Active-Flow Campus: Translating Participatory Evidence, Topography, and Spatial Legibility into a Smart Bicycle-Sharing Network Framework


YILMAZ N., Çelik E. Y., Turhan A.

Sustainability (Switzerland), cilt.18, sa.19, 2026 (SCI-Expanded, SSCI, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 18 Sayı: 19
  • Basım Tarihi: 2026
  • Doi Numarası: 10.3390/su181910225
  • Dergi Adı: Sustainability (Switzerland)
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, CAB Abstracts, Geobase, INSPEC
  • Anahtar Kelimeler: active mobility, bicycle-sharing system, electric bicycles, geographic information systems (GIS), participatory planning, smart campus, spatial legibility, sustainable campus mobility
  • Çukurova Üniversitesi Adresli: Evet

Özet

Large university campuses often remain dependent on internal motorised transport. This study develops the Active-Flow Campus framework for a docked (station-based) bicycle-sharing network at Çukurova University, combining a cross-sectional survey of 304 students, network analysis on the university’s topographic survey map, and a spatial-legibility audit. One respondent (0.3%) reported the bicycle as their main internal mode, whereas 70.1% stated willingness to cycle given safe, continuous infrastructure. Perceived time-saving and access-time burden were positively associated with cycling intention and negatively with perceived topographic difficulty; these associations are not causal, as the predictors and outcomes share one instrument. Phase 1 stations were selected by exhaustive optimisation: the chosen five represent at least one requested location for 295 respondents (97.0%), against 280 under a threshold rule, at equal indicative cost. Minimax-grade route analysis showed that links to the dormitory, main entrance, and southern academic stations exceed a 5% sustained grade, so electrical assistance is needed there from the first phase. Even with all eight candidates, only 65.5% of respondent-weighted faculty demand is within 500 m network distance of a station, showing where the candidate set needs extension.