E-scooter dynamics in a tourism-driven city
Exploring spatiotemporal patterns and nonlinear effects of the built environment in Antalya, Türkiye
Bibliographic Data
| ID | 21233477 |
|---|---|
| Authors | Vaghar Bahojb Ghodsi (0000-0003-1219-5282, TU Wien), Nima Dadashzadeh (0000-0001-5425-0572, University of Huddersfield, corresponding author) |
| Year | 2025 |
| Volume | 132 |
| Pages | 106801 |
| Publication date | 2025-09-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sustainable Cities and Society (JOURNAL) |
| Journal identifiers | ISSN: 2210-6707 • E-ISSN: 2210-6715 |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.scs.2025.106801 |
| OpenAlex | W4414042302 |
| Language | EN |
| Citations received | 2 |
| References cited | 43 |
One of the first studies on e-scooter use in a tourism-driven city. • Seasonal spatiotemporal e-scooter use patterns identified. • Summer: tourism trips dominate in coastal and residential zones. • Winter: educational and residential trips are more prevalent. • Key drivers: land use, intersection count, and bus accessibility. Exploring the travel behavior of e-scooter users and the relationship between the built environment and e-scooter usage helps urban planners and policymakers to allocate urban resources efficiently and meet demand. To the best of our knowledge, this study presents one of the first empirical evidence focusing on e-scooter usage in a tourism-driven city. It explores the nonlinear and threshold effects of the built environment on e-scooter usage using a machine learning technique, i.e., Gradient Boosted Regression Trees (GBRT). To this end, it examines extensive 8-month trajectory records of 16,480 e-scooter trips in Antalya, Türkiye. Trips were recorded mainly in the southwest part of Antalya, specifically along the coastline. In summer, e-scooter is primarily used for tourism in coastal and residential areas, while in winter for educational and residential purposes. Besides, e-scooter usage was impacted negatively by temperature and rain. People tend to ride e-scooters mainly in the evening during the summer and at midday during the winter season. The results indicate that the most influential factors on e-scooter usage were recorded as educational and touristic/offshore land use variables, residential area land use, intersection count, and bus accessibility, with respective 42 %, 24 %, 8.08 %, 5 %, and 4 % contributions. The results of this research can be useful for transportation policies over dockless e-scooter usage in port and touristic cities such as Antalya
Built environment · Empirical research · Evening · Land use · Tourism · Trajectory · TRIPS architecture · Human Mobility and Location-Based Analysis · Urban Design and Spatial Analysis · Urban Transport and Accessibility
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Multicollinearity
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Greedy function approximation
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Spatial analysis of shared e-scooter trips
Spatial variations in urban public ridership derived from GPS trajectories and smart card data
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Influence of the built environment on E-scooter sharing ridership
Nonlinear and threshold effects of the built environment on e-scooter sharing ridership
Free-floating e-scooter usage in urban areas
How the built environment affects E-scooter sharing link flows
Socially Sustainable Mobility as a Service (MaaS)
Gender roles in sustainable mobility
| Citations per year | 2 |
|---|---|
| Citation span | 2025 - 2026 (2) |
| Highly cited | No |