In the last half-decade, three-wheeled battery-operated vehicles (TWBoVs) have emerged as a key mode of sustainable private transport in Asia. The Indian government’s Faster Adoption and Manufacturing of Hybrid and Electric Vehicles (EVs) initiative has significantly promoted electric vehicle adoption, with sales reaching 0.34 million in 2021, primarily driven by two-wheelers and three-wheelers. This transition is vital for reducing fossil fuel dependence and environmental degradation. This study examines the total ownership costs of electric three-wheelers and diesel-powered autos in rural West Bengal, evaluating economic feasibility and environmental impact. A survey of 1,000 drivers yielded 640 valid responses. The study employs a multiple attribute decision-making approach with grey relational analysis (GRA) to prioritize three key performance indicators and develop an ownership model assessing cost efficiency, profitability, and the impact of emissions on income. The findings indicate that electric three-wheelers enhance stakeholder income by 20% while reducing CO2 emissions by 60%. The performance index reveals a strong user preference for electric three-wheelers due to lower operating costs and better profitability. Sensitivity analysis further supports these benefits. Overall, the study highlights the direct impact of ownership cost modelling in promoting clean transport in rural India by lowering emissions, boosting incomes and supporting sustainable growth.
AckaahW., KantonA. T., &; OseiK. K. (2022). Factors influencing consumers’ intentions to purchase electric vehicles in Ghana. Transportation Letters, 14(9), 1031–1042.
2.
Al-AlawiB. M., &; BradleyT. H. (2013). Total cost of ownership, payback, and consumer preference modeling of plug-in hybrid electric vehicles. Applied Energy, 103, 488–506.
3.
AndersonE. (1995). Inequality reexamined, Sen Amartya. Harvard University Press, 1992, 207+ xiv pages. Economics &; Philosophy, 11(1), 182–189.
4.
AndroniceanuA., &; GeorgescuI. (2023). The impact of CO2 emissions and energy consumption on economic growth: A panel data analysis. Energies, 16(3), 1342.
5.
AroraS. C., SharmaM., &; SinghV. K. (2023). Using diffusion of innovation framework with attitudinal factor to predict the future of mobility in the Indian market. Environmental Science and Pollution Research, 30(44), 98655–98670. https://doi.org/10.1007/s11356-022-23149-8
6.
AtallaT., &; BeanP. (2017). Determinants of energy productivity in 39 countries: An empirical investigation. Energy Economics, 62, 217–229. https://doi.org/10.1016/j.eneco.2016.12.003
7.
AyetorG. K., MbonigabaI., &; MasheleJ. (2023). Feasibility of electric two and three-wheelers in Africa. Green Energy and Intelligent Transportation, 2(4), 100106.
8.
BasJ., ZouZ., &; CirilloC. (2023). An interpretable machine learning approach to understanding the impacts of attitudinal and ridesourcing factors on electric vehicle adoption. Transportation Letters, 15(1), 30–41.
9.
BeraR., &; MaitraB. (2019). Identification of priority attributes influencing the choice of plug-in hybrid electric vehicle in Indian megacities. Journal of the Eastern Asia Society for Transportation Studies, 13, 678–697.
10.
BonsuN. O. (2020). Towards a circular and low-carbon economy: Insights from the transitioning to electric vehicles and net zero economy. Journal of Cleaner Production, 256, 120659.
11.
BrückmannG., WillibaldF., &; BlancoV. (2021). Battery electric vehicle adoption in regions without strong policies. Transportation Research Part D: Transport and Environment, 90, 102615. https://doi.org/10.1016/j.trd.2020.102615
12.
CabraalR. A., BarnesD. F., &; AgarwalS. G. (2005). Productive uses of energy for rural development. Annual Review of Environment and Resources, 30(1), 117–144.
13.
ChenD., ChenT., &; FengY. (2024). Comprehensive CO2 emissions analysis and optimization of plug-in hybrid electric vehicles. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 238(7), 2039–2054.
14.
ChhikaraR., GargR., ChhabraS., KarnatakU., &; AgrawalG. (2021). Factors affecting adoption of electric vehicles in India: An exploratory study. Transportation Research Part D: Transport and Environment, 100, 103084.
15.
ContestabileM., OfferG. J., SladeR., JaegerF., &; ThoennesM. (2011). Battery electric vehicles, hydrogen fuel cells and biofuels. Which will be the winner?Energy &; Environmental Science, 4(10), 3754–3772. https://doi.org/10.1039/c1ee01804c
16.
DanielisR., GiansoldatiM., &; ScorranoM. (2019). Consumer and society oriented cost of ownership of electric and conventional cars in Italy. Società Italiana di Economia dei Trasporti e della Logistica (SIET).
17.
DesreveauxA., HittingerE., BouscayrolA., CastexE., &; SirbuG. M. (2020). Techno-economic comparison of total cost of ownership of electric and diesel vehicles. IEEE Access, 8, 195752–195762.
18.
EggersF., &; EggersF. (2011). Where have all the flowers gone? Forecasting green trends in the automobile industry with a choice-based conjoint adoption model. Technological Forecasting and Social Change, 78(1), 51–62.
19.
FengP., CuiL., XuT., LiuX., &; ZhangE. (2018). Research on electric vehicle entry control strategy based on different scenarios. In IOP conference series: Earth and environmental science (Vol. 170, p. 042120). IOP Publishing.
20.
FuS., &; FuH. (2021). A method to predict electric vehicles’ market penetration as well as its impact on energy saving and CO2 mitigation. Science Progress, 104(3), 00368504211040286.
21.
GIZ, NITI Aayog, &; Deloitte. (2021). Status quo analysis of various segments of electric mobility and low carbon passenger road transport in India.
22.
GoetzkeF., &; WeinbergerR. (2012). Separating contextual from endogenous effects in automobile ownership models. Environment and Planning A, 44(5), 1032–1046.
23.
HagmanJ., &; LangbroekJ. H. (2019). Conditions for electric vehicle taxi: A case study in the Greater Stockholm region. International Journal of Sustainable Transportation, 13(6), 450–459. https://doi.org/10.1080/15568318.2018.1481547
24.
HagmanJ., RitzénS., &; StierJ. J. (2017). The TCO paradox—A key problem in the diffusion of energy efficient vehicles?American Journal of Industrial and Business Management, 7(12), 1267. https://doi.org/10.4236/ajibm.2017.712090
25.
HagmanJ., RitzénS., StierJ. J., &; SusiloY. (2016). Total cost of ownership and its potential implications for battery electric vehicle diffusion. Research in Transportation Business &; Management, 18, 11–17. https://doi.org/10.1016/j.rtbm.2016.01.003
26.
HaldarS., MandalR., &; MondalA. (2019). Impact of clean transportation systems in rural economy: A study. In AIP conference proceedings (Vol. 2091). AIP Publishing. https://doi.org/10.1063/1.5096504
27.
HaldarS., MondalS., MondalA., &; BanerjeeR. (2020). Battery management system using state of charge estimation: An IOT based approach. In 2020 national conference on emerging trends on sustainable technology and engineering applications (NCETSTEA) (pp. 1–5). IEEE. https://doi.org/10.1109/NCETSTEA48365.2020.9119945
28.
HarrisonG., &; ThielC. (2017). An exploratory policy analysis of electric vehicle sales competition and sensitivity to infrastructure in Europe. Technological Forecasting and Social Change, 114, 165–178. https://doi.org/10.1016/j.techfore.2016.08.007
29.
HeZ., ZhouY., ChenX., WangJ., ShenW., WangM., &; LiW. (2022). Examining the spatial mode in the early market for electric vehicles adoption: Evidence from 41 cities in China. Transportation Letters, 14(6), 640–650. https://doi.org/10.1080/19427867.2021.1917217
30.
HossainM. A., &; ChenS. (2021). Nexus between Human Development Index (HDI) and CO2 emissions in a developing country: Decoupling study evidence from Bangladesh. Environmental Science and Pollution Research, 28, 58742–58754. https://doi.org/10.1007/s11356-021-14822-5
31.
HossainM. S., KumarL., IslamM. M., &; SelvarajJ. (2022). A comprehensive review on the integration of electric vehicles for sustainable development. Journal of Advanced Transportation, 2022(1), 3868388.
32.
HuY., WangZ., &; LiX. (2020). Impact of policies on electric vehicle diffusion: An evolutionary game of small world network analysis. Journal of Cleaner Production, 265, 121703. https://doi.org/10.1016/j.jclepro. 2020.121703
33.
IbitoyeF. I. (2013). The millennium development goals and household energy requirements in Nigeria. SpringerPlus, 2, 1–9. https://doi.org/10.1186/2193-1801-2-529
34.
International Energy Agency. (2020a). Tracking transport 2020[WWW document]. https://www.iea.org/reports/tracking-transport-2020
35.
International Energy Agency (IEA). (2020b). Global EV outlook 2020. International Energy Agency. Retrieved fromhttps://www.iea.org/reports/global-ev-outlook-2020
36.
IEA. (2024). Global EV outlook 2024. https://www.iea.org/reports/global-ev-outlook-2024
37.
JiangH. D., XueM. M., LiangQ. M., MasuiT., &; RenZ. Y. (2022). How do demand-side policies contribute to the electrification and decarburization of private transportation in China? A CGE-based analysis. Technological Forecasting and Social Change, 175, 121322.
38.
KanagawaM., &; NakataT. (2007). Analysis of the energy access improvement and its socio-economic impacts in rural areas of developing countries. Ecological Economics, 62(2), 319–329. https://doi.org/10.1016/j.ecolecon. 2006.06.005
39.
KempR., &; VolpiM. (2008). The diffusion of clean technologies: A review with suggestions for future diffusion analysis. Journal of Cleaner Production, 16(1), S14–S21. https://doi.org/10.1016/j.jclepro.2007.10.019
40.
KhuranaA., KumarV. R., &; SidhpuriaM. (2020). A study on the adoption of electric vehicles in India: The mediating role of attitude. Vision, 24(1), 23–34. https://doi.org/10.1177/0972262919875548
41.
KromerM. A., &; HeywoodJ. B. (2009). A comparative assessment of electric propulsion systems in the 2030 US light-duty vehicle fleet. SAE International Journal of Engines, 1(1), 372–391. https://doi.org/10.4271/ 2008-01-0459
42.
KumarP., &; ChakrabartyS. (2020). Total cost of ownership analysis of the impact of vehicle usage on the economic viability of electric vehicles in India. Transportation Research Record, 2674(11), 563–572.
43.
LaneB., &; PotterS. (2007). The adoption of cleaner vehicles in the UK: Exploring the consumer attitude–action gap. Journal of Cleaner Production, 15(11–12), 1085–1092. https://doi.org/10.1016/j.jclepro.2006.05.026
44.
LebeauK., LebeauP., MacharisC., &; Van MierloJ. (2013, November). How expensive are electric vehicles? A total cost of ownership analysis. In 2013 world electric vehicle symposium and exhibition(EVS27) (pp.1–12). Barcelona, Spain: IEEE.
45.
LiW., LongR., ChenH., &; GengJ. (2017). A review of factors influencing consumer intentions to adopt battery electric vehicles. Renewable and Sustainable Energy Reviews, 78, 318–328.
46.
LikertR. (1932). A technique for the measurement of attitudes. Archives of Psychology, 22(140), 55.
47.
LinB., &; AhmadI. (2017). Analysis of energy related carbon dioxide emission and reduction potential in Pakistan. Journal of Cleaner Production, 143, 278–287. https://doi.org/10.1016/j.jclepro.2016.12.113
48.
LinB., &; WuW. (2021). The impact of electric vehicle penetration: A recursive dynamic CGE analysis of China. Energy Economics, 94, 105086.
49.
LionelloM., AlettaF., MitchellA., &; KangJ. (2021). Introducing a method for intervals correction on multiple Likert scales: A case study on an urban soundscape data collection instrument. Frontiers in Psychology, 11, 602831.
50.
LunaT. F., Uriona-MaldonadoM., SilvaM. E., &; VazC. R. (2020). The influence of e-carsharing schemes on electric vehicle adoption and carbon emissions: An emerging economy study. Transportation Research Part D:Transport and Environment, 79, 102226. https://doi.org/10.1016/j.trd.2020.102226
51.
ModiV., McDadeS., LallementD., &; SaghirJ. (2005). Energy services for the Millennium Development Goals. The International Bank for Reconstruction and Development/The World Bank/ESMAP.
52.
MoonS., &; LeeD. J. (2019). An optimal electric vehicle investment model for consumers using total cost of ownership: A real option approach. Applied Energy, 253, 113494.
53.
MurthyU., ShaariM. S., MariadasP. A., &; AbidinN. Z. (2021). The relationships between CO2 emissions, economic growth and life expectancy. The Journal of Asian Finance, Economics and Business, 8(2), 801–808.
54.
NITI Aayog. (2017). Changing structure of rural economy of India implications for employment and growth. National Institution for Transforming India, Government of India.
55.
NITI Aayog. (2022, May). Promoting clean energy usage through accelerated localization of e-mobility value chain. https://www.niti.gov.in/sites/default/files/2023-07/Niti-Aayog_Report-VS_compressed_compressed.pdf
56.
OnyegiriI. E., &; OkeS. A. (2017). A grey relational analytical approach to safety performance assessment in an aviation industry of a developing country. Engineering and Applied Science Research, 44(1), 1–15.
57.
OuyangD., ZhouS., &; OuX. (2021). The total cost of electric vehicle ownership: A consumer-oriented study of China’s post-subsidy era. Energy Policy, 149, 112023.
58.
PandeyA., &; VenkataramanC. (2014). Estimating emissions from the Indian transport sector with on-road fleet composition and traffic volume. Atmospheric Environment, 98, 123–133. https://doi.org/10.1016/j.atmosenv.2014.08.039
59.
PettiforH., WilsonC., AxsenJ., AbrahamseW., &; AnableJ. (2017). Social influence in the global diffusion of alternative fuel vehicles—A meta-analysis. Journal of Transport Geography, 62, 247–261. https://doi.org/10.1016/j.jtrangeo.2017.06.009
60.
PotoglouD., WhittleC., TsourosI., &; WhitmarshL. (2020). Consumer intentions for alternative fuelled and autonomous vehicles: A segmentation analysis across six countries. Transportation Research Part D: Transport and Environment, 79, 102243. https://doi.org/10.1016/j.trd.2020.102243
61.
PradeepV. H., AmshalaV. T., &; KadaliB. R. (2021). Does perceived technology and knowledge of maintenance influence purchase intention of BEVs. Transportation Research Part D: Transport and Environment, 93, 102759. https://doi.org/10.1016/j.trd.2021.102759
62.
PriyeS., &; ManojM. (2020). Exploring usage patterns and safety perceptions of the users of electric three-wheeled paratransit in Patna, India. Case Studies on Transport Policy, 8(1), 39–48.
63.
PriyeS., ManojM., &; RanjanR. (2021). Understanding the socioeconomic characteristics of paratransit drivers and their perceptions toward electric three-wheeled rickshaws in Delhi, India. IATSS Research, 45(3), 357–370.
64.
RathiA. (2024). India’s rural economy outpaces urban growth, driven by government spending: Report. IndBiz, Economic Diplomacy Division, Government of India. https://indbiz.gov.in/indias-rural-economy-outpaces- urban-growth-driven-by-government-spending-report
65.
RayS., GhoshB., BardhanS., &; BhattacharyyaB. (2016). Studies on the impact of energy quality on human development index. Renewable Energy, 92, 117–126.
66.
RietmannN., HüglerB., &; LievenT. (2020). Forecasting the trajectory of electric vehicle sales and the consequences for worldwide CO2 emissions. Journal of Cleaner Production, 261, 121038.
67.
SadhukhanS., BanerjeeU. K., &; MaitraB. (2015). Commuters’ perception towards transfer facility attributes in and around metro stations: Experience in Kolkata. Journal of Urban Planning and Development, 141(4), 04014038.
68.
SadhukhanS., BanerjeeU. K., &; MaitraB. (2018). Preference heterogeneity towards the importance of transfer facility attributes at metro stations in Kolkata. Travel Behaviour and Society, 12, 72–83.
69.
SaxenaS. N. (2019). Revolution in growth of three-wheeler electric vehicles in India providing job opportunities to semi-skilled and unskilled people. Journal of Global Tourism Research, 4(2), 117–126.
70.
SharmaR. B., &; MaitraB. (2024). Methodological approach to obtain key attributes affecting the adoption of plug-in hybrid electric vehicle. Case Studies on Transport Policy, 16, 101165.
71.
SinghS., JindelJ., TikkiwalV. A., VermaM., GuptaA., NegiA., &; JainA. (2022). Electric vehicles for low-emission urban mobility: Current status and policy review for India. International Journal of Sustainable Energy, 41(9), 1323–1359.
72.
SinhaS., SadhukhanS., &; PriyeS. (2017). The role of quality assessment for development of sustainable bus service in mid-sized cities of India: A case study of Patna. Procedia Engineering, 198, 926–934.
73.
SinghV., SinghV., &; VaibhavS. (2020). A review and simple meta-analysis of factors influencing adoption of electric vehicles. Transportation Research Part D: Transport and Environment, 86, 102436.
74.
SternD. I. (2011). The role of energy in economic growth. Annals of the New York Academy of Sciences, 1219(1), 26–51.
75.
StrubenJ., &; StermanJ. D. (2008). Transition challenges for alternative fuel vehicle and transportation systems. Environment and Planning B: Planning and Design, 35(6), 1070–1097. https://doi.org/10.2139/ssrn.881800
76.
SyedA. A., GuptaS., &; RaiD. (2021). Psychological, social and economic impact of COVID-19 on the working population of India: Exploratory factor analysis approach. International Journal of Disaster Risk Reduction, 66, 102617.
77.
TareiP. K., ChandP., &; GuptaH. (2021). Barriers to the adoption of electric vehicles: Evidence from India. Journal of Cleaner Production, 291, 125847. https://doi.org/10.1016/j.jclepro.2021.125847
78.
TiwariG. (2011). Key mobility challenges in Indian cities[Discussion paper]. International Transport Forum.
79.
TRW. (2021). Road transport year book (2017–18 &; 2018–19). Ministry of Road Transport &; Highways. Government of India.
80.
VaidyaO. S., &; KumarS. (2006). Analytic hierarchy process: An overview of applications. European Journal of Operational Research, 169(1), 1–29.
81.
WuH. H. (2002). A comparative study of using grey relational analysis in multiple attribute decision making problems. Quality Engineering, 15(2), 209–217.
82.
WuG., InderbitzinA., &; BeningC. (2015). Total cost of ownership of electric vehicles compared to conventional vehicles: A probabilistic analysis and projection across market segments. Energy Policy, 80, 196–214.
