Network Centrality Research Articles

A heuristic method for solving the Steiner tree problem in graphs using network centralities

We propose a heuristic method of using network centralities for constructing small-weight Steiner trees in this paper. The Steiner tree problem in graphs is one of the practical NP-hard combinatorial optimization problems. Given a graph and a set of vertices called terminals in the graph, the objective of the Steiner tree problem in graphs is to find a minimum weight Steiner tree that is a tree containing all the terminals. Conventional construction methods make a Steiner tree based on the shortest paths between terminals. If these shortest paths are overlapped as much as possible, we can obtain a small-weight Steiner tree. Therefore, we proposed to use network centralities to distinguish which edges should be included to make a small-weight Steiner tree. Experimental results revealed that using the vertex or the edge betweenness centralities contributes to making small-weight Steiner trees.

Elucidating Genes and Transcription Factors of Human Peripheral Blood Lymphocytes Involved in the Cellular Response upon Exposure to Ionizing Radiation for Biodosimetry and Triage: An In Silico Approach

Abstract Background Gene expression–based biodosimetry is a promising method for estimating radiation dose following exposure. A panel of highly radio-responsive genes in human peripheral blood was used in the current investigation to create and evaluate a unique gene expression–based radiological biodosimetry method. Methodology In human cellular research, we reviewed the literature on genes and proteins correlating to radiation response in vivo and in vitro. We looked at two publicly accessible independent radiation response gene expression profiles (GSE1977 and GSE1725) and identified the differentially expressed genes (DEGs). Results The obtained data exhibited 42 genes with substantial differential expression, 25 of which were upregulated and 17 of which were downregulated in ionizing radiation exposure groups compared with control groups. The gene ontology enrichment analysis revealed that the hub genes are significantly involved in the regulation of the mitotic cell cycle phase transition, regulation of the mitotic cell cycle, and mitotic cell cycle checkpoint signaling. Out of the 42 DEGs, four top genes (CDK1, CCNB1, UBC, and UBB) were obtained through network centrality features. However, the multicomponent filtering procedure for radiation response genes resulted in cyclin-dependent kinase 1 (CDK1) as a critical gene in the dataset curated. Conclusion Our findings suggest the possibility of discovering novel gene connections involved in the cellular response of human peripheral blood lymphocytes upon exposure to ionizing radiation.

Direct and indirect effects of degree of interdisciplinarity on firms' innovation performance: The moderating role of firms' capabilities

AbstractCombinations of heterogeneous knowledge from different scientific domains may drive highly innovative outcomes. Our study investigates whether firms can benefit from interdisciplinary research and development (R&D) activities by also reflecting on the potential negative consequences of increasing complexity of outcome validation activities at later stages of innovation processes. We explore which resources and organizational capabilities may influence the efficacy of interdisciplinary R&D activities. We examine whether the available financial slack, collaborations with universities, and a high betweenness centrality in scientific networks may promote the flexibility, scope, and efficiency of knowledge integration, and thus moderate the direct and mediated relationships between the degree of interdisciplinarity (DoI) of a firm's R&D activities and innovation performance. To test our hypotheses, we performed an analysis of medical technology firms that are highly dependent on interdisciplinary R&D. We collected a panel dataset of R&D activities and successful market launches of new products from 79 large medical technology firms between 1997 and 2021. The measurement of a firm's DoI is based on a novel approach involving neural networks in a bibliographic data graph. Our results suggest that firms can improve their innovation performance if they conduct interdisciplinary R&D activities. However, higher levels of DoI also increase the complexity of the required outcome validation, which reduces a firm's innovation performance. We also found that high levels of financial slack help to overcome barriers of implementing interdisciplinary R&D activities. Collaborations with universities, and good access to knowledge in scientific networks, further foster interdisciplinary knowledge application in new product development.

Advancing the Measurement of Social Functioning in Schizophrenia: Applications of Egocentric Social Network Analysis.

People with schizophrenia face challenges with forming and maintaining social relationships, often resulting in poor social functioning. Commonly used measures of social functioning provide broad information relating to social relationships, but they do not adequately capture information regarding network structure and characteristics of network members. One method that can assess these more detailed aspects of social networks and provide a more comprehensive understanding of social functioning deficits is egocentric social network analysis (SNA). SNA is a scientific discipline that uses principles of network science and graph theory to analyze social relations quantitatively. Even though some types of SNA have been applied in prior schizophrenia studies, its application as a framework to measure social functioning has been extremely limited. Therefore, this article aims to formally introduce SNA and select quantitative SNA metrics, including measures of network composition, structure, homophily, and centrality, to schizophrenia researchers as novel ways of measuring components of social functioning. To demonstrate the application of SNA, we provide illustrative examples of the SNA metrics and graphical diagrams of social networks for two individuals with schizophrenia.

CTO Network Centrality and Corporate Innovation

Social network centrality of chief technology officers (CTOs) affects corporate innovation. Firms with CTOs who are well-connected within the network of all business professionals invest more in research and development (R&D), receive more patents, attract more patent citations, and create more patent value. Besides the effect of the general business network centrality, higher professional network centrality of CTOs (within the network of all other CTOs) also fosters corporate innovation. In addition, firms innovate more and better if CTOs are hired by the incumbent CEOs. Ultimately, R&D investment of companies with high-centrality CTOs enhances firm value.

Using social networks to explore the social flexibility of urban vervet monkeys

Increasing urbanisation reduces available habitat and increases human-wildlife interactions, presenting social and ecological challenges for many species; however, flexible generalist species, such as the vervet monkey, Chlorocebus pygerythrus, thrive under these pressures. In the urban mosaic, human-food sources represent clumped, monopolisable food that can increase contest competition. Social network analysis (SNA) is a powerful tool to monitor changes in social structure, yet it has rarely been used to study urban wildlife. Using SNA, we investigated the effect of anthropogenic food and human-wildlife interactions on social cohesion in five vervet monkey groups in urban KwaZulu-Natal, South Africa. Over six months, we conducted group scan samples every 30-min on each group and recorded all humans-vervet monkey interactions during dawn to dusk follows. We analysed the effect of foraging on natural and human-related food sources and human-vervet monkey interactions on social network metrics for grooming and aggression at group (density, clustering coefficient and distance) and individual (eigenvector centrality and degree) levels, using linear mixed models. Anthropogenic food influenced almost all social metrics. At the group level, foraging on anthropogenic food was related to increased density and cohesion in both grooming and aggression networks. At the individual level, increasing anthropogenic food affected high-ranking monkeys most: eigenvector centrality and outdegree in aggression networks increased with rank. Social network analysis can be a useful tool to document urban effects on wildlife groups, and aids our understanding of wildlife behavioural flexibility, a key tool in developing educated and effective management strategies.

Peer effect and funding success: Analyzing friendship networks in online credit markets

The challenge of limited information in online credit markets is well-recognized. This study examines the peer effect in microloan transactions using data from a leading Chinese lending platform. Results show that the likelihood of a borrower's funding success is higher when a higher proportion of online friends succeed. Both borrowers’ network centrality and digital footprints strengthen this effect, suggesting two mechanisms: social learning and informational complementarity. The peer effect is stronger among borrowers with larger networks, more loan experience, better repayment, and older age. The research provides new insights to mitigate information asymmetry in financial markets and guide investment decisions.

Do board networks matter for corporate cash holdings? Evidence from Australian firms

PurposeIn today’s interconnected world, social capital has emerged as a crucial business competence, drawing significant attention in recent literature. Using social network analysis, this study aims to investigate the impact of network centrality, established by a firm through its board members (i.e. boardroom networks), on corporate cash holdings.Design/methodology/approachThis study uses extensive panel data comprising 36,963 firm-year observations of firms listed on the Australian Securities Exchange, spanning a 22-year period (2001–2022). The study uses firm fixed-effect regression along with several alternative specifications and an instrumental variable approach to ensure the robustness of the results. Boardroom network centrality is quantified by five measures that capture different perspectives on networks as viable conduits for resource exchange and information flow: degree, two-step reach, closeness, eigenvector and betweenness.FindingsThe authors find evidence for the benefits of board networks. Firms with well-connected boards (central firms) are more likely to have smaller cash holdings. The findings also reveal distinct effects stemming from local and global properties of centrality, with local network measures playing a more pronounced role in shaping cash-holding decisions. Overall, the evidence reflects the ability of connected directors to enhance governance by limiting managerial discretion over cash reserves, thus reducing agency conflicts associated with cash holdings.Research limitations/implicationsThis study offers important insights for regulators, investors and practitioners, highlighting the potential for connected directors to effectively curtail managerial autonomy in deploying corporate cash holdings.Originality/valueThis study contributes to the ongoing discussion about the advantages and drawbacks of board networks, which constitute a vibrant and burgeoning area of research in the finance literature. It also complements scanty network-based studies on firm cash holdings. Importantly, this study extends prior work by providing robust evidence and a comprehensive analysis of the nuanced roles that board networks play in affecting the level of cash reserves.

Optimization of investment portfolios of Chinese commodity futures market based on complex networks

Futures trading in developing countries is now attracting more attention since investors may easily generate more excess return compared to the markets in developed countries, especially in Chinese market. In this paper, we analyzed the relationship between the centrality of commodity in the Chinese commodity futures market network and the optimal weight of each commodity in a portfolio, empirically examined the market systemic factors and commodity idiosyncratic factors that affect the centrality of commodity, and evaluated the effect of network structure on the optimization of commodity portfolio selection under the mean-variance framework. We found that the commodities with high network centrality are often related to industrial products with high volatility and small portfolio weights. We put forward a kind of commodity futures investment strategy based on this network and results showed that cumulative yield is better than other benchmark portfolios. The main contribution of this paper is to apply complex network theory to optimize futures portfolio selection by establishing the relationship between portfolio weight and commodity centrality in Chinese market, which is still under explored.

Sensitivity to network perturbations in the randomized shortest paths framework: theory and applications in ecological connectivity

The randomized shortest paths (RSP) framework, developed for network analysis, extends traditional proximity and distance measures between two nodes, such as shortest path distance and commute cost distance (related to resistance distance). Consequently, the RSP framework has gained popularity in studies on landscape connectivity within ecology and conservation, where the behavior of animals is neither random nor optimal. In this work, we study how local perturbations in a network affect proximity and distance measures derived from the RSP framework. For this sensitivity analysis, we develop computable expressions for derivatives with respect to weights on the edges or nodes of the network. Interestingly, the sensitivity of expected cost to edge or node features provides a new signed network centrality measure, the negative covariance between edge/node visits and path cost, that can be used for pinpointing strong and weak parts of a network. It is also shown that this quantity can be interpreted as minus the endured expected detour (in terms of cost) when constraining the walk to pass through the node or the edge. Our demonstration of this framework focuses on a migration corridor for wild reindeer (Rangifer rangifer) in Southern Norway. By examining the sensitivity of the expected cost of movement between winter and calving ranges to perturbations in local areas, we have identified priority areas crucial for the conservation of this migration corridor. This innovative approach not only holds great promise for conservation and restoration of migration corridors, but also more generally for connectivity corridors between important areas for biodiversity (e.g. protected areas) and climate adaptation. Furthermore, the derivations and computational methods introduced in this work present fundamental features of the RSP framework. These contributions are expected to be of interest to practitioners applying the framework across various disciplines, ranging from ecology, transport and communication networks to machine learning.

Evaluation and impact factors of international competitiveness of China’s cobalt industry from the perspective of trade networks

In recent years, with the development of the new energy industry, the demand for cobalt as a raw material for power batteries has been increasing. However, China itself has a shortage of cobalt resources. Therefore, overcoming poor resource conditions and enhancing the international competitiveness of the cobalt industry have become urgent issues. This paper is based on global trade data on cobalt resources from 2007 to 2020. A panel regression model is constructed from the perspective of trade networks, and Entropy-Topsis is used to construct a comprehensive evaluation index system for the international competitiveness of critical nonferrous metals. This study empirically examines the impact of the trade network characteristics of cobalt resources on international competitiveness, assigns practical significance to trade network characteristic indicators, and analyses the overall competitiveness changes in the global cobalt industry chain and its upstream, midstream, and downstream sectors. The research findings reveal the following key points: (1) In recent years, the competitive focus of the cobalt industry chain in various countries has shifted from upstream and midstream to midstream and downstream, with increasingly fierce trade competition downstream, gradually tilting toward countries such as South Korea, Japan, and China. (2) Cobalt trade competition, which was initially characterized by competition among multiple countries, has gradually become more centralized and stable, with differences in the competitiveness of various countries occurring at different stages of the cobalt industry chain. (3) Network centrality and network heterogeneity both have a significant promoting effect on the international competitiveness of the industry, while network connectivity has a significant inhibitory effect on the improvement of international competitiveness.On this basis, the study also suggests some policy implications. The purpose of the study is to enhance the international competitiveness of China's cobalt industry from a trade perspective and to investigate the developments of cobalt trade between China and the rest of the world.

Does the limelight foster the green transition of listed industrial companies? An empirical analysis from Chinese A-share market

This paper contributes current research by investigating the extent to which equity linkage networks impact enterprise green transition in sustainable development. By adopting a complex network approach, we constructed a common shareholding network based on the top ten shareholders of listed industrial enterprises in Shanghai and Shenzhen A-shares from 2013 to 2022. The empirical results indicate that enterprises closer to the centre of the equity linkage network tend to have higher degrees of green transition. This impact is facilitated through three mechanism channels of capital flow, information exchange, and knowledge transfer within the network. We find enterprises at the core of the network can effectively reduce their financing constraints on enterprises, mitigate risks associated with external environmental uncertainties and managerial myopia, and promote knowledge exchange and innovation cooperation between enterprises. We have also discovered that the centrality of equity network has a greater impact on promoting transition in state-owned, large-scale enterprises, and enterprises with less heavy pollution and the network effect can be enhanced by strong regional environmental regulations. The above findings not only provide policy makers with policy recommendations to guide the enterprises green transition, but also provide industry practitioners with practical paths and directions, which can help promote the green development process of the whole society.

Digital technology and industry-university-research (IUR) R&D network configurations: An exploration of market participation and market maturity

Amidst the rapid transformations ushered in by digital technology, which forges comprehensive digital connections across research & development (R&D) networks, leaders of pioneering organizations are diligently predicting market shifts, leveraging insights from institutional and network theories. This research enriches understanding by exploring how the digital technology adoption focus of innovative organizations affects their position within R&D networks, integrating perspectives from both theories. It identifies market participation and market maturity as key moderating factors and assesses their differential moderation effects. Employing a panel dataset of 1654 records from 2010 to 2022, which scrutinizes industry-university-research (IUR) R&D endeavors in China, the analysis demonstrates that an organization's digital technology adoption orientation positively influences its network centrality but adversely affects its position in structural holes. Additionally, the study finds that market participation diminishes the positive relationship between digital technology adoption focus and both network centrality and structural hole bridging capabilities. Conversely, market maturity enhances the association with network centrality but weakens the capacity to bridge structural holes. Further analysis was conducted on the temporal variations and the relationship between digital technology adoption and R&D network centrality and structural holes within heterogeneous innovative organizations. The investigation concludes with a discussion of the theoretical and practical implications of these findings, rooted in institutional and network theory insights.

Fecal Coprococcus, hidden behind abdominal symptoms in patients with small intestinal bacterial overgrowth

BackgroundSmall intestinal bacterial overgrowth (SIBO) is the presence of an abnormally excessive amount of bacterial colonization in the small bowel. Hydrogen and methane breath test has been widely applied as a non-invasive method for SIBO. However, the positive breath test representative of bacterial overgrowth could also be detected in asymptomatic individuals.MethodsTo explore the relationship between clinical symptoms and gut dysbiosis, and find potential fecal biomarkers for SIBO, we compared the microbial profiles between SIBO subjects with positive breath test but without abdominal symptoms (PBT) and healthy controls (HC) using 16S rRNA amplicon sequencing.ResultsFecal samples were collected from 63 SIBO who complained of diarrhea, distension, constipation, or abdominal pain, 36 PBT, and 55 HC. For alpha diversity, the Shannon index of community diversity on the genus level showed a tendency for a slight increase in SIBO, while the Shannon index on the predicted function was significantly decreased in SIBO. On the genus level, significantly decreased Bacteroides, increased Coprococcus_2, and unique Butyrivibrio were observed in SIBO. There was a significant positive correlation between saccharolytic Coprococcus_2 and the severity of abdominal symptoms. Differently, the unique Veillonella in the PBT group was related to amino acid fermentation. Interestingly, the co-occurrence network density of PBT was larger than SIBO, which indicates a complicated interaction of genera. Coprococcus_2 showed one of the largest betweenness centrality in both SIBO and PBT microbiota networks. Pathway analysis based on the Kyoto Encyclopedia of Genes and Genome (KEGG) database reflected that one carbon pool by folate and multiple amino acid metabolism were significantly down in SIBO.ConclusionsThis study provides valuable insights into the fecal microbiota composition and predicted metabolic functional changes in patients with SIBO. Butyrivibrio and Coprococcus_2, both renowned for their role in carbohydrate fermenters and gas production, contributed significantly to the symptoms of the patients. Coprococcus’s abundance hints at its use as a SIBO marker. Asymptomatic PBT individuals show a different microbiome, rich in Veillonella. PBT’s complex microbial interactions might stabilize the intestinal ecosystem, but further study is needed due to the core microbiota similarities with SIBO. Predicted folate and amino acid metabolism reductions in SIBO merit additional validation.

Advice Network Centrality as a Social Origin of Task Crafting: The Bridging Roles of Basic Psychological Needs.

Little is known about the predictive role of advice networks in task crafting despite the growing academic and practical interest in its antecedents. Accordingly, as centrality in advice networks is expected to have a positive relationship with task crafting, this study develops a research model encompassing the mediating roles of the fulfillment of basic psychological needs to clarify this relationship. The model was tested using a sample composed of 198 employees from various firms in South Korea. The results showed that employees who occupy central positions in the advice network fulfilled their autonomy and competence needs, consequently engaging in task crafting. This study contributes to the literature on social networks, self-determination, and task crafting by discovering hidden antecedents and pivotal mechanisms in determining task crafting.

The adaptive value of density-dependent habitat specialization and social network centrality

Density dependence is a fundamental ecological process. In particular, animal habitat selection and social behavior often affect fitness in a density-dependent manner. The Ideal Free Distribution (IFD) and niche variation hypothesis (NVH) present distinct predictions associated with Optimal Foraging Theory about how the effect of habitat selection on fitness varies with population density. Using caribou (Rangifer tarandus) in Canada as a model system, we test competing hypotheses about how habitat specialization, social behavior, and annual reproductive success (co)vary across a population density gradient. Within a behavioral reaction norm framework, we estimate repeatability, behavioral plasticity, and covariance among social behavior and habitat selection to investigate the adaptive value of sociality and habitat selection. In support of NVH, but not the IFD, we find that at high density habitat specialists had higher annual reproductive success than generalists, but were also less social than generalists, suggesting the possibility that specialists were less social to avoid competition. Our study supports niche variation as a mechanism for density-dependent habitat specialization.

Institutional Investor Information Networks and Stock Price Synchronicity

ABSTRACT The inefficiency of information flow in the capital market has led to a significant increase in stock price synchronicity, which has emerged as a critical challenge to the development of emerging capital markets. Based on a complex network perspective, this article investigates the relationship between institutional investor information networks and stock price synchronicity using data from Chinese public fund heavy holdings between 2011 and 2022. Empirical tests show that network correlation significantly reduces stock price synchronicity, while network centrality improves it. Mechanism analysis suggests that the information network affects stock price synchronicity through information diffusion and spillover effects. Furthermore, the analysis shows that the impact of information network structure on stock price synchronicity varies under different market conditions. The findings of this study provide valuable insights for strengthening the supervision of institutional investors’ behavior and reducing stock price synchronicity in emerging markets.

Developing stable, simplified, functional consortia from Brachypodium rhizosphere for microbial application in sustainable agriculture

The rhizosphere microbiome plays a crucial role in supporting plant productivity and ecosystem functioning by regulating nutrient cycling, soil integrity, and carbon storage. However, deciphering the intricate interplay between microbial relationships within the rhizosphere is challenging due to the overwhelming taxonomic and functional diversity. Here we present our systematic design framework built on microbial colocalization and microbial interaction, toward successful assembly of multiple rhizosphere-derived Reduced Complexity Consortia (RCC). We enriched co-localized microbes from Brachypodium roots grown in field soil with carbon substrates mimicking Brachypodium root exudates, generating 768 enrichments. By transferring the enrichments every 3 or 7 days for 10 generations, we developed both fast and slow-growing reduced complexity microbial communities. Most carbon substrates led to highly stable RCC just after a few transfers. 16S rRNA gene amplicon analysis revealed distinct community compositions based on inoculum and carbon source, with complex carbon enriching slow growing yet functionally important soil taxa like Acidobacteria and Verrucomicrobia. Network analysis showed that microbial consortia, whether differentiated by growth rate (fast vs. slow) or by succession (across generations), had significantly different network centralities. Besides, the keystone taxa identified within these networks belong to genera with plant growth-promoting traits, underscoring their critical function in shaping rhizospheric microbiome networks. Furthermore, tested consortia demonstrated high stability and reproducibility, assuring successful revival from glycerol stocks for long-term viability and use. Our study represents a significant step toward developing a framework for assembling rhizosphere consortia based on microbial colocalization and interaction, with future implications for sustainable agriculture and environmental management.

Navigating agricultural nonpoint source pollution governance: A social network analysis of best management practices in central Pennsylvania.

The Chesapeake Bay watershed is representative of governance challenges relating to agricultural nonpoint source pollution and, more generally, of sustainable resources governance in complex multi-actor settings. We assess information flows around Best Management Practices (BMPs) undertaken by dairy farmers in central Pennsylvania, a subregion of the watershed. We apply a mixed-method approach, combining Social Network Analysis, the analysis of BMP-messaging (i.e. information source, flow, and their influences), and qualitative content analysis of stakeholders' interviews. Key strategic actors were identified through network centrality measures such as degree of node, betweenness centrality, and clustering coefficient. The perceived influence/credibility (by farmers) of BMP-messages and their source, allowed for the identification of strategic entry points for BMP-messages diffusion. Finally, the inductive coding process of stakeholders' interviews revealed major hindrances and opportunities for BMPs adoption. We demonstrate how improved targeting of policy interventions for BMPs uptake may be achieved, by better distributing entry-points across stakeholders. Our results reveal governance gaps and opportunities, on which we draw to provide insights for better tailored policy interventions. We propose strategies to optimize the coverage of policy mixes and the dissemination of BMP-messages by building on network diversity and actors' complementarities, and by targeting intervention towards specific BMPs and actors. We suggest that (i) conservation incentives could target supply chain actors as conservation intermediaries; (ii) compliance-control of manure management planning could be conducted by accredited private certifiers; (iii) policy should focus on incentivizing inter-farmers interaction (e.g. farmers' mobility, training, knowledge-exchange, and engagement in multi-stakeholders collaboration) via financial or non-pecuniary compensation; (iv) collective incentives could help better coordinate conservation efforts at the landscape or (sub-)watershed scale; (v) all relevant stakeholders (including farmers) should be concerted and included in the discussion, proposition, co-design and decision process of policy, in order to take their respective interests and responsibilities into account.

How does institutional theory illuminate the influence of the digital economy on R&D networks?

PurposeThe purpose of this research is to explore how an innovation organization's orientation toward the digital economy influences its position within R&D networks. By using institutional theory, the study aims to forecast market changes and understand how organizations can navigate the digital economy to secure essential resources and minimize dependencies.Design/methodology/approachThis study employs a longitudinal panel dataset with 11,763 entries from 1995 to 2018, covering strategic emerging industries in China to analyze the impact of digital economy orientation on R&D networks. Utilizing advanced statistical models, it assesses the role of the legal environment as a moderator. This methodological approach facilitates a robust examination of the nexus between digital orientation and network dynamics within the context of institutional theory.FindingsThe study reveals that an organization's digital economy orientation enhances its centrality in R&D networks but reduces its control over structural holes. The legal environment negatively moderates the impact of digital economy orientation on network centrality, while positively influencing the relationship with network structural holes. These findings offer new insights into how institutional forces shape the strategic positioning of organizations in R&D collaborations.Originality/valueThis research offers a fresh perspective on the digital economy's impact on R&D networks, particularly in the Industry-University-Research (IUR) context. It extends the discourse by integrating institutional theory to elucidate the adaptation of R&D networks in the digital era. By identifying the legal environment as a moderator, the study provides a nuanced understanding of the strategic alignment within networks influenced by digital advancements. The unique focus on China's R&D networks presents a valuable contribution to the global discussion on digital integration and innovation ecosystems, highlighting the intersection of policy, academia, and industry in shaping research and development trajectories.