Patent portfolios of European wind industry: New insights using citation categories

This study explores the use of citation categories assigned by patent examiners to study overlap of patent portfolios among top wind power firms. Cooperative Patent Classification (CPC) is used to obtain a sample of wind industry patents. CPC is shown to be better than the International Patent Classification for identifying patents relevant to the wind power industry. Results show high inter-firm citation among the top wind industry players that can suggest concentration of innovation. The results can be useful for patent analysts, technology managers and policy makers.     

Technological Trajectories in the Making: Two Case Studies from the Contemporary History of Wind Power

This paper traces the origins of two technological trajectories in the contemporary history of wind power technology: the American Smith‐Putnam Wind Turbine and the Danish Gedser Wind Turbine. Describing the two wind turbine projects in terms of their technical design characteristics, the professional background of the individuals involved, the organizational features of the technological knowledge production, and the historical context, the paper builds on the notion of technological trajectories in the making as a means of identifying emerging selection mechanisms for possible engineering problem solutions, scientific methods, material artifacts, and financial assessment techniques. Conceived during the Great Depression and World War II, respectively, both projects promoted the idea that wind power could make a cost‐effective contribution to the existing electric utility system. The two projects resulted in distinctive wind turbine innovations that paved the way for two technological trajectories in the contemporary history of wind power. Studying the emergence of technological trajectories, it is argued, requires the historian of technology to attend to well‐known features of technological design and its cultural context that in retrospect appear to be significant, but also to tackle the creation of novelty and the inevitability of technological uncertainties about which the logic of trajectories has little to say.     

专利地图与TRIZ融合技术创新指标体系构建及影响因素分析

梳理专利地图与TRIZ融合技术创新的流程,构建其影响因素指标体系。应用粗糙集理论识别专利地图与TRIZ融合技术创新的关键影响因素,并进行实证研究。研究结果表明,粗糙集方法在定量分析处理模糊和不确定性知识方面具有优越性;且在运用专利地图与TRIZ融合技术创新方法进行技术创新时,专利数据源准确性、完整性,专利分析结果有效性和技术创新经济效益是影响企业技术创新的关键因素,研究结果符合企业技术创新实际情况。     

Using international patent data to identify and assess opportunities for technology acquisition from government research agencies

In today's environment of rapid technological change and global competition, it is becoming increasingly difficult for firms to keep up with the advances being made around the world in various high technology fields. This article illustrates how firms can make use of international patent data to identify and assess possible sources of new technology for acquisition, particularly government laboratories. The technological activities of eight French research agencies are assessed through quantitative analyses of the patent applications they filed during the 1980s. The aspects of their technological activities that are examined include: (1) the level and direction of technological activity, measured by counts of international patent families; (2) the technological significance of the work being performed, measured by the number of subsequent patent citations; and (3) the commercial potential of the work, measured by the number of foreign countries in which patent protection for the resulting inventions is sought. It is then shown how firms can interpret this data to identify the technological work of government laboratories that may be of interest for possible licensing or joint venture agreements.     

Identification and evaluation of corporations for merger and acquisition strategies using patent information and text mining

This paper proposes a framework to identify and evaluate companies from the technological perspective to support merger and acquisition (M&A) target selection decision-making. This employed a text mining-based patent map approach to identify companies which can fulfill a specific strategic purpose of M&A for enhancing technological capabilities. The patent map is the visualized technological landscape of a technology industry by using technological proximities among patents, so companies which closely related to the strategic purpose can be identified. To evaluate the technological aspects of the identified companies, we provide the patent indexes that evaluate both current and future technological capabilities and potential technology synergies between acquiring and acquired companies. Furthermore, because the proposed method evaluates potential targets from the overall corporate perspective and the specific strategic perspectives simultaneously, more robust and meaningful result can be obtained than when only one perspective is considered. Thus, the proposed framework can suggest the appropriate target companies that fulfill the strategic purpose of M&A for enhancing technological capabilities. For the verification of the framework, we provide an empirical study using patent data related to flexible display technology.     

Identifying patent infringement using SAO based semantic technological similarities

Companies should investigate possible patent infringement and cope with potential risks because patent litigation may have a tremendous financial impact. An important factor to identify the possibility of patent infringement is the technological similarity among patents, so this paper considered technological similarity as a criterion for judging the possibility of infringement. Technological similarities can be measured by transforming patent documents into abstracted forms which contain specific technological key-findings and structural relationships among technological components in the invention. Although keyword-based technological similarity has been widely adopted for patent analysis related research, it is inadequate for identifying patent infringement because a keyword vector cannot reflect specific technological key-findings and structural relationships among technological components. As a remedy, this paper exploited a subject–action–object (SAO) based semantic technological similarity. An SAO structure explicitly describes the structural relationships among technological components in the patent, and the set of SAO structures is considered to be a detailed picture of the inventor’s expertise, which is the specific key-findings in the patent. Therefore, an SAO based semantic technological similarity can identify patent infringement. Semantic similarity between SAO structures is automatically measured using SAO based semantic similarity measurement method using WordNet, and the technological relationships among patents were mapped onto a 2-dimensional space using multidimensional scaling (MDS). Furthermore, a clustering algorithm is used to automatically suggest possible patent infringement cases, allowing large sets of patents to be handled with minimal effort by human experts. The proposed method will be verified by detecting real patent infringement in prostate cancer treatment technology, and we expect this method to relieve human experts’ work in identifying patent infringement.     

Large firms and the science-technology interface Patents,patent citations,and scientific output of multinational corporations in thin films

Firms operating in science-based technological fields reflect some of the complexities of the science-technology interaction. The present study attempts to investigate these interactions by analyzing patent citations, publication and patent outputs of multinational corporations (MNCs) in 'thin film' technology. In particular we explore different characteristics of knowledge production and knowledge utilization of these firms. The results indicate no correlation between intensity of research activity and patents produced by the MNCs. The relationship between scientific and technological knowledge generation as well as the linkage between science and technology appear to be firm-specific rather than dependent on a technological or industrial sector. The dispersion of journal sources for the majority of patent citations of scientific literature as well as for the majority of scientific outputs is narrow. Basic journals play an important role in patent citation as well as in addressing research of MNCs in thin-film technology.     

Network structure of innovation: can brokerage or closure predict patent quality?

Patents are important intellectual assets for companies to defend or to claim their technological rights. To control R&D cost, companies should carefully examine their patents by patent quality. Approaches to evaluating patent quality are mostly a posteriori uses of factual information of patent quality. This paper examined whether patent quality can be predicted a priori, i.e., during the early years after a patent is granted, by analyzing information embedded in a network of patent citations. Social network analysis was applied to analyze two network positions occupied by a patent, brokerage and closure to determine whether either position is a good predictor of patent quality. Patent renewal decisions and forward citations were adopted as surrogates of patent quality. The analytical results showed that forward citations can be positively predicted by the brokerage position and negatively predicted by the closure position in the early and mature stages. Renewal decisions can be negatively predicted by the brokerage position in the early stage, and the closure position influences the renewal decision in a different way in the early and mature stages. These analytical results imply that a company should focus on developing patents that bridge different technologies as its technological developments reach maturity.     

Technology landscape and a short patentometric review for antibiofilm technologies

This study presents an overview and a short critical review of patented antibiofilm technologies. Patent information was used to determine scenarios that could be used by decision-makers or business intelligence. The study found that academia, mainly from the USA, has been applying for the most patents since 1997. Based on the S-curve analysis, the maturity of this technology sector is emerging. The technological specialization for the 10 most prominent patent applicants and state-of-the-art antibiofilm patents are presented.The high dispersion of patent applicants, the presence of universities among the most active patent applicants, and the content of the patents analyzed are good indicators to infer that developed technologies are close to the academic level. Moreover, many efforts are necessary to bring these technologies into the market.Polymers-N-based, amino acids and peptides, P and S compounds, chelating agents and organometallic complexes, nanoparticles, or composites are claimed to be active against biofilm formation. Such compounds are presented in this work, and in rare cases, they are described as compositions ready for use as marketable products.     

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.     

Identifying technological topics and institution-topic distribution probability for patent competitive intelligence analysis: a case study in LTE technology

An extended latent Dirichlet allocation (LDA) model is presented in this paper for patent competitive intelligence analysis. After part-of-speech tagging and defining the noun phrase extraction rules, technological words have been extracted from patent titles and abstracts. This allows us to go one step further and perform patent analysis at content level. Then LDA model is used for identifying underlying topic structures based on latent relationships of technological words extracted. This helped us to review research hot spots and directions in subclasses of patented technology in a certain field. For the extension of the traditional LDA model, another institution-topic probability level is added to the original LDA model. Direct competing enterprises’ distribution probability and their technological positions are identified in each topic. Then a case study is carried on within one of the core patented technology in next generation telecommunication technology-LTE. This empirical study reveals emerging hot spots of LTE technology, and finds that major companies in this field have been focused on different technological fields with different competitive positions.     

Detecting signals of new technological opportunities using semantic patent analysis and outlier detection

In the competitive business environment, early identification of technological opportunities is crucial for technology strategy formulation and research and development planning. There exist previous studies that identify technological directions or areas from a broad view for technological opportunities, while few studies have researched a way to detect distinctive patents that can act as new technological opportunities at the individual patent level. This paper proposes a method of detecting new technological opportunities by using subject–action–object (SAO)-based semantic patent analysis and outlier detection. SAO structures are syntactically ordered sentences that can be automatically extracted by natural language processing of patent text; they explicitly show the structural relationships among technological components in a patent, and thus encode key findings of inventions and the expertise of inventors. Therefore, the proposed method allows quantification of structural dissimilarities among patents. We use outlier detection to identify unusual or distinctive patents in a given technology area; some of these outlier patents may represent new technological opportunities. The proposed method is illustrated using patents related to organic photovoltaic cells. We expect that this method can be incorporated into the research and development process for early identification of technological opportunities.     

Exploring patent performance and technology interactions of universities, industries, governments and individuals

In the era of the fast-paced knowledge economy, patent data may be analyzed to measure technological competitiveness. This paper aims to explore patent performance by indicators and technology interactions based on patent citation of assignee types. This study involved four types of patent assignees (i.e. universities, industries, governments, and individuals) in five technological fields (i.e. computers and communications; drugs and medical; electrical and electronics; chemical; and mechanical) over three periods (i.e. 1997–2001, 2002–2006, and 2007–2011). Four indicators were chosen for analysis of patent performance; they included, patent share, science linkage, current impact index, and citation density. The findings of this study show that among all four assignee types, industries had the highest patent productivity in all fields, and universities had the highest impact in all fields except for drugs and medical. Other interesting phenomena were also observed. Examples include reciprocal technology interactions between universities and governments; low technology interactions of industries in each field; individuals’ higher patent performance and technology interactions in the field of drugs and medical.     

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.     

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.     

Identification of technological knowledge intermediaries

Intermediaries in a technological knowledge network have recently been highlighted as crucial innovation drivers that accelerate technological knowledge flows. Although the patent network analysis has been frequently used to monitor technological knowledge structures, it has examined only sources or recipients of the technological knowledge by mainly estimating technological knowledge inflows or outflows of a network node. This study, therefore, aims to identify technological knowledge intermediaries when a technology-level knowledge network is composed of several industries. First, types of technological knowledge flows are deductively classified into four types by highlighting industry affiliations of source technologies and recipient technologies. Second, a directed technological knowledge network is generated at the technology class level, using patent co-classification analysis. Third, for each class, mediating scores are measured according to the four types. The empirical analysis illustrates the Korea’s technological knowledge network between 2000 and 2008. As a result, the four types of mediating scores are compared between industries, and industry-wise technological knowledge intermediaries are identified. The proposed approach is practical to explore converging processes in technology development where technology classes act as technological knowledge intermediaries among diverse industries.     

Analysis of developing a specific technological field using the theme code of Japanese patent information

The paper was to establish an easy and effective method to investigate and develop a specific technological field from Japanese patent information. The walking technique of the biped humanoid robot was used as an example to study the relative research capabilities and patent citation conditions for patent owners and patent map by the searching method of the theme code for FI (File Index) and F-term classification system of the Japanese Patent Office (JPO). A formulated technical matrix of patent map was established to indicate that the ZMP (Zero Moment Point) control means was the main technology to achieve stabilized walking control of the humanoid biped robot. This method can aid to establish a specific technological matrix from the specific selected term codes (single viewpoint or multiple viewpoints) of the F-term list in the theme code of the JPO system through Boolean logical operations. The resulting particular technical fields were developed to improve the technological capability or seek the merging technology opportunities.     

The Changing Technological Profile of the Leading ICT Firms: Evidence from US Patent Data, 1981-2000

Drawing upon the patent data for 63 of the largest firms in the information and communication technology (ICT) sector for the period 1981-2000, this paper investigates how the technological profile of these firms has altered in relation to technological advantage, technological diversity and path dependency. Using a previously established measure of revealed technological advantage, the firms in the sample almost universally exhibited a decline over time in this measure. While this result is contrary to other multi-industry research, it may be unique to the ICT industry as many non-ICT oriented firms patent in the area as ICT technology underpins developments in more and more industries. In relation to technological diversity, there were high levels of intra-sector diversification, but little diversity beyond the ICT sector, supporting the notion that the emergence of technology markets will support specialization. In addition, strong evidence of path dependency was found indicating that firms adopt long-term strategies for developing their technology portfolios. Given the rapid growth of technology markets, these findings have considerable implications as to the nature and operation of these markets.     

A bibliometric method for assessing technological maturity: the case of additive manufacturing

While novel technologies have tremendous competitive potential, they also involve certain risks. Maturity assessment analyzes how well a technological development can fulfill an expected task. The technology readiness level (TRL) has been considered to be one of the most promising approaches for addressing technological maturity. Nonetheless, its assessment requires opinions of the experts, which is costly and implies the risk of personal bias. To fill this gap, this paper presents a Bibliometric Method for Assessing Technological Maturity (BIMATEM). It is a repeatable framework that assesses maturity quantitatively. Our method is based on the assumption that each technology life cycle stage can be matched to technology records contained in scientific literature, patents, and news databases. The scientific papers and patent records of mature technologies display a logistic growth behavior, while news records follow a hype-type behavior. BIMATEM determines the maturity level by curve fitting technology records to these behaviors. To test our approach, BIMATEM was applied to additive manufacturing (AM) technologies. Our results revealed that material extrusion, material jetting, powder bed fusion and vat photopolymerization are the most mature AM technologies with TRL between 6 and 7, followed by directed energy deposition with TRL between 4 and 5, and binder jetting and sheet lamination, the least mature, with TRL between 1 and 2. BIMATEM can be used by competitive technology intelligence professionals, policymakers, and further decision makers whose main interests include assessing the risk of implementing new technologies. Future research can focus on testing the method with regard to altmetrics.     

Patent citation analysis: A policy analysis tool

Patent citation analysis is a recent development which uses bibliometric techniques to analyse the wealth of patent citation information. This paper describes the various facets of patent citations and patent citation studies, and their important applications. Construction of technology indicators being an important use of patent citations, various patent citation based technological indicators and their applications are also described.