Identifying implementation-oriented models of urban underground space development in China based on fuzzy-set qualitative comparative analysis (fsQCA)

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Author(s)

  • Wei-Xi Wang
  • Fang-Le Peng
  • Chen-Xiao Ma
  • Yun-Hao Dong

Detail(s)

Original languageEnglish
Article number106007
Journal / PublicationTunnelling and Underground Space Technology
Volume153
Online published9 Aug 2024
Publication statusPublished - Nov 2024

Abstract

The rapid expansion of urban underground space (UUS) has become increasingly popular in densely populated urban areas worldwide. Although data-driven technology has facilitated the planning process successfully, the implementation mechanism of UUS planning remains obscure, potentially undermining the spatial performance. To address this gap, this study employs fuzzy-set qualitative comparative analysis (fsQCA) to analyze the causality of UUS development. Three primary models of UUS development-separate, interconnected, and integrated models-are categorized. Causal conditions and outcomes along with their quantitative metrics are proposed. Subsequently, 30 Chinese cases are analyzed using fsQCA to assess the necessity and sufficiency of UUS development. Three distinct causal paths are identified, namely strong economic strength, robust policy support, and advanced construction technology, which play critical roles in integrated development, while weak economic strength and inadequate policy support lead to separate development. The study underscores the importance of implementing UUS development models and provides valuable insights for UUS planning management. © 2024 Elsevier Ltd

Research Area(s)

  • Fuzzy-set qualitative comparative analysis (fsQCA), Implementation-oriented model, Planning management, Urban underground space

Citation Format(s)

Identifying implementation-oriented models of urban underground space development in China based on fuzzy-set qualitative comparative analysis (fsQCA). / Wang, Wei-Xi; Peng, Fang-Le; Ma, Chen-Xiao et al.
In: Tunnelling and Underground Space Technology, Vol. 153, 106007, 11.2024.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review