The changing adoption behaviors on electric trucks over time during the intention-purchase stage: Insights from freight enterprises’ states and perception features

Abstract

This study analyzed the possibility and time gap in the adoption of electric trucks during the intention-purchase stage. An online survey was conducted with 980 freight fleets in Zhejiang Province, China in May 2021. The survival analysis model was employed to integrate the time variable with the probability of purchase, and various state and perception features that significantly influenced adoption behaviors were identified. The predictive performance of the model was assessed using the C-index and by comparing the results with actual purchase data. The findings indicated that positive state factors effectively reduce the time to purchase during the intention-behavior stage, while negative perception factors substantially decrease the ultimate purchase probability. Specifically, enterprises offering bulk services experienced a 10% increase in their purchase probability during the second year. Conversely, a negative perception of overall profit and empty-running reduction resulted in a 59.5% and 68.5% reduction in the purchase probability, respectively. The model demonstrated good predictive accuracy, particularly for short time periods of less than two years. This research has important implications for mitigating bias in intention survey data, providing policymakers with new incentives derived from the business environment, and facilitating the transition to electric trucks in freight transportation for cleaner production.