A Data Envelopment Analysis Model for Evaluation of Efficiency of Deep-Sea Fishing Industry

원양어업의 효율성 평가를 위한 자료포락 분석 모형

  • 김재희 (전북대학교 경영학부) ;
  • 최강득 (국립군산대학교 경영회계학부) ;
  • 김수관 (국립군산대학교 경영회계학부)
  • Published : 2008.12.31

Abstract

In Korea, deep-sea fishing industry is faced with pressure of being thrown out of business, because of the upcoming unfavorable business conditions such as the fishing regulation of coastal countries, Korea-US Free Trade Agreement(KORUS FTA), and the other socio-economic changes. Hence, we present an evaluation of future business competitive for the deep-sea fishing industry so that the government can develop a concession plan for the deep-sea fishing industry by utilizing the results of this study. In efficiency analysis of deep-sea fishing industry, the decision maker may have two problems: (1) how to deal with multiple inputs and outputs of deep-sea fishing industry and (2) how to assign the weights on different inputs and outputs, In this paper, we proposed to use Data Envelopment Analysis (DEA) to estimate efficiency of deep-sea fishing industry with multiple inputs and outputs. In the DEA, The direct impact of KORUS FTA, fishing regulation of coastal countries, fishing charges, and competitive fishing conditions were used as input parameters while the profitability and secured fishing quarters, as outputs. The results of DEA-BCC model indicate that 6 out of 12 DUMs have better efficiency under variable return to scale assumption.

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