Revealing the Priorities for Rural Infrastructure Maintenance Through Complex Network Analysis: Evidence from 98 Counties in China
Year: 2025
Type: article
Abstract: Driven by the Rural Revitalization Strategy, China has substantially increased its investment in rural infrastructure. Nevertheless, widespread issues such as underutilization and inadequate management persist. Recognizing rural infrastructure as a complex and interdependent system, this study applies complex network analysis to evaluate data from 98 counties, treating each county as an analytical unit and various infrastructure types as network nodes. A rural infrastructure interdependency network is constructed to examine the interdependencies among infrastructure and the overarching structural characteristics of the system. The analysis demonstrates that the rural infrastructure network exhibits pronounced modularity, with three distinct functional clusters: (1) electricity–water–broadband internet, (2) public service infrastructure, and (3) housing–environmental governance infrastructure. Furthermore, by employing a network dismantling approach that simulates facility management failures through the progressive removal of nodes, this study identifies paved roads and electricity supply stability as critical nodes within the rural infrastructure network. The failure of these infrastructures triggers systemic fragmentation and functional collapse, indicating their pivotal role in maintaining overall network integrity. These findings offer theoretical support for the optimization of infrastructure maintenance strategies, with the ultimate goal of enhancing the overall resilience and sustainable development capacity of rural infrastructure systems.
Source: Land
DOI: 10.3390/land14081688
Authors: Zheng Li, Yaofu Huang, Muzhe Pan, Yaxin Pei, Xun Li
Institution: Sun Yat-sen University
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
Award: G5841163797
OpenAlex ID: W4413375902
