research enriches the literature on technology adoption in developing countries, serving as a foundation for future studies in Nepal and similar contexts.
Research Limitations: This study has a few limitations. First, the sample primarily included owners of combustion engine vehicles, which may limit direct insights into the purchasing behavior of actual BEV users. Second, the geographical scope was confined to Kathmandu and specific regions of Nepal, restricting the generalizability of findings to other areas; future research could benefit from broader geographic coverage. Lastly, the study focused on selected UTAUT2 constructs. At the same time, other potentially influential factors, such as prior use experience, fuel efficiency, and brand loyalty, were not explored, leaving room for future studies to investigate these aspects.
Future Research: Future studies could be expanded to include a larger, more diverse sample of existing BEV users across various regions of Nepal, capturing regional variations and developing targeted strategies. They could also explore additional factors like user experience, perceived fuel efficiency, and brand loyalty to enrich understanding consumer decision-making and adoption dynamics. This study also could be extended into longitudinal research by collecting data from various regions of the country. This would diversify the research findings, providing valuable insight into consumer behavior in this evolving BEV market. Furthermore, consumer perceptions and behavior vary due to changing market demands and government policies.
Article Details

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright: Asia-Pacific International University reserve exclusive rights to publish, reproduce and distribute the manuscript and all contents therein.
References
Abbasi, H. A., Johl, S. K., Shaari, Z. B. H., Moughal, W., Mazhar, M., Musarat, M. A., Rafiq, W., Farooqi, A. S., & Borovkov, A. (2021). Consumer motivation by using unified theory of acceptance and use of technology towards electric vehicles. Sustainability, 13(21), 12177. https://doi.org/10.3390/su132112177
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/https://doi.org/10.1016/0749-5978(91)90020-T
Ali, U., Mehmood, A., Majeed, M. F., Muhammad, S., Khan, M. K., Song, H., & Malik, K. M. (2019). Innovative citizen’s services through public cloud in Pakistan: User’s privacy concerns and impacts on adoption. Mobile Networks and Applications, 24, 47–68. https://doi.org/10.1007/s11036-018-1132-x
Bjerkan, K. Y., Nørbech, T. E., & Nordtømme, M. E. (2016). Incentives for promoting battery electric vehicle (BEV) adoption in Norway. Transportation Research Part D: Transport and Environment, 43, 169–180. https://doi.org/10.1016/j.trd.2015.12.002
Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS Quarterly, 29(3), 399–426. https://doi.org/10.2307/25148690
Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research, 14(2), 189–217. https://doi.org/10.1287/isre.14.2.189.16018
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334. https://doi.org/10.1007/BF02310555
Dijkstra, T. K., & Henseler, J. (2015). Consistent Partial Least Squares Path Modeling. Marketing Science , 34(1), 29–48. https://doi.org/10.1287/mksc.2014.0892
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behaviour: An introduction to theory and research. Addison-Wesley.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.2307/3151312
Gunawan, I., Redi, A. A. N. P., Santosa, A. A., Maghfiroh, M. F. N., Pandyaswargo, A. H., & Kurniawan, A. C. (2022). Determinants of customer intentions to use electric vehicle in Indonesia: An integrated model analysis. Sustainability, 14(4), 1972. https://doi.org/10.3390/su14041972
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications.
Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., Ketchen, D. J.,Hair, J. F., Hult, G. T. M., & Calantone, R. J. (2014). Common beliefs and reality about PLS: Comments on Rönkkö and Evermann (2013). Organizational Research Methods, 17(2), 182–209. https://doi.org/10.1177/ 1094428114526928
Huang, X., & Ge, J. (2019). Electric vehicle development in Beijing: An analysis of consumer purchase intention. Journal of Cleaner Production, 216, 361–372. https://doi.org/10.1016/j.jclepro.2019.01.231
IEA. (2023). Global EV outlook 2023. https://www.iea.org/reports/global-ev-outlook-2023
Ingram, E. (2023, October 6). Hydroelectric generation in Nepal grew 500 MW in 2023. https://www.hydroreview.com/hydro-industry-news/new-development/hydroelectric-generation-in-nepal-grew-500-mw-in-2023/
Irle, R. (2023, February 6). Global EV sales for 2022. https://ev-volumes.com/news/ev/global-ev-sales-for-2022/
Jain, N. K., Bhaskar, K., & Jain, S. (2022). What drives adoption intention of electric vehicles in India? An integrated UTAUT model with environmental concerns, perceived risk and government support. Research in Transportation Business & Management, 42, 100730. https://doi.org/10.1016/j.rtbm.2021.100730
Kim, J. H., Lee, G., Park, J. Y., Hong, J., & Park, J. (2019). Consumer intentions to purchase battery electric vehicles in Korea. Energy Policy, 132, 736–743. https://doi.10.1016/j.enpol.2019.06.028
Larson, P. D., Viáfara, J., Parsons, R. V., & Elias, A. (2014). Consumer attitudes about electric cars: Pricing analysis and policy implications. Transportation Research Part A: Policy and Practice, 69, 299–314. http://www.sciencedirect.com/science/article/pii/S0965856414002134
Lee, J., Baig, F., Talpur, M. A. H., & Shaikh, S. (2021). Public intentions to purchase electric vehicles in Pakistan. Sustainability, 13(10), 5523. https://doi.org/10.3390/su13105523
Liu, H., Sato, H., & Morikawa, T. (2015). Influences of environmental consciousness and attitudes to transportation on electric vehicle purchase intentions. Asian Transport Studies, 3(4), 430–446. https://www.jstage.jst.go.jp/article/eastsats/3/4/3_430/_pdf
Low, L. P., & Chee, D. (2023, December 11). Asia Pacific net zero economy index 2023. PricewaterhouseCoopers. https://www.pwc.com/gx/en/issues/esg/esg-asia-pacific/net-zero-economy-index-asia-pacifics-transition-2023.html?gad_source=1&gclid=Cj0KCQjwv_m
Manutworakit, P., & Choocharukul, K. (2022). Factors influencing battery electric vehicle adoption in Thailand—Expanding the unified theory of acceptance and use of technology’s variables. Sustainability, 14(14), 8482. https://doi.org/10.3390/su14148482
McKinsey & Company. (2022). Global energy perspective 2022. McKinsey & Company. https://www.mckinsey.com/~/media/McKinsey/Industries/Oil%20and%20Gas/Our%20Insights/Global%20Energy%20Perspective%202022/Global-Energy-Perspective-2022-Executive-Summary.pdf
Ministry of Physical Infrastructure and Transport (MOPIT), Nepal (2023). Annual report on electric vehicle registrations. https://mopit.gov.np/en/sources/9/81011959
Okada, T., Tamaki, T., & Managi, S. (2019). Effect of environmental awareness on purchase intention and satisfaction pertaining to electric vehicles in Japan. Transportation Research Part D: Transport and Environment, 67, 503–513. https://doi.org/10.1016/j.trd.2019.01.012
Paudel, N. (2023, February 27). Devices to read smart driving licenses lacking. https://risingnepaldaily.com/news/23237
Samarasinghe, D., Kuruppu, G. N., & Dissanayake, T. (2024). Factors influencing the purchase intention toward electric vehicles; a nonuser perspective. South Asian Journal of Marketing, 5(2), 149–165. https://doi.org/10.1108/SAJM-04-2023-0026
Sang, Y.-N., & Bekhet, H. A. (2015). Modelling electric vehicle usage intentions: An empirical study in Malaysia. Journal of Cleaner Production, 92, 75–83. https://doi.org/https://doi.org/10.1016/j.jclepro.2014.12.045
Shmueli, G., Ray, S., Velasquez Estrada, J. M., & Chatla, S. B. (2016). The elephant in the room: Predictive performance of PLS models. Journal of Business Research, 69(10), 4552–4564. https://doi.org/10.1016/j.jbusres.2016.03.049
Thananusak, T., Rakthin, S., Tavewatanaphan, T., & Punnakitikashem, P. (2017). Factors affecting the intention to buy electric vehicles: Empirical evidence from Thailand. International Journal of Electric and Hybrid Vehicles, 9(4), 361–381. https://doi.org/10.1504/IJEHV.2017.089875
The HRM. (2023, August 23). The Nepali EV market. The HRM Nepal. https://thehrmnepal.com/cover-story/the-nepaliev-market/
Tiep, H. S., Ling, G. M., & Pei, L. P. (2023, July 14–16). Factors influencing customers loyalty towards online food delivery applications in Klang Valley, Malaysia [Paper presentation]. In 2023 International Conference on Digital Applications, Transformation & Economy (ICDATE), Miri, Sarawak, Malaysia. https://doi.org/10.1109/icdate58146.2023.10248502
Tran, V., Zhao, S., Diop, E. B., & Song, W. (2019). Travelers’ acceptance of electric carsharing systems in developing countries: the case of China. Sustainability, 11(19), 5348. https://doi.org/10.3390/su11195348
Tu, J.-C., & Yang, C. (2019). Key factors influencing consumers’ purchase of electric vehicles. Sustainability, 11(14), 3863. https://doi.org/10.3390/su11143863
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. https://doi.org/10.1016/j.rtbm.2022.100784
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. https://doi.org/10.2307/30036540
Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
Verkijika, S. F. (2018). Factors influencing the adoption of mobile commerce applications in Cameroon. Telematics and Informatics, 35(6), 1665–1674. https://doi.org/10.1016/j.tele.2018.04.012
Wang, X.-W., Cao, Y.-M., & Zhang, N. (2021). The influences of incentive policy perceptions and consumer social attributes on battery electric vehicle purchase intentions. Energy Policy, 151, 112163. https://doi.org/10.1016/j.enpol.2021.112163
Wang, Z., Zhao, C., Yin, J., & Zhang, B. (2017). Purchasing intentions of Chinese citizens on new energy vehicles: How should one respond to current preferential policy? Journal of Cleaner Production, 161, 1000–1010. https://doi.org/10.1016/j.jclepro.2017.05.154
Wolf, A., & Seebauer, S. (2014). Technology adoption of electric bicycles: A survey among early adopters. Transportation Research Part A: Policy and Practice, 69, 196–211. https://doi.org/https://doi.org/10.1016/ j.tra.2014.08.007
Yamane, T. (1973). Statistics: An introductory analysis. Harper and Row.
Zamil, A. M., Ali, S., Akbar, M., Zubr, V., & Rasool, F. (2023). The consumer purchase intention toward hybrid electric car: A utilitarian-hedonic attitude approach. Frontiers in Environmental Science, 11, 1101258. https://doi.org/10.3389/fenvs.2023.1101258
Zhou, M., Long, P., Kong, N., Zhao, L., Jia, F., & Campy, K. S. (2021). Characterizing the motivational mechanism behind taxi driver’s adoption of electric vehicles for living: Insights from China. Transportation Research Part A: Policy and Practice, 144, 134–152. https://ideas.repec.org/a/eee/transa/v144y2021icp134-152.htm