关键词: 数据包络分析（DEA）, 逼近理想解的排序方法（TOPSIS）, 相对效率, 多属性决策, 松弛改进量

Abstract: In an increasingly competitive environment, decision making and efficiency have become to be the key factors. But in practice, managers usually appear to achieve the purpose of optimizing decision-making with the sacrifice efficiency. This practice is very easy to make managers in the dilemma of care for this and lose that.Therefore, ensuringor even improving efficiency is crucial during the process of optimization of decision making. However, no scholars have combined the data envelopment analysis(DEA) method with the decision method in existing researches, which is in order to solve the problem of optimizing the decision based on the current relative efficiency.From the perspective of multi criteria decision making,based on the current efficiency, the DEA method is firstly combined with technique for order preference by similarity to an ideal solution(TOPSIS) method. The DEA-TOPSIS integrated method can deal with the issue of multi criteria decision making on the base of efficiency assurance.DEA is a non-parametric method that measures therelative efficiencies of organizations, which is with multi inputs and outputs.This method also can calculate the inputs and outputs'slack improvements of ineffective decision making units(DMUs). These slack improvements provide a clear direction and goal for further decision making optimization based on the efficiency. TOPSIS method is widely used in multi criteriadecision making problems.As DEA method, TOPSIS method'sbasic idea is to sort alternatives according to the evaluation of ideal and negative ideal distance between the targets. So it is feasible in theory to integrate the DEA method and TOPSIS method.DEA-TOPSIS integrated method consists of two stages: the first stage is to measure theDMUs'relative efficiencyby DEA, and determine the decision alternatives set according to the efficiency values and decision goals. The second stage is to constructthe decision matrix according to the projections of inefficiency DMUs, then rank the alternatives using TOPSIS method. Taking Capital Medical University for example, the organization is assumed, in order to improve its efficiency, intend to increase the numbers of DEA efficient DMUs. Meanwhile the organization' objective is to minimize the slack improvements (i.e. let the revolution easier) during the efficiency improvement. The 10 class1, Grade 3 general affiliation hospitals as the DMUs, we study the technical efficiency by using the DEA-TOPSIS integrated method. 2008 ~ 2013 is taken as the observation period, and 3 inputs-including the number of employees(person), the purchase of medical equipment gross this year(million yuan) and the number of beds(zhang)-and 1 output-outpatients(person) are selected. The data are derived from the Beijing health Yearbook 2009~2014. The results show that DEA-TOPSIS method can not only rank the alternatives effectively, but also reflect the actual situation by choosing different models or index disposal methods. This research can provide some management ideas and references for similar organizations, such as administrations of hospital,education departments, group corporations, etc.

Key words: data envelopment analysis (DEA), technique for order preference by similarity to ideal solution (TOPSIS), relative efficiency, multicriteria decisionmaking, slack improvements