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The Analysis of Oceans and Fisheries Human Resources Development Education Efficiency Using Bootstrap-DEA

Bootstrap-DEA를 이용한 해양수산 인재 양성교육의 효율성 분석에 관한 연구

  • Kim, Jong-Cheon (Department of Marine and Fisheries Business and Economics, Pukyong National University) ;
  • KIM, Byoung-Ho (Department of Marine and Fisheries Business and Economics, Pukyong National University)
  • 김종천 (국립부경대학교 해양수산경영학과) ;
  • 김병호 (국립부경대학교 해양수산경영학과)
  • Received : 2016.02.25
  • Accepted : 2016.03.24
  • Published : 2016.03.31

Abstract

The purpose of this study is to investigate production efficiency of Oceans and Fisheries Human Resources Development Programs Efficiency using Bootstrap-DEA. The study extracts 33 officials curriculum, 11 fisheries managers curriculum for its analytical. First, the study estimates technical, pure technical, and scale efficiency of each curriculums based on traditional DEA under the assumption of CRS and VRS. 8(official 7, managers 1) curriculums are identified as efficient DMUs under the CCR-model, and 13(official 10, managers 3) under the BCC-model. We provide inputs that allow inefficient curriculum to be efficient DMUs on a production frontier, and a reference set for their bench-marking. Second, rank test, Wilcoxon-Mann-Whitney test to find a statistical significance of heterogeneity existing in efficiences between Bootstrap-DEA tenical vs Bootstrap-DEA pure technical was no significant difference. We have identified that G10, 11, 12 13, 25, 31, 33, 39 curriculums are the most efficiently produced in the technical and pure technical efficiency. Also we managed to measure the inefficiency which exists in efficiently produced curriculums when estimating the bias corrected efficiency scores. In Technical efficiency, Operation and facility was significant at the 10%. In Pure technical efficiency, facility was significant at the 10%.

Keywords

References

  1. Banker, R. D. et al. (1984), "Some models for estimating technical and scale inefficiencies in data envelopment analysis," Management Science, 30, 1078-1092. https://doi.org/10.1287/mnsc.30.9.1078
  2. Charnes, A., Cooper W. W. and Rhodes, E. (1978), "MeasuringEfficiency of Decision Making Units," European Journal of Operations Research, 2, 429-444. https://doi.org/10.1016/0377-2217(78)90138-8
  3. Choi, J. Y. et al. (2003), "Evaluating Managerial Efficiency of Fisheries Cooperatives in Korea: Data Envelopement Analysis," Journal of Fisheries Business Administration, 34 (2), 109-129.
  4. Efron, B. (1979), "Bootstrap Methods: Another Look at the Jackknife," Annals of Statistics, 7 : 1-26. https://doi.org/10.1214/aos/1176344552
  5. Fitzsimmons, J. A. et al. (1994), "Service Management for Competitive Advantage," Mcgraw-Hill, New York, 1-462.
  6. Jang, W. H. et al. (2011), "An Analysis of Efficiency of Agricultural Education and Training Programs," Journal of Agricultural Education and Human Resource Development, 43 (3), 95-117.
  7. Kim, D. H. (2006), "Measurement of Fishing Capacity of offshore Fisheries in Korea," Journal of Fisheries Business Administration, 37 (1), 1-24.
  8. Khong, R. S. (1982), "A study on the Successor-Cultivation in Fisheries Management," Journal of Fisheries Business Administration, 13 (1), 1-46.
  9. Khong, R. S. (1984), "The Theory of Fisherman's Successor-Cultivation," Journal of Fisheries Business Administration, 15 (1), 1-57.
  10. Lee, K. W. (2011), "Management Evaluation on the Regional Fisheries Cooperatives using Data Envelopment Analysis Model," Journal of Fisheries Business Administration, 42(2), 15-30.
  11. Lee, J. D. and Oh, D. H. (2012), "Theory Efficiency analysis," JIPHIL, 1-372.
  12. Lee, K. N. et al. (2015), "Return sea.country survey and short-term.long-term development measures," Ministry of Oceans and Fisheries.
  13. Oh, H. J. (2001), "Performance Evaluation of Information Technology Firms using DEA Model," Kyonggi University graduate school, a doctoral dissertation, 1-80.
  14. Pyo, H. D. and Kim, J. C. (2010), "Evaluating Production Efficiency in a Fisheries Wholesale Sector," Journal of Fisheries Business Administration, 41 (3), 21-44.
  15. Park, C. H. (2010), "A Study on the Efficiency of Fishing-Ports Based on Super-SBM," Journal of Fisheries Business Administration, 41 (3), 129-151.
  16. Park, C. H. and Choi, C. H. (2012), "The Comparative Analysis of the Aquaculture Efficiency Based on DEA," The Journal of Korean Island, 24 (1), 33-49.
  17. Park, J. W. et al. (2011), "A Study on Cultivativation of a Fisheries Expert to revitalize Transfer of Fisheries Management Right," Journal of Fishery and Marine Science Education, 23 (3), 361-373.
  18. Park, M. H. (2008), "Efficiency and Productivity Analysis," kstudy, 13-151.
  19. Park, M. H. (2014), "An Efficiency Analysis of Public Enterprises Using Bootstrap DEA," Journal of Contents, 475-487.
  20. Ray, C. and Bhadra, D. (1993), "Nonparametric Tests of Cost Minimizing Behavior," Journal of American Agricultural Economics, 75, 990-999. https://doi.org/10.2307/1243986
  21. Seo, J. N. and Song, J. H. (2009), "A Study on Efficiency Estimation of Aquaculture: the Case of the Korean Seaweed Farms," Journal of Fisheries Business Administration, 40 (1), 1-26.
  22. Simar, L. and Wilson, P. W. (1998), "Sensitivity Analysis of Efficiency Scores: How to Bootstrap inNonparametric Frontier Models," Management Science, 44 : 49-61. https://doi.org/10.1287/mnsc.44.1.49
  23. Simar, L. and Wilson, P. W. (1999), "Estimating and Bootstrapping Malmquist Indices," European Journal of Operational Research, 115 : 459-471. https://doi.org/10.1016/S0377-2217(97)00450-5
  24. Simar, L. and Wilson, P. W. (2000a), "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, 13 : 49-78. https://doi.org/10.1023/A:1007864806704
  25. Simar, L. and Wilson, P. W. (2000b), "A General Methodology for Bootstrapping Nonparametric Frontier Models," Journal of Applied Statistics, 27 : 779-802. https://doi.org/10.1080/02664760050081951
  26. Simar, L. and Wilson, P. W. (2007), "Estimation andInference in Two-Stage, Semi-Parametric Models of Production Processes," Journal of Econometrics, 136, 31-64. https://doi.org/10.1016/j.jeconom.2005.07.009