• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.813-818
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• 2008

Highly cited patents (HCPs) were selected from the patents published from 2002 to 2006. Citation frequencies of patents were obtained from the database provided by DWPI and were analyzed with respect to the IPC (International Patent Classifications). HCPs were selected as those who occupy top 1% of citations in the sets of patents given by IPCs and publication year. After selecting the HCPs their distribution over IPCs, Industrial Classifications and patent assignees' nationalities were analyzed. According to the result the US held 5,634 patents (66.9%) out of the total 8,416 patents occupying the the first rank in the distribution of patent assignees' nationalities. Japan and Germany ranked the 2nd and 3rd place holding 885 (10.5%) and 521 (6.2%) HCPs, respectively. On the other hand, Korea were positioned at 6th holding 151 (1.8%) HCPs. Among the industrial sectors classified by the Industrial Classifications provided by the Korean Intellectual Property Office, Manufacturing Sector occupied the 1st place with 7,692 HCPs (81.7%) and Waste Treatment Sector occupied the 2nd place with 578 HCPs (5.9%).

• 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.

• 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.

• Journal of the military operations research society of Korea
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• v.32 no.2
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• pp.143-164
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• 2006

This paper considers the technology spillover effects on industries by analyzing patents. Registered patents in the United States from Korea in 1990 and 1995 are compared by quantity of registrations as well as patent analysis indices, namely, cites per patent, technology cycle time and science linkage. Several regression models between these indices as predictor variables and the value added of an industry as a dependent variable were investigated. The results show that the value added of an industry positively correlates to the number of patent registrations and cites per patent.

• Economic Analysis
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• v.25 no.4
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• pp.25-57
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• 2019

This paper studies localization effects of knowledge spillovers in Korea using U.S. patents granted over the period 1996-2015. The "sample-matching" analysis initiated by Jaffe, Trajtenberg, and Henderson (1993) is adopted. We do not find evidence of positive localization effects in Korea. In particular, controlling for the existing geographic distribution of knowledge production, the frequency of domestic citations of Korean patents is no more than the citation frequency from overseas, and the difference is decreasing within the sample period. We also examine localization effects across regions and industries, and compare Korea with Taiwan and Japan.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.657-661
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• 2006

오늘날 지식기반사회에서 새로운 과학의 출현이 새로운 산업으로 확산되어 국가경쟁력에 이바지하고 있다. 일반적으로 논문을 통한 연구는 과학을 대변하고, 기술은 특허로 대체되는 것으로 인지하고 있다. 현재 과학은 SCI 의 인용색인 데이터를 바탕으로 각 문헌에 대한 인용통계정보를 제공하는 저널평가 테이터베이스인 JCR을 활용하여 분석하고 평가, 파악하고 있는 실정이다. 과학기술 분야의 누적된 논문수, 인용횟수, 연구자 분석 등 다양하게 적용할 수 있다. 반면 특허는 전체 출원, 등록건수 등 국가의 거시적인 흐름을 평가하는 수단으로는 주로 활용되어지고 있으나 정보소스의 한계나 분석시의 한계로 인하여 다양한 분석이 활용되기 어려운 실정이다. 인용정보로서 활용시 이를 위한 과도한 전처리 작업이 요구되며, 분석이 번거롭고 용이하지 않는 현실이므로 다양하게 분석시 사용하기가 어렵다. 이를 활용하여 문헌에 적용된 분석을 활용하여 새로운 고부가 정보를 제안해 보고자 한다.

• Proceedings of the Technology Innovation Conference
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• 2004.02a
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• pp.178-201
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• 2004

경제의 패러다임이 지식의 확산과 공유가 경제 성장의 주요한 요소로 대두되는 지식기반경제로 변화하게 되고, 융합 기술(fusion technology)의 중요성에 대한 인식으로부터 학제간(inter-disciplinary) 연구나 기술개발이 활발해지면서, 각 산업이 타산업과 맺고 있는 특정한 연계구조에 대한 분석은 정부의 기술정책이나 기업의 기술전략 수립에 필수적인 것으로 받아들여지고 있다. 특히 산업간 지식흐름의 구조를 파악하는 것은 산업간 협력(collaboration)의 형태나 파급효과에 대한 분석뿐만 아니라 기술 혁신을 촉진하기위한 혁신 클러스터(innovative cluster) 형성의 기초를 제공하는 것이라 하겠다. 따라서 본 연구는 기술집약적 장비에 체화된 유형자원의 간접적 지식 확산이 아닌, 특허 인용의 명백한 지식 흐름을 활용하여 한국 제조업의 지식 흐름 구조를 분석하고 이를 토대로 클러스터를 나누는 것을 목적으로 한다. 이를 위하여 특허 인용 정보가 존재하는 미국특허청(USPTO)의 자료를 이용하며, 여기에서 도출된 한국 특허의 인용관계를 통해 한국 제조업의 네트워크 및 클러스터를 생성하였다. 즉, 특허 분류를 산업 분류에 매칭(matching)시킴으로써, 특허의 인용관계를 각 특허가 속한 산업간의 지식흐름으로 변환하여 산업간 연계 구조를 파악하고 이를 토대로 한국 산업의 지식 클러스터를 생성함으로써 클러스터간 지식 흐름을 분석하고, 각 클러스터의 기술적 특성을 제시하였다. 본 연구는 한국 산업의 지식흐름을 미국특허청에 출원된 한국 특허를 활용하여 분석했다는 점에서 제기될 수 있는 해외 기술 시장으로의 전략적 차원의 출원에 의한 자료의 편중성문제와 지식흐름의 절대량이 아닌 상대량을 통해 클러스터링함으로써 발생될 수 있는 자료 활용의 한계점을 지니고 있다. 그러나 비체화 지식의 흐름을 특허인용관계를 통해 실증적으로 분석하고, 이를 통해 클러스터를 나누어 산업간 연계구조와 기간에 따른 변화 양상을 조명하며, 각 클러스터의 특성을 다양한 지표(indicators)로부터 설명했다는 데에서 의의를 찾을 수 있다. 본 연구의 결과는 기술혁신을 위한 국가 차원의 산업정책이나 기술개발과 관련한 기업의 기술전략에 활용될 수 있을 것이다.

• 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.

• Journal of Korea Technology Innovation Society
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• v.15 no.4
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• pp.745-765
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• 2012

When attempting to use the income approach for the purpose of technology valuation, it is essential to identify the economic life of the technology in question. From the mid-2000s up to the present, the methods proposed by major Korean institutions for estimating the economic life of technologies have been based on cited patent life (CLT), which is one of the types of technology life. The present study utilizes cited patent life (CLT) to estimate the economic life of technology for the purpose of technology valuation, and proposes a new method of analyzing cited patent life, a method that has been improved by taking into consideration the elapsed period and the time period of investment required for commercialization, two factors which have been hitherto overlooked. Survival curve analysis is a method that has already been widely utilized to estimate the economic life of tangible assets, and this study applies the same method to the calculation of the cited patent life index of technology to provide a more objective method for determining the lifetime of a technology. The remaining life expectancy of cited patent life based on the number of elapsed years was calculated and used to determine the life expectancy of a technology that has reached a specific number of elapsed years, which is referred to as the remaining cited-patent life time (r-CLT).

• Journal of the Korean Society for information Management
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• v.23 no.3 s.61
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• pp.223-239
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• 2006

As the fact that science is the driving force behind technological development and that technological innovation contributes to economic development has been proved empirically convincing, the interaction between science and technology is highly emphasized in advanced countries. But, Korea has not been active in conducting research on science-based technological development and on the scientific fields that have strong relationships with Korean technology. This study attempts to explore the influence of scientific research papers cited in US patents by Koreans on other US patents and identify the interactions between scientific research papers and patents, by examining the scientific references cited in the Korean-originated US patents.