The Coupling and Linkage Effect of Urban Information Network and Enterprise Network: A Case Study of the Twin-City Economic Circle of the Chengdu-Chongqing Region

Cities function as complex systems where subsystems interact to form higher-level urban complexes characterized by intricate nonlinear coupling relationships among various networks. Although a substantial amount of research on urban networks from the perspective of single-factor flow exists both domestically and internationally, such studies have limitations, as they do not fully capture the multifaceted nature of urban systems. Research on multi-city networks in China primarily examines the structural characteristics and dynamic mechanisms of networks with distinct attributes. While international studies have explored interactions and coupling effects among subsystems within complex systems, focusing on aspects like network robustness and cascading failures, relevant studies on urban networks remain relatively limited. This study proposes a comprehensive research framework called Correlation-Multiplex Coupling Networks-Coupling Linkage Effect Evaluation (CMC). Focusing on the coupling of enterprise and information networks in the Chengdu-Chongqing twin-city economic circle, this study further analyzes the coupling linkage effect between these networks. The results indicate that: First, there exists a complex nonlinear coupling relationship between information and enterprise networks, with a correlation coefficient exceeding 0.625 and different degrees of interactive coupling between nodes; second, from 2011 to 2020, there were notable differences in the core-edge structures of the three networks within the twin-city economic circle. Interactions between cities in core areas were more frequent than those in peripheral areas, displaying a prominent "rich man clubs" phenomenon and preferential links. The hierarchical structure and "Matthew effect" of the urban network were evident. The enterprise network evolved from a dual-core, single-strong link structure to a dual-core, multiple-strong-link structure, achieving a more balanced network over time. The information network transitioned from a single-centered structure around Chengdu to a weaker dual-core structure, with Chongqing as a secondary core. Third, from 2011 to 2020, differences in coupling and linkage effects between enterprises and information networks were significant, with node coupling and linkage primarily at medium to low levels. Link coupling and linkage were mainly at medium to high levels, and interactive linkage weakened over time. The "rich club" phenomenon in coupled networks was stronger than in information networks but weaker than in enterprise networks. Compared to enterprise networks, the "Matthew effect" of coupled networks was less pronounced. In 2020, due to COVID-19 impacts, coupling and linkage between enterprise networks and information networks were significantly weakened, and urban comprehensive capacity did not markedly improve. This study expands the research perspective on urban networks, enriching the field by using a multiplex network approach and coupling coordination model, providing a methodological reference for similar research in other regions and enhancing understanding of the linkage effects among urban subsystems.