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This study aims to explore the effect of competitive aggressiveness on firm performance and the moderating effect of firm 2019s ego-network structures in the international coopetition network.

From the perspective of strong cooperation of the global automobile industry in recent years, this study uses the global automobile firms in Factiva database as samples to test hypotheses using the least squares dummy variable (LSDV) model.

This study finds that there is different relationship between the number and variety of competitive actions and firm performance. In addition, ego-network structures have different coefficients for the number and variety of competitive actions.

The conclusions provide theoretical support and policy suggestions for firms to develop effective competitive strategies according to ego-network structures in the international coopetition network.

Drawing on social network and information diffusion theories, the authors study the impact of the structural characteristics of a seller’s local social network on her promotion effectiveness in social commerce.

The authors define a local social network as one formed by a focal seller, her directly connected users and all links among these users. Using data from a large social commerce website in China, the authors build econometric models to investigate how the density, grouping and centralization of local social networks affect the number of likes received by products posted by sellers.

Local social networks with low density, grouping and centralization are associated with more likes on sellers’ posted products. The negative effects of grouping and centralization are reduced when density is high.

The paper deepens the understanding of the determinants of social commerce success from a network structure perspective. In particular, it draws attention to the role of sellers’ local social networks, forming a foundation for future research on social commerce.

The purpose of this research is to investigate the R&D investment (RDI) of manufacturing firms from the perspective of supply chain network, especially the effect of firms' supply chain network structures (network power and network cohesion) on its RDI, and further to explore the contingency conditions of this effect within the context of Chinese manufacturing supply chains.

The authors collect a large sample of Chinese manufacturing firms over the period 2014–2019 and construct a large-scale supply chain network, and finally obtain 2,390 firms from 20,483 observations. Ordinary least squares regression was adopted to analyse how supply chain network structures affect RDI in manufacturing firms.

It is surprising that firm's supply chain network structures have a negative effect on RDI. In addition, knowledge and technology intensity (KTI) positively moderate the relationship between network cohesion and RDI.

This study contributes to the innovation stream from the perspectives of supply chain network, and provides the empirical findings that the negative role of a firm's supply chain network structure on its RDI for the first time. The rationale for these negative effects is straightforward according to the social capital theory that manufacturing firms with a high level of social capital that are possibly to accept established patterns of thinking and behaviour, causing them to decrease the enthusiasm of RDI.

Climate change requires the reduction of direct and indirect greenhouse gas (GHG) emissions, a task that seems to clash with increasing supply chain complexity. This study aims to analyse the upstream supply chain complexity dimensions suggesting the importance of understanding the information processing that these may entail. Reducing equivocality can be an issue in some dimensions, requiring the introduction of written guidelines to moderate the effects of supply chain complexity dimensions on GHG emissions at the firm and supply chain level.

A three-year panel data was built with information obtained from Bloomberg, Trucost and Compustat. Hypotheses were tested using random effect regressions with robust standard errors on a sample of 394 SP500 companies, addressing endogeneity through the control function approach.

Horizontal complexity reduces GHG emissions at the firm level, whereas vertical and spatial complexity dimensions increase GHG emissions at the firm and supply chain level. Although the introduction of written guidelines neutralises the negative effects of vertical complexity on firm and supply chain GHG emissions, it is not sufficient in the presence of spatial complexity.

This paper offers novel insights by suggesting that managers need to reconcile the potential trade-off effects on GHG emissions that horizontally complex supply chain structures can present. Their priority in vertically and spatially complex supply chain structures should be to reduce equivocality.

Prior research on supply chain management has advanced substantially our understanding of how suppliers’ knowledge affects manufacturers’ green innovation. However, overlooking the suppliers’ diverse green knowledge in supplier networks, namely, green knowledge diversity, has limited our understanding of both supply chain management and green innovation development. To address this important issue, this study aims to rely on social network theory as the overarching framework and knowledge-based view as the underlying theoretical foundation to examine how green knowledge diversity contributes to manufacturers’ green innovation performance, while considering three types of supplier network properties (network strength, network heterogeneity and network density).

This study collects both survey and secondary proxy data from 209 manufacturing firms over three time periods (mid-2018, mid-2019 and mid-2020). PROCESS macro is applied to test the research hypotheses.

The results provide compelling evidence that green knowledge management processes partially mediate the effect of green knowledge diversity on manufacturers’ green innovation performance. The effect of green knowledge diversity is strengthened by supplier network strength and supplier network heterogeneity, but hindered by supplier network density.

This study provides a practical guide to help manufacturers enhance green innovation performance by properly managing and leveraging their suppliers’ diverse green knowledge domains in supplier networks.

This study contributes to the supply chain management and green innovation literature by offering novel theoretical and empirical insights into how manufacturers can use their supplier networks to strengthen green innovation.

This study aims to examine the impact of transformational leadership on green innovation and green learning in construction supply chains.

A theoretical framework of research hypotheses between transformational leadership, green learning and green innovation is developed. Using a survey questionnaire, data are collected from construction firms in Vietnam. Structural equation modeling is used to test the research hypotheses.

The results indicate that transformational leadership promotes both green learning and green innovation (i.e. green product innovation and green process innovation) while green learning positively affects green process innovation. Furthermore, it is found that green learning mediates the linkage between transformational leadership and green process innovation.

This study contributes to the development of leadership research in construction by showing the significance of leadership at the supply chain level.

Leadership is regarded as a key factor for most organizations' success and competitive advantages. In construction, leadership has been widely studied at the project and organizational levels while its important role is also explored at the supply chain level. Nevertheless, in terms of construction supply chains, there has been still very limited evidence about the effects of transformational leadership. Thus, this study fills the gap in knowledge by empirically examining the relationships between transformational leadership, green learning and green innovation.

The purpose of this study is to assess factors related to sorority women connecting with people who exacerbate feelings of exercise guilt and body dissatisfaction (BD), both of which preclude compulsive exercise.

In all, 207 sorority women (egos) completed online surveys measuring physical activity, BD, compulsive exercise and egocentric networks (n = 1,105 social ties/alters). Two random coefficient multilevel models assessed factors related to an ego connecting to someone who makes her feel: guilty about her exercise habits and good about her looks.

Exercise patterns within networks related to how often an alter made ego feel guilty about her exercise habits; alter gender and communication frequency related to how often an alter made ego feel good about her looks; and ego’s BD score was related to both feelings of guilt and body satisfaction.

The findings of this study support and extend literature highlighting the importance of someone’s immediate social network on their body image and related behaviors.

The purpose of this paper is to examine the information flows, in terms of content and process, underpinning the sharing of knowledge by managers and owners. Such an examination reveals similarities and differences that will influence the generation and dissemination of knowledge used in tourism business operations and contribute to innovation.

This paper examines information flows within the theoretical and methodological framework of social network analysis. The findings were derived from a quantitative study of tourism managers and owners of a tourism hub in South-West England.

The main finding was that network structure characteristics determine the flow of information within owners’ and managers’ social networks. The owners of smaller businesses received information from several sources and, therefore, had fewer structural constraints and reported larger structural holes. In comparison, the managers had more brokerage opportunities to disseminate the information within their social networks.

This paper highlights knowledge sharing between tourism business managers and owners in an open network structure. First, an open network structure builds innovation through the provision of nonredundant information. This is determined through the effective size of structural holes and the dissemination of information through brokerage roles. Second, the knowledge capability of a destination is built up through the social networking of managers and owners. The generation and dissemination of knowledge in a tourism destination are facilitated by the social networking activities of managers and owners.

Managers and owners of tourism businesses require knowledge through information to assist with innovative business practices. The practical implication of this is that the social networks of managers and owners have different network characteristics, and that these differences result in consequences for the innovation of business practices. Another practical implication relates to the importance of managers in knowledge dissemination based on having several brokerage roles in the tourism destination.

These findings are important because an understanding of social networks and the flow of information is one of the keys to determining the influences on knowledge sharing within tourism destination knowledge networks of owners or managers and their potential contributions to innovation.

This paper examines the relationship between supply chain network structures and firm financial performance and the moderating role of international relations. In this study, which is grounded in social capital theory and applies the perspective of systemic risk, the authors theorize the effects of supply chain network structures on firm performance.

The authors extracted data from two Chinese databases and constructed a supply chain network of the firms concerned based on nearly 4,300 supply chain relations between 2009 and 2018. The authors adopted the fixed effects model to investigate the relationship between supply chain network structures and firm financial performance.

The econometrics results indicate that network structures, including the degree, centrality, clustering coefficients and structural holes, are significantly related to firm financial performance. A significant and negative relationship exists between international relations and firm financial performance. The authors also find that international relations strongly weaken the relationship between supply chain network structures and firm financial performance.

This study, which collects secondary data from developing countries (e.g. China) and explores the impacts of supply chain network structures on firm stock performance, contributes to the existing literature and provides practical implications.

Chinese internet literature (CIL) platforms afford freedom for creative expression and opportunities for direct interactions between writers and fans and among fans. Enabled by these platforms' technological and commercial arrangement, a new form of literary production and consumption has emerged, the most significant of which is the role of fans participation. A social network analysis of the interaction patterns in online fan communities was conducted to investigate fan communication activities at scale. Of particular interest is how the socio-technical system of the site influences its network topology.

Online forums for 10 popular fiction titles in Qidian, the leading CIL platform, were analyzed. Social networks were constructed based on a post–reply–reply threaded discussion structure. Various aspects of fan interactions were analyzed, including number of replies per post, post length and emerging network patterns.

Similarities in network topology shared by CIL fan forums and other online communities, such as small-world and scale properties, were discovered; however, distinct network dynamics were also identified. Consistent with previous findings, writers and moderators, along with a few highly ranked fans, occupied the central positions in the network. This was due to their social roles and the nature of their posts rather than, as the conventional explanation goes, preferential attachment.

The findings demonstrate how community-specific circumstances and norms influence interaction patterns and the resultant network structure. It was revealed that in the CIL sites, the users adopted the technologies in unexpected ways. And the resulting network topology can be attributed to the interplay between the sites' official arrangement and users' adaptive tactics.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2021-0596.