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Studies have indicated that international innovation collaboration has promoted technology transfer and knowledge spillover between countries. The conclusion of various international intellectual property (IP) treaties has played an essential role in optimizing the international innovation and collaboration environment. This study investigates the effect of IP treaties on international innovation collaboration and whether international IP treaties can promote collaboration between a country and other economies in the world.

After collecting and extracting the patent record data from the United States Patent and Trademark Office (USPTO), a final dataset of 3,213,626 cooperative patents and 465,236 pairs of collaborations between two countries or regions is established. Based on the international patent collaboration data of 192 countries during 1976–2017, the changes in patent collaboration indicators after these countries joined 23 IP treaties are analyzed.

International IP treaties have significantly increased the number of patent cooperation countries of a country and its importance in international cooperation networks. The role of IP treaties is more manifested by the increased opportunities for a country's international innovation cooperation than its influence on global innovation; this is of extreme significance for developing countries to introduce advanced technologies.

Ginarte and Park (1997) have confirmed that IP treaties have helped to raise the level of IP protection. In this study, the increase in the degree centrality of the international innovation network is evidence of IP treaties to promote innovation cooperation. For a developing country, joining an intellectual property treaty may strengthen intellectual property protection and optimize its own international innovation cooperation methods.

Patents as one of the important components of intellectual capital are emerging as a new source for mining insights on open innovation (OI) practice of the organizations. Their role in value creation through collaboration and the inter-firm differences is yet to be explored in depth.

To achieve the aim, survey data is analyzed to rank OI practices (collaboration) of the firms, while patent data are analyzed to carry out descriptive and bivariate analysis to study the inter-firm differences in collaboration.

The survey findings highlight mergers and acquisitions (M&A) and patent pooling as the top two preferred modes of OI, while from patent data M&A has emerged as a predominant OI practice for mainly nonresident firms. At the firm level characteristics, out of firm age, number of granted patents and firm size, firm age has been found to be somewhat significant in few cases of OI practices.

It provides an alternative source, in this case patent data to study open innovation capabilities of firms in India. There is contribution to the patent value theory from profit motive to deriving strategic decisions on collaboration.

The managerial implications of this study lie in realizing granted patents as important business tools for seeking collaboration, tracing competitive intelligence and the geography of innovation of the firms' competitors.

The dataset of granted patents at the Indian Patent office (2005–2017), the sample of pharmaceutical firms drawn from this list of patents, patent data– based OI insights and the use of multiple imputation technique to missing data for meaningful insights are some of the unique aspects of this paper.

The purpose of this paper is twofold: to analyze to what extent innovation output of R & D collaborations, proxied by co-patenting activities in terms of quantity, characteristics and value, differs depending on whether the engaged R & D partners have a certain type of relationship (allies, suppliers and subsidiaries); to identify possible automakers co-patenting patterns taking into account the differences in the innovation output with their R & D partners.

To reach the aims, the authors matched two types of data: co-assigned patent portfolio of four automakers and relationship type between automakers and their co-assignees. Matching the company names of the two data sources allowed the authors to obtain the final data set used to carry out extensive descriptive and regression analysis, both on a firm- and patent-level.

Results show differences in the characteristics and the technological value of patented inventions in relation with the type of collaboration partner; they also support the authors in the identification of four co-patenting patterns (contingent, purposive, watchful and advanced) according to the co-patenting propensity and the presence of a preferred relationship type.

The paper contributes to the literature by investigating the presence of differences across the patenting activities of a selection of automakers and their supplier, allied and subsidiary firms. The issue related to patent value represents an emerging area of interest in the field of collaborations for innovation. The methodology constitutes a novelty by matching two different sources and standardizing the company names (“name game”) through an automated algorithm and a double manual check, by searching company web sites and corporate trees.

The purpose of this paper is to understand if and how the technological diversifications of collaborating firms and public research organisations (PROs) affect the technological impact of the resulting joint-patented innovations.

The authors conduct an analysis on a database of 590 dyadic joint patents, assigned to both firms and PROs, registered from 1976 to 2010 to the US Patent and Trademark Office and belonging to green technological classes, as defined by the International Patent Classification green inventory.

The study reveals that the assignees’ technological diversification has a significant influence on the impact of the patents jointly developed. Indeed, the results show that the most impactful joint patents result from collaborations involving technologically diversified firms.

This research sheds further light on the establishment of R&D collaborations between firms and PROs to jointly innovate. Specifically, it provides a novel perspective to investigate the impact of joint patents, by focussing on the assignees’ technological profile.

The present work suggests that firms characterised by a higher degree of technological diversification are more likely to co-develop patent of higher technological impact, as resulting from collaboration with PROs.

This study investigates the factors affecting the impact of joint patents resulting from collaborations between firms and PROs. In particular, the present research focusses on the effect of a relevant characteristic of the partners, such as their technological diversification.

The purpose of this paper was to study how public regulation promotes or hinders openness in the food industry, specifically how European novel food regulation has affected external ties among novel food pioneers seen through patents and their inventors.

A multiphase mixed-methods design was used to combine data as follows: Worldwide patents originating from Norwegian novel food pioneers 2004–2019, downloaded through the European Patent Office database. Application data and interviews were analysed together with substantial information on 88 patents.

Firms use patenting and novel food applications as part of a wider intellectual property rights strategy to guard against unintended spillovers and to shape external collaboration. Examinations of patents indicate a pattern of selective partnership with research and development (R&D) providers.

Food industry actors can combine property rights strategies to maintain a pattern of openness and external collaboration. R&D providers should consider the food industry's flag-planting strategies by integrating these into contractual regulations.

Little is known earlier about how novel food pioneers collaborate with suppliers, research actors, governmental actors, distributors and customers regarding new product development.

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.

Energy conservation and environmental protection industry (ECEPI) is a strategic choice to promote energy conservation and emission reduction, develop green economy and circular economy. However, China’s ECEPI is still in the stage of rapid development and the overall scale is relatively small, what development periods have the ECEPI experienced? This study aims to contribute to a better understanding of collaborative innovation evolution based on social network analysis from the perspective of multi-dimensional proximity.

Methodologically, this study uses social network analysis method to explore the co-evolution of multidimensional collaboration networks. It divides China’s ECEPI into four periods based on national policies from 2001 to 2020. This contribution constructs collaborative innovation networks from geographical, technological and organizational proximity.

The results show that the collaborative innovation network was initially formed in the central region of China, gradually expanded to neighboring cities and the core positions of Beijing, Jiangsu and Guangdong have been continuously consolidated. C02F has been the core of the collaboration networks, and the research focus has gradually shifted from the treatment of wastewater, sewage or sludge to the separation field. Enterprises always occupy a dominant position in the collaboration networks.

This research investigates the dynamic evolution process of collaborative innovation network in China’s ECEPI from the perspective of multidimensional proximity, explores the community structure, important nodes and multidimensional proximity features in the network, expands the research perspective on evolution characteristics of innovative network and the research field of social network analysis. Theoretically, this study enriches collaborative innovation theory, social network theory and multi-dimensional proximity theory.

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 purpose of this study is to investigate whether repeated alliances between two members of a patent pool boost enterprise innovation. Furthermore, this paper intends to determine whether the innovation performance becomes higher or lower based on the partnership characteristics.

In this empirical study, hierarchical regression is used to analyze the longitudinal data obtained from 12 patent pools managed by MPEG LA during a time period ranging from 2006 to 2018. The members of patent pools comprise research institutions, firms and universities. Research analyses are performed based on a sample of 68,400 member pairs who had established repeated alliances. The information regarding such pairs is gathered from public databases.

Repeated alliances positively correlate with enterprise innovation performance in patent pools; this performance is higher when the two enterprises have exploratory collaborations. Conversely, the performance is lower when the partners have a similar technology base and are engaged in a technological competition (competitive learning and patent litigation). Moreover, the performance is lower when one partner demonstrates higher network centrality and richer structural holes than the other partner.

Patent pools play an instrumental role in eliminating patent-licensing barriers, thereby allowing mutual acquisition of complementary technologies, and cooperatively strengthening technology development. From the perspective of theories of coopetition, knowledge management and social network, this study explores the impact of patent pools on enterprise innovation performance and ascertains the moderating roles of technology coopetition, technology similarity and network position, thereby expanding the scope of innovation effect in the context of patent pools.

As the university–industry collaboration (UIC) gradually attracts the attention of various national governments, the number of studies on UIC has increased substantially. Past UIC studies have mostly focused on investigating the incentives and the motivation for UIC, forms of UIC and performance output of UIC. However, they have not actively identified the key technologies and technology distribution that are conductive to the commercialization of UIC outcomes. Therefore, this study aims to adopt the licensed UIC patents as the basis for analysis and to construct a patent licensing technology network.

This study focused on licensed patents because past studies have indicated that such patents usually have higher value. Moreover, patent licensing can be seen as the final step for the commercialization of UIC outcomes. Finally, past studies have rarely explored patent examiners’ views on key technologies. However, during the substantive examination of patents, patent examiners often use their background knowledge regarding the technology to include citations to other patented technologies that they consider valuable or indispensable. Therefore, this study focused on investigating the patents recognized and cited by patent examiners and conducted key technology identification.

The results indicated that past key technologies in UIC focused on surveying, medicine, biochemistry and electric digital data processing; these fields are crucial to the commercialization of key UIC technologies. Finally, the USA, Japan, Sweden and Germany play critical roles in the network of global university–industry cooperation and technology licensing.

Patent examiners’ perspectives were adopted to establish a patent licensing technology network, through which the key technologies that could promote UIC patent licensing were mined. This study can also serve as a reference for resource allocation in university research and development and for governments to promote new technologies.