Assessing coreness and intermediarity of technology sectors using patent co-classification analysis: the case of Korean national R&D

Rapid technological advancements and increasing research and development (R&D) costs are making it necessary for national R&D plans to identify the coreness and intermediarity of technologies in selecting projects and allocating budgets. Studies on the coreness or intermediarity of technology sectors have used patent citations, but there are limitations to dealing with patent data. The limitations arise from the most current patents and patents that do not require citations, e.g. Korean patents. Further, few or no studies have simultaneously considered both coreness and intermediarity. Therefore, we propose a patent co-classification based method to measure coreness and intermediarity of technology sectors by incorporating the analytic network process and the social network analysis. Using IPC co-classifications of patents as technological knowledge flows, this method constructs a network of directed knowledge flows among technology sectors and measures the long-term importance and the intermediating potential of each technology sector, despite the limitations of patent-based analyses. Considering both coreness and intermediarity, this method can provide more detailed and essential knowledge for decision making in planning national R&D. We demonstrated this method using Korean national R&D patents from 2008 to 2011. We expect that this method will help in planning national R&D in a rapidly evolving technological environment.     

Factors affecting the diffusion of patented military technology in the field of weapons and ammunition

In this paper, we carry out an empirical analysis to address some questions concerning the flow of knowledge stemming from military patented technologies. Patented military technology consists of a set of inventions which nature, uses or/and applications have defensive or offensive purposes. In this paper, we focus on the field of weapons and ammunition. Our objective is to identify, why the knowledge embedded in a military technology diffuses into other patented technologies. The methodology relies on a patent citations analysis and involves the specification of several multilevel logit models to identify the individual and country characteristics that determine the citation of military patents in subsequent patents. The data contain 1,756 citations to 582 patents of military origin with a simultaneous Europe–US protection and registered by companies/institutions from 1998 to 2003. The results reveal that military knowledge diffuses more intensively across civil patents, when the original military patent includes diverse technologies (civil and military) and is progressively less specific in terms of weapons and ammunition. Military patents filed by British, French, US, Japanese and German companies are, in this order, more likely to have a larger number of citations in subsequent civil patents. The ownership of the original military patent is not a determining factor for explaining the diffusion into civil patents, but it does influence the diffusion across mixed and military technologies. Finally, the technological capacity of the citing company also affects the type and intensity of the diffusion of the military knowledge.     

Prediction of emerging technologies based on analysis of the US patent citation network

The network of patents connected by citations is an evolving graph, which provides a representation of the innovation process. A patent citing another implies that the cited patent reflects a piece of previously existing knowledge that the citing patent builds upon. A methodology presented here (1) identifies actual clusters of patents: i.e., technological branches, and (2) gives predictions about the temporal changes of the structure of the clusters. A predictor, called the citation vector, is defined for characterizing technological development to show how a patent cited by other patents belongs to various industrial fields. The clustering technique adopted is able to detect the new emerging recombinations, and predicts emerging new technology clusters. The predictive ability of our new method is illustrated on the example of USPTO subcategory 11, Agriculture, Food, Textiles. A cluster of patents is determined based on citation data up to 1991, which shows significant overlap of the class 442 formed at the beginning of 1997. These new tools of predictive analytics could support policy decision making processes in science and technology, and help formulate recommendations for action.     

Identifying rapidly evolving technological trends for R&;D planning using SAO-based semantic patent networks

Patents constitute an up-to-date source of competitive intelligence in technological development; thus, patent analysis has been a vital tool for identifying technological trends. Patent citation analysis is easy to use, but fundamentally has two main limitations: (1) new patents tend to be less cited than old ones and may miss citations to contemporary patents; (2) citation-based analysis cannot be used for patents in databases which do not require citations. Naturally, citation-based analysis tends to underestimate the importance of new patents and may not work in rapidly-evolving industries in which technology life-cycles are shortening and new inventions are increasingly patented world-wide. As a remedy, this paper proposes a patent network based on semantic patent analysis using subject-action-object (SAO) structures. SAO structures represent the explicit relationships among components used in a patent, and are considered to represent key concepts of the patent or the expertise of the inventor. Based on the internal similarities between patents, the patent network provides the up-to-date status of a given technology. Furthermore, this paper suggests new indices to identify the technological importance of patents, the characteristics of patent clusters, and the technological capabilities of competitors. The proposed method is illustrated using patents related to synthesis of carbon nanotubes. We expect that the proposed procedure and analysis will be incorporated into technology planning processes to assist experts such as researchers and R&D policy makers in rapidly-evolving industries.     

Exploring the quality of environmental technology in Europe: evidence from patent citations

In this paper we carry out an empirical analysis to address some questions concerning the production and quality of technology in environmental sectors. The methodology involves patents as a measure of the generation of new knowledge, and patent citations as a proxy for the quality of a technological invention. The sample contains more than 12,000 environmental European patents from firms and government institutions from 1998 to 2004. From our econometric analysis, we found that environmental patents applied by individual inventors present on average less quality that those applied by institutional inventors. The size of family patent is relevant to explain forward patent citation. Furthermore, patents coming from abroad (out of Europe), in particular with US and Japan priority, are more cited on average than local patents (with European priority). Lastly, the specialization in environmental fields of a patent plays a negative role in determining the frequency of forward citation.     

Transnational citation, technological diversity and small world in global nanotechnology patenting

Despite the extensive studies conducted in the field of nanotechnology based on US patent data, the choice of a single database may impede a wider view of this technology frontier. Based on patent data from the Derwent Innovation Index database that covers the data of 41 major patent offices, we review the development of nanotechnology patenting from the dimensions of patenting authority and technological classification. We find that a small number of countries dominating the technology have similar technological diversity in terms of nanotechnology patents. After the discussion and summary of the citation modes and citation rate curve, we construct the patent citation networks at the patent document level and discuss the distinctive transnational citation patterns. We then use Search Path Count Method to extract the technological trajectory, where we find very high selectiveness. In the final section of this paper, we discover the small world phenomenon in the citation networks, which is widely investigated in undirected networks such as co-authorship networks, but rarely touched in citation networks due to the limitations of the presumptions. We propose the reachable path length and citation clustering in the revised small world model for acyclic directed networks and provide the realistic meaning of the new measures.     

Evolution monitoring for innovation sources using patent cluster analysis

According to the increasing importance of advanced technologies for economy growth and the incremental complexity of research and development management, a novel methodology is proposed in this paper to monitor the evolution trace of innovation sources. This approach focuses on the knowledge-transfer among technologies using patent cluster analysis. More specifically, a citation network model, consisting of patents in “Coherent Light Generators” classification, is established with the data collected from the United States Patent and Trademark Office. In addition, dynamical topological structure is investigated to probe into the overview properties and identify key milestones for the expanding citation network from 1976 to 2014. Next, a novel framework for patent clustering is developed to find out knowledge chunks of which internal knowledge-flows are dense while cut edges are sparse. Community detection algorithms are compared with different assessment indices based on citation network and the selected solution is improved using optimization objectives of cluster analysis. Then, the dynamical structure of the detected knowledge chunks is investigated and the evolution of innovation sources, identified by k-core decomposition, is monitored to unveil the technology development trace. Finally, analysis results are discussed and related conclusions are summarized. This article improves approaches for patent cluster analysis and develops a new follow-up investigation methodology for detected knowledge chunks. It is discovered there are not only scale increases, but also the integration for knowledge chunks during the focal period. Identifying the knowledge chunks which obtain rapid growth in both cluster scale and innovation source is useful to detect technology development opportunities.     

What makes the first forward citation of a patent occur earlier?

Identifying the economic value of a patent is crucial to technology management. It also facilitates the commercialization and transactions of patents. As a proxy of patent value, forward citation counting is widely used, but it takes a long time for a patent to be sufficiently cited. In this context, we suggest the first citation lag, namely the time taken until the first citation, as a proxy of patent value, as it is positively correlated with the patent value and considers the fact that important patents with a high economic value tend to receive many citations in a short space of time. We explore the influential patent attributes related to the first citation lag to build a model to predict the patent value. By using the Cox proportional hazard model on green inventory patent data, we find that patents with a shorter technology cycle time and a larger number of IPC four-digit classes, claims, patent family, and backward citations are associated with the shorter first citation lag, while a patent’s science linkage has an inverse U-shaped relationship with the first citation lag. Further, patents having an unconventional technological core have a longer first citation lag and among patents having an unconventional technological core, the presence of a novel element makes the first citation earlier. Our study is expected to help patent evaluation in the early stage of technology transfer.     

Hybrid documents co-citation analysis: making sense of the interaction between science and technology in technology diffusion

The paper presents a methodology called hybrid documents co-citation analysis, for studying the interaction between science and technology in technology diffusion. Our approach rests mostly on patent citation, cluster analysis and network analysis. More specifically, with the patents citing Smalley RE in Derwent innovations index as the data sets, the paper implemented hybrid documents co-citation network through two procedures. Then spectrum cluster algorithm was used to reveal the knowledge structure in technology diffusion. After that, with the concordance between network properties and technology diffusion mechanisms, three indicators containing degree, betweenness and citation half-life, were calculated to discuss the basic documents in the pivotal position during the technology diffusion. At last, the paper summarized the hybrid documents co-citation analysis in practise, thus concluded that science and technology undertook different functions and acted dominatingly in the different period of technology diffusion, though they were co-activity all the time.     

Analyzing technology impact networks for R&D planning using patents: combined application of network approaches

Recently, national governments have tried to improve technology ecology, by formulating research and development (R&D) policies and investing in R&D programs. For strategically designed national R&D plans, analytic approaches that identify and assess the impact of each technology from short-term and long-term perspectives are necessary. Further, in methodological perspective, the approaches should be able to synthetically consider the most recent technological information, the direct and hidden impacts among technologies, and the relative impacts of the focal technology in globally-linked technological relationship from the overall perspective. However, most previous studies based patent citation networks are insufficient for these requirements. As a remedy, we present a combined approach for constructing a technology impact network and identifying the impact and intermediating capability of technology areas from the perspective of a national technology system. To construct and analyze the technology impact network, our method integrates three network techniques: patent co-classification (PCA), decision making trial and evaluation laboratory (DEMATEL), and social network analysis (SNA). The advantages of the proposed method are threefold. First, it identifies the directed technological knowledge flows from the most recent patents, by employing PCA. Second, the proposed network contains both the direct and indirect impacts among different technology areas, by applying the DEMATEL method. Third, using SNA, the method can analyze the characteristics of the technologies in terms of the comprehensive impacts and the potential brokerage capabilities. The method is illustrated using all of the recent Korean patents (58,279) in the United States patent database from 2008 to 2012. We expect that our method can be used to provide input to decision makers for effective R&D planning.     

Tracing knowledge diffusion

Knowledge diffusion is the adaptation of knowledge in a broad range of scientific and engineering research and development. Tracing knowledge diffusion between science and technology is a challenging issue due to the complexity of identifying emerging patterns in a diverse range of possible processes. In this article, we describe an approach that combines complex network theory, network visualization, and patent citation analysis in order to improve the means for the study of knowledge diffusion. In particular, we analyze patent citations in the field of tissue engineering. We emphasize that this is the beginning of a longer-term endeavor that aims to develop and deploy effective, progressive, and explanatory visualization techniques for us to capture the dynamics of the evolution of patent citation networks. The work has practical implications on resource allocation, strategic planning, and science policy. This revised version was published online in June 2006 with corrections to the Cover Date.     

Discovering and assessing fields of expertise in nanomedicine: a patent co-citation network perspective

Discovering and assessing fields of expertise in emerging technologies from patent data is not straightforward. First, patent classification in an emerging technology being far from complete, the definitions of the various applications of its inventions are embedded within communities of practice. Because patents must contain full record of prior art, co-citation networks can, in theory, be used to identify and delineate the inventive effort of these communities of practice. However, the use patent citations for the purpose of measuring technological relatedness is not obvious because they can be added by examiners. Second, the assessment of the development stage of emerging industries has been mostly done through simple patent counts. Because patents are not all valuable, a better way of evaluating an industry’s stage of development would be to use multiple patent quality metrics as well as economic activity agglomeration indicators. The purpose of this article is to validate the use of (1) patent citations as indicators of technological relatedness, and (2) multiple indicators for assessing an industry’s development stage. Greedy modularity optimization of the ‘Canadian-made’ nanotechnology patent co-citation network shows that patent citations can effectively be used as indicators of technological relatedness. Furthermore, the use of multiple patent quality and economic agglomeration indicators offers better assessment and forecasting potential than simple patent counts.     

Analyzing the value of technology based on the differences of patent citations between applicants and examiners

Patent applicants and examiners do not always have the same point of view when conducting a prior-art search. Although several studies have suggested differences between citations by applicants and examiners, the data and range of empirical studies are too incomplete to generalize the characteristics of relationships between citation types and the value of a technology or invention. To overcome this limitation, it is crucial to compare citations by applicants and by examiners in depth, with diverse perspectives and data, to determine the value of patent information for technological innovation. Thus, this paper suggests that the differences in the composition of technical information and patent quality in patent-level investigations as well as the locus of the knowledge source and knowledge recentness in knowledge-level investigations according to patent citation type (by applicants and examiners) reflect Pavitt’s perspective on the nature, impact, and source of technological innovation. We found that the quality of patents cited by applicants is higher than that of those by examiners in four industries, excluding a supplier-dominated industry. The citation types are related to the locus of the knowledge source in four industries, excluding the supplier-dominated industry. In particular, the patents cited by examiners tended to be more recently issued in all sectoral fields. This research contributes to confirming the technological value of patents based on the citation behaviors of applicants and examiners through empirical analysis. The results can be utilized to investigate signals or noise in technological innovation and improve processes or systems of patent examination. In addition, it can help applicants conduct more thorough prior-art searches by comprehending the examiner’s perspective toward citations to increase the probability of patent registration.     

Development trend forecasting for coherent light generator technology based on patent citation network analysis

A forecasting methodology for technology development trends is proposed based on a two-level network model consisting of knowledge-transfer among patents and patent subclasses, with the aim to confront the increasing complex challenge in technology investment and management. More specifically, the patents of the “coherent light generators” classification, granted from 1976 to 2014 by examiners of the United States Patent and Trademark Office, are collected and with which the first-level citation network is constructed first. Then, a new approach to assess patent importance from the perspective of topological structure is provided and the second-level citation network, which consists of patent subclasses, is produced with the evaluation results. Moreover, three assessment indices of the subclass citation network are abstracted as impact parameters for technology development trends. Finally, two typical time series models, the Bass and ARIMA model, are utilized and compared for development trend forecasting. Based on the results of evolution prediction and network analysis, the highlighted patent subclasses with more development potential are identified, and the correlation between technology development opportunity and topological structure of the patent citation network is discussed.     

Patent citation network analysis of core and emerging technologies in Taiwan: 1997–2008

Identifying core technologies and emerging technologies is essential for formulating national technology strategies and policies for pursuing technological competitive advantage. This study presents a quantitative method for identifying core technologies and emerging technologies in the Taiwan technological innovation system. The objective was to gain an overview of technological development in the country by analyzing patent citation networks and by identifying five core technologies and emerging technologies in Taiwan based on United States Patent and Trademark Office (USPTO) patents granted to Taiwan during 1997–2008. The findings indicate the most appropriate management of technology and innovation and the best patent strategy and technology policy that the Taiwan government should pursue. Research institutes, industries and academia are also given research directions for choosing the technologies in which they should invest resources in order to strengthen the Taiwan technological innovation system and to increase its competitive advantage in global technology.     

Analyzing the time delay between scientific research and technology patents based on the citation distribution model

Promoting knowledge diffusion and reducing the delay between scientific research and technology patents is important to achieve success in the highly competitive global environment. This paper studies the time delay between scientific research and technology patents, and focuses on the key components of time in the promotion of knowledge transformation. Based on United States Patent and Trademark Office patent data, we apply periodical citation distribution models to the patent process. The results show that our transfer function model is better than others, and is suitable for calculating the delay between basic scientific research activities and technology patents.     

Technological change in lithium iron phosphate battery: the key-route main path analysis

Technological change evolves along a cyclical divergent-convergent pattern in knowledge diffusion paths. Technological divergence occurs as a breakthrough innovation, or discontinuity, inaugurating an era of ferment in which several competing technologies emerge and gradually advance. Technological convergence occurs as a series of evolutionary, variant changes that are gradually combined or fused together to open the industry to successive dominant designs or guideposts. To visualize such a pattern of technological evolution, we choose to study lithium iron phosphate (LFP) battery technology through an extension of the citation-based main path analysis, namely the key-route main path analysis. The key-route method discloses the main paths that travel through a specified number of key citations. The resulting multiple paths reveal the structure of the knowledge diffusion paths. The citation network is constructed from 1,531 academic articles on LFP battery technology published between 1997 and early 2012. Findings illustrate that LFP battery technology has completed two full technological cycles and is in the middle of the third cycle.     

Patents cited in the scientific literature: An exploratory study of 'reverse' citation relations

This paper reports on a new approach to study the linkage between science and technology. Unlike most contributions to this area we do not trace citations of scientific literature in patents but explore citations of patents in scientific literature. Our analysis is based on papers recorded in the 1996-2000 annual volumes of the CD-Edition of Science Citation Index (SCI) of the Institute for Scientific Information (ISI) and patent data provided by the US Patent and Trademark Office. Almost 30,000 US patents were cited by scientific research papers. We analysed the citation links by scientific fields and technological sectors. Chemistry-related subfields tended to cite patents more than other scientific area. Among technological sectors, chemical clearly dominates followed by drugs and medical patents as the most frequently cited categories. Further analyses included a country-ranking based on inventor-addresses of the cited patents, a more detailed inspection of the ten most cited patents, and an analysis of class-field transfers. The paper concludes with the suggestions for future research. One of them is to compare our 'reverse' citation data with 'regular' patent citation data within the same classification system to see whether citations occur, irrespectively of their directionality, in the same fields of science and technology. Another question is as to how one should interpret reverse citation linkages.     

Citations as a measure of technological impact: A review of forward citation-based measures

The number of forward citations a patent receives accumulates over time and appears to be correlated to the patent‘s (i.e. invention's) technological impact. A dominant theory suggests that highly cited patents contain an important technological advance. However, a variety of citation based measures have been proposed by different authors. This study, via a narrative literature review, identified nine forward citation-based measures that appear of particular relevance. We describe each measure and present them in a comparative format.The measures are divided into two broad categories: firstly the ones that are particularly relevant to the patent level (citation index, forward citation frequency, generality, influence), and secondly the ones that are relevant to the patent portfolio level (current impact index, herfindal-hirschman index, hindrance index, relative patent position, technology strength).We hope research scholars and industrial users find this review helpful for citation analysis and intellectual property analytics, especially when wanting to employ forward citation-based measures to assess technological impact.     

Patent protection: does it promote or inhibit the patented technological knowledge diffusion?

Patents not only promote the dissemination of technological knowledge through the disclosure of innovative information, but restrict the use of patented technology by the public within the scope of the law. With this exclusive protection on the premise of information disclosure, it is ambiguous whether patents help or hinder the diffusion of knowledge within the span of patents. This study first constructs a multidimensional index of patented technological knowledge diffusion (PTKD) from spatiotemporal aspects, and compares the differences in technological knowledge diffusion of four types of patents—valid patent (VP), zero-cited patent before expiration (Z-B), zero-cited patent after expiration (Z-A), and non-zero-cited patent before and after expiration (NZ-BA). Then, the impact of patent protection—patent lifetime (PL), the number of independent claims (NIC), the number of words in the first independent claim (NWF)—on the degree of PTKD is explored. The results demonstrate that NZ-BA has the highest level of PTKD in terms of growth rate, technological and geographical breadth and depth, followed by VP. Meanwhile, PL affects the diffusion growth rate and technological and geographical breadth negatively, NIC positively affects the diffusion average speed and technological and geographical depth while NWF only positively affects the technological depth of diffusion. These findings highlight the role of different types of patents in promoting technological innovation and promote a better understanding of the correlation between patent protection and PTKD, which provides support for decision-makers to protect property protection and guides the patentees to protect their long-term economic and technological benefits.