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The consulting team intervenes in the integrated construction consulting (ICC) network structure centered on “client-contractor-consultant.” Team boundary-spanning behavior (TBB) driven by the network structure is crucial to project performance. This article investigated how to stimulate the consulting project performance (CPP) improvement by considering the interactive effect of network structure and TBB. To be specific, this paper explored the configuration between structural characteristics of project networks, the dimension of TBB, and project performance in ICC projects.

Network density and centrality were used to reflect network structure. This study collected 216 valid responses from construction professionals (including project managers, department managers, and project engineers) via a questionnaire survey and analyzed the data using fsQCA.

Combining with the corresponding typical project case and analysis, the results concluded four types of configurations for achieving high performance in the ICC projects. Meanwhile, network centrality, density, ambassadorial behavior, coordination behavior, and detection behavior significantly impact high consulting project performance. Matching ICC network characteristics with the TBB is important. There are also three low performance configurations for the ICC projects. Low performance state also occurs when network centrality or density and coordination behavior is simultaneously low. Only the right match between the network characteristics and TBB can produce high consulting project performance.

The network centrality and density, the implementation of TBB vary, and the paths to achieve high consulting project performance are different. Clients, ICC projects, and consulting teams should choose the appropriate development paths according to the actual situation. (1) Clients should commit to applying the ICC project model with high network centrality, density, and coordination behavior of ICC enterprises to promote project performance. (2) Consulting enterprises should carry out ICC business based on detecting behavior and coordinating behavior. (3) The market should cultivate head consulting enterprises with independence and integration, and bring into play the effectiveness of consulting team ambassadorial behavior.

Comparing the results of the four high CPP configurations, the network structure characteristics are essential, which means that in the Chinese consulting practice between the owner and the consulting firm pay attention to the use of appropriate ICC organizational structure model and arrange the degree of centralization of authorized responsibilities. Coordination behavior is necessary to achieve high CPP. Therefore, Chinese consulting firms should pay attention to effective communication and exchange with project contractors in order to get high CPP in conducting business; meanwhile, enabling behavior can achieve high CPP both in the presence and absence of configuration H1 and H4, which indicates that enabling behavior has substitution effect. Comparing the three low CPP configurations also contrarily confirms the indispensability of coordinating behavior. Comparing the results of high and low CPP configurations, the TBB is seriously missing and not properly applied in CPP enhancement. In detail, Chinese consulting firms have been regarded as independent third parties providing services, and less attention has been paid to the TBB of Chinese consulting firms in past practice, thus leading to the dilemma of inadequate empowerment of consulting firms due to their unclear status. To solve this dilemma, the findings of this paper offer a solution at the micro level to change the previous perception of consulting and demonstrate that Chinese consulting practice needs to pay attention to TBB with owners and contractors, and apply it well to enhance the reputation, management consulting level and capability, and experience and expertise of consulting firms to achieve high CPP.

The research results changed from the previous bilateral project governance to a new perspective of network embedding. It provided a theoretical basis for the improvement path of high consulting project performance, as well as providing ideas for clients on the organizational design of ICC projects. On the other hand, it provided a practical reference for TBB positioning of ICC enterprises for transformation and upgrading development.

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.

This study proposes a novel method utilising a speech-word pair bipartite network to examine the correlation structure between members of parliament (MPs) in the context of the UK- China relationship.

We construct MP-word pair bipartite networks based on the co-occurrence relationship between MPs and words in their speech content. These networks are then mapped into monopartite MPs correlation networks. Additionally, the study calculates correlation network indicators and identifies MP communities and factions to determine the characteristics of MPs and their interrelation in the UK-China relationship. This includes insights into the distribution of key MPs, their correlation structure and the evolution and development trends of MP factions.

Analysis of the parliamentary speeches on China-related affairs in the British Parliament from 2011 to 2020 reveals that the distribution and interrelationship of MPs engaged in UK-China affairs are centralised and discrete, with a few core MPs playing an integral role in the UK-China relationship. Among them, MPs such as Lord Ahmad of Wimbledon, David Cameron, Lord Hunt of Chesterton and Lord Howell of Guildford formed factions with significant differences; however, the continuity of their evolution exhibits unstableness. The core MP factions, such as those led by Lord Ahmad of Wimbledon and David Cameron, have achieved a level of maturity and exert significant influence.

The research has several limitations that warrant acknowledgement. First, we mapped the MP-word pair bipartite network into the MP correlation network for analysis without directly analysing the structure of MPs based on the bipartite network. In future studies, we aim to explore various types of analysis based on the proposed bipartite networks to provide more comprehensive and accurate references for studying UK-China relations. In addition, we seek to incorporate semantic-level analyses, such as sentiment analysis of MPs, into the MP-word -pair bipartite networks for in-depth analysis. Second, the interpretations of MP structures in the UK-China relationship in this study are limited. Consequently, expertise in UK-China relations should be incorporated to enhance the study and provide more practical recommendations.

Firstly, the findings can contribute to an objective understanding of the characteristics and connotations of UK-China relations, thereby informing adjustments of focus accordingly. The identification of the main factions in the UK-China relationship emphasises the imperative for governments to pay greater attention to these MPs’ speeches and social relationships. Secondly, examining the evolution and development of MP factions aids in identifying a country’s diplomatic focus during different periods. This can assist governments in responding promptly to relevant issues and contribute to the formulation of effective foreign policies.

First, this study expands the research methodology of parliamentary debates analysis in previous studies. To the best of our knowledge, we are the first to study the UK-China relationship through the MP-word-pair bipartite network. This outcome inspires future researchers to apply various knowledge networks in the LIS field to elucidate deeper characteristics and connotations of UK-China relations. Second, this study provides a novel perspective for UK-China relationship analysis, which deepens the research object from keywords to MPs. This finding may offer important implications for researchers to further study the role of MPs in the UK-China relationship.

This study proposes a novel scheme for analysing the correlation structure between MPs based on bipartite networks. This approach offers insights into the development and evolving dynamics of MPs.

A small-world network is a type of network structure in which nodes are highly clustered and at short distances without being directly linked. This article analyzes whether the network of interlocking directorates among the largest Brazilian corporations follows a small-world network structure and if the small-world properties (high clustering and short distance between nodes) influence the occurrence of M&A at the domestic and international level.

The authors tested hypotheses regarding the relationship between small-world network properties and M&A based on a sample of large publicly-listed corporations in Brazil for the time series of 2000–2015 and using network analysis and regression techniques (probit and OLS).

The results show that while the Brazilian corporate network fits the small-world features of high clustering and short path lengths, only the distance among connected firms has a significant effect on international M&A: the shorter the distance between firms, the more likely firms undertake M&A abroad. Moreover, being integrated into the main component has a significant positive effect on national and international M&A. These findings suggest that the information and knowledge to undertake M&A can be better acquired by belonging to large business communities and not local cohesive clusters.

This research contributes to theories and ongoing debates about the network effects on organizational decisions and the determinants of M&A in emerging markets. In addition, this is the first study to analyze the impact of small-world networks on international M&A while controlling for country-level variables.

This paper explains why some firms manage to capture disproportionate value from their network of relationships, leading to superior performance. The paper examines how a firm's dependencies affect its value appropriation potential (VAP) in economic networks.

The paper follows the axiomatic method and the embeddedness perspective of firms to develop an index called nodal power, which captures the power that accrues to a firm in exchange-based economic networks. Thereafter, using the formal method and simulation, it shows nodal power reflects a firm's VAP in economic networks.

The study analysis and findings prove that a firm's dyadic level exchange relations and the embedded network structure determine its VAP by affecting the nodal power. A firm with lesser nodal power is likely to appropriate less value from its relations even if it equally contributes to the value creation. This finding explains how the structural and relational characteristics of a firm's network enable disproportionate value appropriation.

Nodal power furthers the scope of analyzing firms' economic relationships and changing power equations in dynamic networks. It can help firms build optimal strategic networks and manage the portfolio of relationships by predicting the impact of changing relations on firms' VAP.

The paper's original contribution is to explain, through formal analysis, why and how the structure and nature of relations of firms affect their VAP. The paper also formalizes the power-dependence principle through a dependency-based index called nodal power and uses it to show how interfirm dependencies are key to value appropriation.

Cross-laminated timber (CLT) is an innovative construction material that provides a balanced mix of structural stiffness, fabrication flexibility and sustainability. CLT development and innovation diffusion require close collaborations between its supply chain architectural, engineering, construction and manufacturing (AECM) stakeholders. As such, the purpose of this study is to provide a preliminary understanding of the knowledge diffusion and innovation process of CLT construction.

The study implemented a longitudinal social network analysis of the AECM companies involved in 100 CLT projects in the UK. The project data were acquired from an industry publication and decoded in the form of a multimode project-company network, which was projected into a single-mode company collaborative network. This complete network was filtered into a four-phase network to allow the longitudinal analysis of the CLT collaborations over time. A set of network and node social network analysis metrics was used to characterize the topology patters of the network and the centrality of the companies.

The study highlighted the scale-free structure of the CLT collaborative network that depends on the influential hubs of timber manufacturers, engineers and contractors to accelerate the innovation diffusion. However, such CLT supply collaborative network structure is more vulnerable to disruptions due to its dependence on these few prominent hubs. Also, the industry collaborative network’s decreased modularity confirms the maturity of the CLT technology and the formation of cohesive clusters of innovation partners. The macro analysis approach of the study highlighted the critical role of supply chain upstream stakeholders due to their higher centralities in the collaborative network. Stronger collaborations were found between the supply chain upstream stakeholders (timber manufacturers) and downstream stakeholders (architects and main contractors).

The study contributes to the field of industrialized and CLT construction by characterizing the collaborative networks between CLT supply chain stakeholders that are critical to propose governmental policies and industry initiatives to advance this sustainable construction material.

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.

The purpose of this paper is to explore the dynamic interdependence structure and risk spillover effect between the Chinese stock market and the US stock market.

This paper mainly uses the multivariate R-vine copula-complex network analysis and the multivariate R-vine copula-CoVaR model and selects stock price indices and their subsector indices as samples.

The empirical results indicate that the Energy, Materials and Financials sectors have leading roles in the interdependent structure of the Chinese and US stock markets, while the Utilities and Real Estate sectors have the least important positions. The comprehensive influence of the Chinese stock market is similar to that of the US stock market but with smaller differences in the influence of different sectors of the US stock market on the overall interdependent structure system. Over time, the interdependent structure of both stock markets changed; the sector status gradually equalized; the contribution of the same sector in different countries to the interdependent structure converged; and the degree of interaction between the two stock markets was positively correlated with the degree of market volatility.

This paper employs the methods of nonlinear cointegration and the R-vine copula function to explore the interactive relationship and risk spillover effect between the Chinese stock market and the US stock market. This paper proposes the R-vine copula-complex network analysis method to creatively construct the interdependent network structure of the two stock markets. This paper combines the generalized CoVaR method with the R-vine copula function, introduces the stock market decline and rise risk and further discusses the risk spillover effect between the two stock markets.

This study aims to propose a combined effect framework to explore the relationship between research and development (R&D) team networks, knowledge diversity and breakthrough technological innovation. In contrast to conventional linear net effects, the article explores three possible types of team configuration within enterprises and their breakthrough innovation-driving mechanisms based on machine learning methods.

Based on the patent application data of 2,337 Chinese companies in the biopharmaceutical manufacturing industry to construct the R&D team network, the study uses the K-Means method to explore the configuration types of R&D teams with the principle of greatest intergroup differences. Further, a decision tree model (DT) is utilized to excavate the conditional combined relationships between diverse team network configuration factors, knowledge diversity and breakthrough innovation. The network driving mechanism of corporate breakthrough innovation is analyzed from the perspective of team configurations.

It has been discerned that in the biopharmaceutical manufacturing industry, there exist three main types of enterprise R&D team configurations: tight collaboration, knowledge expansion and scale orientation, which reflect the three resource investment preferences of enterprises in technological innovation, network relationships, knowledge resources and human capital. The results highlight both the crowding-out effects and complementary effects between knowledge diversity and team network characteristics in tight collaborative teams. Low knowledge diversity and high team structure holes (SHs) are found to be the optimal team configuration conditions for breakthrough innovation in knowledge-expanding and scale-oriented teams.

Previous studies have mainly focused on the relationship between the external collaboration network and corporate innovation. Moreover, traditional regression methods mainly describe the linear net effects between variables, neglecting that technological breakthroughs are a comprehensive concept that requires the combined action of multiple factors. To address the gap, this article proposes a combination effect framework between R&D teams and enterprise breakthrough innovation, further improving social network theory and expanding the applicability of data mining methods in the field of innovation management.

As the foundation of social and economic development, infrastructure development projects are characterized by large initial investment, high technical requirements and thus generally delivered through complex contractor–subcontractor collaboration chains. This study aims to characterize the complexity of collaborative networks between contractors and subcontractors for infrastructure development through comparing the structural characteristics and the formation mechanisms of contractor–subcontractor collaborative networks for the following two different types of infrastructure: public works (PWCN) owned and operated by government agencies, and public utilities (PUCN) owned and operated by nongovernment agencies.

Based on the method of stochastic actor-oriented models and the longitudinal dataset of National Quality Award Projects in China during 2001–2020, this study compares how the structural characteristics of project-based collaborative networks between contractors and subcontractors for the two types of projects are different and how related micro-mechanisms, including both structure-based endogenous network effects and attribute-based exogenous homophily effects (institutional, organizational and geographical homophily), collectively underpin the formation of the networks.

The empirical results provide evidence that while the two networks are both characterized by relatively low levels of network density, PWCN is more globally connected around a minority of superconnected contractors as compared with PUCN. The results further reveal that compared with PUCN, the formation of PWCN is more significantly related to the structure-based anti in-isolates effect, suggesting that PWCN is more open for new entrant subcontractors. With regard to the attribute-based homophily effects, the results provide evidence that while both significantly and positively related to the effects of organizational (same company group) and geographical homophily (same location), the formation of PWCN and PUCN is oppositely driven by the institutional homophily effect (same ownership type).

As an exploratory effort of using network perspective to investigate the formation mechanisms of contractor–subcontractor relationships in the infrastructure development domain, this study contributes to a network and self-organizing system view of how contractors select subcontractors in different types of infrastructure projects. The study also provides insights into how contractor–subcontractor collaborative relationships can be better manipulated to promote the development of complex infrastructure in different contexts.