The data envelopment analysis （DEA） model is used to evaluate the relative economic efficiency of a given set of decision making units （DMUs）. In this paper, the DEA production possibility set is transferred from ...The data envelopment analysis （DEA） model is used to evaluate the relative economic efficiency of a given set of decision making units （DMUs）. In this paper, the DEA production possibility set is transferred from the conventional sum form into the intersection form which is represented by a linear inequality system. Although it is time consuming to obtain the intersection form of the production possibility set, it suggests a new angle to investigate the properties of DMUs and to extend the DEA research further beyond the efficiency measurement. Following the intersection form, the analytical formula of the efficiency indicator and projection is given. Various aspects of technical efficiency, returns to scale and evidence of congestion of the DMUs are studied. The relationship between the weak DEA efficiency and the weak Pareto solution is discussed. Finally, a procedure for DMU grouping is proposed to help the decision makers for better resource reallocation and strategy adjustment.展开更多
This research proposes a new method to estimate returns to scale(RTS) of decision making units(DM Us) with multiple inputs and outputs.The state of return to scale includes increasing RTS,constant RTS,decreasing RTS a...This research proposes a new method to estimate returns to scale(RTS) of decision making units(DM Us) with multiple inputs and outputs.The state of return to scale includes increasing RTS,constant RTS,decreasing RTS and evidence of congestion.The method is based on the production possibility set in the intersection form given by a set of linear inequalities.We propose and prove the necessary and sufficient conditions for the RTS estimation.With the new procedure,to estimate the RTS of a DM U is simply to check the position of the DM U on the production frontiers.We point out that the procedure is particularly important for dealing with a large number of DM U s.Therefore,it can be regarded as a complementary to the data mining.展开更多
基金This research is supported by the National Natural Science Foundation of China under Grant Nos. 70531040, 70871114, and the 985 Research Grant of Renmin University of China, and the Hong Kong CERG Research Fund PolyU5457/06H and PolyU 5485/09H.
文摘The data envelopment analysis （DEA） model is used to evaluate the relative economic efficiency of a given set of decision making units （DMUs）. In this paper, the DEA production possibility set is transferred from the conventional sum form into the intersection form which is represented by a linear inequality system. Although it is time consuming to obtain the intersection form of the production possibility set, it suggests a new angle to investigate the properties of DMUs and to extend the DEA research further beyond the efficiency measurement. Following the intersection form, the analytical formula of the efficiency indicator and projection is given. Various aspects of technical efficiency, returns to scale and evidence of congestion of the DMUs are studied. The relationship between the weak DEA efficiency and the weak Pareto solution is discussed. Finally, a procedure for DMU grouping is proposed to help the decision makers for better resource reallocation and strategy adjustment.
基金supported by National Natural Science Foundation of China (Grant Nos.70531040,70871114)The Hong Kong CERG Research Fund (Grant Nos.5485/09H,5515/10H)
文摘This research proposes a new method to estimate returns to scale(RTS) of decision making units(DM Us) with multiple inputs and outputs.The state of return to scale includes increasing RTS,constant RTS,decreasing RTS and evidence of congestion.The method is based on the production possibility set in the intersection form given by a set of linear inequalities.We propose and prove the necessary and sufficient conditions for the RTS estimation.With the new procedure,to estimate the RTS of a DM U is simply to check the position of the DM U on the production frontiers.We point out that the procedure is particularly important for dealing with a large number of DM U s.Therefore,it can be regarded as a complementary to the data mining.
