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Previous studies examined the effect of inter-organizational collaboration relationships on organizational innovation. However, most focused on the configuration of the network from the static network perspective, and few examined the influence of network structure stability on an organization's exploratory innovation from the ego-network perspective. This study addresses this research gap by focusing on ego-network stability and its effect on an organization's exploratory innovation.

The empirical setting is the smartphone collaboration network from 2004 to 2017. We selected one-site schemes and panel data of patents from the Derwent Innovation Database. A negative binomial model with fixed effects was used to test our hypotheses.

The regression results show that an organization's ego-network stability has an inverted-U-shaped relationship with its exploratory innovation. Global cohesion of the focal organization's knowledge network moderates the process in such a way that when it is at a high level, an organization's exploratory innovation can benefit more from a moderate level of ego-network stability. However, local cohesion moderates in such a way that, at a low level, an organization's exploratory innovation can benefit more from a moderate level of ego-network stability.

This study highlights the importance of ego-network stability and its effect on the focal organization's exploratory innovation. It contributes to the literature on the relationship between ego-network stability and exploratory innovation by investigating the moderating role of global cohesion and local cohesion in knowledge networks.

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.

The authors selected global automobile manufacturing firms whose sales ranked within 100 in the five years from 2014 to 2018 in the Factiva database to examine how the characteristics of a firm's whole network and ego-network in a transnational coopetition network influence network performance.

The authors analyzed the public news of the sample firms about the coopetition by structural content analysis to build the coopetition networks and access to data on the competitive actions of firms. Then, to measure the variables associated with the coopetition network, such as the structural hole, centrality and ego-network stability, the authors use UCINET 6 that is a widely used piece of software for social network analysis to establishing five undirected binary adjacency matrices.

The authors find that a firm's competitive aggressiveness mediates the relationship between a firm's whole network position and network performance that emphasizes the need for integrating competitive dynamics research and coopetition research and shows how valuable insights can be gained through such integration. And the interaction of structural hole and centrality impacts competitive aggressiveness and network performance, and the interaction is different under high and low ego-network stability. The integration of whole network and ego-network literature studies provides new insights into firm network literature.

In the process of cooperation, firms should consider whether they can occupy the structural hole and center as important indicators for partner selection. Too stable relationship will prevent firms from obtaining new resources. Firms should weigh the period of cooperation according to specific situation.

These results indicate that ego-network stability, as an important complementary characteristic of coopetition network, has a significant synergistic effect with structural holes and centrality on competitive aggressiveness and network performance. And these findings expand the current literature on the relationship between characteristics of network, competitive aggressiveness and network performance.

Facing the global public health emergency (GPHE), the conflict of cultural differences and the imbalance of vital resources such as knowledge among different organizations are becoming more severe, which affects the enthusiasm and sustainability of firms' innovation heavily. It is an urgent problem to be solved for firms how to make use of internal knowledge and external power to help firms' sustainable innovation (FSI). Thus, the purpose of this study is to deeply analyze how firms' internal knowledge diversity (KD) and external ego-network structures [ego-network density (ED) and honest brokers (HB)] affect FSI, as well as how the ego-network structures (ED and HB) moderate the relationship between KD and FSI based on the perspective of the ego network.

Based on the data of the alliance innovation networks of China's new energy industries in 2009–2019, this study uses the social network analysis method and negative binomial regression model to explore the effect of KD and ego-network structures (ED and HB) on FSI, as well as the moderating effects of ego-network structures (ED and HB) on the relationship between KD and FSI based on the perspective of ego network.

This study finds that KD, ED and HB can boost FSI. Moreover, ED plays a negative moderating role in the relationship between KD and FSI. However, the negative moderating effect of HB on the relationship between KD and FSI is not significant.

This study presents fresh empirical evidence and new insights for firms on how to make full use of firms' internal KD and external ego-network structures to facilitate FSI.

First, this study not only enriches the research on the consequences of KD but also expands our understanding of the knowledge-based view to some extent. Second, this study not only enriches the motivation research of the FSI based on the perspective of ego-network in the context of the GPHE but also expands the application scope of social network theory and sustainable innovation' theory in part. Third, this paper is a new attempt to apply social network theory and knowledge-based view at the same time.

Previous research has analyzed the consequence of network stability; however, little is known about how partner type diversity influence network stability in R&D network. Based on knowledge-based view and social network theory, the purpose of this paper is to unravel the internal mechanisms between partner type diversity and network stability through the mediating role of knowledge recombination in R&D network.

The authors collected an unbalanced panel patent data set from information communication technology industry for the period 1994–2016. Then, the authors tested the different dimensions of partner type variety and its relevance in the R&D network and the mediating role of knowledge recombination through adopting the multiple linear regression.

Results indicate an inverted U-shaped relationship between partner type diversity (variety and relevance) and network stability, whereas knowledge recombination partially mediate these relationships.

From the perspective of R&D networks, this paper explores that there are the under-researched phenomena the antecedent of network stability through nodal attributes (i.e. partner type variety and partner type relevance). Moreover, this paper empirically examined the mediating role of knowledge recombination in the partner type diversity–network stability relationships. The novel perspective allows focal firm to recognize importance of nodal attributes, which are critical to fully excavate the potential capabilities of cooperating partners in R&D network.

This paper aims to propose the following questions: How does dynamic positioning influence organization’s innovation performance? Does knowledge base mediate the relationship between them?

The empirical setting of this study is the smartphone collaboration network from 2004 to 2017; the authors selected one-site schemes and data of patents from the Derwent Innovation Database. Furthermore, the authors adopted the negative binomial model with random effects to test the hypotheses.

The regression results show that organization’s dynamic positioning has an inverted-U-shaped relationship with its exploratory innovation. Similarly, organization’s dynamic positioning has an inverted-U-shaped relationship with its exploitative innovation. Besides, knowledge base mediates the relationship between dynamic positioning and organization’s innovation performance.

This study empirically confirms the relationship between dynamic positioning and organization’s innovation performance by separately examining exploratory and exploitative innovation. Furthermore, this study provides a contribution to the literature linking dynamic positioning and organization’s innovation performance by investigating the mediating role of knowledge base.

Building on theories of inter-organizational knowledge flows and social network, we explored how two types of collaboration network embeddedness (NE) (i.e. structural embeddedness (SE) and relational embeddedness (RE)) drive firms' inbound and outbound open innovation (OI) practices from a knowledge flow perspective, and further examined these relationships are to what extent contingent on network inertia (NI).

In this empirical research, the authors collected a sample of patents in the unmanned aerial vehicle (UAV) industry over the period of 2000–2018. Then the authors examined the direct roles of SE and RE in collaboration networks on firms' inbound and outbound OI practices from a knowledge flow perspective, and the moderating role of NI by using negative binomial regression.

Empirical results from our study of 96 firms showed that both bridging structural holes position in collaboration networks (i.e. SE) and having stronger tie strength (i.e. RE) would positively affects firms' inbound OI practices, whereas only having stronger tie strength in collaboration networks (i.e. RE) would facilitate outbound OI practices. In addition, NI strengthens the relationships between SE and firm OI practice, but weakens the positive roles of RE on firm OI practice.

This empirical research provides new insights into whether and how firms can grasp the benefits of collaboration NE to conduct OI activities by exploring NI contingencies. It further sheds lights on the scope of the NE–OI issue from a knowledge flow perspective by extending its research context to UAV industry.

This study aims to explore the different effects of inter-community group networks and intra-community group networks on group innovation.

The authors used a pooled panel dataset of 12,111 self-organizing innovation groups in 463 game product creative workshop communities from Steam support to test the hypothesis. The pooled ordinary least squares (OLS) model is used for analyzing the data.

The results show that network constraint is negatively associated with the innovation performance of online groups. The average path length of the inter-community group network negatively moderates the relationship between network constraint and group innovation, while the average path length of the intra-community group network positively moderates the relationship between network constraint and group innovation. In addition, both the network density of inter-community group networks and intra-community group networks can negatively moderate the negative relationship between network constraint and group innovation.

The findings of this study suggest that network structural characteristics of inter-community networks and intra-community networks have different effects on online groups’ product innovation, and therefore, group members should consider their inter- and intra-community connections when choosing other groups to form a collaborative innovation relationship.

Research involving interorganizational relationships (IORs) has grown at an impressive rate. Several datasets have been used to understand the nature and performance implications of these relationships. Given the importance of such relationships, we describe a relatively new dataset, Bloomberg SPLC, which contains data regarding the percentage of costs and revenues attributed to suppliers and customers, as well as allows researchers to construct a comprehensive dataset of IORs of buyer–supplier networks. Because of this, Bloomberg SPLC data can be used to uncover new and exciting theoretical and empirical implications. This chapter provides background information about this dataset, guidance on how it can be leveraged, and new theoretical terrain that can be charted to better understand IORs.

This study aims to explore the effect of innovation ecosystem stability (IES) on innovation performance of enterprises through the mediating role of knowledge acquisition (KA), and to study how these effects are moderated by unabsorbed slack.

This study draws on data from 327 Chinese enterprises and adopts the multiple linear regression method and bootstrapping method to explore the mediating effect of KA and its moderated mediating effect.

The results demonstrate that IES is positively associated with innovation performance of enterprises, and KA plays a partially mediating role. Moreover, unabsorbed slack negatively moderates the relationship between IES and KA as well as the mediating effect of KA.

This study investigates the relationship between IES and innovation performance, and the mechanism of influence, which has not been previously studied in the field of innovation ecosystem. This study also examines the interaction between unabsorbed slack and IES and further clarifies the mechanism and boundary conditions of the impact of IES on innovation performance.