Drivers of Electric Vehicle Adoption in Nigeria An Extended UTAUT Framework Approach
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Abstract
Electric vehicles (EVs) represent a significant advancement in automotive technology, utilizing electricity as a power source in place of traditional fossil fuels and incorporating sophisticated navigation and autopilot systems. These vehicles align with multiple Sustainable Development Goals (SDGs) by offering a more environmentally sustainable alternative to internal combustion engine vehicles (ICEVs). Despite their potential, the adoption of EVs in developing nations such as Nigeria remains constrained. The Unified Theory of Acceptance and Use of Technology (UTAUT) framework is expanded in this study by including important enablers such as poor infrastructure, problems with affordability, and government support in the broader category of facilitating conditions. Additionally, it scrutinizes variables such as trust, performance expectations, social influences, and network externalities to identify the primary determinants influencing Nigerian consumers' propensity to adopt EVs. Results show that the percentage increase of H6 (facilitating conditions → behavioral intentions) compared to H5 (network externalities → behavioral intentions) is approximately 32.35%, indicating that traditional drivers significantly influence individuals' willingness to purchase EVs and are particularly strong factors in adoption decisions. The paper concludes with a discussion of these findings and proposes strategies for future research to further explore the barriers and drivers of EV adoption in Nigeria.
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Copyright (c) 2024 Qasim Ajao, Lanre Sadeeq, Oluwatobi Oluwaponmile Sadiq (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Qasim Ajao, Georgia Southern University, Statesboro, Georgia, USA.
Department of Electrical Engineering,
Georgia Southern University, Statesboro, Georgia, USA.
Lanre Sadeeq, Microsoft Corporation, Ontario, Canada.
Research Scholar and Subject Matter Expert,
Microsoft Corporation, Ontario, Canada.
Oluwatobi Oluwaponmile Sadiq, University of Lagos, Nigeria.
Department of Electrical Engineering,
University of Lagos, Nigeria.
Abu-Shanab, E. a. (2009). Internet banking in Jordan: An Arabic instrument validation process. Int. Arab J. Inf. Technology.
Abu-Shanab, E. a. (2013). The influence of language on research results. Management Research & Practice.
Ajao, Q. a. (2023). Drivers of Mobile Payment Acceptance: The Impact of Network Externalities in Nigeria. arXiv preprint arXiv:2305.15436.
https://doi.org/10.20944/preprints202305.1555.v1 DOI: https://doi.org/10.20944/preprints202305.1555.v1
Ajao, Q. a. (2023). Overview Analysis of Recent Developments on Self-Driving Electric Vehicles. arXiv preprint arXiv:2307.00016.
https://doi.org/10.20944/preprints202305.0248.v1 DOI: https://doi.org/10.20944/preprints202305.0248.v1
Aldhanhani, T. a. (2024). Future trends in smart green iov: Vehicle-to-everything in the era of electric vehicles. IEEE Open Journal of Vehicular Technology.
https://doi.org/10.1109/OJVT.2024.3358893 DOI: https://doi.org/10.1109/OJVT.2024.3358893
Al-Saedi, K. a.-E. (2020). Developing a general extended UTAUT model for M-payment adoption. Technology in society.
https://doi.org/10.1016/j.techsoc.2020.101293 DOI: https://doi.org/10.1016/j.techsoc.2020.101293
Attuquayefio, S. a. (2014). Using the UTAUT model to analyze students' ICT adoption. International Journal of Education and Development using ICT.
Breschi, V. a. (2022). Fostering the mass adoption of electric vehicles: A network-based approach. IEEE Transactions on Control of Network Systems.
https://doi.org/10.1109/TCNS.2022.3164969 DOI: https://doi.org/10.1109/TCNS.2022.3164969
Brislin, R. W. (1970). Back-translation for cross-cultural research. Journal of cross-cultural psychology.
https://doi.org/10.1177/135910457000100301 DOI: https://doi.org/10.1177/135910457000100301
Brown, S. A. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS quarterly.
https://doi.org/10.2307/25148690 DOI: https://doi.org/10.2307/25148690
Cheng, Y. a.-B.-K.-Y.-L.-H.-M.-M.-L. (2011). Mass absorption efficiency of elemental carbon and water-soluble organic carbon in Beijing, China. Atmospheric Chemistry and Physics.
https://doi.org/10.5194/acp-11-11497-2011 DOI: https://doi.org/10.5194/acp-11-11497-2011
Cohen, A. (1983). Comparing regression coefficients across subsamples: A study of the statistical test. Sociological Methods and Research.
https://doi.org/10.1177/0049124183012001003 DOI: https://doi.org/10.1177/0049124183012001003
Collett, K. A. (2021). Can electric vehicles be good for Sub-Saharan Africa? Energy Strategy Reviews.
https://doi.org/10.1016/j.esr.2021.100722 DOI: https://doi.org/10.1016/j.esr.2021.100722
Dwivedi, Y. K. (2011). Governance and Sustainability in Information Systems. Managing the Transfer and Diffusion of IT: IFIP WG 8.6 International Working Conference, Hamburg, Germany, September 22-24, 2011. Proceedings. Springer.
Franke, T. a. (2015). Advancing electric vehicle range displays for enhanced user experience: the relevance of trust and adaptability. Proceedings of the 7th international conference on automotive user interfaces and interactive vehicular applications.
https://doi.org/10.1145/2799250.2799283 DOI: https://doi.org/10.1145/2799250.2799283
Gicha, B. B. (2024). The electric vehicle revolution in Sub-Saharan Africa: Trends, challenges, and opportunities. Energy Strategy Reviews.
https://doi.org/10.1016/j.esr.2024.101384 DOI: https://doi.org/10.1016/j.esr.2024.101384
Hair, J. F. (2012). Multivariate data analysis. Multivariate data analysis.
https://doi.org/10.1007/978-3-642-04898-2_395 DOI: https://doi.org/10.1007/978-3-642-04898-2_395
Haruvy, E. a. (1998). Optimal product strategies in the presence of network externalities. Information Economics and Policy.
https://doi.org/10.1016/S0167-6245(98)00014-6 DOI: https://doi.org/10.1016/S0167-6245(98)00014-6
Hsu, C.-W. a.-C. (2022). What drives older adults' use of mobile registration apps in Taiwan? An investigation using the extended UTAUT model. Informatics for Health and Social Care.
https://doi.org/10.1080/17538157.2021.1990299 DOI: https://doi.org/10.1080/17538157.2021.1990299
Jen, W. a.-T. (2009). An integrated analysis of technology acceptance behaviour models: Comparison of three major models. MIS REVIEW: An International Journal.
Macedo, I. M. (2017). Predicting the acceptance and use of information and communication technology by older adults: An empirical examination of the revised UTAUT2. Computers in human behavior.
https://doi.org/10.1016/j.chb.2017.06.013 DOI: https://doi.org/10.1016/j.chb.2017.06.013
Malima, G. C. (2023). Are electric vehicles economically viable in sub-Saharan Africa? The total cost of ownership of internal combustion engine and electric vehicles in Tanzania. Transport Policy.
https://doi.org/10.1016/j.tranpol.2023.07.014 DOI: https://doi.org/10.1016/j.tranpol.2023.07.014
Purwanto, E. a. (2020). The intention and use behaviour of the mobile banking system in Indonesia: UTAUT Model. Technology Reports of Kansai University.
Qasim, H. a.-S. (2016). Drivers of mobile payment acceptance: The impact of network externalities. Information Systems Frontiers.
https://doi.org/10.1007/s10796-015-9598-6 DOI: https://doi.org/10.1007/s10796-015-9598-6
Slade, E. L. (2015). Modeling consumers' adoption intentions of remote mobile payments in the United Kingdom: extending UTAUT with innovativeness, risk, and trust. Psychology and marketing.
https://doi.org/10.1002/mar.20823 DOI: https://doi.org/10.1002/mar.20823
Un-Noor, F. a.-P. (2017). A comprehensive study of key electric vehicle (EV) components, technologies, challenges, impacts, and future direction of development. Energies. DOI: https://doi.org/10.20944/preprints201705.0090.v1
https://doi.org/10.3390/en10081217 DOI: https://doi.org/10.3390/en10081217
Venkatesh, V. a. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the association for Information Systems.
https://doi.org/10.17705/1jais.00428 DOI: https://doi.org/10.17705/1jais.00428
Venugopala, P. a. (2016). User Acceptance of Electronic Health Records: Cross Validation of Utaut Model. Global Management Review.