애스크로AIPublic Preview
← 학술논문 검색
학술논문한국경영과학회지2016.02 발행KCI 피인용 32

Cumulative DEA/Malmquist Index 기법을 이용한 정부출연 연구기관 연구개발 효율성 변화 분석

Analysis of the Change in R&D Efficiency in a Government-Funded Research Institute in Korea: Cumulative DEA/Malmquist Analysis Approach

이수철(한국과학기술정보연구원); 이동호(국방과학연구소)

41권 1호, 99~111쪽

초록

This paper presents a framework to analyze the change in the research and development (R&D) efficiency of government-funded research institutes (GRIs) in Korea. Cumulative data envelopment analysis/Malmquist index method is utilized to analyze the changes in R&D efficiency of GRIs. Data analysis of the R&D activities of 10 GRIs in Korea Research Council of Fundamental Science & Technology showed that the average R&D efficiency of the 10 GRIs improved from 2009 to 2013. However, the efficiency of a few GRIs decreased in terms of the catch-up index. The proposed framework can help management teams diagnose the current state of R&D activities and determine the efficacy of strategic actions by comparing efficiencies in the past.

Abstract

This paper presents a framework to analyze the change in the research and development (R&D) efficiency of government-funded research institutes (GRIs) in Korea. Cumulative data envelopment analysis/Malmquist index method is utilized to analyze the changes in R&D efficiency of GRIs. Data analysis of the R&D activities of 10 GRIs in Korea Research Council of Fundamental Science & Technology showed that the average R&D efficiency of the 10 GRIs improved from 2009 to 2013. However, the efficiency of a few GRIs decreased in terms of the catch-up index. The proposed framework can help management teams diagnose the current state of R&D activities and determine the efficacy of strategic actions by comparing efficiencies in the past.

발행기관:
한국경영과학회
DOI:
http://dx.doi.org/10.7737/JKORMS.2016.41.1.099
분류:
경영학

AI 법률 상담

이 논문의 주제에 대해 더 알고 싶으신가요?

460만+ 법률 자료에서 관련 판례·법령·해석례를 찾아 답변합니다

AI 상담 시작
Cumulative DEA/Malmquist Index 기법을 이용한 정부출연 연구기관 연구개발 효율성 변화 분석 | 한국경영과학회지 2016 | AskLaw | 애스크로 AI