투입 및 산출 분해모형을 활용한 산학연 협력연구의 효율성 분석

국문 초록 (Abstract)

본 연구는 한국 정부에서 ‘13～’15년에 지원한 정부연구개발사업중 산학연 협력연구 과제를 대상으로 협력유형을 주관기관별로 유형화하여 효율성을 분석하였다. 효율성 분석을 위해 6단계에 걸쳐 순수연구개발과제만을 분류하였으며, 투입과 산출변수를 다양한 조합의 투입과 산출변수를 분해 모형을 만들어 투입과 산출변수간의 효율성 차이점을 분석하기 위해 하여 산출지향 규모수익가변(VRS: Variable Return to Scale)의 DEA 모형으로 효율성을 분석하였다. 또한, 산출변수와 관련 있는 과학적, 기술적, 경제적 성과 모형의 효율성 분석결과를 활용하여 계층적 군집분석으로 클러스터를 확인하고, 클러스터별 강점과 약점에 맞는 산학연 협력유형별 정부 연구개발예산의 투자 포트폴리오 및 투자전략을 제시하였다. 효율성 분석결과 주관기관별 산학연 협력유형의 효율성은 각 모형별로 차이가 있었으나 전반적으로 대기업과 출연연구기관이 상대적으로 효율적이고, 중견기업, 중소기업, 그리고 대학은 상대적으로 비효율적인 것으로 분석되었다. 계층적 군집분석결과 3개 유형의 클러스터가 형성되었으며, 클러스터별로 논문, 특허, 기술료․사업화에서 강점과 약점이 있는 협력유형이 나타나서, 이에 대한 차별적인 투자전략을 제시하였다.

다국어 초록 (Multilingual Abstract)

This study analyzed collaborative R&D projects funded by the Korean government from 2013- 2015. For this analysis, input and output variables of projects were considered, and a combination of those variables was itemized. The output-oriented variable return to scale (VRS) model extended from the DEA methodology was adopted to evaluate the cooperation efficiency of the types of R&D collaboration, which were classified according to the project leader"s organizations. In addition, hierarchical cluster analysis was conducted using the efficiency results of the scientific, technical, and economical outcome models. The results showed that cooperation efficiency between large companies and public research institutions was relatively high. Conversely, cooperation among medium-sized companies, small businesses and universities was particularly inefficient. The clustering results demonstrated the various strengths and weaknesses of the types depending on publications, patents, technical loyalties and the number of commercialization. In conclusion, this study suggests differentiated investment portfolios and strategies based on the efficiency results of diverse cooperation types among industries, universities and public research institutions.

목차 (Table of Contents)

• 요약
• Abstract
• 1. 서론
• 2. DEA의 이론적 배경 및 선행연구
• 3. 연구대상 및 방법
• 4. 분석결과
• 5. 결론
• References

참고문헌 (Reference)

1 이성희, "정부출연연구기관의 산학연 공동연구 성과 평가" 대한산업공학회 43 (43): 154-163, 2017

2 정선양, "산학연 협력의 새로운 방향: 산학연 협력연구실 구축을 중심으로" 기술경영경제학회 16 (16): 17-40, 2008

3 J. D. Lee, "Theory of Efficiency Analysis:Data Envelopment Analysis" Jiphil media 2012

4 K.K. Ko, "Theory of Efficiency Analysis : Data Envelopment Analysis and Stochastic Frontier Approach" MoonWooSa 2017

5 Henry Etzkowitz, "The dynamics of innovation: from National Systems and “Mode 2” to a Triple Helix of university–industry–government relations" Elsevier BV 29 (29): 109-123, 2000

6 J. H. Kim, "The R&D Efficency Comparison Analysis by Technical Sectors and Research Participants of Research Institutions Selected by Government" 146 (146): 21-35, 2004

7 M. J. Farrell, "The Measurement of Productive Efficiency" JSTOR 120 (120): 253-290, 1957

8 H.Y Kim, "The Efficiency Analysis by Collaboration Types of National R&D Programs : A Case of Pure National R&D Programs by Employing DEA" 373-382, 2016

9 M. H. Park, "The Analysis of Efficiency and Productivity" Korean Studies Information 52-192, 2008

10 R. D. Banker, "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis" Institute for Operations Research and the Management Sciences (INFORMS) 30 (30): 1078-1092, 1984

11 S. C. Chang, "Returns to Scale in DEA Models for Performance Evaluations" 78 (78): 1389-1396, 2011

12 Y. Yu, "Research on the Technology Transfer Efficiency Evaluation in Industry-University-Research Institution Collaborative Innovation and Its Affecting Factors Based on the Two-Stage DEA Model" 237-249, 2017

13 H.W. Chesbrough, "Open Innovation: The New Imperative for Creating and Profiting from Technology" Harvard Business School Press 2003

14 A. Charnes, "Measuring the efficiency of decision making units" Elsevier BV 2 (2): 429-444, 1978

15 Carlos Serrano-Cinca, "Measuring DEA efficiency in Internet companies" Elsevier BV 38 (38): 557-573, 2005

16 Ministry of Science, "ICT and Future Planning·KISTEP (2016), Main Science & Technology Indicators of Korea 2015" KISTEP 2016

17 G. Callender, "Efficiency and Management" Routledge 2009

18 S. H. Kim, "Efficiency Analysis:Theory and Applications" Seoul economics and management 2007

19 John S. Liu, "Data envelopment analysis 1978–2010: A citation-based literature survey" Elsevier BV 41 (41): 3-15, 2013

20 W.W. Cooper, "Data Envelopment Analysis: Theory, Methodology, and Applications, References and DEA-Solver Software" Kluwer Academic Publishers 2000

21 배성훈, "DEA모형을 활용한 나노기술 분야 국가 R&D 과제의 효율성 분석" 한국산업경영시스템학회 39 (39): 64-71, 2016

22 고대경, "DEA를 활용한 해운·물류 기업의 경영성과에 관한 연구" 한국항만경제학회 30 (30): 93-112, 2014

23 이철행, "DEA를 이용한 보건의료기술 R&D사업의 효율성 분석과 전략적 포트폴리오 모형 : 중개연구를 중심으로" 대한산업공학회 40 (40): 172-183, 2014

24 박한석, "DEA 모형을 활용한 BT 및 NT 분야 연구개발 효율성 측정 : 한국의 기초연구사업을 대상으로" 성균관대학교 대학원 2014

25 A. Y. So, "Analyzing Efficiency of National Convergence R&D Programs Using Data Envelopment Analysis and Malmquist Productivity Index" 1 (1): 26-51, 2015

26 Wesley M. Cohen, "Absorptive Capacity: A New Perspective on Learning and Innovation" JSTOR 35 (35): 128-, 1990

27 Larry Jenkins, "A multivariate statistical approach to reducing the number of variables in data envelopment analysis" Elsevier BV 147 (147): 51-61, 2003

28 J.H. Oh, "A Study on the Relative Efficiency of the Materials and Components Enterprises by Using Data Envelopment Analysis" Graduate School of Kyungsung University 2011

29 H.J. Lee, "A Study on Analyzing The Efficiency of Defense R&D Projects: An Expanded DEA Approach" Graduate School of Konkuk University 2015