Patent Citation Analysis Research Articles

Corrected Measures for Patent Citation Analysis: Accounting for Published Patent Applications

This article investigates patent citations made to published patent applications. Although citations to patent publications are conceptually indistinguishable from citations to granted patents, they are omitted from all standard measures. We find that publication citations are a large and growing portion of patent citations, and that they differ statistically from citations to granted patents on several important dimensions. We conclude that omitting publication citations is likely to generate biased measures, and that standard measures of patent citations should be corrected. We release our computer code and corrections for future use.

Multiple patent network analysis for identifying safety technology convergence

Purpose Using the large database of patent, the purpose of this paper is to structure a technology convergence network using various patent network analysis for integrating different results according to network characteristics. Design/methodology/approach The patent co-class analysis and the patent citation analysis are applied to discover core safety fields and technology, respectively. In specific, three types of network analysis, which are centrality analysis, association rule mining analysis and brokerage network analysis, are applied to measure the individual, synergy and group intensity. Findings The core safety fields derived from three types of network analysis used by different nature of data algorithms are compared with each other to understand distinctive meaning of cores of patent class such as medical safety, working safety and vehicle safety, differentiating network structure. Also, to be specific, the authors find the detailed technology contained in the core patent class using patent citation network analysis. Practical implications The results provide meaningful implications to various stakeholders in organization: safety management, safety engineering and safety policy. The multiple patent network enables safety manager to identify core safety convergence fields and safety engineers to develop new safety technology. Also, in the view of technology convergence, the strategy of safety policy can be expanded to collaboration and open innovation. Originality/value This is the initial study on applying various network analysis algorithms based on patent data (class and citation) for safety management. Through comparison among network analysis techniques, the different results are identified and the collective decision making on finding core of safety technology convergence is supported. The decision maker can obtain the various perspectives of tracing technology convergence.

Patterns of Learning in Dynamic Technological System Lifecycles—What Automotive Managers Can Learn from the Aerospace Industry?

Not only with respect to the common overlaps within the market of urban air mobility, but also in terms of their requirement profile with regard to the systemic core, all mobility industries are converging. This article focuses on the required patterns of learning in order to cope with these changes, and what automotive managers can learn from the aerospace industry in this context. As organizational learning is the central parameter of economic evolution, and technology develops over trajectory shifts, companies are, at the very least, cyclically forced to learn ambidextrously, or are squeezed out of the market. They have to act and react as complex adaptive systems in their changing environment. Especially in these dynamics, ambidextrous learning is identified to be a conditio sine qua non for organizational success. Especially the combination of efficiency-oriented internal exploitation with an explorative and external-oriented open innovation network turns out to be a superior strategy. By combining patent data, patent citation analysis and data on the European Framework Programs, we show that there are temporal differences, i.e., position of the product in the product, technique, technology, and industry life cycle. Furthermore, we draw a conclusion dependent on the systemic product character, which enforces different learning requirements concerning supply chain position and, as an overarching conclusion, we identify product structure to be decisive for how organizational learning should be styled.

Identifying potential users of technology for technology transfer using patent citation analysis: a case analysis of a Korean research institute

The purpose of this study is to examine whether patent citation analysis can be used for making decisions of technology transfer. More precisely, the authors of this paper are interested in the matter of identifying potential users of technology by patent citation analysis. Previous research relied on patents’ keywords, and as a consequence it was difficult to implement in practice where organizations retain huge number of patents to transfer. In this study, we attempt to use IPCs instead of keywords. Our approach is to identify dominant IPC and sub-classes of an organization by applying co-classification analysis, and explore firms that cited the patents in the dominant IPC. Our view is that the organizations explored in this process can be potential users of technology. To verify our view, we examined the patents and technology transfer cases of two divisions in K Research Institute in Korea. The results show that our view was right only for a limited field. We suppose that the reasons may stem from technological characteristics and firm size effect. Therefore, we suggest that there should be further research considering technological characteristics and firm size.

Testing the science/technology relationship by analysis of patent citations of scientific papers after decomposition of both science and technology

The relationship of scientific knowledge development to technological development is widely recognized as one of the most important and complex aspects of technological evolution. This paper adds to our understanding of the relationship through use of a more rigorous structure for differentiating among technologies based upon technological domains (defined as consisting of the artifacts over time that fulfill a specific generic function using a specific body of technical knowledge).

Early identification of emerging technologies: A machine learning approach using multiple patent indicators

Patent citation analysis is considered a useful tool for identifying emerging technologies. However, the outcomes of previous methods are likely to reveal no more than current key technologies, since they can only be performed at later stages of technology development due to the time required for patents to be cited (or fail to be cited). This study proposes a machine learning approach to identifying emerging technologies at early stages using multiple patent indicators that can be defined immediately after the relevant patents are issued. For this, first, a total of 18 input and 3 output indicators are extracted from the United States Patent and Trademark Office database. Second, a feed-forward multilayer neural network is employed to capture the complex nonlinear relationships between input and output indicators in a time period of interest. Finally, two quantitative indicators are developed to identify trends of a technology's emergingness over time. Based on this, we also provide the practical guidelines for implementation of the proposed approach. The case of pharmaceutical technology shows that our approach can facilitate responsive technology forecasting and planning.

Investigating the Dynamics of Interdisciplinary Evolution in Technology Developments

In a global economy where technology plays a vital role, technology fusion is important for developing designs of outstanding innovations. These designs often involve the transfer of knowledge between different technological industries, a term known as “interdisciplinarity”. This paper aims to contribute to the literature of interdisciplinary innovation by using patent indicators to explore how conventional technologies have evolved into interdisciplinary technologies in different industries. Patent citation analysis and negative binomial regression were conducted to: 1) observe the dynamics and evolution of interdisciplinary technologies and, 2) explore how interdisciplinary knowledge influences technology developments. The study found that interdisciplinary knowledge plays a significant role in the development of valuable technologies in all investigated industries. An important managerial implication from this is that firms should consider developing interdisciplinary technologies whenever possible.

The impact of policy consistency on technological competitiveness: A study on OECD countries

This study investigates the impact of policy consistency on technological competitiveness using patent citation analysis. Policy support plays a key role in promoting firms’ investment in research and development (R&D) activities, especially in emerging sectors. Policy consistency increases technological competitiveness, since it encourages firms to invest in R&D activities. Although previous studies argue policy design and characteristics, few deal with policy consistency, and they lack a quantitative measure of policy consistency and explanation of its effects. Therefore, this study proposes the quantitative indexes for policy consistency and potential technological competitiveness.The indexes are applied to the case of renewable energy sector since energy sector is highly dependent on the government policy and thus needs high policy consistency. The result shows that renewable energy technology development is affected by policy and the higher the policy consistency especially in emerging sectors. It also shows that countries of high policy consistency tend to achieve higher technological competitiveness and thus are likely to secure higher technological competitiveness in the future. The findings of this study can be used in designing policy for sustainable technological competitiveness and will be a corner stone for researches on assessing policy consistency.

Investigating the dynamics of interdisciplinary evolution in technology developments

In a global economy where technology plays a vital role, technology fusion is important for developing designs of outstanding innovations. These designs often involve the transfer of knowledge between different technological industries, a term known as “interdisciplinarity.” This paper aims to contribute to the literature on interdisciplinary innovation by using a novel methodological approach to explore how conventional technologies have evolved into interdisciplinary technologies in different industries. The new methodological approach was based on patent citation analysis and negative binomial regressions conducted to: 1) observe the dynamics and evolution of interdisciplinary technologies, and 2) explore how interdisciplinary knowledge influences technology developments. The study found that interdisciplinary knowledge plays a significant role in the development of valuable technologies in all investigated industries. An important managerial implication from this is that firms should consider developing interdisciplinary technologies whenever possible.

Hawkes process-based technology impact analysis

Abstract Patent citation analysis is considered a useful tool for technology impact analysis. However, the outcomes of previous methods do not provide a fair reflection of a technology’s future prospects since they are based on deterministic approaches, assuming that future trends will remain the same as those in the past. As a remedy, we propose a Hawkes process-based patent citation analysis method to assess the future technological impact and uncertainty of a technology in a time period of interest by employing the future citation counts of the relevant patents as a quantitative proxy. For this, we construct a citation interval matrix from the United States Patent and Trademark Office (USPTO) database, and employ a Hawkes process - a special case of path-dependent stochastic processes - as a method for patent citation forecasting. Specifically, the Hawkes process models the idiosyncratic and dynamic behaviours of a technology’s evolution and obsolescence by increasing the likelihood of another subsequent citation by oneself (i.e., self-excitation) and decaying the likelihood back towards the initial level naturally. A case study of the patents about molecular amplification diagnosis technology shows that our method outperforms previous deterministic approaches in terms of accuracy and practicality.

Visualization Method of Patent Citation Analysis Based on Improved Hyperbolic Tree

Citation analysis is an important content of patent analysis. Aimimg at the problems of visualizing the large hierarchical data in the limited display area, an improved hyperbolic tree for the visualization of patent citation analysis is proposed. The method combines the traditional hyperbolic tree with fisheye and other visualization technologies, and it can reveal the multi-level patent information, as well as display the overall layout and local details. Thus, the interaction between the overall and local data may be realized easily, and it is convenient for the users to understand the interested information.

Structural embeddedness and innovation diffusion: the moderating role of industrial technology grouping

Industrial technology grouping is a common phenomenon that occurs as an industry develops and evolves. However, the research on innovation diffusion has given little attention to the role of industrial technology grouping. This paper extends the prior research to analyze the impact of industrial technology grouping on innovation diffusion within the framework of structural embeddedness. In our empirical study, we selected a sample of patents in the smart phone industry during the 2004---2014 period. We used both hierarchical regression analysis and patent citation analysis to explore the impact of industrial technology grouping on innovation diffusion in the two dimensions of clustering and bridging ties, which yielded several valuable results. First, industrial technology grouping is a common phenomenon in the development of industrial technology. Moreover, the dynamic changes of technology clusters are an important driving force shaping the trends and diversity of industrial technology. Second, industrial technology grouping does not have a significant effect on firm innovation diffusion, whereas structural embeddedness directly affects innovation diffusion. Third, industrial technology grouping positively moderates the impact of structural embeddedness on firm innovation diffusion in both dimensions of clustering and bridging ties.

Patent Citations Analysis and Its Value in Research Evaluation: A Review and a New Approach to Map Technology-relevant Research

Abstract Purpose First, to review the state-of-the-art in patent citation analysis, particularly characteristics of patent citations to scientific literature (scientific non-patent references, SNPRs). Second, to present a novel mapping approach to identify technology-relevant research based on the papers cited by and referring to the SNPRs. Design/methodology/approach In the review part we discuss the context of SNPRs such as the time lags between scientific achievements and inventions. Also patent-to-patent citation is addressed particularly because this type of patent citation analysis is a major element in the assessment of the economic value of patents. We also review the research on the role of universities and researchers in technological development, with important issues such as universities as sources of technological knowledge and inventor-author relations. We conclude the review part of this paper with an overview of recent research on mapping and network analysis of the science and technology interface and of technological progress in interaction with science. In the second part we apply new techniques for the direct visualization of the cited and citing relations of SNPRs, the mapping of the landscape around SNPRs by bibliographic coupling and co-citation analysis, and the mapping of the conceptual environment of SNPRs by keyword co-occurrence analysis. Findings We discuss several properties of SNPRs. Only a small minority of publications covered by the Web of Science or Scopus are cited by patents, about 3%–4%. However, for publications based on university-industry collaboration the number of SNPRs is considerably higher, around 15%. The proposed mapping methodology based on a “second order SNPR approach” enables a better assessment of the technological relevance of research. Research limitations The main limitation is that a more advanced merging of patent and publication data, in particular unification of author and inventor names, in still a necessity. Practical implications The proposed mapping methodology enables the creation of a database of technology-relevant papers (TRPs). In a bibliometric assessment the publications of research groups, research programs or institutes can be matched with the TRPs and thus the extent to which the work of groups, programs or institutes are relevant for technological development can be measured. Originality/value The review part examines a wide range of findings in the research of patent citation analysis. The mapping approach to identify a broad range of technology-relevant papers is novel and offers new opportunities in research evaluation practices.

The knowledge network dynamics in a mobile ecosystem: a patent citation analysis

The paradigm of the mobile ecosystem is rapidly changing, especially since the uction of smart devices. New important players are emerging, and the scope of the mobile ecosystem is expanding and encroaching on the technological boundaries of other IT ecosystems. However, our understanding of the mobile ecosystem has been limited given the few existing studies. Therefore, in this paper, we empirically examine the network structure of a mobile ecosystem by measuring the technology knowledge flows between firms based on a patent citation analysis of the mobile industry. We found that platform providers are emerging as the center of the knowledge flow activity in the ecosystem. By introducing a new network index, the Network Concentration Index, which measures a firm's knowledge concentration ratio toward subsectors, we also found that each platform provider shows distinctive changing patterns in their technology knowledge network and that each is forming its own sub-network with increased influence on affiliated firms.

Forecasting and identifying multi-technology convergence based on patent data: the case of IT and BT industries in 2020

Having a new technology opportunity is a significant variable that can lead to dominance in a competitive market. In that context, accurately understanding the state of development of technology convergence and forecasting promising technology convergence can determine the success of a firm. However, previous studies have mainly focused on examining the convergence paths taken in the past or the current state of convergence rather than projecting the future trends of convergence. In addition, few studies have dealt with multi-technology convergence by taking a pairwise-analysis approach. Therefore, this research aimed to propose a forecasting methodology for multi-technology convergence, which is more realistic than pairwise convergence, based on a patent-citation analysis, a dependency-structure matrix, and a neural-network analysis. The suggested methodology enables both researchers and practitioners in the convergence field to plan their technology development by forecasting the technology combination that will occur in the future.

The Knowledge Network Dynamics in a Mobile Ecosystem: A Patent Citation Analysis

The paradigm of the mobile ecosystem is rapidly changing, especially since the introduction of smart devices. New important players are emerging, and the scope of the mobile ecosystem is expanding and encroaching on the technological boundaries of other IT ecosystems. However, our understanding of the mobile ecosystem has been limited given the few existing studies. Therefore, in this paper, we empirically examine the network structure of a mobile ecosystem by measuring the technology knowledge flows between firms based on a patent citation analysis of the mobile industry. We found that platform providers are emerging as the center of the knowledge flow activity in the ecosystem. By introducing a new network index, the Network Concentration Index, which measures a firm’s knowledge concentration ratio toward subsectors, we also found that each platform provider shows distinctive changing patterns in their technology knowledge network and that each is forming its own sub-network with increased influence on affiliated firms.

Do patent citations indicate knowledge linkage? The evidence from text similarities between patents and their citations

Abstract Whether patent citations indicate knowledge linkage is still a controversial issue, which is very important for the widespread use of the patent citation analysis method. We hypothesize that there exists technological knowledge linkage between patents and their citations, and that the linkage can be detected through measuring text similarities between them. To test the hypothesis, we selected citing-cited patent pairs as the observation group and selected patent pairs without citing-cited relationship as the control group. Using the VSM with WF-IDF weighting method, we calculated text similarity values of the two groups. Through comparing text similarity values between the two groups, we validate that in the vast majority of cases text similarity values of citing-cited pairs are much higher than those of non-citing-cited pairs. The study in nano-technology field shows that the above results are the same, although patents in the same technological area are more relevant than in different technological areas. Furthermore, by comparing text similarities between applicant and examiner citing-cited pairs, the results show that in more cases examiner citations indicate knowledge linkage a bit better than applicant citations. Preferably, examiner citations can be regarded as not only the supplement of applicant citations but also the more important technological background and the prior art closely related to the patents. Compared to applicant citations, examiner citations are a good indicator of knowledge linkage rather than an incomplete and noisy indicator. In short, the results suggest that most certainly patent citations can indicate knowledge linkage, and more likely examiner citations can indicate knowledge linkage a bit better than applicant citations, especially for the component of patent claims. Therefore, we accept the hypothesis that patent citations can indicate knowledge linkage, which is the basic assumption of the patent citation analysis method.

Unconnected component inclusion technique for patent network analysis: Case study of Internet of Things-related technologies

Abstract In this study, we propose an unconnected component inclusion technique (UCIT) for patent citation analysis. Our method generates a cluster solution that includes unconnected and connected components of a direct citation network, enabling a more complete analysis of the technology fields. Case studies of Internet of Things-related technologies were conducted to test the effectiveness of our proposed method. We observed that UCIT increased the number of nodes especially in relatively small networks. Additionally, we analyzed how the clusters changed by adding unconnected patents to the citation network and identified four types of clustering phenomenon. Our method can be used by patent officers, R&D managers, and policy makers when they want to understand the technology landscape better.

Evolutionary Patterns of Renewable Energy Technology Development in East Asia (1990–2010)

This study investigates the evolutionary patterns of renewable energy technology in East Asian countries—Japan, Korea, and China—as an emerging technology where the catch-up strategy is actively taking place. To reflect the quality of technology development activities, we assess each country’s research and development (R&D) activities using patent citation analysis. The goal of this study is to overcome the limitations of prior research that uses quantitative information, such as R&D expenditures and number of patents. This study observes the process of technological catch-up and leapfrogging in the East Asian renewable energy sector. Furthermore, we find that each nation’s technology development portfolio differs depending on the composition share of technologies. Policymakers in emerging economies can use the findings to shape R&D strategies to develop the renewable energy sector and provide an alternative method of evaluating the qualitative development of technology.

Exploring Potential Users of Patents for Technology Transfer: Utilizing Patent Citation Data

The purpose of this study is to examine whether potential users of technology can be identified by patent citation analysis. Previous research relied on patent's keywords, and as a consequence it was difficult to implement in practice where organizations retain huge number of patents to transfer. In this study, we attempt to use IPC instead of keywords. Our approach is to identify dominant IPC and sub-classes of an organization by applying co-classification analysis, and explore firms that cited the patents in the dominant IPC. Our view is that the organizations explored in this process can be potential users of technology. To verify our view, we examined the patents and technology transfer cases of K Research Institute's Division A. The results show that our view was right only for the field with co-classification of B01J and C07C, and it was not possible to confirm our argument for other classes. We suppose that the reasons may stem from technological characteristics and firm size effect. Therefore, we suggest that there should be further research considering technological characteristics and firm size.