• Title/Summary/Keyword: patent citation analysis

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A Study on the Determinants of Patent Citation Relationships among Companies : MR-QAP Analysis (기업 간 특허인용 관계 결정요인에 관한 연구 : MR-QAP분석)

  • Park, Jun Hyung;Kwahk, Kee-Young;Han, Heejun;Kim, Yunjeong
    • Journal of Intelligence and Information Systems
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    • v.19 no.4
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    • pp.21-37
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    • 2013
  • Recently, as the advent of the knowledge-based society, there are more people getting interested in the intellectual property. Especially, the ICT companies leading the high-tech industry are working hard to strive for systematic management of intellectual property. As we know, the patent information represents the intellectual capital of the company. Also now the quantitative analysis on the continuously accumulated patent information becomes possible. The analysis at various levels becomes also possible by utilizing the patent information, ranging from the patent level to the enterprise level, industrial level and country level. Through the patent information, we can identify the technology status and analyze the impact of the performance. We are also able to find out the flow of the knowledge through the network analysis. By that, we can not only identify the changes in technology, but also predict the direction of the future research. In the field using the network analysis there are two important analyses which utilize the patent citation information; citation indicator analysis utilizing the frequency of the citation and network analysis based on the citation relationships. Furthermore, this study analyzes whether there are any impacts between the size of the company and patent citation relationships. 74 S&P 500 registered companies that provide IT and communication services are selected for this study. In order to determine the relationship of patent citation between the companies, the patent citation in 2009 and 2010 is collected and sociomatrices which show the patent citation relationship between the companies are created. In addition, the companies' total assets are collected as an index of company size. The distance between companies is defined as the absolute value of the difference between the total assets. And simple differences are considered to be described as the hierarchy of the company. The QAP Correlation analysis and MR-QAP analysis is carried out by using the distance and hierarchy between companies, and also the sociomatrices that shows the patent citation in 2009 and 2010. Through the result of QAP Correlation analysis, the patent citation relationship between companies in the 2009's company's patent citation network and the 2010's company's patent citation network shows the highest correlation. In addition, positive correlation is shown in the patent citation relationships between companies and the distance between companies. This is because the patent citation relationship is increased when there is a difference of size between companies. Not only that, negative correlation is found through the analysis using the patent citation relationship between companies and the hierarchy between companies. Relatively it is indicated that there is a high evaluation about the patent of the higher tier companies influenced toward the lower tier companies. MR-QAP analysis is carried out as follow. The sociomatrix that is generated by using the year 2010 patent citation relationship is used as the dependent variable. Additionally the 2009's company's patent citation network and the distance and hierarchy networks between the companies are used as the independent variables. This study performed MR-QAP analysis to find the main factors influencing the patent citation relationship between the companies in 2010. The analysis results show that all independent variables have positively influenced the 2010's patent citation relationship between the companies. In particular, the 2009's patent citation relationship between the companies has the most significant impact on the 2010's, which means that there is consecutiveness regarding the patent citation relationships. Through the result of QAP correlation analysis and MR-QAP analysis, the patent citation relationship between companies is affected by the size of the companies. But the most significant impact is the patent citation relationships that had been done in the past. The reason why we need to maintain the patent citation relationship between companies is it might be important in the use of strategic aspect of the companies to look into relationships to share intellectual property between each other, also seen as an important auxiliary of the partner companies to cooperate with.

Analysis of Factors Influencing Patent Citations (특허 인용에 영향을 미치는 요인 분석)

  • Yoo, Jae-Bok;Chung, Young-Mee
    • Journal of the Korean Society for information Management
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    • v.27 no.1
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    • pp.103-118
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    • 2010
  • Recently, the valuation of patented technology has been greatly emphasized, and patent citation has been accepted as a very useful index of this technology. In this study, we performed correlation analyses between the patent citation counts and 17 explanatory variables of morphological, technological, and conceptual factors with a test dataset of U.S. patents in five subject fields. Seven variables having 5% or more standardized variances($r^2$) with patent citation counts were identified; number of pages, number of claims, reference-average-citation rate, patent increase/decrease rate, strength of bibliographic coupling, co-citation counts and document similarity. The result of the ANOVA test shows that the mean values of these variables vary among most subject fields.

A Study on the Estimation of Technology Economic Life Using Patent Citation Life Analysis (특허인용 수명분석을 이용한 기술의 경제적 수명 추정에 대한 연구)

  • Sung, Oong-Hyun;Yoo, Sun-Hi
    • Knowledge Management Research
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    • v.8 no.1
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    • pp.49-63
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    • 2007
  • This paper presents a new methodology that allows the influence of technological obsolescence and technology composite competitiveness to estimate technology economic life. In this paper the patent citation life analysis is used to estimate technology representative life, and technology residual life analysis is employed to estimate residual life using the linear and inverse functions. The technology economic life will be determined by combining the estimation results of patent citation life analysis and technology residual life analysis. This paper includes an example of applying it to the US patent data for 5 communications areas. Therefore, this logical concept can be applied usefully to determine the technology economic life and be expected to contribute to obtain credibility of technology valuation.

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Analysis of Factors Influencing Patent Citations: Focused on Korea Medical Device Patents (특허 인용에 영향을 미치는 요인 분석: 국내의료기기 특허를 중심으로)

  • Yoon, Jae Woong;Lee, Chang Seop;Lee, Suk Jun
    • Journal of the Korean Society for information Management
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    • v.33 no.2
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    • pp.103-133
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    • 2016
  • The valuation of patented technology has been recently emphasized, and the patent citation is known as an important factor. This study performed a generalized linear model to find variables that effect the patent citation. We classified 13 variables as morphological, technological and conceptual factors and used them to find out effective variables in 14 medical devices classification. Through the empirical study, we found seven effective variables (assignee nationality, assignee character, the number of inventors, the number of application countries, the number of IPC, the number of references, the strength of bibliographic coupling). In order to apply to Korean industry, this study has significance that provides basic research to citation analysis model.

A Study on Developing a Prediction Model of Patent Citation Counts (특허인용 예측모형 구축에 관한 연구)

  • Yoo, Jae-Bok;Chung, Young-Mee
    • Journal of the Korean Society for information Management
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    • v.27 no.4
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    • pp.239-258
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    • 2010
  • The purpose of this study is to develop a prediction model of patent citation counts based on major factors which affect patent citation. To this end, we performed multiple regression analysis between the patent citation counts and five explanatory variables such as the number of pages, the number of claims, the reference-average-citation rate, the strength of bibliographic coupling, and the document similarity proved as having 5% or more standardized variances($r^2$) with patent citation counts, with a test dataset of U.S. patents in five subject fields. As a result, our prediction models showed 58.3% to 89.6% predictability depending on subject fields and revealed the document similarity has the highest impact on citation counts among the five predictive variables in all the subject fields. The result of comparison between the predicted citation counts and the actual ones confirmed the usefulness of the citation prediction models built for each subject field.

A Study on Estimation of Technology Life Span Using Analysis of Patent Citation (특허인용분석을 통한 기술분야의 수명예측에 관한 연구)

  • Yoo, Sun-Hi;Lee, Yong-Ho;Won, Dong-Kyu
    • Journal of the Korean Operations Research and Management Science Society
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    • v.31 no.4
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    • pp.1-11
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    • 2006
  • A citation-based method of estimating the life span of a patented technology is proposed In this study. The suggested framework Includes : (1) estimation of citation frequency of an individual patent within a technology group. (2) calculation of a mutual citation frequency between citing patent and cited patents, (3) calculation of the period for cited patents from the year of registration to the year of being cited most recently and (4) description for technology group using descriptive statistics such as mean, median, mode, etc. The framework suggested in this study was applied to the US patent data between 1976 and 2004 for 5 communications areas.

The Effect of Patent Citation Relationship on Business Performance : A Social Network Analysis Perspective (특허 인용 관계가 기업 성과에 미치는 영향 : 소셜네트워크분석 관점)

  • Park, Jun Hyung;Kwahk, Kee-Young
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.127-139
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    • 2013
  • With an advent of recent knowledge-based society, the interest in intellectual property has increased. Firms have tired to result in productive outcomes through continuous innovative activity. Especially, ICT firms which lead high-tech industry have tried to manage intellectual property more systematically. Firm's interest in the patent has increased in order to manage the innovative activity and Knowledge property. The patent involves not only simple information but also important values as information of technology, management and right. Moreover, as the patent has the detailed contents regarding technology development activity, it is regarded as valuable data. The patent which reflects technology spread and research outcomes and business performances are closely interrelated as the patent is considered as a significant the level of firm's innovation. As the patent information which represents companies' intellectual capital is accumulated continuously, it has become possible to do quantitative analysis. The advantages of patent in the related industry information and it's standardize information can be easily obtained. Through the patent, the flow of knowledge can be determined. The patent information can analyze in various levels from patent to nation. The patent information is used to analyze technical status and the effects on performance. The patent which has a high frequency of citation refers to having high technological values. Analyzing the patent information contains both citation index analysis using the number of citation and network analysis using citation relationship. Network analysis can provide the information on the flows of knowledge and technological changes, and it can show future research direction. Studies using the patent citation analysis vary academically and practically. For the citation index research, studies to analyze influential big patent has been conducted, and for the network analysis research, studies to find out the flows of technology in a certain industry has been conducted. Social network analysis is applied not only in the sociology, but also in a field of management consulting and company's knowledge management. Research of how the company's network position has an impact on business performances has been conducted from various aspects in a field of network analysis. Social network analysis can be based on the visual forms. Network indicators are available through the quantitative analysis. Social network analysis is used when analyzing outcomes in terms of the position of network. Social network analysis focuses largely on centrality and structural holes. Centrality indicates that actors having central positions among other actors have an advantage to exert stronger influence for exchange relationship. Degree centrality, betweenness centrality and closeness centrality are used for centrality analysis. Structural holes refer to an empty place in social structure and are defined as efficiency and constraints. This study stresses and analyzes firms' network in terms of the patent and how network characteristics have an influence on business performances. For the purpose of doing this, seventy-four ICT companies listed in S&P500 are chosen for the sample. UCINET6 is used to analyze the network structural characteristics such as outdegree centrality, betweenness centrality and efficiency. Then, regression analysis test is conducted to find out how these network characteristics are related to business performance. It is found that each network index has significant impacts on net income, i.e. business performance. However, it is found that efficiency is negatively associated with business performance. As the efficiency increases, net income decreases and it has a negative impact on business performances. Furthermore, it is shown that betweenness centrality solely has statistically significance for the multiple regression analysis with three network indexes. The patent citation network analysis shows the flows of knowledge between firms, and it can be expected to contribute to company's management strategies by analyzing company's network structural positions.

Patent citation network analysis (특허 인용 네트워크 분석)

  • Lee, Minjung;Kim, Yongdai;Jang, Woncheol
    • The Korean Journal of Applied Statistics
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    • v.29 no.4
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    • pp.613-625
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    • 2016
  • The development of technology has changed the world drastically. Patent data analysis helps to understand modern technology trends and predict prospective future technology. In this paper, we analyze the patent citation network using the USPTO data between 1985 and 2012 to identify technology trends. We use network centrality measures that include a PageRank algorithm to find core technologies and identify groups of technology with similar properties with statistical network models.

Identifying Promising Service Areas for Technology-based Firms (기술기반 기업의 유망 서비스 영역 탐색)

  • Kim, Chulhyun
    • Journal of the Korea Safety Management & Science
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    • v.15 no.4
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    • pp.407-416
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    • 2013
  • This paper proposes an approach to analyzing the relationship between technology and services, and to identifying promising service areas for technology-based firms with the analysis of business model (BM) patents. First, BM patents and technology patents are collected and classified into their relevant categories, respectively. Second, patent citation analysis is conducted to analyze the linkage and impacts between each technology and service field at macro level. Third, as a micro level analysis, patent co-classification analysis is employed to identify the interrelationships among specific technology and service areas. Finally, the promising service areas for technology-based firms seeking service areas for diversification is investigated with portfolio analysis. The working of the proposed approach is provided with the help of a case study of IT and mobile services. The proposed approach could guide and help managers of technology-based firms to discover the opportunity of the diversification to new areas in emerging service fields.

The Analysis of Inter-Industrial Knowledge Flow Structure among Northeast Asian Countries Based on Patent Citation Data: Comparison of Korea, Japan, and Taiwan (특허 인용 자료를 활용한 동북아국가의 산업간 기술지식 흐름 및 구조 분석 : 한국, 일본, 대만을 중심으로)

  • 윤병운;이욱;박용태
    • Journal of Technology Innovation
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    • v.13 no.3
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    • pp.197-224
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    • 2005
  • Recently, the notion of National Innovation System (NIS) has attracted considerable attention as a key driver of the economic success. Amongst others, the Northeast Asian countries deserve highlight as central cases of NIS. This research attempts to examine inter-industrial knowledge flows and structure among Northeast Asian countries. To this end, Korea, Japan and Taiwan are selected and the patent citation data, a proxy of disembodied knowledge flows, from United Stated Patents and Trademark Office (USPTO) are employed for cluster analysis and network analysis. Some meaningful findings are presented and distinctive characteristics of respective countries are contrasted.

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