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<p>The growing complexity of urban infrastructure planning necessitates decision-support tools capable of managing conflicting objectives while incorporating behavioural dynamics. This study proposes a hybrid framework that integrates travel behaviour modelling with Multi-Criteria Decision-Making (MCDM) techniques to prioritise Transit-Oriented Development (TOD) zones. Structural Equation Modelling (SEM) is employed to quantify behavioural relationships, and the resulting path coefficients are systematically integrated into the Fuzzy Best–Worst Method (FBWM) to derive behaviourally enriched criteria weights, which are subsequently used in Fuzzy TOPSIS for zone ranking. The empirical analysis is based on a primary survey of 520 commuters across four major TOD zones in Delhi. The results indicate that Perceived Accessibility significantly influences Travel Behaviour Intention (β = 0.42), while both Environmental Concern (β = 0.31) and behavioural intention (β = 0.38) affect Actual Usage Behaviour. Incorporating these behavioural effects into the MCDM framework leads to a prioritisation where Anand Vihar Intermodal Hub and Karkardooma Metro Station emerge as the highest-ranked zones, followed by Sarai Kale Khan Intermodal Hub and Mukundpur Metro Station. Sensitivity analysis confirms the robustness of the ranking outcomes under varying weighting scenarios. The study focuses on four TOD zones, ensuring methodological consistency and eliminating ambiguity in ranking outcomes. The study introduces a behaviourally enriched decision-support framework in which SEM-derived constructs directly inform fuzzy MCDM weighting. The proposed model offers a scalable and replicable tool for TOD prioritisation in rapidly urbanising cities.</p>

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Integrating multi-criteria decision-making and travel behaviour modelling for prioritising transit-oriented development zones in urban infrastructure planning

  • 期刊论文

  • 发表日期：

    2026年7月20日

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  • Shashikant Nishant Sharma,
  • Kavita Dehalwar

摘要

The growing complexity of urban infrastructure planning necessitates decision-support tools capable of managing conflicting objectives while incorporating behavioural dynamics. This study proposes a hybrid framework that integrates travel behaviour modelling with Multi-Criteria Decision-Making (MCDM) techniques to prioritise Transit-Oriented Development (TOD) zones. Structural Equation Modelling (SEM) is employed to quantify behavioural relationships, and the resulting path coefficients are systematically integrated into the Fuzzy Best–Worst Method (FBWM) to derive behaviourally enriched criteria weights, which are subsequently used in Fuzzy TOPSIS for zone ranking. The empirical analysis is based on a primary survey of 520 commuters across four major TOD zones in Delhi. The results indicate that Perceived Accessibility significantly influences Travel Behaviour Intention (β = 0.42), while both Environmental Concern (β = 0.31) and behavioural intention (β = 0.38) affect Actual Usage Behaviour. Incorporating these behavioural effects into the MCDM framework leads to a prioritisation where Anand Vihar Intermodal Hub and Karkardooma Metro Station emerge as the highest-ranked zones, followed by Sarai Kale Khan Intermodal Hub and Mukundpur Metro Station. Sensitivity analysis confirms the robustness of the ranking outcomes under varying weighting scenarios. The study focuses on four TOD zones, ensuring methodological consistency and eliminating ambiguity in ranking outcomes. The study introduces a behaviourally enriched decision-support framework in which SEM-derived constructs directly inform fuzzy MCDM weighting. The proposed model offers a scalable and replicable tool for TOD prioritisation in rapidly urbanising cities.