Electric Vehicle Adoption: AI Driven Charging Recommendation System on Electric Vehicle (EV) adoption : A case of India

Sammanfattning

Adopting electric vehicles (EVs) reduces carbon emissions and promotes sustainable transportation. However, limited and insufficient charging stations make it hard for more people to use EVs, especially in India. Challenges such as worrying about running out of battery, uneven distribution of charging stations, and long waiting times create barriers for potential users. This study examines the factors influencing users’ intention to adopt AI-driven electric vehicle (EV) charging station recommendation systems in India, applying the Unified Theory of Acceptance and Use of Technology (UTAUT) as the guiding framework. Drawing on survey data and statistical analysis, the research finds that performance expectancy, effort expectancy, social influence, and facilitating conditions all exert significant positive effects on adoption intention, with social influence emerging as the strongest predictor. The findings underscore that while infrastructure readiness is an important enabler, the widespread uptake of AI-enabled charging solutions will depend more on perceptions of usefulness, ease of use, trust, and social legitimacy. These insights contribute to technology adoption research in emerging markets and offer actionable implications for policymakers, service providers, and developers seeking to advance smart mobility in India.