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Social information is crucial to credit ratings and can improve the accuracy of the traditional credit assessment model. Drawing on the resource-based view (RBV) and social capital theory (SCT), this research explores the relationships between corporate social activities, network centrality and corporate credit behavior.

The authors used social network analysis (SNA) and regression analysis to analyze the data collected from 14,544 enterprises on the Alibaba platform.

The results indicate that among the four types of social activities, the number of corporate questions and posts shows a positive relationship with credit behavior; while the number of corporate comments has negative relationship with credit behavior. Further, degree and betweenness centralities mediate the relationship between the number of corporate questions, posts and comments with credit behavior.

This study contributes to the literature on non-financial factors (soft information) by exploring the social behavioral factors related to corporate credit. In addition, this study offers a new theoretical lens and reasonable explanations for investigating the relationship between corporate social activities, network centrality and credit behavior from the perspective of the resource-based view, while most studies are predictive and methodological. Moreover, this study provides new insights for platforms to evaluate enterprise credit and for managers to improve credit behavior.

In contrast to the vertical supply chain structure, firms are increasingly engaging in horizontal inter-firm collaborations to develop new technologies, products and services, yet, little is known about factors that influence the governance mechanism and performance of such collaborative projects. The purpose of this paper is to investigate how different factors affect the role or the centrality of the governing mechanism (the broker) in inter-firm collaborative networks.

Using a case study method approach, this paper studies three dynamic networks comprising firms that are not in a traditional supply chain relationship. The networks comprised firms engaged in the development of different aspects of an innovative automotive technology.

The study finds that broker’s centrality varies over time and is directly related to project performance; network structure and perceived broker power are related to broker centrality in dynamic networks. The more loosely connected a network is (open network), the more the degree of broker centrality. The higher the degree of expert power that a broker is perceived to possess, the higher is the degree of broker centrality.

Investigating governance mechanism and determinants of network outcomes in inter-firm collaboration for new product development represents a departure from the traditional studies on similar phenomena in vertically structured supply chain arrangements; thus, contributes to the literature on innovation in inter-firm arrangements. Understanding how the salient factors contribute to performance at the network level builds on firm level and dyadic level of analysis or focus of previous studies.

The purpose of this paper is to explore the nature of the relationship between a scholar’s research performance (using weighted journal-impact factor average) and their degree centrality; the impact of author-homophily (in terms of gender, institutional sector, academic age, academic ranks, province and city) on this relationship is investigated as well.

Using scientific publishing data and journal-impact factors from Thomson Reuters’ ISI Web of Science (SCI) and Journal Citation Reports, respectively, the domestic co-authorship network of chemistry researchers in Pakistan during 2002-2009 was constructed then modeled via ordinary least squares regression.

Results show that the personal characteristics of a researcher do not necessarily lead to high degree centrality, i.e. attributes may not be causal to co-author relationships. Instead, high degree centrality is more so a function of the forerunning research performance of the researcher: those whom publish more in terms of impact factor, attract more co-authors (high degree centrality). Moreover, the relationship between research performance and degree centrality is positively moderated by age and province homophily and negatively moderated by city homophily.

Data are sourced wholly from the Pakistani chemistry research community; results many not be generalizable to other sub-populations or the wider research community.

The findings provide insights to performance-seeking authors: knowing that their research performance enhances their centrality, which in-turn may lead to increased research performance and various other desirable professional outcomes. In addition, researchers can look toward establishing similar (homophilous) or dissimilar (heterophilous) ties knowing that the relationship between research performance and centrality will likely be stronger when similarity or dissimilarity exists.

This study supports the idea that high research performance attracts more potential co-authors, which in-turn may lead to ever greater research performance, which suggests that the research community will be fragmented between high- and low-performing researchers. Also researcher will have similar or dissimilar ties in terms of various characteristics which in turn moderate the research performance centrality relationship.

This paper counteracts the empirical belief that researchers are attractive as potential co-authors according to their personal and professional characteristics. It is actually their research performance and homophily or heterophily of their ties which matters.

Recently, decoupling between the US and China has emerged as an important issue in global economics. We propose an analytical framework for trade decoupling analysis, borrowing the idea from the production function in non-competitive input-output tables. Using that methodology, we analyze the mobile phone trade network subject to various measures imposed by the US. A scenario analysis is performed to compare the extent of decoupling after a trade war with worst-cases. In bilateral trade, China’s share of total US imports fell significantly in 2019 compared to 2017. However, China’s indirect exports to the US increased during the same period. A similar pattern is observed in the global trade network visualized via multidimensional scaling (MDS). China’s out-degree centrality decreased slightly, while Vietnam’s role expanded. Actual figures for 2019 show a decreased out-degree centrality for Chinese final good exports, but a much higher one in the scenarios. Also, China’s indirect exports to the US have increased. But China does not appear to play a key role in the network as assumed in the scenario. Throughout the study, intermediate goods were treated homogeneously, and further studies considering the heterogeneity of input-output linkages are needed.

This study explores the characteristics of high-speed rail (HSR) and air transportation networks in China based on the weighted complex network approach. Previous related studies have largely implemented unweighted (binary) network analysis, or have constructed a weighted network, limited by unweighted centrality measures. This study applies weighted centrality measures (mean association [MA], triangle betweenness centrality [TBC], and weighted harmonic centrality [WHC]) to represent traffic dynamics in HSR and air transportation weighted networks, where nodes represent cities and links represent passenger traffic. The spatial distribution of centrality results is visualized by using ArcGIS 10.2. Moreover, we analyze the network robustness of HSR, air transportation, and multimodal networks by measuring weighted efficiency (WE) subjected to the highest weighted centrality node attacks. In the HSR network, centrality results show that cities with a higher MA are concentrated in the Yangtze River Delta and the Pearl River Delta; cities with a higher TBC are mostly provincial capitals or regional centers; and cities with a higher WHC are grouped in eastern and central regions. Furthermore, spatial differentiation of centrality results is found between HSR and air transportation networks. There is a little bit of difference in eastern cities; cities in the central region have complementary roles in HSR and air transportation networks, but air transport is still dominant in western cities. The robustness analysis results show that the multimodal network, which includes both airports and high-speed rail stations, has the best connectivity and shows robustness.

The understanding of leaders’ network centrality in social networks has been acknowledged as a major topic that can advance the social network field; most studies in this area have either taken firms as the subject by which the network centrality of firms was measured or/and have been conducted for the functional project context. Very little research has been done in the pure project context. This paper aims to revisit the centrality–performance link in the singular specialized project context.

The proposed relationships using panel data on 48 movie directors who lead pure projects has been studied. Freeman’s (1979) and Wasserman and Faust’s (1994) procedures have been adopted to compute our three centrality measures and their effects have been examined on box-office and artistic performance. A random effect and a mixed-effects Poisson model have been fit to examine the significance of the centrality–performance relationship.

The findings provide empirical evidence to support three out of the six hypotheses. The findings suggested that degree and closeness centrality are positively related to commercial performance and betweenness centrality is negatively related to commercial performance. However, it was found that only the degree centrality is related to artistic performance.

This study has two features that distinguish it from prior studies that link centrality to performance. First, the focus is on centrality attached to the leaders instead of the centrality attached to functional project teams or firms, as previously investigated. Second, this study is the first attempt of its kind to analyse the proposed relationship for an Asian market.

The purpose of this paper is to investigate how complementors’ marketing capability and technology capability affect their performance. Drawing on social capital theory, the authors examine platform network centrality as a mediator and platform reputation as a moderator of the relationships between these two capabilities and complementor performance.

This study collects data by questionnaire from 154 Chinese firms adopting e-commerce platforms. Hierarchical multiple regression is used to test the hypotheses of this study.

This study finds that complementors’ marketing capability and technology capability positively affect performance by increasing their platform network centrality. Moreover, platform reputation positively moderates the relationship between platform network centrality and complementor performance, and it strengthens the mediating role of platform network centrality.

This paper emphasizes the critical role of marketing capability and technology capability on complementor performance. It explores the improvement path of complementor performance from the perspective of network position, which is a key element for complementors to effectively leverage their capabilities to build competitive advantage.

Using overlapped portfolio data on public equity funds in Korea, the authors construct several types of fund-stock weighted bipartite networks and measure fund network centrality. The authors also examine the relationship between network centrality and fund investment performance. The authors' results are three-fold. First, the authors find that the fund centrality of the network in which funds and stocks are connected based on the most active investing behavior positively affects the fund performance. Second, the funds with a high centrality level based on the same network generate higher returns by holding stocks with high value uncertainty. Third, the authors find that fund centrality is not associated with herd behavior. Based on these results, the authors argue that fund centrality is a proxy of information advantage and skill of fund managers. The authors' paper shows that network analysis could be a new way to identify funds with better performance and measure the skill and information advantage to construct an optimal portfolio.

This paper examines the role of co-inventor collaboration with China and/or the USA on a country's increase in centrality in global knowledge networks. It also explores the role of specific institutional factors – corruption and intellectual property rights (IPR) protection – on this relationship.

In the study, co-inventor data from the United States Patent and Trademark Office (USPTO) applications have been used to construct networks of technological knowledge collaboration at the country level over the years 2002–2015. Using eigenvector centrality as the dependent variable, the study uses fixed effect regression analyses on a panel of 171 countries, contributing to recent debates on knowledge networks and international cooperation.

Building on research in economic development, innovation and social network theory, this research finds that co-patenting with Chinese inventors is positively related to a country's centrality in global knowledge networks and that this relationship is negatively moderated by collaboration with the current most central knowledge network – namely that of the USA – suggesting a substitution effect. It also finds a partial substitution between institutional factors, IPRs protection and transparency, and collaboration with China on a country's knowledge centrality.

Regarding policymakers, the findings can be used to encourage international collaboration for increased access to new sources of knowledge that fosters innovation while keeping a close eye on local institutions, especially emerging economies that want to increase their international knowledge network centrality.

This study creates a unique panel data set and extends the social networks approach in international business literature, focusing on institutional characteristics related to participation in knowledge networks.

The purpose of this study is to bridge the gap in the literature on supply chain finance (SCF) by exploring the relationship between network capabilities and corporate financial performance (CFP) in financial supply chains (FSCs).

The authors collect panel data and adopt regression analysis to analyse the joint investment activities among 1359 manufacturing firms and 289 financial service providers in China to explore how network capabilities, both network power and network centrality, improve CFP in the FSCs.

Under the FSCs environments, network centrality (i.e. eigenvector centrality, closeness centrality and betweenness centrality) raises CFP (ROA, ROE and Tobin's Q) and network power (node degree, clustering coefficient) also improves CFP. However, node strength from the network power stream has a negative effect on Tobin's Q, indicating that when the partner of a firm has an extremely strong influence in FSCs; this weakens the bargaining ability and flexibility of the focal firm, thus reducing its long-term financial performance.

The joint investment activities among supply chain partners and financial service providers help managers understand the advanced financing solutions generated by internal and external network organisations as well as be aware of network capabilities' impact on CFP in FSCs.

This study answers the call for more empirical research on SCF to provide a broader sample to examine financial supply chain management. This is one of the earliest studies to shed light on a new perspective – how network capabilities improve CFP in the FSCs.