Decoding acceptance of driver monitoring systems: Evaluating alternative measurement models, cross-country variations, and behavioural intention

Abstract

Driver monitoring systems (DMS) demonstrate significant potential for enhancing road safety. It is imperative to comprehend potential users’ attitudes towards DMS to optimise their benefits and increase public acceptance. This study investigates potential users’ acceptance of DMS in conditionally automated driving systems (SAE level 3) by evaluating alternative measurement models and assessing cross-country variations across nine countries (i.e., Germany, Spain, France, Japan, Poland, Sweden, the United Kingdom, the United States, and China). Utilising survey data from 9025 drivers, we compared the principal component analysis and the four models (a single-factor model, a six factors model, a two higher-order factors model, and a two lower-order factors model) via structural equation modelling. A model with two correlated factors, General Acceptance and Concerns, emerged as the optimal solution with high reliability across constructs. Significant cross-country differences in all constructs were found, although only 0.3% of the variance in behavioural intention was attributable to country-level differences. A linear mixed model demonstrated that the general acceptance factor positively related to behavioural intention, whereas concerns had a small but significant negative effect. The implications for research and practice suggest that while individual-level perceptions are paramount, country context also plays a role, albeit a modest one, in shaping users’ willingness to adopt DMS technologies.