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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.

This article reviews emergent global trends in intellectual property protection and identifies patenting as a strategic initiative. Recent developments in software and method‐of‐doing‐business patenting are fast transforming the e‐business landscape. The article discusses the emergent global regulatory framework concerning intellectual property rights and the strategic value of patenting. Important features of a corporate patenting portfolio are described.

The purpose of the paper is to advance a framework that can assess and analyze the value of patent portfolios. On this purpose, the framework develops a conceptual and comprehensive index, the patent portfolio value index (PPVI), to assess the patent innovation level and suggest economic-strategic guidelines.

The authors have designed and applied a framework that synthesizes into a single index the results of a multiple criteria approach, based on information derived from quantitative objective data (claims, citations, and market coverage), information related to qualitative determinants (strategic positioning and economic importance), and information derived from decision makers’ perceptions and judgments.

The authors have applied the PPVI to the 3,532 patent portfolio documents in an Italian worldwide player in aerospace and defense market. The combined analysis, provided by the PPVI and a qualitative synoptic representation, has made it possible to understand the strategic positioning and alignment of patents with the core business of the company. The results of the analysis have provided managers with the necessary suggestions regarding action items to be performed: to reinforce, license, try to dismiss, or sell some of the examined patents of the portfolios.

The PPVI supplies a quick procedure to ascertain the profitability of patents and accounts for the value of a patent portfolio from an internal business perspective.

As it is built and defined, the PPVI shows elements of novelty compared to the other indexes existing in the literature, in that it follows a multiple criteria approach by merging quantitative and qualitative information.

The purpose of the study is to examine the relationship between the value of created knowledge and financial performance. It also assesses how knowledge breadth moderates the aforementioned relationship.

Focusing on the US biotechnology industry, the study matches patents data from the National Bureau of Economic Research and the United States Patent and Trademark Office with firms’ data from COMPUSTAT. Generalized least squares estimation is used as an analytical technique, and random-effects models are used to evaluate effects of the independent variables based on both within- and between-organization variances.

The findings reveal that biotechnological firms that create knowledge of higher values are likely to have higher financial performance than those creating knowledge of less value. Moreover, knowledge breadth is shown to positively moderate the relationship between knowledge value and firm performance.

Some of the limitations include not controlling for more firm-related and environmental factors that might have influenced firm performance.

The study provides evidence that the quality of knowledge should be significantly considered when creating new knowledge. That is, managers should prioritize the creation of highly valuable knowledge, even if it occasionally results in creating fewer numbers of patents. The paper also suggests that creating valuable knowledge that is broad and flexible should be an important objective for managers as it provides more opportunities to generate future rents.

The study emphasizes how the value of created knowledge impacts the financial performance of firms. It also illustrates how knowledge breadth moderates that relationship. The paper contributes to a stream of research that links knowledge management abilities and firm performance.

This paper aims to provide a complete analysis framework and prediction method for the construction of the patent securitization (PS) basic asset pool.

This paper proposes an integrated classification method based on genetic algorithm and random forest algorithm. First, comprehensively consider the patent value evaluation model and SME credit evaluation model, determine 17 indicators to measure the patent value and SME credit; Secondly, establish the classification label of high-quality basic assets; Then, genetic algorithm and random forest model are used to predict and screen high-quality basic assets; Finally, the performance of the model is evaluated.

The machine learning model proposed in this study is mainly used to solve the screening problem of high-quality patents that constitute the underlying asset pool of PS. The empirical research shows that the integrated classification method based on genetic algorithm and random forest has good performance and prediction accuracy, and is superior to the single method that constitutes it.

The main contributions of the article are twofold: firstly, the machine learning model proposed in this article determines the standards for high-quality basic assets; Secondly, this article addresses the screening issue of basic assets in PS.

Purpose – Recent research suggests that the positive effect of knowledge diversification on the value of corporate knowledge is limited.

Design/methodology/approach – This study uses an information processing perspective to explore the highest value that firms can draw from knowledge diversification and to argue that R&D cooperation and foreign direct investment help develop this value.

Findings: Regressions on a sample of 21.434 patents of German manufacturing firms show that technologically diversified knowledge has an inverted U-shaped influence on the value of technological knowledge. The findings also suggest that R&D cooperation increases the value generated by technologically diversified knowledge. However, foreign direct investment does not seem to have a moderating influence on the relationship between technological diversification and value.

Research limitations – We use patent citations to measure knowledge transfers. However, not all inventions are patented.

Originality/value – The information processing theory, which we apply in this chapter, provides consistent explanations for both the inverted U-shape of diversification and the extension of the optimal diversification of knowledge by R&D cooperation.

This paper proposes that patents are real options that allow holders of patents the right but not the obligation to sue others. We suggest that the likelihood of a patent being litigated is positively associated with value of the patent and the extent of disclosure (prior art cited) in the patent. However, under conditions of greater value, increases in disclosure reduce the likelihood of litigation of the focal patent. Similarly, under conditions of greater disclosure, increases in value reduce the likelihood of litigation of the focal patent. Rare events logit analyses of business method patents that were litigated, compared to patents that were not litigated, offer empirical evidence supporting the hypotheses.

The number of patents in China has grown rapidly in recent years. The purpose of this paper is to investigate how patents impact economic development in China.

This paper developed an empirical model by using panel data of 42 China's patent-intensive industries to investigate the economic contribution made by Chinese patent-intensive manufacturing industries.

This paper found that the intensity of valid patents is strongly positively related to economic growth. The intensity of yearly added patents presented an inverse U-shaped and a U-shaped curve with the economy made by China’s patent-intensive industries. The correlativity mainly depended on whether the patent intensity converges near the economic indicators. Meanwhile, from the perspective of input–output efficiency, for China’s patent-intensive industries, R&D institutes were overinvested, followed by R&D intensity and R&D staff.

Investigating patent influence on economic development is quite complex research. Existing studies have mainly focused on patent protection in legal systems, but have not provided a definitive answer to what the real influence is. This study sought to narrow this gap from the patent economy perspective.

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.

Since 2015, China has made efforts to reform its intellectual property rights (IPR) system to better protect and stimulate innovation. These reforms are a result of the demand for more stringent intellectual property (IP) protection from China’s domestic, innovative industries and a measure to ease the pressure exerted by its foreign trading partners, particularly against the background of the US-China trade dispute that started at the beginning of 2018. This paper summarizes these reforms and their implications.

This paper combines a variety of sources, including academic articles, government websites, news reports, industry surveys and expert opinions, to offer insights in China’s IPR system and its recent reforms.

This paper summarizes and discusses (1) the state’s law amendments, including the 2015 amendment of the “Law on Promoting the Transformation of Scientific and Technological Achievements”, the second amendment of the “Anti-Unfair Competition Law” with regard to trade secret protection, the fourth amendment of the “Patent Law”, and the legislations and regulations addressing the criticisms of the US administration over China’s so-called “forced” technology transfer policies; (2) the establishment of the specialized IP courts and tribunals since 2014; (3) the restructuring of the State IP Office; and (4) the issuing of an “Outline for Building an IPR Powerhouse (2021–2035)”.

This paper highlights China’s efforts to make its IPR system stronger and more just. It also discusses international observers’ reactions and pinpoints specific areas for further improvement.