[논문]자동차 자율주행 기술 특허분석을 통한 기술협력 네트워크 분석

임호근; 김병근; 정의섭

doi:10.5762/kais.2020.21.12.688

자동차 자율주행 기술 특허분석을 통한 기술협력 네트워크 분석
Technological Cooperation Network Analysis through Patent Analysis of Autonomous Driving Technology 원문보기

한국산학기술학회논문지 = Journal of the Korea Academia-Industrial cooperation Society, v.21 no.12, 2020년, pp.688 - 701

임호근 (한국기술교육대 기술경영학과) , 김병근 (한국기술교육대학교 산업경영학부) , 정의섭 (한국과학기술정보연구원)

초록
AI-Helper

본 연구는 자동차 산업의 기술협력 네트워크의 특성과 변화 요인들에 대해 분석한다. 전 세계 주요 자동차 기업들이 2000년부터 2017년까지 출원한 112,009건의 자율주행 관련 특허를 사회연결망 분석(SNA: Social Network Analysis, 이하 SNA)을 활용하여 기술협력 네트워크의 구조를 분석한다. 네트워크 분석지표 중 구조적 특성 분석을 통해 밀도 등의 네트워크 특성을 분석한다. 연결 정도 중심성, 매개 중심성 및 관계 중심성 등의 지위적 특성 지표 분석을 통해서는 기술협력 네트워크의 구조적 특성을 확인한다. 분석 결과는 토요타, 현대자동차 등 완성차 기업들과 부품 공급 업체인 보쉬, 콘티넨탈 등이 자율주행과 관련한 기술 개발 실적이 높은 것으로 확인되었다. 네트워크의 구조적 특성 분석 결과 자율주행 기술 개발의 협력 네트워크에 참여한 기업들의 수가 증가하고 다양해졌으며 지위적 특성 지표들은 모두 감소하는 결과를 보였다. 이는 기업 간의 수평적이며 보완적인 기술협력 형태가 증가하는 현상으로 해석할 수 있다. 그리고 자동차 자율주행 기술 분야의 참여자가 많아지고 네트워크가 더 복잡해짐을 확인하였다.

Abstract ▼ AI-Helper

This study analyzes the characteristics and change factors of technological cooperation networks in the automotive industry. Using Social Network Analysis (SNA) of 112,009 autonomous driving-related patents filed from 2000 to 2017 by major automotive firms in the world, we investigate the structure of the technological cooperation network. Network characteristics such as density are analyzed through structural characteristic analysis among the network analysis indicators. The structural characteristics of the technology cooperation network are confirmed through analysis of status characteristic indicators, such as the degree of centrality, betweenness centrality, and closeness centrality. Results show that car makers such as Toyota and Hyundai Motors, as well as parts suppliers such as Bosch and Continental, have high-performance technology developments related to autonomous driving. The structural characteristics of the network show that companies participating in cooperative networks for autonomous driving technology development have increased in number and are diversified, and all of the status characteristics indicators have decreased. This can be interpreted as an increasing number of horizontal and complementary forms of technological cooperation between firms. In addition, it was confirmed that the number of participants in the field of autonomous driving technology has increased, and the networks have become more complex.

주제어

표/그림 (25)

그림 Fig. 1. Patents application status
표 Table 1. Network properties
표 Table 2. Network Centrality
그림 Fig. 2. Applicants network
표 Table 3. Patent ranking of Applicants
표 Table 4. Patent status by Application Group
표 Table 5. Network properties
표 Table 6. Patent status by Single and Co-application
표 Table 7. Co-application Patent status by Group
표 Table 8. Co-application Patent properties by Group
표 Table 9. Network centrality by Group
그림 Fig. 3. Degree of Centrality in 2000year
표 Table 10. Network properties by applicants
표 Table 11. Network centrality by applicants
표 Table 12. Degree of Centrality by applicants
그림 Fig. 4. Degree of Centrality in 2010year
그림 Fig. 5. Degree of Centrality in 2017year
표 Table 13. Betweenness Centrality by applicants
표 Table 14. Closeness Centrality by applicants
그림 Fig. 6. Total Degree of Centrality
표 Table 15. IPC Frequency
표 Table 16. Degree of Centrality by IPC
그림 Fig. 7. Degree of Centrality in 2000year
그림 Fig. 8. Degree of Centrality in 2010year
그림 Fig. 9. Degree of Centrality in 2017year

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