Search Results (7)

This study examines the structural evolution of Knowledge Innovation Networks (KINs) and Technology Innovation Networks (TINs) across Chinese cities (2015–2024). Using SCI/SSCI co-authorship and prefecture-level patent data, we construct dual-layer networks and assess their resilience through metrics such as average clustering coefficient, path length, global efficiency, and largest-component ratio. Our framework clarifies how network structure, spatial proximity, and urban hierarchy jointly shape innovation dynamics and opportunity distribution. Three main findings emerge. First, KINs have moved toward polycentricity yet remain hierarchically rigid, with persistent core–periphery gaps despite improved connectivity in tier 2–4 cities. TINs show greater cross-tier adaptability, creating new innovation gateways while intensifying intra-tier polarization. Second, under simulated disruptions, KINs are vulnerable to targeted attacks and exhibit path-dependent degradation, whereas TINs maintain efficiency until a critical threshold, then collapse abruptly. Third, MRQAP analysis reveals that economic and geographic proximity facilitate collaboration in KIN but constrain linkages in TINs, with spatial proximity exerting a stronger influence on knowledge flows. These results demonstrate how innovation networks mediate urban–rural interactions, affect spatial inequality, and shape regional resilience. We argue for differentiated policies that strengthen core–periphery connectivity while mitigating proximity-induced lock-in, fostering more inclusive, resilient, and sustainable urban innovation systems. Full article

This study focuses on cultural and urban development policies under China’s 14th Five-Year Plan, exploring the content and semantic structure of discussions on the “East Asian Cultural Capital” project on the Weibo platform. It analyzes how national cultural development policies are reflected in the discourse system related to the “East Asian Cultural Capital” on social media and emphasizes the guiding role of policies in the dissemination of online culture. When China announced the 14th Five-Year Plan in 2021, the strategic direction and policy framework for cultural development over the five-year period from 2021 to 2025 were clearly outlined. This study employs text mining and semantic network analysis methods to analyze user-generated content on Weibo from 2023 to 2024, aiming to understand public perception and discourse trends. Word frequency and TF-IDF analyses identify key terms and issues, while centrality and CONCOR clustering analyses reveal the semantic structure and discourse communities. MR-QAP regression is employed to compare network changes across the two years. Findings highlight that urban cultural development, heritage preservation, and regional exchange are central themes, with digital media, cultural branding, trilateral cooperation, and cultural–economic integration emerging as key factors in regional collaboration. Full article

With the acceleration of the digital revolution and free trade, the producer services industry has become a new driving force for countries to enhance their global value chain (GVC). The further integration of GVCs has promoted the formation of a global value network covering a wider range of regions and industries. The way of establishing strong core capabilities and competitive advantages for a country’s producer services industry in the vast value network is of great practical significance for achieving industrial structure transformation and upgrading in an open economy. Therefore, based on the Asian Development Bank Multi-Regional Input–Output Database (ADB-MRIO) and the bilateral export value-added accounting method (WWZ), this study constructs a value network of producer services and analyzes its structural evolution and driving factors. The results show the following: (1) The domestic value-added (DVA) network and foreign value-added (FVA) networks of producer services trade exhibit dense characteristics in terms of trade depth. The DVA network has a small-world topological structure, while the FVA network does not have this feature most years. (2) Western countries, represented by the USA, Germany, and the UK, are located at the hub of the global value network, while China’s network status is rising and gradually occupying a core position not only in the Asian region but also in the world. The value chain of producer services shows a pattern of being led by developed countries and extending to developing countries. (3) The broader tendency of modularity is decreasing, indicating that the development process of the DVA and FVA networks is becoming globalized. The members of the community can not only achieve trade interdependence due to geographical proximity but also break through regional limitations and complement each other. (4) The network evolution process is driven by a variety of factors. Industrial and technological distances are conducive to the expansion of the global value flow in producer services. Geographical and linguistic proximity are the main influencing factors, while the role of institutional proximity tends to be weakened. Full article

This paper employs social network analysis to investigate the characteristics and determinants of co-movement in the volatility of net cross-border capital flows. We have identified a significant “small-world” pattern in the co-movement network. Economies with highly positive or negative co-movement of volatility in net capital flows display regional differences. Furthermore, economies with high trade intensity, large interest-rate spreads, membership in the same economic organization, and geographical adjacency exhibit significantly increased co-movement of volatility in net private capital flows and net other investment flows. Economies with large differences in economic growth present less co-movement of volatility in net portfolio flows. Full article

The realization of the “double carbon” goals and the development of green transportation require a focused approach to reducing carbon emissions from private cars. Starting from the perspective of social network analysis, this paper constructs the carbon emission network of private car cross-district mobility based on vehicle trajectory big data in Guangzhou and Foshan and analyzes its spatial network characteristics. Next, the MRQAP model is constructed to examine the impact of built environment factors on carbon emissions from private cars. Furthermore, the paper explores the moderating effect of private car mobility in the central urban area. The results indicate the following: (1) Private vehicle cross-district mobility in the Guangzhou and Foshan region are closely interconnected and exhibit a phenomenon of central clustering. (2) Both population density and the number of road intersections have a positive relationship with private car carbon emissions, and after a series of robustness tests, the results are still valid. (3) Private vehicle mobility in central urban areas contributes to an increase in carbon emissions, and the positive impact is reinforced by population density, while road intersections and private car mobility in central urban areas have a substitutive effect on private car carbon emissions. Full article

We demonstrate the use of agent-based models to simulate the interactions of two mobile dating applications that possess divergent interaction features. We reproduce several expected outcomes when compared to extant literature. We also demonstrate the use of a standard social network analysis technique—the network regression, Multiple Regression Quadratic Assignment Procedure—in conducting a principled and interpretable comparison between the two models with strong results. This combined approach is novel and allows complex system modelers who utilize agent-based models to reduce their reliance on idealized network structures (small world, scale-free, erdos-renyi) when applying underlying network interactions to agent-based models that can often skew results and mislead from a full picture of system-level properties. This work serves as a proof-of-concept in the integration of classical social network analysis methods and contemporary agent-based modeling to compare software designs and to enhance the policy-generation process of online social networks. Full article

Social network analysis has been highlighted as a powerful tool to enhance the evidence-based management of captive-housed species through its ability to quantify the social experience of individuals. We apply this technique to explore the social structure and social roles of 50 Livingstone’s fruit bats (Pteropus livingstonii) housed at Jersey Zoo, Channel Islands, through the observation of associative, affiliative, and aggressive interactions over two data collection periods. We implement binomial mixture modelling and characteristic-based assortment quantification to describe the complexity and organisation of social networks, as well as a multiple regression quadratic assignment procedural (MRQAP) test to analyse the relationship between network types. We examine the effects of individual characteristics (i.e., sex, age, and dominance rank) on social role by fitting models to explain the magnitude of node metrics. Additionally, we utilize a quadratic assignment procedural (QAP) test to assess the temporal stability of social roles over two seasons. Our results indicate that P. livingstonii display a non-random network structure. Observed social networks are positively assorted by age, as well as dominance rank. The frequency of association between individuals correlates with a higher frequency of behavioural interactions, both affiliative and aggressive. Individual social roles remain consistent over ten months. We recommend that, to improve welfare and captive breeding success, relationships between individuals of similar ages and dominance levels should be allowed to persist in this group where possible, and separating individuals that interact frequently in an affiliative context should be avoided. Full article