Understanding Individuals’ Continuance Intention to Use Advanced Driver Assistance Systems: An Integrated Application of Partial Least Squares Structural Equation Modeling and Necessary Condition Analysis

Abstract

This study aimed to understand the factors that influence individuals’ intention to continue using advanced driver assistance systems (ADASs) through an integrated approach that extends the technology acceptance model (TAM). First, perceived safety, perceived quality, and satisfaction were incorporated into the traditional TAM framework as additional constructs to address the complexities of ADAS usage. Second, an approach that combines partial least squares structural equation modeling (PLS-SEM) and necessary condition analysis (NCA) was employed to identify both the sufficient and necessary conditions for the continuous intention to use ADASs. This combined approach was directed toward data collected from 843 drivers hailing from the Greater Bay Area of China and experienced with ADAS usage. The findings revealed that perceived usefulness, perceived quality, perceived safety, and satisfaction significantly influenced continuance intention, while perceived ease of use indirectly affected it through perceived usefulness and satisfaction. This study underscores the paramount importance of safety and quality perceptions in ADAS adoption and offers practical insights that can help product design and marketing professionals enhance the acceptance and sustained use of ADAS technologies.