International Journal of Data Envelopment Analysis
Volume:7 Issue: 4, Nov 2019

This study intends to expand a set of proper performance evaluation indices which embraces strategies for sustaining top performance using SWOT analysis inside a balanced scorecard (BSC) outline for the large commercial bank branches in IRAN by operating a fuzzy Data Envelopment Analysis (FDEA). Through literature reviews and the banks’ experts and managers opinions and who have real practical experiences in the bank strategy planning, satisfactory performance evaluation indices have been selected throughout SWOT analysis. Then, utilizing the decision making trial and evaluation laboratory (DEMATEL) and analytic network process (ANP), respectively, further establishes the causality between the four BSC perspectives as well as the relative weights between evaluation indices. An empirical grading of the bank strategies is exemplified by applying fuzzy data envelopment analysis. The DEA model ranks the DMUs based on mathematical and scientific logic. Fuzzy DEA technique is utilized for ranking the branches.

In the environment of business‐to‐business e‐commerce, Buyers and sellers in mature industrial markets can turn single transactions into long-term beneficial relationships by a deeper understanding of the complex connection between the two and buyers and sellers are uncertain about their roles. A “must-do” for the sellers, in particular, is to understand patterns of investment and reward, and effectively manage the process that defines the dynamics of buyer-seller evolution. This paper tries to use data envelopment analysis as a reliable and achievable tool for performance evaluating, quality and performance improvement of Buyer-Seller Relationship, in the situation where the information flows are imprecise data between buyers and sellers.

The purposed-the main purpose of this study is to look at the development of efficiency and productivity in the military hospital sector of Tehran province, by applying a nonparametric method. Design/methodology/approach- The study applied the nonparametric method to assess the efficiency of military hospitals service in Iran, Tehran, over the period 2013-2016. Utilizing non-parametric methodology, Data Envelopment Analysis (DEA) and Malmquist productivity index (MPI), individual hospital efficiency and productivity changes which took place within this period are estimated. Practical implications- the present study helps to understand the productivity and technological change and change in technical efficiency in this area, which is essential for policy making identifying improvement opportunities in resource allocation. The difference in productivity in this study is attributed to technological change rather than technical efficiency change. It was observed that military hospitals did not improve the efficiency with which they employed their inputs (i.e., staff and supplies) over the study period; moreover, the Malmquist Index Productivity increases and decreases interchangeably over the period. They did achieve gains and losses through the application of technologies. These results should be both informative and reassuring to military leaders and citizen alike. Originality/value- This paper provides a thorough study on the productivity growth of health care service in military hospitals in Iran using a non-parametric framework with Malmquist Productivity Index. Using panel data, this paper uses the Malmquist Productivity Index with Data Envelopment Analysis that provides new empirical evidence on the long-term trends in the efficiency of military hospitals in Iran.

By using the Double Frontiers Criteria, Hurwicz succeeded to achieve The Most Productive Scale Size of decision making units. This Double frontiers criteria was achieved by using two models of “CCR” in optimistic viewpoint in input form and the “CCR” model in pessimistic viewpoint in input form. In this paper, we intend to find a criteria for Double frontiers of super efficiency by using two models of super efficiency in input form and in both viewpoint of optimistic and pessimistic in such a way that conclude in Hurwicz Double frontiers of MPSS.

DEA (Data Envelopment Analysis) is a technique for evaluating the relative effectiveness of decision-making units (DMU) with multiple inputs and outputs data based on non-parametric modeling using mathematical programming (including linear programming, multi-parameter programming, stochastic programming, etc.). The classical DEA methods are developed to handle the information in the form of crisp number but have no capability in dealing with fuzzy information like triangular intuitionistic fuzzy numbers (TIFNs), which is flexible in reflecting the uncertainty and hesitation associated with the decision-makers’ opinion. In this paper, an extended model of DEA is proposed under the triangular intuitionistic fuzzy environment where the inputs and outputs of DMUs are TIFNs. At first, the definition and characteristics of a classical model of DEA and the comparative TIFNs are introduced. In addition, a new ranking function considering the interaction between membership and non-membership values of different intuitionistic fuzzy sets are defined. Then, the triangular intuitionistic DEA model is proposed. Finally, the new approach is illustrated with the help of a numerical example.

One way to increase the discrimination ability in data envelopment analysis (DEA) is to use the pessimistic view in the performance evaluation. A traditional and usual approach to move from the optimistic to the pessimistic view is to expand the production possibility set. By expanding the production possibility set, the distance between each unit can be increased from the efficiency frontier, and then a smaller number of units are located on the boundary. On the other hand, in practical applications, we are confronted with imprecise inputs and outputs. Expressions of inputs and outputs as imprecise data can give us an opportunity to use it in order to increase the efficiency discrimination. Our view of the ambiguity in the data focus on fuzzy relation. We introduce a fuzzy monotonicity assumption and construct a fuzzy production possibility set (FPPS) with varying degrees of feasibility. Using the tolerance approach a nonsymmetric fuzzy linear programming model and subsequently, a parametric DEA model is constructed. By applying this model, it will be seen that, for a specific and small tolerance of constraints, The discrimination efficiency of the units increases. Finally, we propose a procedure for ranking of DMUs and employ it to rank Iranian national universities.