A Study on the Impact of Perceived Benefits on Customer Preference for Electric Vehicles
Keywords:Customer Perception, EV Infrastructure, Perceived Benefits, Renewable Energy
Indian roads are currently dominated by petrol and diesel cars and bikes with only one percent of the vehicles in India being Electric Vehicles (EVs). India is not self-sufficient and it imports crude oil from other countries, which is a huge burden on the country's balance of payments. India is making efforts to adapt to the EV trend and various automobile manufacturers are taking advantage of the situation by producing and marketing EV vehicles. However, the Indian customer’s mindset is not favourable for the promotion of EV’s. Hence, an attempt has been made to identify the various aspects that influence or prevent consumers from switching from carbon-fuelled vehicles to electric vehicles. The primary data collected through a well-structured questionnaire has been analysed using Percentage Analysis and Chi- Square analysis. The study found that awareness level is not a significant factor, although awareness was considered a major factor in consumers’ preference for buying electric vehicles in earlier literature. Statistically significant results indicate that changes in ‘fuel price’, ‘environmental consciousness’ and ‘same price as petrol/diesel’ significantly influence consumers’ buying preferences for an electric vehicle.
How to Cite
Copyright (c) 2023 Catherine Nirmala J, Joyan Dsouza
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Almeida, P. R., Soares, F. J., and Lopes, J. A. P. (2013). Impacts of large-scale deployment of electric vehicles in the electric power system. Electric Vehicle Integration into Modern Power Networks, 203-249. https://doi. org/10.1007/978-1-4614-0134-6_7 DOI: https://doi.org/10.1007/978-1-4614-0134-6_7
Ashok, M. B. (2019). A study on customer perception towards E-vehicles in Bangalore. JETIR, 6, 579-588.
Das, H. S., Rahman, M. M., Li, S., and Tan, C. W. (2020). Electric vehicles standards, charging infrastructure, and impact on grid integration: A technological review. Renewable and Sustainable Energy Reviews, 120, 109618. https://doi.org/10.1016/j.rser.2019.109618 DOI: https://doi.org/10.1016/j.rser.2019.109618
Habib, S., Kamran, M., and Rashid, U. (2015). Impact analysis of vehicle-to-grid technology and charging strategies of electric vehicles on distribution networks – A review. Journal of Power Sources, 277, 205-214. https://doi.org/10.1016/j.jpowsour.2014.12.020 DOI: https://doi.org/10.1016/j.jpowsour.2014.12.020
Hawkins, T. R., Gausen, O. M., and Stromman, A. H. (2012). Environmental impacts of hybrid and electric vehicles— a review. The International Journal of Life Cycle Assessment, 17, 997-1014. https://doi.org/10.1007/ s11367-012-0440-9 DOI: https://doi.org/10.1007/s11367-012-0440-9
Kempton, W., and Letendre, S. E. (1997). Electric vehicles as a new power source for electric utilities. Transportation Research Part D: Transport and Environment, 2(3), 157- 175. https://doi.org/10.1016/S1361-9209(97)00001-1 DOI: https://doi.org/10.1016/S1361-9209(97)00001-1
Liu, L., Kong, F., Liu, X., Peng, Y., and Wang, Q. (2015). A review on electric vehicles interacting with renewable energy in smart grid. Renewable and Sustainable Energy Reviews, 51, 648-661. https://doi.org/10.1016/j. rser.2015.06.036 DOI: https://doi.org/10.1016/j.rser.2015.06.036
Liu, K., Li, Y., Hu, X., Lucu, M., and Widanage, W. D. (2019). Gaussian process regression with automatic relevance determination kernel for calendar ageing prediction of lithium-ion batteries. IEEE Transactions on Industrial Informatics, 16(6), 3767-3777. https://doi. org/10.1109/TII.2019.2941747 DOI: https://doi.org/10.1109/TII.2019.2941747
Mahmud, K., Town, G. E., Morsalin, S., and Hossain, M. J. (2018). Integration of electric vehicles and management in the internet of energy. Renewable and Sustainable Energy Reviews, 82, 4179-4203. https:// doi.org/10.1016/j.rser.2017.11.004 DOI: https://doi.org/10.1016/j.rser.2017.11.004
Manmohan, A. (2020, December). Comparison of unidirectional and bidirectional charging optimization using a composite EV load model [Conference Presentation]. CIGRE 2020, Toronto, Canada. Rahman, I., Vasant, P. M., Singh, B. S. M., Abdullah-Al-
Wadud, M., and Adnan, N. (2016). Review of recent trends in optimization techniques for a plug-in hybrid, and electric vehicle charging infrastructures. Renewable and Sustainable Energy Reviews, 58, 1039-1047. https://doi.org/10.1016/j.rser.2015.12.353 DOI: https://doi.org/10.1016/j.rser.2015.12.353
Richardson, D. B. (2013). Electric vehicles and the electric grid: A review of modeling approaches, Impacts, and renewable energy integration. Renewable and Sustainable Energy Reviews, 19, 247-254. https://doi. org/10.1016/j.rser.2012.11.042 DOI: https://doi.org/10.1016/j.rser.2012.11.042
Rout, D., Mishra, S. J., Kantha, R. K., and Pal, S. (2020). A case study on the perception of consumers of Bhubaneswar towards electric vehicles. International Journal of Research Culture Society, 4, 59-67.
Sanguesa, J. A., Torres-Sanz, V., Garrido, P., Martinez, F. J., and Marquez-Barja, J. M. (2021). A review on electric vehicles: Technologies and challenges. Smart Cities, 4(1), 372-404. https://doi.org/10.3390/smartcities4010022 DOI: https://doi.org/10.3390/smartcities4010022
Sharma, P. (2020). A study on the viewpoints of average people and EV purchase intent in India [Doctoral dissertation, Amity University].
Shuai, W., Maille, P., and Pelov, A. (2016). Charging electric vehicles in the smart city: A survey of economydriven approaches. IEEE Transactions on Intelligent Transportation Systems, 17(8), 2089-2106. https://doi. org/10.1109/TITS.2016.2519499 DOI: https://doi.org/10.1109/TITS.2016.2519499
Yong, J. Y., Ramachandaramurthy, V. K., Tan, K. M., and Mithulananthan, N. (2015). A review on the state-ofthe- art technologies of electric vehicle, its impacts and prospects. Renewable and sustainable energy reviews, 49, 365-385. https://doi.org/10.1016/j.rser.2015.04.130 DOI: https://doi.org/10.1016/j.rser.2015.04.130