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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.

In the modern knowledge-intensive economy, a nation’s competitiveness depends on the ability of its constituent firms to innovate. Extant research in national systems of innovation highlights institutions and public policies toward innovation as key determinants that affect firms’ innovation activities. This paper aims to widen the investigation by arguing that co-inventor connectivity allows firms to access the most tacit knowledge within global innovation systems. Therefore, it is one of the key factors that underpin a nation’s ability to develop and sustain its competitiveness.

Using a data set of 406,168 patents from US Patent and Trademark Office during the period of 1975-2004, this study analyzed the Japanese system of innovation through co-inventor networks.

Surprisingly, the authors found that compared to other advanced countries such as Germany and Denmark, the Japanese innovation system is quite closed.

The dimension of tacit knowledge is crucial in the current environment of rapid cycle time, short product lifespans and increasing emphasis on exploratory innovation. Hence the authors speculate that closedness to global innovation systems could be one of the reasons why many of Japan’s traditionally powerful multinational enterprises exhibit weak performance in recent years.

The purpose of this paper is to explore how firms achieve competitiveness by implementing design-driven innovation.

This paper is a detailed longitudinal analysis of the design innovation underpinning the Norwegian furniture industry. Using a data set spanning 40 years (1976-2015) of design patents by both Norwegian firms and inventors, the authors map the coinventor connectivity of the design-innovation clusters of Norway, both within the country and with foreign locations.

Using network analysis, the authors find that most of the rise of co-inventor connectivity within Norwegian furniture industry’s design innovation is occurring within the country. More surprisingly, the leading firms and star inventors are less likely to collaborate internationally, i.e. they are characterized by greater innovative “lock-in”.

The exploration of all the potential reasons for the “lock-in” in design innovation of the Norwegian furniture industry is beyond the scope of this paper. A particularly interesting avenue for future research would be to compare the coinventor connectivity of traditional sectors like furniture with more high technology sectors within Norway.

By assessing a detailed and historical context of the evolution of Norwegian furniture industry, the paper provides a fairly comprehensive study of design innovation as a source of firms’ competitiveness, which has been rarely explored. The authors suggest that innovative “lock-in” may be more likely to arise in the traditional sectors of an economy and the forces may be particularly strong for those firms and individuals that have the highest domestic connectedness and status.

Contemporary life is replete with all manner of rankings, metrics, and benchmarks (Power, 1997; Espeland & Stevens, 1998). From J.D. Power evaluations of cars to Zagat restaurant reviews to US News and World Report ratings of colleges and universities, modern life seems to be deep in the grip of assessment and evaluation. In the early decades of the twentieth century, the introduction of scientific management transformed the workplace, altering relations between labor and capital, and embedding control over the nature and pace of work into the technical organization of production (Edwards, 1979; Shenhav, 1995). In a similar fashion, the current embrace of rankings may reflect a new “Taylorism,” as metrics have the capacity to not only reorder the social institutions they are purported to assess, but also provide a patina of objectivity, especially for the uninitiated.

The purpose of this paper is to understand the relationship between foreign direct investment (FDI) and cities and how the relationship between multinational enterprise (MNEs) and local firms facilitates regional cleantech innovation.

Using a combination of social network analysis, regression analysis and interview analysis, the authors map and analyze a cleantech cluster to investigate the relationship between MNEs and local firms and the resulting effects on cleantech innovation.

The findings of the paper indicate that FDI plays a crucial role in cities and their local clusters by acting as a broker between a diverse set of actors: firms, institutions, universities, financial and other intermediaries. Additionally, connectedness to MNEs improves local firms’ innovation.

This study is not free of limitations, mainly, because of the aspects that the analysis is based on one city and one cleantech hub. Further research could verify whether the findings of this paper hold in other cities and industries.

The findings, elucidating the connection between MNEs and local firms, as well as MNEs being important brokers in the local system, and the resulting impact, will help policymakers to take appropriate actions and support the local cleantech innovation. It is important to not only attract high-quality FDI into local clusters, but also to create and support collaborations between foreign firms and local actors, because colocation does not automatically leads to positive spillovers and a lot depends on how MNEs are integrated into the local milieu.

The present paper argues that FDI plays an important role in local cleantech innovation and it is important to integrate foreign firms in local social networks.

The authors analyze FDI patterns in an emerging industry at the city and local cluster level using a unique database containing the information on relationships between MNEs and local firms, as well as interview data.

The purpose of this paper is to find out the characteristics and evolutionary trends of China’s inter-regional innovation correlation network, the status and roles of each province in China’s inter-regional innovation correlation network and the influencing factors of China’s inter-regional innovation correlation effect.

Based on the patent data of 30 provinces (autonomous regions and municipalities) in China from 1991 to 2017, social network analysis was used to find out the characteristics and evolutionary trends of China’s inter-regional innovation correlation network and the status and roles of each province in China’s inter-regional innovation correlation network. Furthermore, the QAP method was used to find out the influencing factors of China’s inter-regional innovation correlation effect.

China’s inter-regional innovation correlation is becoming increasingly close and inter-regional innovation correlation network is becoming increasingly stable. Jiangsu, Zhejiang, Beijing, Shanghai, Guangdong and other eastern coastal provinces are at the core in the inter-regional innovation correlation network, while the western regions are marginal actors. China’s regional innovation development territory can be divided into four blocks, namely, “bidirectional spillover block,” “net spillover block,” “main beneficial block” and “net beneficial block,” and gradient transfer mechanism is obvious between the blocks. The geographical adjacency and similarity in regional industrial structure, urbanization level and government attention degree have significant positive effect on China’s inter-regional innovation correlation effects.

This paper only uses patent application as a measure of regional innovation level to analyze inter-regional innovation correlation effect. Meanwhile, this paper carries out an empirical study only from the provincial level and not from the city level.

This paper provides the practical basis for further promoting the coordinated development of regional innovation and promoting the construction of regional innovation systems with different characteristics.

This paper contributes to understand the status and role of each province in inter-regional innovation correlation network. Meanwhile, this paper also helps to understand the influence of the proximity and external environmental factors on inter-regional innovation correlation effect.

The purpose of this paper is to study the influence mechanism of different levels of social capital (Structure holes–local network attributes and indirect ties–global network attributes) and organizational culture on the creativity of key inventors, and the role of organizational culture between social capital and creativity.

The paper tested the hypotheses with a sample of patent data accumulated from 46 firms in Chinese electronic information and automobile sectors. Negative binomial regression was used to explore the factors influencing the creativity of key inventors.

The paper discovers that structural holes are valuable social capital for the creativity of key inventors and very important in firms with a collective and conservative culture. Moreover, it also locates that key inventor are more creative in firms with an individualistic and competitive culture than those in firms with a collective and conservative culture.

This study emphasizes the influence of social capital on creativity and contributes to R&D management. It highlights structural holes are certainly important to key inventors in a collective and conservative culture, thus contradicting preceding studies that locate structural holes useful solely in an individualistic culture. This finding broadens our knowledge of the benefits of this network structure. Also, this debate challenges several basic views on structural holes currently.

Knowledge transfer (KT) has been attracting significant attention from the scientific community. The need to establish collaborative network relationships to achieve effective KT has led to a large volume of studies that attempt to identify how collaborative networks influence KT processes. However, papers, which link KT and networks have not been systematised. This study aims to provide an overview of this academic field and sets an agenda for future research.

The authors followed the preferred reporting items for systematic reviews and meta-analyses method to conduct a systematic review of the literature published in 2000–2020. The authors sourced the sample from the Web of Science and Scopus databases. The authors screened the references under the management and business categories that were published in the first two quartiles of the Journal Citation Report. This search returned 190 impactful papers across the 53 journals that were analysed.

The authors present the main results in two sections. First, this paper elaborates a conceptual model of the field; second, the authors review KT between firms and other agents, which allows us to identify KT flows within and between companies, universities and public institutions.

This paper provides the first systematic review of collaborative networks and KT. Five areas of action are identified for future research and are specified in several research questions. The authors also provide several practical implications. In a world in which more and more dynamic agents coexist, it is important to be aware of the needs of organisations that create and disseminate specific knowledge.

Prior literature has long argued that knowledge networks contain great opportunities for innovation, and researchers can identify these opportunities using the properties of knowledge networks (PKNs). However, previous studies have examined only the relationship between structural PKNs (s-PKNs) and innovation, ignoring the effect of qualitative PKNs (q-PKNs), which refer to the quality of the relationship between two elements. This study aims to further investigate the effects of q-PKNs on innovation.

Using a panel data set of 2,255 patents from the Chinese wind energy industry, the authors construct knowledge networks to identify more PKNs and examine these hypotheses.

The results show that q-PKNs significantly influence recombinant innovation (RI), reflecting the importance of q-PKNs analysed in this study. Moreover, the results suggest that the combinational potential of an element with others may be huge at different levels of q-PKNs.

This study advances the understanding of PKNs and RI by exploring how q-PKNs impact RI. At different levels of PKNs, the potential of the elements to combine with others and form innovation are different. Researchers can more accurately identify the opportunities for RI using two kinds of PKNs. The findings also provide important implications on how government should provide support for R&D firms.