The role of drivers for sustainable development in the electric vehicle adoption: A two-staged structural equation modelling-artificial neural network technique

• Highlights the unique barriers and facilitators in emerging economies. • Identifies public opinion and awareness as crucial mediators. • Combines Structural Equation Modelling (SEM) with Artificial Neural Networks (ANN) to analyze linear and non-linear relationships. • Demonstrates the ANN model's 76.3 % predictive accuracy, validating the framework. Automobile technology is improving, enabling the development of electric vehicles, which are expected to replace traditional combustion-powered vehicles. The study explores the role of perceived benefits, policy interventions, public opinions, knowledge, and awareness toward using and buying electric vehicles. 434 random responses were analyzed about their intention. The study uses public opinion and awareness as mediating variables towards adopting electric vehicles with an advanced, “two-staged structural equation modelling-artificial neural network” technique. Findings suggest that the public's opinion, policy interventions, perceived benefits, and perceived risk are significantly related to buying electric vehicles. The sample includes 55.76 % male and 44.24 % female respondents. 30 % are postgraduate, 78 % are single, and 80 % live in urban. The findings will be essential for manufacturers and policymakers to formulate and implement strategies to boost electric vehicle market penetration. Based on the result, the study discussed the practical and managerial implications of adopting electric vehicles in an emerging market and provided suggestions for future directions. Source: Author created