Network DEA-SBM을 이용한 지역별 산업단지의 생산 · 환경효율성 추정
가정희, 김재연
Abstract
가정희, 김재연
Abstract
Data Envelopment Analysis (DEA) is a widely used method to evaluate efficiency. In data envelopment analysis, there are several methods for measuring efficiency changes over time, In the actual industry, single division model is not suitable for efficiency evaluation. To cope with this situation, this study applies a slack-based measure network DEA(SBM-NDEA) model to evaluate efficiency of the production and environmental sectors in regional industrial complexes. NSBM and SBM-DEA are used to evaluate the changes in efficiency of the production and environmental sectors in 11 to 12 regions between 2011 and 2013. Overall efficiency was also assessed. The results show that NSBM efficiency was always less than the efficiency of the SBM. Also, the efficiency was tended to increase the production and environmental efficiency during 2011 to 2013, and according to the regional rankings, Daegu was the first in three years of the average efficiency, Gyeongbuk was valued at no. 12.
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Data Envelopment Analysis (DEA) is a widely used method to evaluate efficiency. In data envelopment analysis, there are several methods for measuring efficiency changes over time, In the actual industry, single division model is not suitable for efficiency evaluation. To cope with this situation, this study applies a slack-based measure network DEA(SBM-NDEA) model to evaluate efficiency of the production and environmental sectors in regional industrial complexes. NSBM and SBM-DEA are used to evaluate the changes in efficiency of the production and environmental sectors in 11 to 12 regions between 2011 and 2013. Overall efficiency was also assessed. The results show that NSBM efficiency was always less than the efficiency of the SBM. Also, the efficiency was tended to increase the production and environmental efficiency during 2011 to 2013, and according to the regional rankings, Daegu was the first in three years of the average efficiency, Gyeongbuk was valued at no. 12.
Key concepts: Data envelopment analysis, Production efficiency, Production (economics), Eco-efficiency, Efficiency, Division (mathematics), Measure (data warehouse), Economic efficiency