Determining ergonomics-based sustainability for public utility vehicles: integrating higher-order structural equation modelling and random forest classifier

Ergonomics-based sustainability (EBS) in public utility vehicles (PUVs) requires an integrated approach that balances environmental, social and economic factors while enhancing commuter and driver well-being. This study develops an EBS framework for PUVs in the Philippines by integrating higher-order structural equation modelling (H-SEM) and the random forest classifier (RFC). Analysing 350 survey responses, results indicated that environmental sustainability, particularly pollution reduction and energy efficiency, had the greatest influence on overall sustainability. Social dimensions, such as driver well-being and vehicle safety, were also critical, while economic factors like affordability and investment played a supporting role. The RFC model highlighted immediate operational concerns, emphasising safety and usability, which complement SEM’s long-term sustainability insights. This study provides a data-driven framework for policymakers and transport planners to improve PUV ergonomics, enhance commuter satisfaction and promote sustainable mobility, with adaptability for global applications in EBS.