Analysis of the factors affecting the Electric Vehicle (Two-wheeler) sales in India using Machine learning models

Abstract

The adoption of electric two wheelers in India is the result of a complex interplay involving vehicle range charging infrastructure, technological advances, government policies and consumer perception. This study investigates these factors in detail to present a comprehensive understanding of how they influence the transition to electric mobility for environmental concerns and the need for reduction in dependence on fossil fuels. Electric two wheelers are emerging as a primary solution to reduce air pollution in cities while at the same time providing low-cost transportation. most of these barriers to wide scale adoption include range anxiety, inadequate charging infrastructure, high upfront costs and perceptual differences among consumers. Vehicle range is found to be the Most important factor affecting the purchasing decision of a consumer. Range anxiety or the fear of running out of power when one cannot locate a charging station remains a big stumbling block. Consumers maintained that long range electric two wheelers would dominate and made urgent calls for the development of advanced battery technology to help alleviate this anxiety. Availability and accessibility are relevant; their impact on buying decisions is lower compared to vehicle range. In other words that would imply mere expansion of charging infrastructure cannot give sufficient fillip to the adoption unless accompanied by substantial technological advancement in batteries. The results of this study point to the view that improvement in battery technology can help Original Equipment Manufacturers improve range and reduce the range concern for electric two wheelers. Demographic differences in the perception of vehicle range, charging station, quality reliability and the possible impact of new technologies like the battery swapping and fast charging solutions are some other avenues for future research. The study mentions the use of a decision tree model to analyze factors affecting consumer choices for electric vehicles. This model helps prioritize variables such as battery range and infrastructure development by splitting decisions hierarchically based on their importance. Additionally, future research could leverage models like predictive analytics and clustering algorithms to identify consumer behavior patterns, optimize charging infrastructure, and forecast EV adoption trends based on demographic and regional data Longitudinal studies may be able to track the trends of electric two-wheeler adoptions over a period and hence yield valuable insights on changes in consumer preference and long-term effectiveness in policy interventions. In sum accelerating the pace of adoption in India will need many prongs in its approach: technological advancement infrastructural development consumer education supportive policies all coming together for sustainable and greener transport of the future.