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Evaluating multimodal travel choices through MGWR: insights from the Ankara-Istanbul corridor

  • İsmail Adalıoğlu*
  • , Murat Ergün
  • *Corresponding author for this work
  • Istanbul Technical University
  • Yalova University

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

This study examines multimodal transportation choices along the high-demand Ankara–Istanbul corridor using Multiscale Geographically Weighted Regression (MGWR) to capture spatial heterogeneity in travel behavior. Focusing on total travel time as the dependent variable, the analysis incorporates access and trip durations for buses, high-speed rail, and air travel, excluding private vehicle use. The MGWR framework reveals four key findings: (1) Terminal access time is a crucial determinant, with shorter access durations favoring specific modes; (2) Socio-economic factors significantly influence mode choice, as higher-income travelers predominantly opt for air travel, while older individuals demonstrate a preference for bus services; (3) Weather conditions and travel frequency exhibit spatially varying effects, with frequent travelers showing a strong inclination toward rail transport; and (4) The accessibility gap between Ankara and Istanbul underscores the need for targeted infrastructure improvements, particularly in airport and rail connectivity. These findings highlight the importance of spatially adaptive policy interventions. Enhancing rail accessibility in Ankara and optimizing airport connectivity in Istanbul could mitigate regional disparities in travel efficiency. Overall, the results underscore the necessity for spatially nuanced policy interventions and demonstrate the utility of MGWR in formulating integrated, user-centric multimodal transportation strategies.

Original languageEnglish
Article number101045
JournalTravel Behaviour and Society
Volume40
DOIs
Publication statusPublished - Jul 2025

Bibliographical note

Publisher Copyright:
© 2025 Hong Kong Society for Transportation Studies

Keywords

  • Multi-modal transportation
  • Multiscale geographically weighted regression (MGWR)
  • Travel behavior

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