Data Envelopment Analysis(DEA) and Ratio Analysis(RA) are two widely used methods for measuring units' productivity and any other criteria that could be assessed based on the available input and output variables.A number of researchers have studied DEA and RA and noted the positive and negative differences between them.Aggregated ratio analysis(ARA) model,which provide an important linkage between DEA and RA theory,is equivalent to the CCR DEA model,and this equivalence property offers a great deal of opportunities for DEA to be interpreted and applied in different ways.This paper extends the results of ARA model and proposes an extended aggregated ratio analysis(EARA) model,similar as the development from CCR model to BCC model in DEA context.The proposed model can offer an insight into the characteristic of returns to scale,playing the corresponding role as BCC model does.The numerical example is revisited in the paper and the results are compared.
The traditional data envelopment analysis(DEA)model can evaluate the relative efficiencies of a set of decision making units(DMUs)with exact values of inputs and outputs,but it cannot handle imprecise data.Imprecise data,for example,can be expressed in the form of the interval data or mixtures of interval data and ordinal data.In this study,a cross-efficiency method is introduced into the DEA model to calculate the interval of cross-efficiency values,based on which a new TOPSIS method is proposed to rank the DMUs.Two examples are presented to illustrate and validate the proposed method.
