Towards Smart and Resilient City Networks: Assessing the Network Structure and Resilience in Chengdu–Chongqing Smart Urban Agglomeration

Systems, Journal Year: 2025, Volume and Issue: 13(1), P. 60 - 60

Published: Jan. 19, 2025

The mobility and openness of smart cities characterize them as particularly complex networks, necessitating the resilience enhancement city regions from a network structure perspective. Taking Chengdu–Chongqing urban agglomeration case study, this research constructs economic, information, population, technological intercity networks based on theory gravity model to evaluate their spatial over five years. main conclusions are follows: (1) subnetworks exhibit ‘core/periphery’ with significant evolution trend, metropolitan area integration degree capital has significantly improved; (2) technology is most resilient but was affected by COVID-19, while population information least resilient, resulting poor hierarchy, disassortativity, agglomeration; (3) can be improved through system optimization node enhancement. System should focus more improving coordinated development due low synergistic level resilience, adjust strategies according dominance, redundancy, role nodes. This study provides reference framework assess cities, assessment results provide valuable regional planning for building in regions.

Language: Английский

Structural characteristics and influencing factors of agricultural carbon emissions spatial correlation network: evidence from Shandong Province

Frontiers in Sustainable Food Systems, Journal Year: 2025, Volume and Issue: 9

Published: April 2, 2025

Introduction With the development of agricultural industry clustering and scale expansion, carbon emissions (ACEs) have gradually formed a spatial association network. Clarifying correlation network (ACESCN) its influencing factors in Shandong Province is crucial for advancing low-carbon development. Methods Based on ACE 16 cities Province, this study uses Social Network Analysis (SNA) Quadratic Assignment Procedure (QAP) to investigate spillover effects driving ACESCN from 2010 2022. Results discussion The findings show that following: (1) overall, has shown trend initially increasing then decreasing. (2) improved both connectivity robustness, forming structure centered around Weifang, Jinan, Tai’an. However, degree remains relatively loose, indicating needs optimization. Within network, there are significant agglomeration effects. (3) Geographical proximity, economic level, industrial structure, opening-up impact correlation. Therefore, suggests associations should be fully utilized enhance cross-regional production interactions cooperation. This approach will help form rational providing scientific basis achieve regional coordinated emission reductions.

Language: Английский