Network Relationships Research Articles

The gut microbiota-immune-brain axis in a wild vertebrate: dynamic interactions and health impacts.

The gut microbiota-immune-brain axis is a feedback network which influences diverse physiological processes and plays a pivotal role in overall health and wellbeing. Although research in humans and laboratory mice has shed light into the associations and mechanisms governing this communication network, evidence of such interactions in wild, especially in young animals, is lacking. We therefore investigated these interactions during early development in a population of common buzzards (Buteo buteo) and their effects on individual condition. In a longitudinal study, we used a multi-marker approach to establish potential links between the bacterial and eukaryotic gut microbiota, a panel of immune assays and feather corticosterone measurements as a proxy for long-term stress. Using Bayesian structural equation modeling, we found no support for feedback between gut microbial diversity and immune or stress parameters. However, we did find strong relationships in the feedback network. Immunity was negatively correlated with corticosterone levels, and microbial diversity was positively associated with nestling body condition. Furthermore, corticosterone levels and eukaryotic microbiota diversity decreased with age while immune activity increased. The absence of conclusive support for the microbiota-immune-brain axis in common buzzard nestlings, coupled with the evidence for stress mediated immunosuppression, suggests a dominating role of stress-dominated maturation of the immune system during early development. Confounding factors inherent to wild systems and developing animals might override associations known from adult laboratory model subjects. The positive association between microbial diversity and body condition indicates the potential health benefits of possessing a diverse and stable microbiota.

Response of soil fungal-community structure and function to land conversion to agriculture in desert grassland.

Land conversion to agriculture is an important factor affecting soil ecological processes in the desert grasslands of northern China. However, soil fungal-community structure and function in response to Land conversion remain unclear. In this study, desert grassland, artificial shrubland, and land conversion were investigated in the western part of the Mu Us Sandland (Yanchi, Ningxia; Dingbian, Shaanxi). We found that land conversion significantly increased soil total carbon, nitrogen, and phosphorus, and available phosphorous and potassium contents. In the early stage of conversion to agricultural (April), soil fungal operational taxonomic units and abundance-based coverage estimator were lower than those of dessert grasslands and shrubland plots and had significant correlations with pH, electric conductivity, and available phosphorus and potassium. The dominant phyla strongly correlated with soil physicochemical properties. Concomitantly, the relative abundance of Glomeromycota was significantly lower, and the complexity of the network in the land conversion plots was lower than that in the shrubland plots. In the late stage of land conversion (September), soil fungal operational taxonomic units and abundance-based coverage estimator were lower in the conversion plots than in the desert grassland plots, with more complex network relationships compared to the desert grassland or shrubland plots. Symbiotrophic groups, a functional group of desert grassland soil fungi, can be used as a predictor of environmental change; in addition, land conversion decreases the relative abundance of arbuscular mycorrhizal functional groups. Our study highlights the response of soil fungal communities and functions to human disturbances in desert grasslands. Considering the potential of land conversion to agriculture to influence soil secondary salinization, there is a need for continued observation of soil ecological health over the time continuum of land conversion to agriculture.

Accountability as a function of power relationships in public governance networks

AbstractIn public governance, power and accountability are inextricably linked. However, although an integrated exploration of these concepts could enhance our understanding of how governance operates, few studies have examined them together. Drawing on resource dependency theory, we suggest that power relationships within networks shape accountability and have a concomitant impact on the prevailing governance paradigm. Specifically, where principals possess important resources that enable them to exercise power over agents and hold them to account through hierarchical mechanisms, Traditional Public Administration approaches predominate. Where resources are diffused within elite networks in New Public Management contexts, individual actors can exercise greater power to achieve their objectives, and accountability arrangements become increasingly multidirectional and complex. Finally, if resources are shared across society as in the New Public Governance paradigm, actors generate power with each other to achieve shared goals, and accountability relationships are more horizontal with a focus on learning.

Hypergraph-Based Influence Maximization in Online Social Networks

Influence maximization in online social networks is used to select a set of influential seed nodes to maximize the influence spread under a given diffusion model. However, most existing proposals have huge computational costs and only consider the dyadic influence relationship between two nodes, ignoring the higher-order influence relationships among multiple nodes. It limits the applicability and accuracy of existing influence diffusion models in real complex online social networks. To this end, in this paper, we present a novel information diffusion model by introducing hypergraph theory to determine the most influential nodes by jointly considering adjacent influence and higher-order influence relationships to improve diffusion efficiency. We mathematically formulate the influence maximization problem under higher-order influence relationships in online social networks. We further propose a hypergraph sampling greedy algorithm (HSGA) to effectively select the most influential seed nodes. In the HSGA, a random walk-based influence diffusion method and a Monte Carlo-based influence approximation method are devised to achieve fast approximation and calculation of node influences. We conduct simulation experiments on six real datasets for performance evaluations. Simulation results demonstrate the effectiveness and efficiency of the HSGA, and the HSGA has a lower computational cost and higher seed selection accuracy than comparison mechanisms.

Understanding the relationships among adolescents’ internet dependence, reward, cognitive control processing, and learning burnout: a network perspective in China

Alterations in the reward and cognitive control systems are commonly observed among adolescents with internet dependence (ID), and this impairment is often accompanied by social dysfunctions, such as academic burnout. However, the intercorrelations among ID, reward, cognitive control processing, and learning burnout remain unclear. We recruited 1074 Chinese adolescents to investigate the complex interrelationships among these variables using network analysis. The resulting network revealed patterns that connected ID to the behavioral inhibition/activation system (BIS/BAS), self-control, and learning burnout; these results exhibited reasonable stability and test–retest consistency. Throughout the network, the node of BAS-drive was the critical influencing factor, and the node of self-control was the protection factor. In addition, several symptoms of learning burnout and ID were positively associated with sensitivity to punishment. As revealed by the network comparison test, the network constructed among internet dependent (ID) group differed from the network constructed among internet nondependent (IND) group not only in the edges between BIS and learning burnout but also in terms of the edges associated with learning burnout. In conclusion, this study provides insights into the complex mechanisms underlying ID among adolescents from the perspective of the network relationships between core influencing factors and negative consequences. It validates the dual-system model of risky behavior among adolescents and offers a foundation for early warning and interventions for ID in this context.

Factor Structure and Criterion Validity of the 15-item Network Relationship Inventory-Social Provisions Version (NRI-SPV-15) in Chinese Children and Adolescents

Factor Structure and Criterion Validity of the 15-item Network Relationship Inventory-Social Provisions Version (NRI-SPV-15) in Chinese Children and Adolescents

Analyzing the role of social media in addressing public health development in india through a multi-criteria decision-making approach

Nowadays, social media plays a vital role in managing public health developments. This research study has analyzed the factors of social media enhancing public health development. The analytic hierarchy process (AHP) is used to rank the factors, and the Decision-making trial and evaluation laboratory (DEMATEL) is used to find out the network relationship map of the role of social media in public health development. Results of AHP revealed that social media enhances public engagement and participation, collaboration of health professionals worldwide, and helps in remote monitoring of patients. Results of DEMATEL show that the development of health policies, repository of public health-related information, and prevention of health-related misinformation and fake news are classified as the topmost causal factors. Real-time monitoring of health conditions is the factor with the most significant impact on other factors. Policymakers and stakeholders should focus on improving public health through social media. Social media enhances collaboration among health professionals worldwide, and various stakeholders use it to address public health issues in the case of COVID-19.

The effects of social network relationships and social media influencer characteristics on consumer purchase intention in Chinese online community

The effects of social network relationships and social media influencer characteristics on consumer purchase intention in Chinese online community

Cognitive characteristics of concept derivation phase in environmental art design: A epistemic network analysis of design scheme construction process

Currently, there is a lack of in-depth research on the associative evaluation and developmental trajectory of the environmental design scheme construction process. Epistemic Network Analysis (ENA) is an analytical method for describing individual or group cognitive framework patterns, which can dynamically represent the cognitive characteristics of designers in the design process. In this paper, through experimental research, ‘Discover, Define, Develop’ are taken as coding dimensions for the design scheme process, and ENA is used to identify network relationships between cognitive elements of different groups, visually expressing the cognitive characteristics of the design scheme construction process. Excellent groups demonstrate cognitive patterns of divergence to convergence, and in the ideation phase, they can deeply contemplate specific design modules. Strategies are proposed from the perspectives of design education, and selection of design thinking paths to assist in cultivating innovative thinking in environmental art design.

Biodegradation of organosulfur with extra carbon source: Insights into biofilm formation and bacterial metabolic processes

Organosulfur compounds are prevalent in wastewater, presenting challenges for biodegradation, particularly in low-carbon environments. Supplementing additional carbon sources not only provides essential nutrients for microbial growth but also serves as regulators, influencing adaptive changes in biofilm and enhancing the survival of microorganisms in organosulfur-induced stress bioreactors. This study aims to elucidate the biodegradation of organosulfur under varying carbon source levels, placing specific emphasis on functional bacteria and metabolic processes. It has been observed that higher levels of carbon supplementation led to significantly improved total sulfur (TS) removal efficiencies, exceeding 83 %, and achieve a high organosulfur CH3SH removal efficiency of ~100 %. However, in the reactor with no external carbon source added, the oxidation end-product SO42− accumulated significantly, surpassing 120 mEq/m2-day. Furthermore, the TB-EPS concentration consistently increasedwith the ascending glucose concentration. The analysis of bacterial community reveals the enrichment of functional bacteria involved in sulfur metabolism and biofilm formation (e.g. Ferruginibacter, Rhodopeudomonas, Gordonia, and Thiobacillus). Correspondingly, the gene expressions related to the pathway of organosulfur to SO42− were notably enhanced (e.g. MTO increased by 27.7 %). In contrast, extra carbon source facilitated the transfer of organosulfur into amino acids in sulfur metabolism and promoted assimilation. These metabolic insights, coupled with kinetic transformation results, further validate distinct sulfur pathways under different carbon source conditions. The intricate interplay between bacteria growth regulation, pollutant biodegradation, and microbial metabolites underscores a complex network relationship that significantly contributes to efficient operation of bioreactors.

The spatio-temporal evolution of spatial structure and supply-demand relationships of the ecological network in the Yellow River Delta region of China

Rapid urbanization has caused unregulated transformation of land use/land cover, further exacerbating the imbalance in ecological supply-demand relationships. Constructing the ecological supply-demand network by integrating natural ecological processes and human ecological demands into a unified spatio-temporal framework and considering their internal dynamic flow characteristics is an effective approach to address this issue. However, there is currently a lack of evaluation methods for the coordination of ecological network supply-demand relationships, which could provide essential guidance and reference. This article takes Yellow River Delta region (YRDR) as an example and utilizes the integrated traditional ecological network paradigm and ecosystem services theory to simulate the ecological supply-demand network for the years 2000, 2010, and 2020 in the study area. Then, a novel evaluation index system for the ecological network supply-demand relationships was proposed from the perspectives of intensity, capacity, and equilibrium. Based on this, combined with a graph-based network structure evaluation system, it reveals the spatio-temporal evolution process of the spatial structure and supply-demand relationship of the ecological network in the study area. The study results showed that: (1) The quantity of elements in the ecological supply network and the demand network show opposite trends, leading to an exacerbation of the spatial imbalance in the arrangement of ecological supply-demand network elements. (2) Although the structural changes in the ecological supply network were significantly greater than those in the ecological demand network, the overall structure of the ecological supply-demand network gradually improved. (3) However, under the coupled influence of imbalanced change in the spatial distribution and connectivity of ecological elements, the overall coordination of the ecological supply-demand relationships within the YRDR's ecological network is gradually deteriorating. (4) The proposed optimization strategy, "Two zones, Three belts, Four corridors", for the ecological security pattern in YRDR can accommodate the ecological process cycle and human ecological demand. This study can provide scientific references for "harmonious coexistence between humans and nature" ecological protection and sustainable development planning under the background of rapid urbanization.

Quality-driven sustainability in Jordan’s food export supply chains

Purpose This paper aims to address the imperative of establishing adaptive sustainable supply chain management (SSCM) within the context of export food supply chains (EFSC) in Jordan, with potential global applicability. The research introduces a new conceptual framework validated through the analytic hierarchy process (AHP), prioritizing critical factors based on five expert opinions. The practical and managerial outcomes emphasize achieving sustainable supply chain performance through quality-driven sustainability (QDS), encapsulated in a practical framework (SSCQM). Employing the concept of QDS, this study aims to develop a novel decision framework for Sustainable Supply Chain Quality Management (SSCQM). Design/methodology/approach Conducted as an empirical qualitative study in Jordan, the research employs a systematic literature review to identify research gaps and establish the initial conceptual framework. A pilot case is subsequently conducted to refine the framework, followed by Case Studies of four Triads, elucidating network relationships between suppliers, manufacturers and customers. A total of 32 semi-structured interviews, complemented by observations, tours and document analysis, individually explored each case during the exploratory stage. Cross-analysis of the four cases at the explanatory stage provides empirical insights, and data triangulation, literature review and validation using NVivo enhance the robustness of the findings. Findings The amalgamation of the three perspectives, when treated individually, results in the integrated category of QDS influencing sustainability (SUST) performance, evident in economic, environmental and social dimensions. Various sustainable initiatives have emerged through the relationships within the Triad, comprising a company, supplier and customer in the supply chain and its broader environment, including society, aiming for enhanced sustainable development and SUST performance. Recognizing the urgency of Supply Chain Management (SCM) in the Middle East, where global supply chains are susceptible to disruptions leading to food shortages and insecurity, this research investigates the state of EFSC in the export food industry in Jordan. The novel decision (SSCQM) framework equips managers and policymakers with knowledge and practices applicable to focal actors in Triads within their EFSCs, particularly in developing countries, thereby contributing to enhancing the export food industry’s sustainability. Research limitations/implications This research provides empirical and contextual justifications for the supply chain-quality model (SSCQM) that advocates for business organizations how a desirable, sizeable and significant outcome/shock can be triggered via embedding quality elements in an international supply chain specifically in Jordan. The research also offers significant implications for practising supply chain experts in terms of how they can effectively utilize the supply chain quality to align other players in the supply chain, revenue potential, customer retainability and employee retention to achieve superior organizational performance. The research selectively encompasses three key perspectives of supply chain networks (SCN), total quality management (TQM) and SUST to elucidate the essence of SCM. Originality/value This research contributes towards filling the gap as a lack of empirical research.

Revealing academic networks’ impact: driving innovation in Chinese high-tech enterprises

ABSTRACT Innovation is a critical aspect in China’s development as a great modern socialist country and in realizing its second-century goals. As key decision-makers in enterprises, the academic network resources carried by senior executives are seldom noticed. This study is going to explore whether senior executives’ academic network relationships (i.e. senior executives are or were employed by universities or research institutions) will spur corporate innovation performance. Drawing on panel data from Chinese A-share high-tech listed companies from 2014 to 2021, the study examines this relationship through multiple linear regression analysis and investigates the mediating role of R&D manipulation in this connection. The results of the study show that the more academic network relationships embedded in senior executives, the better the high-tech firms’ innovation performance. Additionally, R&D manipulation serves as an intermediary factor between senior executives’ academic network relationships and corporate innovation performance. Furthermore, when these individuals hold key positions and have a higher level of academic background, the facilitating effect of senior executives’ academic network relationships is more pronounced. This study broadens the application scope of social network theory and provides valuable insights for high-tech companies aiming to augment their knowledge-based innovation performance and refine their managerial recruitment strategies.

Five commonly used traditional Chinese medicine formulas in the treatment of ulcerative colitis: A network meta-analysis.

Currently, traditional Chinese medicine (TCM) formulas are commonly being used as adjunctive therapy for ulcerative colitis in China. Network meta-analysis, a quantitative and comprehensive analytical method, can systematically compare the effects of different adjunctive treatment options for ulcerative colitis, providing scientific evidence for clinical decision-making. To evaluate the clinical efficacy and safety of commonly used TCM for the treatment of ulcerative colitis (UC) in clinical practice through a network meta-analysis. Clinical randomized controlled trials of these TCM formulas used for the adjuvant treatment of UC were searched from the establishment of the databases to July 1, 2022. Studies that met the inclusion criteria were screened and evaluated for literature quality and risk of bias according to the Cochrane 5.1 standard. The methodological quality of the studies was assessed using ReviewManager (RevMan) 5.4, and a funnel plot was constructed to test for publication bias. ADDIS 1.16 statistical software was used to perform statistical analysis of the treatment measures and derive the network relationship and ranking diagrams of the various intervention measures. A total of 64 randomized controlled trials involving 5456 patients with UC were included in this study. The adjuvant treatment of UC using five TCM formulations was able to improve the clinical outcome of the patients. Adjuvant treatment with Baitouweng decoction (BTWT) showed a significant effect [mean difference = 36.22, 95% confidence interval (CI): 7.63 to 65.76]. For the reduction of tumor necrosis factor in patients with UC, adjunctive therapy with BTWT (mean difference = -9.55, 95%CI: -17.89 to -1.41), Shenlingbaizhu powder [SLBZS; odds ratio (OR) = 0.19, 95%CI: 0.08 to 0.39], and Shaoyao decoction (OR = -23.02, 95%CI: -33.64 to -13.14) was effective. Shaoyao decoction was more effective than BTWT (OR = 0.12, 95%CI: 0.03 to 0.39), SLBZS (OR = 0.19, 95%CI: 0.08 to 0. 39), and Xi Lei powder (OR = 0.34, 95%CI: 0.13 to 0.81) in reducing tumor necrosis factor and the recurrence rate of UC. TCM combined with mesalazine is more effective than mesalazine alone in the treatment of UC.

Nanoplastics exposure simplifies the network structure of sea cucumber (Apostichopus japonicus) gut microbiota and improves cluster randomness

Nanoplastics (NPs) are abundant in ocean environments, leading to environmental pollution and notable disruptions to the physiological functions of marine animals. To investigate the toxic effects of NPs on echinoderms, specifically sea cucumbers (Apostichopus japonicus), they were exposed to varying concentrations of NPs (0, 102, 104 particles/L) for 14 d. Subsequently, the 102 particles/L exposure group was purified for 35 d to elucidate the impact of both NPs exposure and purification on the intestinal bacteria structure and function. The results showed that the richness and variety of intestinal bacteria in sea cucumbers significantly reduced under NPs exposure, and then they could be restored to the pre-exposure treatment state after 35 d of purification. With the increase of NPs exposure concentration in the environment, the intestinal core bacteria gradually changed from Firmicutes and Proteobacteria to Pseudoalteromonas and Vibrio. The KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway database annotated that the gut microbiota of sea cucumbers was significantly downregulated in the glycosylation, carbohydratic and amino acid metabolic pathways (P < 0. 05), exogenous substance biodegradation and metabolism, DNA replication and repair pathways were significantly up-regulated (P < 0.05) under the exposure of NPs. In addition, nanoplastics exposure simplified the symbiotic network relationships of the gut bacteria, reduced the selective effect of host on the intestinal bacteria, and increased stochasticity. In conclusion, waterborne NPs can adversely affect the structure and function of sea cucumber intestinal bacteria, with these effects persisting for a duration. However, as the purification time lengthens, these adverse effects gradually diminish. This study aims to provide some theoretical basis for the biotoxic effects of NPs.

Root-soil-microbiome interaction in the rhizosphere of Masson pine (Pinus massoniana) under different levels of heavy metal pollution

Heavy metal pollution of the soil affects the environment and human health. Masson pine is a good candidate for phytoremediation of heavy metal in mining areas. Microorganisms in the rhizosphere can help with the accumulation of heavy metal in host plants. However, studies on its rhizosphere bacterial communities under heavy metal pollution are still limited. Therefore, in this study, the chemical and bacterial characteristics of Masson pine rhizosphere under four different levels of heavy metal pollution were investigated using 16 S rRNA gene sequencing, soil chemistry and analysis of plant enzyme activities. The results showed that soil heavy metal content, plant oxidative stress and microbial diversity damage were lower the farther they were from the mine dump. The co-occurrence network relationship of slightly polluted soils (C1 and C2) was more complicated than that of highly polluted soils (C3 and C4). Relative abundance analysis indicated Sphingomonas and Pseudolabrys were more abundant in slightly polluted soils (C1 and C2), while Gaiella and Haliangium were more abundant in highly polluted soils (C3 and C4). LEfSe analysis indicated Burkholderiaceae, Xanthobacteraceae, Gemmatimonadaceae, Gaiellaceae were significantly enriched in C1 to C4 site, respectively. Mantel analysis showed that available cadmium (Cd) contents of soil was the most important factor influencing the bacterial community assembly. Correlation analysis showed that eight bacterial genus were significantly positively associated with soil available Cd content. To the best of our knowledge, this is the first study to investigate the rhizospheric bacterial community of Masson pine trees under different degrees of heavy metal contamination, which lays the foundation for beneficial bacteria-based phytoremediation using Masson pines in the future.

Mobile genetic elements define the non-random structure of the Salmonella enterica serovar Typhi pangenome.

Bacterial relatedness measured using select chromosomal loci forms the basis of public health genomic surveillance. While approximating vertical evolution through this approach has proven exceptionally valuable for understanding pathogen dynamics, it excludes a fundamental dimension of bacterial evolution-horizontal gene transfer. Incorporating the accessory genome is the logical remediation and has recently shown promise in expanding epidemiological resolution for enteric pathogens. Employing k-mer-based Jaccard index analysis, and a novel genome length distance metric, we computed pangenome (i.e., core and accessory) relatedness for the globally important pathogen Salmonella enterica serotype Typhi (Typhi), and graphically express both vertical (homology-by-descent) and horizontal (homology-by-admixture) evolutionary relationships in a reticulate network of over 2,200 U.S. Typhi genomes. This analysis revealed non-random structure in the Typhi pangenome that is driven predominantly by the gain and loss of mobile genetic elements, confirming and expanding upon known epidemiological patterns, revealing novel plasmid dynamics, and identifying avenues for further genomic epidemiological exploration. With an eye to public health application, this work adds important biological context to the rapidly improving ways of analyzing bacterial genetic data and demonstrates the value of the accessory genome to infer pathogen epidemiology and evolution.IMPORTANCEGiven bacterial evolution occurs in both vertical and horizontal dimensions, inclusion of both core and accessory genetic material (i.e., the pangenome) is a logical step toward a more thorough understanding of pathogen dynamics. With an eye to public, and indeed, global health relevance, we couple contemporary tools for genomic analysis with decades of research on mobile genetic elements to demonstrate the value of the pangenome, known and unknown, annotated, and hypothetical, for stratification of Salmonella enterica serovar Typhi (Typhi) populations. We confirm and expand upon what is known about Typhi epidemiology, plasmids, and antimicrobial resistance dynamics, and offer new avenues of exploration to further deduce Typhi ecology and evolution, and ultimately to reduce the incidence of human disease.

A dual-level consensus model for large-scale group decision-making driven by trust relationships in social networks

In large-scale group decision-making, obtaining reasonable and reliable decision results is the research focus. To this end, a dual-level consensus model for large-scale group decision-making is constructed. In the model, we first presented a method for measuring the two-dimensional similarity between decision-makers. The method considered the opinion similarity at evaluation scales and ranking results level, which provided a more comprehensive measure of the opinion differences between decision-makers. A hierarchical clustering algorithm based on the two-dimensional similarity-trust matrix is proposed. By considering the two-dimensional similarity and trust relationships among decision-makers, the method contributed to the formation of subgroups with excellent cooperative and communicative atmospheres. Furthermore, we introduced a dual-level consensus measures method to comprehensively and accurately assess the group consensus level. To increase the efficiency of decision-making and the satisfaction of decision-makers, we proposed a personalized feedback adjustment mechanism for decision-makers. Additionally, for the subgroups that have not reached consensus, a social networks DeGroot model is constructed to adjust the opinion of subgroups. Finally, a case study of low-carbon supplier selection verified the feasibility and applicability of the model. The effectiveness and superiority of the model are demonstrated by comparative and simulation analysis. The analysis results show that the model is conducive to promoting cooperation and coordination among decision-makers and obtaining highly acceptable and quality decision results.

Research on Identification of the Capacity Influencing Factors of Youth Sports Clubs in China

Since the 1970s, nonprofit organizations have identified organizational capacity as the key to improving organizational effectiveness. Youth sports clubs have long been trapped in a predicament that makes it difficult for them to keep non-profit nature, operate independently and maintain high performance for a long time. This study investigates which influencing factors can act on the capacity of youth sports clubs to ensure their non-profit nature whilst achieving healthy and sustainable development. The organizational theory systems view emphasizes the relationship between open internal structures and the role of external environmental factors, therefore the capacity influencing factors of youth sports clubs can be comprehensively considered to achieve this by considering both the internal and external influencing components of organizational capacity. The focus of this study was obtained by searching 11 relevant policy documents, 21 papers, and in-depth interviews with 26 experts including youth sports club managers, coaches, and venue management personnel and scholars studying in the field of youth sports research or practice. The study revealed the internal and external influences on youth sports club capabilities, including strategic leadership, service innovation, resource acquisition, network relationships, policy, social media, and environmental uncertainty; and constructed a relationship between internal and external influences on youth sports club capabilities and organizational effectiveness. In addition, we found that Social media had the highest weight, policy had the lowest weight, and the rest of the influences did not differ significantly by the method of the weight calculation. We recommend that youth sports clubs increase the application of social media, stimulate employees&amp;apos; service and innovation ability, and cultivate the strategic leadership ability of leaders.

A Large-Scale Group Decision-Making Model Considering Expert Authority Degree and Relationship Evolution Under Social Network

In Large-Scale Group Decision-Making (LSGDM), effectively implementing consensus models is pivotal for managing decision complexity. While trust-based LSGDM has garnered attention, there remains a need for deeper insights into the dynamics of interexpert trust and the impact of authority effects on the decision-making process. This study introduces a sophisticated model for large-scale group decision-making, incorporating considerations of expert “trustworthiness-authority.” Initially, the study assesses the trustworthiness of experts based on social network relationships and opinion similarity while using background information and consensus levels to establish their authority. Subsequently, experts are categorized into four distinct regions based on their trustworthiness and authority assessments. Furthermore, tailored consensus adjustment methods are proposed for each region based on social contagion theory to facilitate consensus achievement. Additionally, a case study is conducted to demonstrate the rationality and effectiveness of the proposed LSGDM model, considering expert “trustworthiness-authority.” Finally, the necessity and superiority of the proposed model are further verified through comparison analysis and sensitivity analysis.