Author
Listed:
- Dan Zhu
(School of Economics and Management, Tianjin Chengjian University, Tianjin 300384, China)
- Xinhang Li
(School of Economics and Management, Tianjin Chengjian University, Tianjin 300384, China)
- Hongchang Li
(School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China)
Abstract
In recent years, urban risk incidents have become more common. Enhancing infrastructure resilience is not only crucial for adapting to climate change and addressing natural disasters but also serves as a key cornerstone for sustaining urban sustainable development. The research objects for this study are 17 coastal cities in the Bohai Rim region of China. Based on the Complex Adaptive System (CAS) theory, from the multi-dimensional perspective of urban sustainable development, a resilience evaluation index system covering five subsystems, namely transportation, water supply and drainage, energy, environment, and communication, is constructed. Employing panel data from 2013 to 2022, this study develops the entropy weight–TOPSIS model to quantify resilience levels, and applies the obstacle degree model, geographical detector, and Geographically and Temporally Weighted Regression (GTWR) model to analyze influencing factors. The main research results are as follows: (1) The regional infrastructure resilience shows a slow upward trend, but the insufficient synergy among subsystems restricts urban sustainable development; (2) The primary barrier is the drainage and water supply system, and the environmental and communication systems’ notable spatial heterogeneity will result in uneven regional sustainable development; (3) The influence of driving factors such as economic level gradually weakens over time. Based on the above research results, the following paths for resilience improvement and urban sustainable development are proposed: Improve the regional coordination and long-term governance mechanism; Focus on key shortcomings and implement a resilience enhancement plan for water supply and drainage systems; Implement dynamic and precise policy adjustments to stimulate multiple drivers; Enhance smart empowerment and build a digital twin-based collaborative management platform.
Suggested Citation
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2025:i:18:p:8232-:d:1748635. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.