Predicting post-COVID-19 commuter transportation choice in greater Jakarta: A logistic regression approach to behavioral analysis and adaptation strategies

This study explores the factors influencing commuter transportation choices in Jakarta during the COVID-19 pandemic through logistic regression analysis, integrating the Theory of Planned Behavior (TPB) with Customer Satisfaction Theory to examine the impact of psychological factors, service-related aspects, and environmental awareness on public transport use. Based on a survey of 254 commuters across Greater Jakarta, the research employs a forward stepwise logistic regression approach to identify key predictors of transportation behavior. The final model demonstrates robust predictive power with a classification accuracy of 69.7% and an ROC score of 0.697, revealing that private vehicle preference and health concerns negatively influence public transport adoption, while environmental awareness and fatigue from driving positively affect modal shift intentions. The findings emphasize the necessity of both push strategies—addressing health and safety concerns—and pull strategies—enhancing public transportation attractiveness through improved reliability, comfort, and environmental messaging. The research highlights the critical need for targeted urban mobility policies that integrate health-focused and environmental messaging to promote sustainable transportation choices, particularly in rapidly urbanizing areas like Jakarta. By addressing multifaceted challenges through comprehensive approaches that combine immediate health concerns with long-term environmental benefits, policymakers can develop more resilient urban mobility systems and reduce reliance on private vehicles in the post-pandemic era.