Publications (WoS)

@article{nokey,

title = {Measuring the impact of built environment factors on station-level contributions to link-level crowding using a novel crowding contribution index},

author = {Blessy David Xavier and Varun Varghese and Makoto Chikaraishi and Akimasa Fujiwara},

url = {https://www.nature.com/articles/s41598-025-27483-y},

doi = {https://doi.org/10.1038/s41598-025-27483-y},

issn = {2045-2322},

year  = {2025},

date = {2025-12-10},

urldate = {2025-12-10},

journal = {Scientific Reports},

volume = {15},

number = {43535},

abstract = {Metro crowding undermines passenger comfort, operational efficiency and network reliability. While prior research has examined station-level and system-wide crowding, little attention has been given to quantifying how individual stations contribute to link-level overcrowding. This study addresses this gap by introducing the Crowding Contribution Index (CCI), a metric that quantifies the extent to which destination stations drive overcapacity flows on preceding links. The CCI is computed via a structured framework integrating Automated Fare Collection (AFC) and GTFS link-network data. Applied to over 80 million trips across 237 Delhi Metro stations, 142 200 hourly CCI values reveal that 46.35% of station-hours exceed capacity, with highest contributions clustered in specific stations. A Type II Tobit model assesses built-environment (BE) variables, showing that POI and intersection densities increase contributions, while POI entropy reduces them, underscoring land-use diversity’s role. Random Forest and XGBoost models corroborate these findings, ranking BE variables as the strongest CCI predictors. These insights emphasise the need for integrated land-use and transport strategies. The CCI framework offers operators a scalable tool for real-time service adjustments, such as targeted short-turns and dynamic fleet deployment, and guides planners toward sustainable, integrated land-use planning, making it especially valuable for rapidly urbanising, data-constrained cities.},

keywords = {Transit-oriented development, Transportation},

pubstate = {published},

tppubtype = {article}

}

@article{ABDULLAH2024105871,

title = {Managing transit-oriented development: A comparative analysis of expert groups and multi-criteria decision making methods},

author = {Reza Abdullah and Blessy David Xavier and Hyewon Namgung and Varun Varghese and Akimasa Fujiwara},

url = {https://www.sciencedirect.com/science/article/pii/S2210670724006954},

doi = {https://doi.org/10.1016/j.scs.2024.105871},

issn = {2210-6707},

year  = {2024},

date = {2024-01-01},

journal = {Sustainable Cities and Society},

volume = {115},

pages = {105871},

abstract = {A key challenge for transport managers and planners in sustainable development is evaluating transit facilities' performance. While Multi-Criteria Decision-Making (MCDM) tools are often used, they can be influenced by experts' subjective biases. This study applies MCDM to assess Mass Rapid Transit (MRT) stations in Jakarta, Indonesia, focusing on Transit-Oriented Development (TOD). The primary goal is to compare stakeholder perspectives and MCDM methods, complemented by a sensitivity analysis and validation with real-world smart card data. The findings reveal significant differences in criteria weighting between Indonesian and non-Indonesian experts, and between academic and non-academic experts, especially in transit connectivity and land use diversity. The study also shows variations in station rankings across different MCDM methods. Sensitivity analysis identifies transit connectivity as the most critical criterion. Simple Additive Weighting (SAW) with linear normalisation aligns well with actual usage data and shows robustness in sensitivity analysis, making it the most reliable method for TOD evaluation. The study highlights the need for continuous TOD performance monitoring and the regular collection of real-world data on ridership and TOD indicators.},

keywords = {Fuzzy AHP, Jakarta, MRT, Multi-criteria decision making, Sensitivity coefficient, Transit-oriented development},

pubstate = {published},

tppubtype = {article}

}