Slow motion in corona times: Modeling cyclists’ spatial choice behavior using real-time probe data

Kourtit K., Osth J., Nijkamp P., Türk U.

Journal of Transport and Land Use, cilt.17, sa.1, ss.805-826, 2024 (SSCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 17 Sayı: 1
  • Basım Tarihi: 2024
  • Doi Numarası: 10.5198/jtlu.2024.2398
  • Dergi Adı: Journal of Transport and Land Use
  • Derginin Tarandığı İndeksler: Social Sciences Citation Index (SSCI), Scopus, Directory of Open Access Journals
  • Sayfa Sayıları: ss.805-826
  • Anahtar Kelimeler: bicycles, COVID-19, real-time probe data, sensors, Shapley decomposition, Slow motion, spatial autocorrelation, spatial regression, volunteered geographical information
  • Abdullah Gül Üniversitesi Adresli: Evet

Özet

The recent COVID-19 pandemic has provided a renewed impetus for empirical research on slow and active modes of transportation, specifically bicycling and walking. Changes in modal choice appear to be sensitive to the actual quality of the environment, the attractive land use and built environment conditions, and the ultimate destination choice. This study examines and models the influence of cyclists’ health concerns during the pandemic on their spatial destination and route choices. Using a large real-time dataset on the individual daily mobility of cyclists in the province of Utrecht, the Netherlands, collected through GPS-linked sensors on bikes (VGI, or volunteered geographical information), the analysis employs spatial regression models, Shapley decomposition techniques, and spatial autocorrelation methods to unveil the backgrounds of changes in spatial behavior. The results reveal that the perceived wellbeing benefits of bicycling in green areas during the pandemic have significantly influenced cyclists’ choice behavior, in particular route and destination choice.