교차효율분석을 활용한 원양어업의 업종별 경쟁력 추정
An Estimation of Competitive Power of Deep-Sea Fishing Industries by Using Cross Efficiency Analysis
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Currently, there is a need to develop scrap programs for deep-sea fishing industry of Korea, since the business environment becomes more uncertain and competitive. Accordingly, it is required to evaluate the competitive power of individual deep-sea fishing industry by considering multiple inputs and outputs of the deep-sea fishing industries. In the efficiency evaluation, Data Envelopment Analysis (DEA) can be used because it is able to handle multiple inputs and outputs in spite of the lack of weight coefficients. The DEA, however, has a drawback of generating 'maverick' decision making unit (DMU)s as well as producing too many efficient DMUs. Therefore, we applied cross efficiency analysis to estimate the relative efficiency of individual deep-sea fishing industry and explicitly rank the all DMUs. In the cross efficiency analysis for deep-sea fishing industries, we considered two outputs of the profitability and secured fishing quarters, while considering the impact of Korea-US FTA, fishing regulation of coastal countries, fishing charges, and competitive fishing conditions as input parameters. The results of our approach indicate that cross efficiency analysis can be successfully used to rank the deep-sea fishing industries. The results of the cross efficiency analysis indicate that Tuna purse seine, Indonesia trawl, and Falkland trawl fishery are expected to have better competitive efficiency.
Abstract
Currently, there is a need to develop scrap programs for deep-sea fishing industry of Korea, since the business environment becomes more uncertain and competitive. Accordingly, it is required to evaluate the competitive power of individual deep-sea fishing industry by considering multiple inputs and outputs of the deep-sea fishing industries. In the efficiency evaluation, Data Envelopment Analysis (DEA) can be used because it is able to handle multiple inputs and outputs in spite of the lack of weight coefficients. The DEA, however, has a drawback of generating 'maverick' decision making unit (DMU)s as well as producing too many efficient DMUs. Therefore, we applied cross efficiency analysis to estimate the relative efficiency of individual deep-sea fishing industry and explicitly rank the all DMUs. In the cross efficiency analysis for deep-sea fishing industries, we considered two outputs of the profitability and secured fishing quarters, while considering the impact of Korea-US FTA, fishing regulation of coastal countries, fishing charges, and competitive fishing conditions as input parameters. The results of our approach indicate that cross efficiency analysis can be successfully used to rank the deep-sea fishing industries. The results of the cross efficiency analysis indicate that Tuna purse seine, Indonesia trawl, and Falkland trawl fishery are expected to have better competitive efficiency.
참고문헌 (14)
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