Promoting green travel behaviour is essential for advancing sustainable urban mobility. This study explores the behavioural, perceptual, and socio-demographic factors that influence individuals’ adoption of environmentally friendly travel modes. Drawing on structured survey data, two outcomes were analysed: (1) self-reported frequency of green travel and (2) scenario-based willingness to switch to green transport options. To address multicollinearity and enhance model interpretability, both binary logistic and multinomial logistic regression techniques were employed across reduced variable sets. Significant predictors include infrastructure quality (e.g., road and parking conditions), perceived accessibility, travel time sensitivity, health-related motivations, and demographic attributes such as age, income, and bike ownership. The models demonstrate strong predictive performance according to standard statistical evaluation indicators. Findings underscore the importance of both contextual infrastructure and individual-level factors in shaping sustainable travel behaviour. This dual modelling framework offers actionable insights for urban planners and policymakers aiming to promote green mobility through user-centric design and targeted behavioural interventions.
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