한국산학기술학회논문지 (Journal of the Korea Academia-Industrial cooperation Society)

  • 제18권12호
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  • Pages.473-484
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  • 2017
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  • 1975-4701(pISSN)
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  • 2288-4688(eISSN)
한국산학기술학회 (The Korea Academia-Industrial cooperation Society)
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투입 및 산출 분해모형을 활용한 산학연 협력연구의 효율성 분석

An Efficiency Analysis of Industry-University-Public Research Institute Collaborative Research: Employing the Input-Output Itemization Model

  • 김홍영 (한국과학기술기획평가원 성장동력사업센터) ;
  • 정선양 (건국대학교 기술경영학과)
  • Kim, Hong-Young (Center of Growth Engine R&D Coordination, Korea Institute of S&T Evaluation and Planning) ;
  • Chung, Sunyang (Department of Technology Management, Konkuk University)
  • 투고 : 2017.10.30
  • 심사 : 2017.12.08
  • 발행 : 2017.12.31
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초록

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.

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.

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