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Immersed in a global industry consolidation process, corporate managers are witnessing, in recent years, the proliferation of inter‐organizational collaborative agreements, which aim to develop, manufacture and commercialize knowledge intensive products. The decision within a knowledge management (KM) framework to collaborate in knowledge sharing networks becomes a complicated issue, since such a decision needs to be made often under conditions of uncertainty and irreversibility. The present study deals with questions such as why, how, and when to be a member of a knowledge network and provides some empirical evidence about the formation of inter‐organizational networks in knowledge intensive industries.

This chapter explains how to design and operationalize a knowledge network analysis. The authors walk through a nine-step methodology that addresses each stage of the process. The nine-step process is the result of an in-depth review of the theoretical and applied literature. The authors explain how and why each step contributes to the quality and goodness of the analysis. The risks of skipping or sub-optimizing steps are explained. The step-by-step process highlights the dependence of a knowledge network analysis on data sources. The authors explain the importance of identifying, collecting, and curating sources.

This chapter describes capacity building as a general concept and as a networking capability specifically. There are two essential components to building capacity. The first is building the network capacity, building relational capital, and sharing knowledge. The second is building the capacity to support knowledge network analyses. The authors offer a set of key questions for determining the health of networking capacity at the strategic, operational, and individual levels. The chapter also describes the roles and competencies required for network analysts, managers, and general employees.

This study aims to present how an inter-organisational cooperation network can contribute to the competitive performance of higher education institutions (HEI) and also to students’ academic performance. The intention is also to examine how knowledge-sharing processes should develop to meet the needs of maintaining cooperation networks.

This study adopts a qualitative approach, using the case study (network) method. The data were collected through semi-structured interviews, group interviews and documentary analysis. The convenience sampling technique was used. Data analysis was carried out through a data triangulation process.

The general benefits arising from cooperation networks are encouraging. The HEIs improved not only through creating an environment that supports learning processes and knowledge-sharing efficiently, but also through cooperation between students and lecturers.

The cooperation network experience studied here can be used by other universities or HEIs as an approach/strategy to launch a cooperation initiative in order to increase levels of knowledge, learning, innovation and competitiveness. The results also help university or HEI leaders to understand the importance of academic cooperation networks, letting them form innovative teaching strategies that stimulate academic and competitive performance, as well as economic growth.

The central elements of originality lie in advancing a new vision of cooperation networks, creating a new, innovative framework that considers the dimensions presented from the theoretical and practical point of view. The framework helps to understand what is necessary for network cooperation to develop and create value for HEIs. Combining different perspectives of the cooperation network inevitably represents a significant innovation.

This paper aims to investigate the antecedents of recombinant innovation from the perspective of ego–network dynamics, and further disentangle whether ego–network stability or ego–network expansion is more conducive to recombinant innovation under heterogeneous knowledge base.

This paper uses 1,801 patent data in China’s biotechnology field as a sample and adopts fixed effects regression model to examine the effects of ego–network dynamics on recombinant innovation and further uses the Wald tests to discern which ego–network dynamic is more conducive to recombinant innovation under heterogeneous knowledge base.

The empirical results indicate that ego–network dynamics have a positive impact on recombinant innovation. Specifically, for firms with high knowledge breadth and high knowledge depth as well as high knowledge breadth and low knowledge depth, ego–network stability is more conducive to recombinant innovation. By contrast, for firms with low knowledge breadth and high knowledge depth, recombinant innovation benefits more from ego–network expansion. As for firms with low knowledge breadth and low knowledge depth, both ego–network stability and ego–network expansion can promote recombinant innovation, while the effects are not significant.

This research may enlighten managers to choose suitable ego–network dynamics strategies for recombinant innovation based on their knowledge base.

This research not only contributes to the literature on recombinant innovation by revealing the impact of different ego–network dynamics on recombinant innovation but also contributes to network dynamics theory by exploring whether ego–network stability or ego–network expansion is more conducive to recombinant innovation under a heterogeneous knowledge base.

Although research on how the downstream calculations of a patent’s profit potential influence invention renewal decisions is extensive, the impact of the upstream knowledge creation stages is overlooked. The purpose of this study is to address this theoretical vacuum by examining the intra-organizational configuration of knowledge networks and collaboration networks.

The data consist of 491 global pharmaceutical firms that patent in the USA. Drawing on patent records, the authors simultaneously construct intra-organizational knowledge networks and collaboration networks and identify network cohesion features (i.e. local and global). The authors employ panel fixed-effects models to test the hypotheses.

The results show that local knowledge cohesion and local social cohesion decrease invention renewals, while global knowledge cohesion and global social cohesion increase renewals. Moreover, the marginal effects of local and global social cohesion are stronger than those of local and global knowledge cohesion, respectively.

The hypotheses are tested using the pharmaceutical industry as a research setting, which limits the generalizability of our findings. In addition, potential formal and informal contingencies are not considered.

Despite its limitations, this study provides valuable implications. First, managers are cautioned against the adverse effects of local cohesion structures on invention renewal. Second, firms can dynamically adjust their local and global network configuration strategies to harmonize the generation of valuable inventions and the retention of good ideas.

Complementary to previous research that focused on inventions’ performance feedback, this study delves into upstream knowledge creation stages to understand invention renewals.

This study aims to investigate the influence of inventors’ abilities to acquire external knowledge, provide broad and professional knowledge and patenting output (i.e. different types of inventors) on the formation of structural holes.

The authors collected 59,798 patents applied for and granted in the USA by 33 of the largest firms worldwide in the pharmaceutical industry between 1975 and 2014. A random-effects tobit model was used to test the hypotheses.

The inventors’ ability to acquire external knowledge contributes to the formation of structural holes. While inventors’ ability to provide broad knowledge positively affects the formation of structural holes, their ability to provide professional knowledge works otherwise. In addition, key inventors and industrious inventors are more likely to form structural holes than talents.

The results identify individual factors that affect the formation of structural holes and improve the understanding of structural hole theory. This study is unique in that most scholars have studied the consequences of structural hole formation rather than their antecedents. Studies on the origin of structural holes neglect the effect of inventors’ knowledge abilities and patenting output. By addressing this gap, this study contributes to a more comprehensive theoretical understanding of structural holes. The results can guide managers in managing structural holes in accordance with inventors’ knowledge abilities and patenting outputs, which optimize the allocation of network resources.

This study deals with the processes of innovation in the medium technology industrial sectors. First, it illustrates the differences between the linear model of innovation and the systemic and cognitive model of knowledge creation. Then, it focuses on the concepts of connectivity, creativity, and speed of change, which characterize the processes of interactive learning in the industrial clusters. Finally, it illustrates a typology of regions, where problems and policy fields are different, and it indicates the guidelines of a governance of interregional knowledge and innovation networks.