Banking industry has significant contribution in development of economies of developing countries. Most banks execute their operations through different branches. Therefore it is important to measure the relative efficiencies of these branches. Data envelopment analysis (DEA) is one of the most useful tools in measuring banks’ performance. The present paper aims to extract ranking pattern of banks based on performance evaluation using DEA analysis. In the present research, 120 bank branches of Bank Shahr in city of Tehran were selected and their efficiencies were evaluated using DEA technique. The results are discussed and compared with similar studies.

The primary purpose of this study is to measure the technical efficiency of 30 doctorate-granting universities, the universities or the higher education institutes with PhD training programs, in Vietnam, applying the sensitivity analysis of data envelopment analysis (DEA). The study uses eight sets of input-output specifications using the replacement as well as aggregation/disaggregation of variables. The measurement results allow us to examine the sensitivity of the efficiency of these universities with the sets of variables. The findings also show the impact of variables on their efficiency and its “sustainability”.

Performance measurement is one of the primary tasks in every organization and it helps organization setup appropriate targets for future. There are several ways to assess the performance of the organization, and data envelopment analysis (DEA) is one of the most important methods. DEA is an appropriate technique to measure the efficiency of decision-making units, but does not provide complete information about the unit & apos; s productivity. Malmquist productivity index is one of the methods for measuring productivity and the main advantage of this index is the possibility of the productivity changes over time. In this study, DEA is used to measure service performance and economic foundation so that the performance of four companies within a 3-month period were evaluated. In this work, the cost of the system and investment were used as inputs, revenue and profit were considered as the output and constant returns to scale (CCR) was used to analyze the system, which yields 0.9 for all units when all input/output data were considered in crisp form. The efficacy of different units using interval data also showed different productivity compared with the crisp model. The productivity measures of the companies in three-month period were studied using the Malmquist based productivity index and the results were analyzed.

During the past few years, there have been tremendous efforts on development of Iranian banking industry in an attempt to fight against monopoly of banking system. Bank Pasargad is one of the biggest Iranian banks established for offering retail, commercial as well as investment banking services. The firm was established in 2005 as part of the government & apos; s privatization of the banking system. This paper presents an empirical investigation to determine the most efficient locations for development of this bank. The study uses three main criteria, customer services (C1), Equipment (C2) and Profitability (C3) to compare different alternatives for establishing new branches in city of Tehran, Iran. Using fuzzy data envelopment analysis the study has determined that center of the city could receive the most important attraction followed by north region, west region as well as south west.

Data Envelopment Analysis (DEA) is a decision making tool based on linear programming for measuring the relative efficiency of a set of comparable units. DEA helps us identify the sources and level of inefficiency for each of the inputs and outputs. This approach has been used to evaluate the efficiency of the safety department in five construction companies. A three-input, safety workforce, safety training, and safety budget, and two-output, Perfect days and Uptime, constant returns-to-scale (CRS) model was developed. The model indicated the necessary improvements required in the inefficient unit’s inputs and outputs to make it efficient, by identifying what factor is responsible for the low efficiency of performance, and also what factor should be improved in order to improve the efficiency of the safety department. The result shows that the safety department of firm A, B and D are efficient, but Firm C and Firm E can improve their efficiency by reducing inputs up to 3.34% and 6.05%, respectively. The inputs identified for reduction were; number of safety staffs and safety budget for Firm C and E respectively.

Measuring the relative efficiency of similar units has been a popular research especially when the units were mostly non-financial. Even, similar financial units may not be necessarily evaluated based on traditional financial figures such as return of equities, return of assets, etc. In this paper, we present an empirical investigation to measure the relative efficiency of 30 branches of an Iranian bank named Bank Mellat. The study considers four inputs including operating expenses, interest paid, capital expenditures and fixed assets. In addition, we use customers’ bank deposit, commissions and loans paid as output parameters. Using three different data envelopment analyses, the study measures the relative efficiencies of all units. The preliminary results indicate that most banks were working under desirable level of efficiency.

Measuring the relative efficiency of financial units plays essential role for making strategic decisions such as business development, downsizing, etc. This paper presents an empirical investigation to rank different branches of a credit institution named Samen in city of Semnan, Iran. The proposed study uses data envelopment analysis (DEA) for measuring the relative efficiency of 17 units. The results indicate that five units were efficient and using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the efficient units are ranked based on some inputs/outputs. The results of this study indicate that most branches of this financial unit performed poorly and a restructure in their businesses is necessary. In addition, the study has provided some evidences that considering employee wage, bank deposit and administration expenses as inputs for DEA implementation seems to provide better results than using total assets and equities.

In this study, we provide six complementary models of data envelopment analysis to analyze the financial efficiency of chosen decision-making units for firms listed on Tehran Stock Exchange. For this purpose, we consider tapered modeling, the concept of accounting costs and economic costs and divide the whole process into the two sub-processes in modeling. After the modeling process, we choose the seventeen companies and thereby, provide a new method for analyzing the financial efficiency. The proposed method seems to be more appropriate than the methods proposed in the past and it can deliver better understanding of real-world cases. Finally, we understand that how this method works for analyzing the financial efficiency of organizations.

Measuring the relative efficiency of banking industry has been a popular subject among both practitioners and academicians. Data envelopment analysis (DEA) has been widely applied for different purposes. This paper presents an empirical investigation to measure the relative efficiency of various banks located in province of Semnan, Iran. The proposed study uses DEA method to rank all units and using Anderson and Peterson method (1993) [Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39, 1261-1264], we provide some super efficiency for inefficient units. The study also provides reference numbers for inefficient units and gives some target values for all inefficient units.

There are many opportunities and challenges in the area of Indian technical education due to liberalization and globalization of economy. One of these challenges is how to assess the performance of technical institutions based on multiple criteria. The purpose of this paper is to describe and illustrate an application of a structured approach to determine relative performance and ranking of seven Indian Institutes of Technology (IITs) under multi-criteria environment. To evaluate the alternatives in respect to stakeholders’ preference we suggest a new methodology consisting of fuzzy AHP, DEA and TOPSIS. Fuzzy AHP technique is used to determine the weights of criteria and some linguistic terms are applied to assess performance under each criterion, then in order to determine the value of linguistic terms we use the data envelopment analysis (DEA) method. Finally TOPSIS method is used to aggregate performance scores under different criteria into an overall performance score for each institution and ranking the institution according to their overall performance score. The proposed fuzzy AHP–DEA–TOPSIS methodology is applicable to any multiple criteria decision making (MCDM) problem due to its generic nature.