Abstract
While theoretically High-Speed Rail (HSR) should stimulate local development, in practice, the emergence of prosperous HSR-driven new towns is not always guaranteed. A depth and comprehensive exploration of determinants of HSR new town development, especially station-district conditions, is lacking. Using a dataset of newly constructed HSR stations in China for the period 2009–2019, we employ an interpretable model combining Gradient Boosting Decision Tree (GBDT) and SHapley Additive exPlanations (SHAP) to explore how macro-level urban development, the meso-level HSR station-district conditions, and the micro-level HSR station environment influence HSR station area development. The results indicate that travel convenience to HSR station and station location significantly enhance the development of HSR new towns. Public transit lines and metro have positive effects, and the distances to the city center or pre-existing station exhibit negative impacts. We also identify an inverse relationship that urban and station-district economic levels drive HSR new town development. What's more, we identify the nonlinear and threshold effects and analyze the interactive effects of different influencing factors. These findings offer new perspectives on the promotion of the efficient development of HSR new towns.
| Original language | English |
|---|---|
| Pages (from-to) | 241-253 |
| Number of pages | 13 |
| Journal | Transport Policy |
| Volume | 159 |
| DOIs | |
| State | Published - Dec 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- GBDT
- HSR new town
- Influencing factors
- Nighttime lighting data
- Station location
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