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Nuclear power is a stable and reliable energy source that can improve energy structure while reducing carbon emissions, which is of great significance for environmental protection and combating climate change. As a unique industry, it is facing rare development opportunities in China and has broad market prospects. However, the characteristics of technical difficulty, loose organizational structure and uneven regional distribution limit the expansion of the nuclear power industry. This paper aims to a better understanding of the accumulation process for innovation capability from the perspective of network evolution and provides policy guidance for the market development of the nuclear power industry (NPI).

Methodologically, social network analysis is used to explore the co-evolution of multidimensional collaboration networks. First, the development and policy evolution of the NPI is introduced to divide the evolution periods. Then, the authors identify and analyze the core organizations, technologies and regions that promote nuclear power patent collaboration. Furthermore, three levels of collaboration networks based on organizations, technologies and regions are constructed to analyze the coevolution of patent networks in China’s NPI.

The results show that nuclear power enterprises always play the foremost role in the organizational collaboration network (OCN), and the dominance of foreign enterprises is replaced by Chinese state-owned enterprises in the third period. The technology hotspot has shifted from nuclear power plant construction to the control system. The regional collaboration network was initially formed in the coastal areas and gradually moved inland, with Guangdong and Beijing becoming the two cores of the network. The scale of three collaboration networks is still expanding but the speed has slowed down.

In response to the pain points of the NPI, this research focuses on multidimensional collaborative innovation, investigates the dynamic evolution process of collaborative innovation networks in China’s NPI and links policy evolution with network evolution creatively. The ultimate result not only helps nuclear power enterprises integrate innovative resources in complex environments but also promotes industrial upgrading and market development.

This chapter examines factors that maximize collaboration among various stakeholders with the purpose of health policy making in Turkey. The field research reveals that policy networks have been formed in the sub-areas of public health, healthcare construction, and health tourism in the years between 2011 and 2015. Content analysis of 24 semi-structured interviews with policy and professional experts is conducted to assess Network Collaborative Capacity, built upon three dimensions, namely, structural, relational, and institutional. The findings reveal that networks differ in their capacity to collaborate as well as their impact on policy making resulting in three distinct models of network policy making. In the cases under investigation, network impact takes the form of (a) policy innovation through expertise sharing and evidence-based policy making associated with particularly high levels of relational capacity; (b) policy effectiveness through contract enforcement within a clear legal framework associated with particularly high levels of institutional capacity; and (c) policy coherence through organizational-knowledge-sharing and actor coordination. Findings also suggest that institutionalization in the form of network embeddedness in the surrounding political and economic environment is crucial for maintaining a collaborative momentum as well as achieving policy effectiveness at the stage of policy implementation. Based on these findings, further studies should focus on the institutionalization of policy networks, particularly in those middle-income countries such as Turkey that aim and often fail to address various policy challenges through short-lived practices of multi-stakeholder action. Finally, this study emphasizes the importance of incorporating neo-institutional approaches to network analysis.

This study aims to identify which actors play leadership and brokerage roles in voluntary environmental collaborations and how the corporate social responsibility (CSR) of actors is associated with such voluntary networking behaviours in Cambodia.

To achieve these purposes, this study mainly uses social network analysis to capture the properties of networking behaviours in the voluntary collaborative activities underlying three main environmental issues: waste disposal, energy and water pollution. The study focusses on the collaborative efforts undertaken by actors across multiple sectors: governmental organizations, for-profits and civil society organizations.

The results show that the government plays the leading role in voluntary environmental collaborations across environmental issues; however, the actual implementation is expanded to be undertaken by non-state actors. Moreover, CSR has positive associations with networking and brokerage roles; therefore, this study reveals the utility of various voluntary policy instruments.

This study demonstrates the role of governmental initiation and its influence on non-state actors, even for voluntary environmental tools. The CSR initiatives of private actors can also be supported and encouraged by the government, which will promote participation by private actors in voluntary collaborative networks and their leading role as network facilitators.

By understanding the positions and roles of each actor in the environmental collaborative networks, environmental policymakers can better understand the possibilities and the capabilities of each actor both to improve policy design and learning and to respond to policy changes effectively.

Voluntary collaboration and CSR are non-regulated policy tools; however, they can be promoted and introduced into society by governmental organizations, and they affect each other.

The purpose of this paper is as follows: studying a case for technological innovation in Iran; studying the process of network creation; studying different challenges in finding, forming and performing of a collaboration network; studying comprehensive identification and analysis of the challenges in the network creation process; studying an active collaboration network in the field of medical equipment; and studying a network with different partners (consisting of a large company, a small- and medium-sized company, two subcontractors, three universities, a start-up, an accelerator and a venture capital fund).

The qualitative research method has been used because of a deep and rich analysis of the studied network. The study also provides an overview of finding and forming of partners and details of collaborations in the network, including partner’s goals from network entry, initial negotiations between members, business plan, shared resources and final results are expressed. The data used in this study has been collected by a totally seven semi-structured interviews. To analyze the collected data by open coding, the MAXQDA12 software was used and the basic concepts were identified and were categorized based on their similarities.

The studied network was identified as a strategic alliance. Details of finding, forming and performing of the studied network were explained. In total, 4 collaboration models and 28 different challenges in the network creation process were identified. In total, 28 different challenges were divided into 7 categories (based on their existence or absence in each of the 4 identified collaboration models). In total, seven categories of challenges were analyzed completely and the relations between challenges and partners of collaboration models were studied.

The collaboration network studied in this research involves several technological collaborations among different actors. Saadat, as the hub of this network, has been involved in all these collaborations, and other members have joined the network in accordance with network requirements and their capabilities. This network has been formed and developed with the aim of developing and producing various modules of vital signs monitoring since 2009. Some of the collaborations in this network, which are for production of a specific module and require long-term collaboration between the partners (such as the production of electrocardiograph or heart attack rapid diagnostic module), continue to be ongoing and some of them that focus on research and development or acquisition of technical knowledge (such as academic collaboration) after the specified result has been ended.

Researchers agree that collaboration networks can be an important implement in a firm’s innovation process, but there is limited empirical evidence on actually how they facilitate the new product development (NPD). The paper aims to discuss these issues.

Using longitudinal and multisource data on a sample of firms engaged in the Chinese automobile industry, the authors examine the structural properties of collaboration networks and their possible influences on firms’ NPD performance.

The results indicate that the structural features of the technology-based collaboration networks in the automobile industry have a low degree of collaborative integration and they influence firms’ NPD performance in diverse ways. The authors find that the direct ties, indirect ties and structural holes of the collaboration networks are all positively associated with firms’ number of new products. However, the authors have not found the evidence that the number of direct ties can moderate the relationship between the indirect ties and the NPD performance.

First, previous researches concerning the network mainly focused on their influence on technology innovation, few scholars studied the relationship between collaboration network and NPD. Second, the data used in this paper are true and valid, they are all from relevant departments of the Chinese government. Third, the empirical research of new products in China’s manufacturing industry is relatively new.

The purpose of this paper is to analyze the inverted U-shaped relationship between external search in the collaboration network and firm innovation outcomes. It also seeks to explore whether these curvilinear relationships are moderated by the network centrality and structural holes in the knowledge network.

In this empirical research, the authors collected a sample of patents in the smartphone industry over the period of 2000-2017. Then the authors examined the direct roles of external search breadth and depth in the collaboration network and the moderating role of network embeddedness in the knowledge network by using negative binomial regression.

Results found that external search in the collaboration network contributes more to firm innovation outcomes when the breadth and depth of the external search are moderate rather than high or low. Furthermore, both network centrality and structural holes in the knowledge network have positive effects on the external search breadth – innovation outcomes and external search depth – innovation outcomes relationships.

The authors collected the patent data within the single industry and excluded other types of industries. This may limit the generalization of the findings.

The paper has practical implications for adopting appropriate search strategies in the collaboration network and developing a better understanding of the effect of network embeddedness in the knowledge network on firm innovation outcomes. The findings suggest future directions for technology-intensive industries to improve their innovation output.

This study adds value to open innovation literature by pointing out a curvilinear relationship (inverted U-shaped) between external search breadth/depth and innovation outcomes in collaboration networks, in contrast to studies focused on firms’ external collaboration strategies in a certain industry context. Furthermore, this study reinforces the key contingent role of embeddedness in knowledge networks. This study provides a valuable theoretical framework of innovation outcome determinants by connecting the network perspective of open innovation theory with an embeddedness view.

The concept of collaboration has received increased attention from scholars in public management, as it has been seen as a viable solution to address “wicked” problems. Solving such problems may require a horizontal collaboration within the same governmental jurisdiction or, vertically, between different levels of government. Despite broad interest from the field of public management, the dynamics of public interinstitutional collaboration have received little attention within the literature. This paper aims to provide a systematic overview of the most significant academic contributions on the topic, highlighting the features of this collaborative context and identifying determinants those can foster its performance.

In total, two main literature streams have occasionally dealt with public interinstitutional collaboration and related performance management: the “collaborative governance” stream and “public network performance”. Through a systematic literature review (SLR), this paper answers the following research question: what has been done and what is missing in order to assess performance in the context of public interinstitutional collaboration?

The findings of this study suggest that the most relevant papers are those dealing with public interagency collaboration, as this form of collaboration presents several similarities with public interinstitutional circumstances. Furthermore, the authors provide an analysis of the main determinants of public interinstitutional performance, which highlight the effects of trust, power sharing, leadership style, management strategies and formalization on the achievement of efficient and effective collaboration between public entities.

By drawing on two autonomous literature streams, this paper describes the main features of public interinstitutional collaboration. It contributes to the field by offering a systematic overview of how specific performance determinants, which are widely recognized as relevant for collaboration in general, work in the specificity of public–public contexts.

This study aims to explore the effect of collaboration networks (domestic and international collaboration networks) on the innovation performance of small and medium-sized enterprises (SMEs). It also investigates the mediating role of business model innovation, the moderating role of entrepreneurial orientation and government institutional support between them.

Hierarchical regression analysis is adopted to test the hypotheses based on survey data provided by 223 manufacturing SMEs in China.

The results reveal that domestic and international collaboration networks positively affect SMEs' innovation performance. Business model innovation mediates domestic and international collaboration networks-SMEs’ innovation performance relationships. Entrepreneurial orientation positively moderates international collaboration networks–SMEs’ innovation performance relationship, and government institutional support positively moderates domestic and international collaboration networks–SMEs’ innovation performance relationships.

The findings indicate that managers of SMEs should invest in domestic and international collaboration networks and business model innovation to enhance SMEs' innovation performance. Moreover, entrepreneurial orientation and government institutional support should be valued when SMEs try to enhance their innovation performance by embedding in domestic and international collaboration networks.

This study broadens the authors' understanding of the relationship between collaboration networks and firms' innovation performance by classifying collaboration networks into domestic and international dimensions and investigating their direct impacts on SMEs' innovation performance. Besides, this study reveals how and when domestic and international collaboration networks influence the innovation performance of SMEs.

This paper examines the role of co-inventor collaboration with China and/or the USA on a country's increase in centrality in global knowledge networks. It also explores the role of specific institutional factors – corruption and intellectual property rights (IPR) protection – on this relationship.

In the study, co-inventor data from the United States Patent and Trademark Office (USPTO) applications have been used to construct networks of technological knowledge collaboration at the country level over the years 2002–2015. Using eigenvector centrality as the dependent variable, the study uses fixed effect regression analyses on a panel of 171 countries, contributing to recent debates on knowledge networks and international cooperation.

Building on research in economic development, innovation and social network theory, this research finds that co-patenting with Chinese inventors is positively related to a country's centrality in global knowledge networks and that this relationship is negatively moderated by collaboration with the current most central knowledge network – namely that of the USA – suggesting a substitution effect. It also finds a partial substitution between institutional factors, IPRs protection and transparency, and collaboration with China on a country's knowledge centrality.

Regarding policymakers, the findings can be used to encourage international collaboration for increased access to new sources of knowledge that fosters innovation while keeping a close eye on local institutions, especially emerging economies that want to increase their international knowledge network centrality.

This study creates a unique panel data set and extends the social networks approach in international business literature, focusing on institutional characteristics related to participation in knowledge networks.

This study attempts to use a new source of data collection from open government data sets to identify potential academic social networks (ASNs) and defines their collaboration patterns. The purpose of this paper is to propose a direction that may advance our current understanding on how or why ASNs are formed or motivated and influence their research collaboration.

This study first reviews the open data sets in Taiwan, which is ranked as the first state in Global Open Data Index published by Open Knowledge Foundation to select the data sets that expose the government’s R&D activities. Then, based on the theory review of research collaboration, potential ASNs in those data sets are identified and are further generalized as various collaboration patterns. A research collaboration framework is used to present these patterns.

Project-based social networks, learning-based social networks and institution-based social networks are identified and linked to various collaboration patterns. Their collaboration mechanisms, e.g., team composition, motivation, relationship, measurement, and benefit-cost, are also discussed and compared.

In traditional, ASNs have usually been known as co-authorship networks or co-inventorship networks due to the limitation of data collection. This study first identifies some ASNs that may be formed before co-authorship networks or co-inventorship networks are formally built-up, and may influence the outcomes of research collaborations. These information allow researchers to deeply dive into the structure of ASNs and resolve collaboration mechanisms.