과학문화의 경쟁력과 효율성 분석 = Analysis of Competitiveness and Efficiency of Scientific Culture

국문 초록 (Abstract)

본 연구의 목적은 전남이 연구개발비와 연구개발인력에 있어서 상대적 열위에 처한 이유를 밝히는데 있다. 연구방법은 변이할당분석, 자료포락분석, BCG 분석을 이용한다. 연구 결과로 지역의 경쟁력 약화로 전남의 R&D 예산증가가 국가 R&D 예산 증가에 미치지 못하며, 전남의 연구개발비는 부산, 대구, 경남, 울산, 충북, 세종, 전북, 강원, 울산 10개 지역에 대해 열위를 보일 뿐만 아니라 열위가 점차 커진다는 것을 보인다. 또한 연구개발인력에 있어서 전남의 경쟁력이 증가에 기여한다는 것과, 대구, 울산, 경남, 인천, 경기, 대전, 전북 7개 지역에 대해 열위이며, 열위가 꾸준히 지속된다는 것을 밝힌다. 이러한 분석 결과는 자료포락분석에서 나타난 바와 같이 전남은 효율성이 0.336으로 대단히 낮아 연구개발인력과 연구개발조직을 대폭 축소해야 하나, 규모수익 증가가 적용됨에 따라 규모를 축소하는 것보다 확대하는 것이 합리적이라는 것을 시사함을 보인다.

다국어 초록 (Multilingual Abstract)

The purpose of this study is to find out the factors causing Jeonnam’s relative disadvantage in R&D expenditure and personnel. This paper shows that the region effect has a negative effect on Jeonnam’s R&D expenditure but acts as a factor increasing Jeonnam’s R&D personnel using the shift-share analysis. The analysis also shows that the competitive effect is a major factor affecting Jeonnam’s R&D expenditure as well as personnel. The efficiency of R&D expenditure and personnel is analyzed by DEA. The result shows that one of 17 DMUs is found to be technically efficient and the technical efficiency of Jeonnam is merely 0.34. The results that pure technical efficiencies are, however, lower than scale efficiencies mean that it is rational to increase the inputs rather than downsize the scale. It is evident fron the fact that all inefficient DMUs including Jeonnam have increasing returns to scale.

참고문헌 (Reference)

1 통계청, "국가통계포털"

2 송진웅, "국가 수준의 과학문화 실태 진단을 위한 지표 체제 개발" 한국과학교육학회 28 (28): 316-331, 2008

3 Epstein, M. K., "data envelopment analysis for managerialcontrol and diagnosis" 20 : 90-119, 1989

4 Nunamaker, T. R., "Using data envelopment analysis to measure the efficiency ofnonprofit organizations : a critical evaluation" 6 : 50-58, 1985

5 Gross, A. G., "The roles of rhetoric in the public understanding of science" 3 : 3-23, 1994

6 Kuhn, D., "The importance of learning about knowing : Creating a foundationfor development of intellectual values" 3 : 112-117, 2009

7 Nazara, S., "Spatial structure and taxonomy of decompositionin shift-share analysis" 35 (35): 476-490, 2004

8 Ezcurra, R., "Spatial inequality in productivity in theEuropean union : Sectoral and regional factors" 30 (30): 384-407, 2007

9 Banker, R. D., "Some models for estimatingtechnical and scale Inefficiencies in data envelopment analysis" 30 : 1078-1092, 1984

10 Fitzsimmons, J. A., "Service Management for CompetitiveAdvantage" Mcgraw-Hill Inc 1994

11 Lee, C. D., "Practice that supports learning and development : A commentary" 24 (24): 141-145, 2020

12 Lobato, E. J. C., "Examining how people reason aboutcontroversial scientific topics" 25 (25): 231-255, 2019

13 Blank, J. M., "Does partisanship shape attitudes toward scienceand public policy? The case for ideology and religion" 658 : 18-35, 2015

14 Espa, G., "Decomposing regionalbusiness change at plant level in Italy : A novel spatial shift-share approach" 93 : S113-S135, 2014

15 홍봉영, "DEA를 이용한 소매점의 효율성측정" 한국경영학회 32 (32): 429-448, 2003

16 Nyhan, R. C., "Comparative performance measurement-a primeron data envelopment analysis" 22 : 348-364, 1999

17 Boussofiane, A., "Applied data envelopmentanalysis" 32 : 1-15, 1991

18 Arcelus, F. J., "An extension of shift-share analysis" 15 (15): 3-8, 1984

19 Mussini, M., "A spatial decomposition of the shift-share components of labourproductivity inequality in Italy" 98 (98): 283-306, 2019

20 Artige, L., "A new shift-share method" 45 (45): 667-683, 2014

21 Arbia, G., "A new class of spatial concentration measures" 53 (53): 4471-4481, 2009

22 Herath, J., "A dynamic shift share analysisof economic growth in West Virginia" 6 (6): 155-169, 2011

23 Finicelli, A., "A disaggregated analysis of theexport performance of some industrial and emerging countries" 8 (8): 93-113, 2011