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In this study, the authors sought to investigate how the implicit social ties of both project owners and potential backers are associated with crowdfunding project success.

Drawing on social ties theory and factors that affect crowdfunding success, in this research, the authors developed a model to study how project owners' and potential backers' implicit social ties are associated with crowdfunding projects' degrees of success. The proposed model was empirically tested with crowdfunding data collected from Kickstarter and social media data collected from Twitter. The authors performed the test using an ordinary least squares (OLS) regression model with fixed effects.

The authors found that project owners' implicit social ties (specifically, their social media activities, degree centrality and betweenness centrality) are significantly and positively associated with crowdfunding projects' degrees of success. Meanwhile, potential project backers' implicit social ties (their social media activities and degree centrality) are negatively associated with crowdfunding projects' degrees of success. The authors also found that project size moderates the effects of project owners' social media activities on projects' degrees of success.

This work contributes to the literature on crowdfunding by investigating how the implicit social ties of both potential backers and project owners on social media are associated with crowdfunding project success. This study extends the previous research on social ties' roles in explaining crowdfunding project success by including implicit social ties, while the literature explored only explicit social ties.

Networks linking tourist attractions or organizations are a major focus of tourism research. Despite extensive research on tourism networks, academic research on the spatial structure and formation of wine tourism networks is limited. This study aims to investigate the spatial structure and factors influencing the development of a network among Ningxia wineries, an emerging wine tourism destination in China.

This study uses social network analysis to uncover “what” the spatial structure of wine tourism networks looks like. Sixteen in-depth interviews were conducted among key stakeholders to explain the “why” of such structural characteristics.

The results show that in an emerging wine tourism destination, popular tourist attractions enjoy high centrality and hold key positions in the wine tourism network. Small wineries exhibit high closeness centrality, and only one winery serves as a network broker. According to the stakeholders, the importance of network actors will increase as their economic and political importance increase, while small wineries that lack differentiation in the network may perish.

Local governments can implement the suggested measures for improving network connections, and wineries are advised to find suitable positions to improve the experiences of tourists.

This study pioneers the identification of the distinct structure and factors influencing the network of an emerging wine tourism destination, thus enriching the understanding of the interplay and roles of different actors.

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.

With the development of science and technology, more creators are trying to use new crafts to represent the cultural trends of the social media era, which makes cultural heritage innovative and new genres emerge. This compels the academic community to examine craft from a new perspective. It is very helpful to understand the hidden representational structure of craft more deeply and improve the craft innovation system of cultural and creative products that we deconstruct the craft based on Complex Network and discover its intrinsic connections.

The research crawled and cleaned the craft information of the top 20% products on the Forbidden City’s cultural and creative products online and then performed Complex Network modeling, constructed three craft representation networks among function, material and technique, quantified and analyzed the inner connections and network structure of the craft elements, and then analyzed the cultural inheritance and innovation embedded in the craft representation networks.

The three dichotomous craft representation networks constructed by combining function, material and technique: (1) the network density is low and none of them has small-world characteristics, indicating that the innovative heritage of the craft elements in the Forbidden City’s cultural and creative products is at the stage of continuous exploration and development, and multiple coupling innovation is still insufficient; (2) all have scale-free characteristics and there is still a certain degree of community structure within each network, indicating that the coupling innovation of craft elements of the Forbidden City’s cultural and creative products is seriously uneven, with some specific “grammatical combinations” and an Island Effect in the network structure; (3) the craft elements with high network centrality emphasize the characteristics of decorative culture and design for the masses, as well as the pursuit of production efficiency and economic benefits, which represent the aesthetic purport of contemporary Chinese society and the ideological trend of production and life.

The Forbidden City’s cultural and creative products should continue to develop and enrich the multi-coupling innovation of craft elements, clarify and continue their own brand unique craft genes, and make full use of the network important nodes role.

This study aims to model tourist activities in a network and explore the properties of the network. Such network enables the author to explain and quantify how tourist activities are connected in determining tourist consumption as well as the organization of destination supply.

The author developed a network formation mechanism to create edges between nodes based on the joint probability of a pair of activities undertaken by tourists at a destination. By adjusting network sparsity, the author created an ensemble of four topologically similar networks for empirical testing. The author used tourist activity data of Hong Kong inbound tourists to test the network model.

The author found a robust hub–periphery topological structure of the tourist activity network. In addition, the network is featured by high clustering, short diameter and positive correlations between four node centralities, namely, degree, closeness, betweenness and eigenvector centralities. The author also generated the k-cores of the networks to further unravel the structure of hub nodes. The author found that the k-cores are dominated by tourist activities related to shopping or sightseeing, suggesting the high complementarity of these activities.

This study provides a different lens through which tourist consumption can be understood from a macroscopic angle by examining network topology and from a microscopic angle by examining node centralities.

To the best of the author’s knowledge, this is the first study attempting to model tourist activity and consumption in a network and explore the properties of the network. Not only has this study provided a new real-world network for network research, but it has also suggested an innovative modeling approach for tourist behavior research.

This study aims to develop the alleviating bullwhip effects framework (ABEF) replenishment rules, and bullwhip, inventory fluctuations and customer service fulfilment rates were examined. In addition, automated smoothing and replenishment rules can alleviate supply chain bullwhip effects. This study aims to understand the current artificial intelligence (AI) implementation practice in alleviating bullwhip effects in supply chain management. This study aimed to develop a system for writing reviews using a systematic approach.

The methodology for the present study consists of three parts: Part 1 deals with the systematic review process. In Part 2, the study applies social network analysis (SNA) to the fourth phase of the systematic review process. In Part 3, the author discusses developing research clusters to analyse the research state more granularly. Systematic literature reviews synthesize scientific evidence through repeatable, transparent and rigorous procedures. By using this approach, you can better interpret and understand the data. The author used two databases (EBSCO and World of Science) for unbiased analysis. In addition, systematic reviews follow preferred reporting items for systematic reviews and meta-analyses.

The study uses UCINET6 software to analyse the data. The study found that specific topics received high centrality (more attention) from scholars when it came to the study topic. Contrary to this, others experienced low centrality scores when using NETDRAW visualization graphs and dynamic capability clusters. Comprehensive analyses are used for the study’s comparison of clusters.

This study used a journal publication as the only source of information. Peer-reviewed journal papers were eliminated for their lack of rigorousness in evaluating the state of practice. This paper discusses the bullwhip effect of digital technology on supply chain management. Considering the increasing use of “AI” in their publications, other publications dealing with sensor integration could also have been excluded. To discuss the top five and bottom five topics, the author used magazines and tables.

The study explores the practical implications of smoothing the bullwhip effect through AI systems, collaboration, leadership and digital skills. Artificial intelligence is rapidly becoming a preferred tool in the supply chain, so management must understand the opportunities and challenges associated with its implementation. Furthermore, managers should consider how AI can influence supply chain collaboration concerning trust and forecasting to smooth the bullwhip effect.

Digital leadership and addressing the digital skills gap are also essential for the success of AI systems. According to the framework, it is necessary to balance AI performance and accountability. As a result of the framework and structured management approach, the author can examine the implications of AI along the supply chain.

The study uses a systematic literature review based on SNA to analyse how AI can alleviate the bullwhip effects of supply chain disruption and identify the focused and the most important AI topics related to the bullwhip phenomena. SNA uses qualitative and quantitative methodologies to identify research trends, strengths, gaps and future directions for research. Salient topics for reviewing papers were identified. Centrality metrics were used to analyse the contemporary topic’s importance, including degree, betweenness and eigenvector centrality. ABEF is presented in the study.

The purpose of this article is to explore the association of the Relational Capital (RC) embedded in a medical specialist’s social–professional network with the specialist’s economic performance based on social network analysis (SNA).

Using health insurance claims data regarding ∼108,000 physicians treating ∼72,000,000 patients, social–professional networks (patient-sharing-networks (PSNs)) of ∼26,000 medical specialists were simulated. To explore the correlation of the network's characteristics (degree centrality, density, relative betweenness centrality and referrer concentration) with economic performance, ordinary-least-squares (OLS)-regression models were estimated for ten common specialties (gynecology, internal medicine, orthopedics, ophthalmology, otolaryngology, dermatology, urology, neurology, radiology and rehabilitative medicine).

The study confirms the applicability and strong explanatory power of SNA metrics for RC measurement in ambulatory healthcare. Degree centrality and relative betweenness centrality correlate positively with economic performance, whereas density and referrer concentration exhibit negative coefficients. These results confirm the argument that RC has a strong association with the economic performance of medical specialists.

The study pioneers SNA for RC measurement in healthcare. It is among the first publications on specialists' PSNs. Questions for future research are proposed.

This paper presents a comprehensive study using bibliometric and social network analysis (SNA) to depict the academic community, research hotspots and the correlation between research performance and social network measurements within Library Hi Tech.

Publications from Library Hi Tech between 2010 and 2022 are reviewed and analysed through coauthorship analysis, co-occurrence analysis, SNA and the Spearman rank correlation test.

The annual number of publications in Library Hi Tech increased from 2016 to 2022, indicating that this research has gradually gained global attention. The USA and China are the most significant contributors to the relevant publications. Scholars in this field mainly engage in small-scale cooperation. Academic libraries, digital libraries, libraries, information technology and COVID-19 were hot topics during the study period. In light of the COVID-19 pandemic, there was a marked increase in research on healthcare. Academic interest in the internet of Things and social media has proliferated recently and may soon attract more attention. Spearman rank correlation analysis shows that research performance (i.e. publication count and citation count) is significantly and positively correlated with social network measurements (i.e. degree centrality, betweenness centrality, closeness centrality and eigenvector centrality) in studies of Library Hi Tech.

This paper reveals a systematic picture of the research landscape of Library Hi Tech and provides a potential guide for future research. The relationship between scientific research performance and social network measurements can be objectively identified based on statistical knowledge.

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.

The purpose of this paper is to conceptualize the notion of thin crossing points from a social network perspective and to outline the concrete networking strategies that enable salespeople to foster mutually valuable resource exchange (i.e. to thin crossing points) across a selling ecosystem.

The authors integrate extant theoretical perspectives to advance a conceptual framework of sales-related networking across three key actors in a selling ecosystem: intraorganizational selling actors and actors in customers and external partner organizations.

Thin crossing points are defined as figurative transaction points at the boundary between organizations or organizational subunits at which actors engage in mutually valuable resource exchange in the process of value cocreation. To thin crossing points with key ecosystem actors, salespeople must adapt networking strategies considering the time and trust constraints inherent in a network relationship. Such constraints inform the most advantageous network centralities (degree, eigenvector and betweenness) and actions to impact key network properties (tie strength, contact diversity) that enable salespeople to efficiently develop social capital and thus to optimally thin crossing points across a selling ecosystem.

To the best of the authors’ knowledge, this study is the first social network-based exploration of salespeople’s role in thinning crossing points with key ecosystem actors. It advances a novel conceptual framework of sales-related networking strategies that foster social capital development and optimally thin crossing points across a selling ecosystem.