Data Envelopment Analysis （DEA） is a mathematical tech- nique to assess relative efficiencies of decision making units （DMUs）. The efficiency of 14 Iranian forest companies and forest management units was investig...Data Envelopment Analysis （DEA） is a mathematical tech- nique to assess relative efficiencies of decision making units （DMUs）. The efficiency of 14 Iranian forest companies and forest management units was investigated in 2010. Efficiency of the companies was esti- mated by using a traditional DEA model and a two-stage DEA model. Traditional DEA models consider all DMU activities as a black box and ignore the intermediate products, while two-stage models address inter- mediate processes. LINGO software was used for analysis. Overall pro- duction was divided into to processes for analyses by the two-stage model, timber harvest and marketing. Wilcoxon＇s signed-rank test was used to identify the differences of average efficiency in the harvesting and marketing sub-process. Weak performance in the harvesting sub-process was the cause of low efficiency in 2010. Companies such as Neka Chob and Kelardasht proved efficient at timber harvest, and Neka Chob forest company scored highest in overall efficiency. Finally, the reference units identified according to the results of two-stage DEA analysis.展开更多
This paper expresses the efficient outputs of decisionmaking unit（DMU） as the sum of ＂average outputs＂ forecasted by a GM（1,N） model and ＂increased outputs＂ which reflect the difficulty to realize efficient ou...This paper expresses the efficient outputs of decisionmaking unit（DMU） as the sum of ＂average outputs＂ forecasted by a GM（1,N） model and ＂increased outputs＂ which reflect the difficulty to realize efficient outputs.The increased outputs are solved by linear programming using data envelopment analysis efficiency theories,wherein a new sample is introduced whose inputs are equal to the budget in the issue No.n ＋ 1 and outputs are forecasted by the GM（1,N） model.The shortcoming in the existing methods that the forecasted efficient outputs may be less than the possible actual outputs according to developing trends of input-output rate in the periods of pre-n is overcome.The new prediction method provides decision-makers with more decisionmaking information,and the initial conditions are easy to be given.展开更多
文摘Data Envelopment Analysis （DEA） is a mathematical tech- nique to assess relative efficiencies of decision making units （DMUs）. The efficiency of 14 Iranian forest companies and forest management units was investigated in 2010. Efficiency of the companies was esti- mated by using a traditional DEA model and a two-stage DEA model. Traditional DEA models consider all DMU activities as a black box and ignore the intermediate products, while two-stage models address inter- mediate processes. LINGO software was used for analysis. Overall pro- duction was divided into to processes for analyses by the two-stage model, timber harvest and marketing. Wilcoxon＇s signed-rank test was used to identify the differences of average efficiency in the harvesting and marketing sub-process. Weak performance in the harvesting sub-process was the cause of low efficiency in 2010. Companies such as Neka Chob and Kelardasht proved efficient at timber harvest, and Neka Chob forest company scored highest in overall efficiency. Finally, the reference units identified according to the results of two-stage DEA analysis.
基金supported by the Research Start Funds for Introducing High-level Talents of North China University of Water Resources and Electric Power
文摘This paper expresses the efficient outputs of decisionmaking unit（DMU） as the sum of ＂average outputs＂ forecasted by a GM（1,N） model and ＂increased outputs＂ which reflect the difficulty to realize efficient outputs.The increased outputs are solved by linear programming using data envelopment analysis efficiency theories,wherein a new sample is introduced whose inputs are equal to the budget in the issue No.n ＋ 1 and outputs are forecasted by the GM（1,N） model.The shortcoming in the existing methods that the forecasted efficient outputs may be less than the possible actual outputs according to developing trends of input-output rate in the periods of pre-n is overcome.The new prediction method provides decision-makers with more decisionmaking information,and the initial conditions are easy to be given.
