A Study on Technological Innovation, Cooperation, and R&D Efficiency of Universities in China
- Abstract
- In this paper, through the calculation and analysis of the patent literature data applied by Chinese double-class universities during 2002-2021, we compare and analyze the innovation changes and innovation status of Chinese universities, compare the ranking of technological innovation among Chinese universities through multiple indicators and dimensions, and use cluster analysis and multidimensional scale analysis to classify Chinese universities in terms of innovation, so as to divide the universities with similar innovation levels into the same category and summarize the characteristics of the innovation situation of these universities. The patent cooperation network of Chinese universities is established, the indicators of the patent cooperation network are calculated and counted, and the structural characteristics of the patent cooperation network of universities are explored by using social network analysis, and the evolution of the patent cooperation network of universities is comparatively analyzed and studied by using the patent cooperation data in different stages, and comparing the patent cooperation situation of each university in different stages. The Louvain community discovery algorithm is used to divide the community distribution in each stage, identify the patent cooperation groups, and explore the patent cooperation law of universities. Finally, we analyze the influencing factors and assessment indexes of technological innovation efficiency of universities in each region of China and determine the input and output factors of DEA. The DEA-Malmquist model is used to analyze the static and dynamic statistics of university science and technology in each region of China, and the DEA and Malmquist indexes are used to measure the static efficiency and the dynamic changes of the average efficiency of the input and output of R&D activities of universities in each region. The efficiency of the input and output of R&D activities of universities in each region of China is analyzed, and the current status of the development and management of R&D activities of universities in each region is evaluated and improvements are proposed.
Keywords: social network analysis, technological innovation, technical cooperation, DEA, community testing
|본문은 2002~2021년 중국 이중일류대학이 출원한 특허문헌 데이터의 계산과 분석을 통해 중국 대학의 혁신변화와 혁신현황을 비교분석하고, 여러 지표와 여러 차원을 통해 중국 대학 간 기술혁신 순위를 비교하며, 클러스터 분석과 다차원 척도 분석을 이용하여 중국 대학을 혁신의 각도로 구분함으로써 혁신 수준이 비교적 가까운 대학을 같은 종류로 분류하고, 이들 대학의 혁신상황의 특징을 정리한다.중국 대학의 특허 협력 네트워크를 구축하고 특허 협력 네트워크의 다양한 지표를 계산 및 집계하며 사회 네트워크 분석 방법을 사용하여 대학 특허 협력 네트워크의 구조적 특성을 탐색하고 단계별 특허 협력 데이터를 사용하여 대학의 특허 협력 네트워크의 진화를 비교 분석 및 연구하고 각 대학의 단계별 특허 협력 상황을 비교합니다.Louvain 커뮤니티 발견 알고리즘을 사용하여 각 단계에서 커뮤니티 분포를 나누고 특허 협력 그룹을 결정하고 대학의 특허 협력 규칙을 탐색합니다.마지막으로 중국 각 지역의 대학의 기술 혁신 효율에 영향을 미치는 요인과 평가 지표를 분석하고 DEA의 투입 및 산출 요인을 결정합니다.DEA-Malmquist 모델을 사용하여 중국 각 지역의 대학 과학 기술 통계 데이터에 대한 정적 및 동적 분석을 수행하고 DEA 및 Malmquist 지수를 사용하여 각 지역의 대학 R&D 활동에 투입된 정적 및 평균 효율의 동적 변화를 계산합니다.중국 각 지역의 대학 R&D 활동 투입 생산 효율을 분석하고, 각 지역의 대학 R&D 활동 발전 현황과 관리 업무 현황을 평가하여 개선을 제안한다.
키워드: 소셜 네트워크 분석, 기술 혁신, 기술 협력, DEA, 커뮤니티 테스트
- Issued Date
- 2023
- Awarded Date
- 2023-02
- Type
- Dissertation
- Publisher
- 부경대학교
- Affiliation
- Pukyong National university, Graduate School of Management of Technology
- Department
- 기술경영전문대학원 기술경영학과
- Advisor
- Wonchul Seo
- Table Of Contents
- Chapter 1. Introduction 1
1.1. Background of the Study 1
1.2. Significance of the Study 3
1.3. Content of the Study 6
1.4. Research Methodology 7
Chapter 2. Literature Review 10
2.1. Literature Review of Technological Innovation in Universities 10
2.2. Literature Review of University Collaboration 14
2.3. Literature Review of R&D Efficiency in Universities 22
2.4. Shortcomings of existing studies 27
Chapter 3. A Comparative Study of Innovation Capabilities of Chinese Universities Based on Patents 31
3.1. Definition of Data Source, Scope and Time 31
3.2. Overall Description of Data 32
3.3. Comparative Study of Technological Innovation Activity and Technological Innovation Level 35
3.4. Comparative Study on Complexity of Technological Innovation 37
3.4.1. Average Number of Inventors of Invention Patents in Double-class Universities 37
3.4.2. Average Number of IPC of Invention Patents in Double-class Universities 39
3.5. IPC Distribution 41
3.6. Analysis of Technological Innovation in Double-class Universities 44
3.6.1. Systematic Clustering Analysis 44
3.6.2. Multi-dimensional Scale Analysis 48
3.7. Conclusions 52
Chapter 4. A Study of Cooperation in Chinese Universities Based on Social Network Analysis 55
4.1. Social Network Analysis 55
4.2. Cooperative Patent Data Characteristics 56
4.3. Structural Characteristics and Evolution of Patent Cooperation Networks 61
4.3.1. Structural Characteristics of the Patent Cooperation Network 61
4.3.2. Evolution of the Patent Cooperation Network 64
4.4. Small-world Network Phenomena and Power-law Distribution Laws 71
4.4.1. Small-world Network Phenomena 71
4.4.2. Power-law distribution law of the network 73
4.5. Community Division of Patent Cooperation Network Based on Louvain Algorithm 78
4.5.1. Louvain Community Discovery Algorithm 79
4.5.2. Louvain's Algorithm Steps 80
4.5.3. Division of Cooperative Network Communities 81
4.6. Conclusions 87
Chapter 5. A Comparative Study on the Efficiency of R&D Activities of Universities in China by Region Using DEA–Malmquist 90
5.1. Introduction 90
5.2. Evaluation Index System and Evaluation Analysis Model 92
5.2.1. Evaluation Index System 92
5.2.2. Data Envelopment Analysis (DEA) 93
5.2.3. Malmquist Index Model 95
5.3. Empirical Study 96
5.3.1. Static Analysis of DEA Model 96
5.3.2. Dynamic Analysis of the Malmquist Index 101
5.4. Conclusions and Limitations 109
Chapter 6. Conclusions 111
6.1. Summarization of Essays 111
6.2. Limitations and Suggestions for Future Research 114
References 117
ACKNOWLEDGEMENTS 139
- Degree
- Doctor
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