Understanding the non-users’ acceptability of autonomous vehicle hailing services using SEM-ANN-NCA approach

Abstract

Autonomous vehicle hailing services (AVHSs) incorporate automated technology and shared mobility, resulting in a significant shift in human mobility. To popularize AVHSs, this research aims to develop a conceptual model based on the stimulus-organism-response paradigm to comprehend the formation mechanism of the non-users’ acceptability. Partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN) were applied to capture the linear and nonlinear relationships among factors of the conceptual model. With “sufficiency logic” and “necessity logic”, PLS-SEM and necessary condition analysis (NCA) were used to determine “must have” and “should have” factors. The empirical analysis revealed that government support, information publicity, and social influence positively have different degrees of influence on perceived usefulness, perceived ease of use, and perceived safety, then influencing the acceptability of AVHSs. In addition, perceived usefulness, perceived ease of use, and perceived safety are both “must have” and “should have” factors for acceptability. The research findings help policymakers and business practitioners determine the marketing promotion priorities for AVHSs.