초록 ▼

제 1 장 연구의 배경과 목적
□ 연구의 목적
○ 첫째, 특허 데이터 베이스를 활용하여 기술-산업의 연계 구조를 분석한다. 기술부문간의 연계구조, 산업부문간의 연계구조, 기술부문과 산업의 연계구조를 네트워크 분석방법을 통하여 분석한다. 이를 위하여 기술분류와 산업분류를 연계하는 작업을 선행한다.
○ 둘째, 특허데이터 베이스를 활용하여 한국기업의 특허전략을 평가한다. 한국경제의 고도 성장과정에서 한국기업의 특허전략은 급변하여 왔는데, 이런 변화의 추이를 특허 데이터베이스를 활용하여 파악한다.
○ 셋째, 한국 기업

제 1 장 연구의 배경과 목적
□ 연구의 목적
○ 첫째, 특허 데이터 베이스를 활용하여 기술-산업의 연계 구조를 분석한다. 기술부문간의 연계구조, 산업부문간의 연계구조, 기술부문과 산업의 연계구조를 네트워크 분석방법을 통하여 분석한다. 이를 위하여 기술분류와 산업분류를 연계하는 작업을 선행한다.
○ 둘째, 특허데이터 베이스를 활용하여 한국기업의 특허전략을 평가한다. 한국경제의 고도 성장과정에서 한국기업의 특허전략은 급변하여 왔는데, 이런 변화의 추이를 특허 데이터베이스를 활용하여 파악한다.
○ 셋째, 한국 기업의 연구개발과 특허간의 투입산출 관계, 기업속성과 특허와의 관계를 파악한다.

Abstract ▼

The main motivation to the current research stems from the recognition that the linkage between technology and industry should be investigated in a more systematic and quantitative way. Although similar and related researches have been performed in the past, they are subject to a couple of critical

The main motivation to the current research stems from the recognition that the linkage between technology and industry should be investigated in a more systematic and quantitative way. Although similar and related researches have been performed in the past, they are subject to a couple of critical problems such as data availability and ambiguous definition of technology and industry. As a remedy, this research employed three primary approaches. First, the patent analysis is applied. Second, new industry and technology classification schemes are proposed. Third, network analysis is adopted. To this end, this study transforms conventional classification schemes into new schemes and attempts to match a set of technologies with another set of industries. Then, the network, structure of relationship between technology and industry, is analysed to obtain some strategic and political policy implications. Furthermore, the country-specific patent strategy is examined, by taking such factors as firm size, proportion of exports and the characteristics of conglomerates into consideration. The primary method to this purpose is regression analysis.

The transformation is composed of two processes. Since current study is based on the patent data of USPTO (United States Patent Office), to begin with, we should transform the technology classes of USPTO into the national classification of science and technology in Korea. 400 technology classes of USPTO are projected on 58 classes. The second stage is the transformation between national classification of science and technology and KSIC (Korean Standard Industry Classification). Encompassing manufacturing and service industry, 58 classes are connected with 27 industry classes of KSIC. Then, along the line of two-stage transformation, the individual patent of USPTO is allocated to a specific industry and technology. ISIC (International Standatrd of Industry Classification) and IPC (Internatioanl Patent Classification) are referred as a standard.
To explore the linkage between technology and industry, the preliminary work is to generate two homogeneous networks. Using the classical network analysis, we investigate the networks from three levels. At the first level, the primary concern is the profile of an individual technology or industry. Thus, node profile including information such as the centrality provides the basic reference to weigh the importance of each node. At the mid-level, cluster analysis is applied to the whole set of industries and technologies. The characteristics or labels of each cluster enables us to get a new outlook and manage them more easily. Finally, the network characteristics at the national level facilitates grasping the present condition of national technology-industry structure and explore the future direction. Then, based on these results, the linkage between technology and industry is generated. Some policy and strategy Implications are also discussed.

Broadly, a couple of political implications are drawn from the network analysis. First and foremost, the dynamic is concentrated on electricity and semiconductor industry. Deeply related industries including software, computer, electric application and so on also play an important role. The coverage of influence is wide. The strength of that is far stronger than any other industries. The technology network confirms the similar result again. However, at the same time, two problems are recognized. Inconsistency of importance is the most obvious one. Within the core industries, the role of information processing and broadcast is dominant in terms of coverage and strength. But in the whole industry, the dominant position is occupied by computer and semiconductor. In other words, the diffusion effects of newly developed industries are relatively small. Or the channels for synergy effects between technologies and industries are not vitalized yet. Secondly, the gap between the core technologies and complementary ones is so large that it could be the serious constraint for the development of core industries. Finally, the relationship between technology and industry adds somewhat different implications. Traditional and old industries such as agriculture are almost independent and self-reliant. Material and mechanical industries have a wide coverage over whole industries. Still, the concentration ratio is low. But electricity and telecommunication industries show both a high concentration ration and a wide coverage. Generally, the concentration ratio is in inverse proportion to the coverage. The last cluster is an exceptional one.

The patent strategy of Korean firms is investigated from in various aspects： the trend of patenting activities, the evaluation of patent quality, the evaluation of patenting activities of listed Korean firms, and the analysis of patent competencies of Korean and foreign firms. A selective set of findings is as follows. First, as anticipated, the amount of patents has rapidly increased in 1990s compared to in 1980s. And with the increase, the Korean share of both domestic patents and U.S. patents has risen, recording 58.21% for domestic patents and 1.22% for U.S. patents respectively. Second, the results from the evaluation of patent quality suggest that：1) the average number of the cited is 3.7; the average number of the citing is 5.8; 2) the most prominent companies, when evaluated by TII (Technology Impact Index), are Samsung Electronics, LG Electronics, Hyundai Electronics, and Daewoo Electronics; 3) the average of TS(Technology Scope) of Korean companies is 3.9; and 4) persistent innovators are only 50 companies out of 568 companies. Third, using US and Korean patent data, we evaluate 71 listed companies to select 5 top companies with quantity indices, quality indices, and the combined index - the index which couples the quantity indices and quality indices. Among the sample firms, when judged by the quantity indices, Samsung Electronics is, in general, found out to be the most active patent producer. When measured by the quality indices, various firms are selected so we cannot tell which firm performs distinctively best. When evaluated with the combined index, Samsung Electronics ranks first, followed by Daewoo Electronics and LG Semicon showing a large gap. The result unveils that patenting activities of Korean firms are led by a few top companies, mostly Chaebols. Forth, we examine the patent competitiveness of Korean firms in IT industry and BT industry by comparing one Korean firm with one US firm and one Japanese firm. Using two types of patent portfolios proposed by Ernst in 1998, we compare patent competitiveness of three world best IT firms (Samsung Electronics, Toshiba, and Intel) based on the empirical data. The patent portfolios on the company level and on the technological level need six elements which are measured. The six index are 1) the total number of patent as the index of firm's patent activity, 2) the average citation frequency as patent activity, 3) the range of patent technology, 4) the importance of a patent technological field, 5) the relative patent position, and 6) the technology attractiveness. The results indicate the US patenting characteristics in Samsung between 1981 and 1999, compared with Toshiba and Intel as follows. 1) The patent quantity of Samsung grew fast. 2) The patent quality of Samsung was not so high as Toshiba and Intel. 3) The range of Samsung's patent technology was broad and similar to that of Toshhiba. 4) The intensity of important patent technology fields was lower than that of Intel. 5) Samsung's patent competitiveness was in semiconductor device manufacturing process and television during the period. In BT industry, we compare Korea Green Cross Corporation, Merck and Takeda with several measures. In result, although Korea Green Cross Corporation is patenting actively among Korean biotech companies, it produces neither as many nor as good patents as the US counterpart, Merck, and the Japanese counterpart, Takeda. In addition, those three companies are producing patents in a few core fields of biotechnology so issuing quality patents in those crucial fields can be a future technology strategy for any biotechnology firms.

Finally, the patent production function is estimated which is the input-ouput relationship between R&D investment and patents, examine the relationship between firm characteristics - export-orientation, degree of foreign ownership, and Chaebol-affiliation and patents, and explore how the patent production function differs according to firm characteristics. In the patent production function, R&D input and patents output has contemporaneous relationship and the elasticity is 1.29 for US patents; 1.24 for Korean patents. This implies that as the R&D investment of Korean firms increases in the future, the number of patents will grow at a faster rate. After testing the relationship between firm characteristics and patents individually, we find all three characteristics have positive relationship with patents in both cases of US patents and Korean patents. When testing the relationship between compound firm characteristics and patents, the result is about the same, except that the coefficient for Chaebol-affiliation and US patents is not significant. So based on two testing results, in general, we can conclude exporting firms, firms with higher foreign ownership, and Chaebol firms produce more patents. Finally for the patent production function with firm characteristics, the hypothesis that Chaebol firms have higher efficiency in producing patents is not supported. This result signifies that the characteristic being Chaebol cannot be said to help produce more patents because Chaebol firms are usually export-oriented and have higher foreign ownership.

목차 Contents

• 표지 ... 1
• 제출문 ... 2
• 서문 ... 3
• 목차 ... 4
• 표목차 ... 8
• 그림목차 ... 10
• 요약 ... 12
• 제 1장 연구의 배경과 목적 ... 23
• 제 2장 연구의 이론적 배경과 관련 문헌 ... 26
• 제１절 특허 분석 ... 26
• 제２절 기술-산업 연계 ... 28
• 제３절 특허 전략 분석 ... 30
• 제 3장 산업/기술 분류 및 연계 ... 32
• 제１절 산업/기술 분류 전환체계 ... 32
• 제２절 산업분류 ... 33
• 1. 국제 산업분류 ... 33
• 2. 국내 산업분류 ... 34
• 제３절 기술분류 ... 35
• 1. 국제 기술분류 ... 35
• 2. 국내 기술분류 ... 37
• 제4절 산업분류와 과학기술분류의 호환 ... 39
• 1. 개요 ... 39
• 2. 기술호환(technology concordance) ... 40
• 3. 국가과학기술분류와 한국산업분류 연계표 ... 42
• 제5절 국가과학기술분류와 미국특허기술분류 연계 ... 42
• 1. 개요 ... 42
• 2. 미국특허분류와 국가과학기술분류 연계표 ... 43
• 제 4장 산업과 기술부문에 대한 네트워크 분석 ... 44
• 제1절 네트워크 분석 ... 44
• 제2절 네트워크 분석의 방법론 ... 45
• 제3절 산업에 대한 네트워크 분석 ... 46
• 1. 특허등록 추이와 특징 ... 46
• 2. 흡수형, 방출형, 균형형 산업 ... 48
• 3. 산업간 지식흐름 ... 50
• 4. 산업간 기술 매개중심도 ... 53
• 5. 지식흐름의 밀도 ... 54
• 제4절 기술부문에 대한 네트워크 분석 ... 55
• 1. 특허등록 추이 ... 55
• 2. 흡수형, 균형형, 방출형 기술부문 ... 57
• 3. 기술부문간 지식흐름 ... 59
• 4. 기술 매개중심도 ... 62
• 5. 지식흐름 밀도 ... 62
• 제5절 기술-산업 연계 분석 ... 63
• 1. 개요 ... 63
• 2. 기술-산업 연계 행렬 ... 64
• 3. 기술-산업 연계 네트워크 ... 66
• 4. 기술-산업 연계 지표 ... 67
• 제6절 정책적 시사점 및 과제 ... 69
• 제 5장 지식 교류형 산업과 지식 교류형 기술부문에 대한 네트워크 분석 ... 71
• 제1절 네트워크 분석 ... 71
• 제2절 지식교류형 산업의 네트워크 ... 72
• 1. 개요 ... 72
• 2. 특성분석 ... 72
• 제3절 지식교류형 기술부문 네트워크 ... 74
• 1. 개요 ... 74
• 2. 특성분석 ... 75
• 제4절 정책적 시사점 및 과제 ... 77
• 1. 현황과 문제점 ... 77
• 2. 정책과제 ... 78
• 제 6장 한국기업의 특허활동 분석 ... 80
• 제1절 한국 기업의 국내 및 미국 특허활동 추이 ... 80
• 1. 개관 ... 80
• 2. 한국 특허활동의 국제화 ... 82
• 제2절 특허의 질 평가 ... 88
• 1. Citation Frequency (인용 빈도) ... 88
• 2. TII ( Technical Impact Index ) or CPR ( Citation Performance Ratio ) ... 90
• 3. Technological Scope (기술적 범위) ... 90
• 4. 특허 출원의 지속성 ... 91
• 제3절 상장 기업의 특허 활동 평가 ... 92
• 제4절 한국 기업과 외국 기업의 특허 경쟁력 비교 ... 96
• 1. 특허 경쟁력 비교 방법론 ... 96
• 2. 연구 자료 ... 99
• 3. 삼성전자, 도시바, 인텔의 경쟁력 비교 ... 100
• 4. 녹십자, 머크, 다케다의 특허경쟁력 비교 ... 113
• 제 7장 특허생산함수와 기업속성 ... 122
• 1. 서론 ... 122
• 2. 분석의 이론적 배경과 가설검증을 위한 모형의 도출 ... 122
• 3. 가설과 추정모형 ... 125
• 4. 표본 선정과 변수의 정의 ... 127
• 5. 추정 결과 ... 130
• 6. 결론 및 토의 ... 135
• 참고문헌 ... 137
• 부록 ... 145
• 부록 1 한국산업분류(KSIC) 대/중분류표 ... 146
• 부록 2 국가과학기술표준과 한국산업분류의 호환표 ... 147
• 부록 3 국가과학기술표준분류와 미국특허기술분류의 호환표 ... 149
• 부록 4 영한 기업명 대조 ... 151
• 부록 5 기업별로 1981-1999년 사이에 등록한 미국특허수 ... 153
• 부록 6 기업의 통계적 특성 ... 156
• Summary ... 157
• Table of Contents ... 162
• 끝페이지 ... 164