Performance measurement plays essential role on improving the performance of business units and their efficiencies. During the past few years, there have been tremendous development in banking systems and the primary focus of many managers is to improve the quality of services for market retention. Performance measurement in banking industry is normally involved with various qualitative as well as quantitative criteria, which leads to the implementation of multiple criteria decision making techniques. This paper presents a hybrid grey relational analysis and K-means to cluster and measure the performance of banking system. The proposed study uses different criteria, clusters banks into various segments and ranks 43 different banks in city of Semnan, Iran.

Flexibility has been cited as a key factor to enhance the performance of flexible manufacturing sys-tem (FMS). The main aim of this paper is to rank the flexibility of FMS. The ranking decisions are complex in the manufacturing field to analyze a number of alternatives based on a set of some attributes. In this research, two MADM methods i.e. MOORA (i.e. multi-objective optimization on the basis of ratio analysis) and weighted Euclidean distance based approach (WEDBA) are used for ranking of flexibility in FMS for new part development. MOORA approach can give de-cision with or without considering relative importance of attributes i.e. attribute weights. While in WEDBA, integrated attribute weights are used for evaluation which included the subjective and objective weights of attributes. Objective weights are calculated by entropy method and subjective weights are calculated by analytic hierarchy process. MOORA is applied in two ways i.e. ratio based and reference point analysis. Ranking of fifteen flexibility of FMS done on the basis fifteen variables which effect flexibility of FMS. The results of MOORA and WEDBA approach shows that product flexibility has the top most flexibility in fifteen flexibilities and programme flexibility has the least impact in fifteen flexibilities.

For many years, investors used some basic financial ratios to measure the relative performance of various active industries based on two-digit ISIC classification. However, direct implementation of basic financial figures may not be practical in today & apos; s business environment since investors face with different criteria. The proposed model of this paper uses Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to compare 37 various industries based on different financial figures. We gather the necessary data over the period of 2009-2010 from Tehran Stock Exchange and investigate the data in two stages. In the first stage, we perform fundamental analysis to select the most appropriate firms and the in the second stage, we use TOPSIS to rank selected firms based on different criteria. The results of the study confirm that information and communication technology, which is one of the biggest firms in this exchange is considered as the best option (relative ranking 0.88 in two years) followed by some Cement industry (with relative ranking of 0.26 in 2009 and 0.19 in 2010) and oil refinery units (with relative ranking of 0.23 in 2009 and 0.19 in 2010). The figure also shows that other firms maintain low ratios varied from 0.23 to 0.01. The lowest industry ranking belongs to marine industry.

During the past few years, there has been increasing interest to find a replacement for gas consumption in Iranian small towns and cities. The government believes delivering cheap gas to small towns is not economical and can be replaced with recent technological solar–geothermal hybrid energy system. In this paper, we present an empirical study to calculate internal rate of return (IRR) for a small town located near the city of Qom, Iran. We consider three scenarios of population, namely 1000, 1500 and 2000 households and various rates for gas price from 7 to 40 cents. The results show that a gas distribution unit yields 2% to 20% in terms of return. This brings us to conclude that gas distribution for small towns far from major cities is not economically justified for government. Therefore, we need to use alternative methods such as solar–geothermal hybrid energy system. We use TOPSIS method, as a multi criteria decision making approach, to prioritize ten small towns in Qom province and the results are analyzed.

Performance measurement plays an essential role on management of governmental agencies especially when profitability is not the primary concern and we need to consider other important factors than profitability such as customer satisfaction, etc. In this paper, we propose a multi-criteria decision making method to rank different national Iranian oil refining and distribution companies. The proposed study of this paper uses six factors including per capita supply, energy cost, physical productivity of labor, staff participation, quality control inspection of stations and education per capita. The proposed study uses Entropy to find the relative importance of each criterion and TOPSIS to rank 37 alternatives based on cities and three regions. The results of the implementation of our method indicate that central regions close to capital city of the country maintains the highest ranking (0.9122) while southern regions maintains the lowest comes in the lowest priority (0.0569) and the northern region is in the middle (0.7635).

The purpose of this paper is to determine comparative ranking of agricultural development in different provinces of Iran using taxonomy technique. The independent variables are amount of annual rainfall amount, the number of permanent rivers, the width of pastures and forest, cultivated level of agricultural harvests and garden harvests, number of beehives, the number of fish farming ranches, the number of tractors and combines, the number of cooperative production societies, the number of industrial cattle breeding and aviculture. The results indicate that the maximum development coefficient value is associated with Razavi Khorasan province followed by Mazandaran, East Azarbayjan while the minimum ranking value belongs to Bushehr province.

This paper presents an empirical investigation to measure the performance of a mining firm in province of Semnan, Iran based on fuzzy fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) technique. The proposed study of this paper uses strength, weakness, opportunity and threat (SWOT) technique to analyze the firm and using DEMATEL rank various items based on their relative importance. Based on the results of our survey, cost reduction and increase investment in mining sector are the most important components of this survey. The study also compares the results with similar study, which has recently been accomplished and we believe the proposed model is capable of detecting possible threats and helping us provide possible actions.

Ranking industry normally helps find hot sectors and attract potential investors to invest in appropriate plans. Ranking various industries is also a multiple criteria decision making problem. In this paper, we present an empirical investigation to rank different industries using the art of data envelopment analysis (DEA). The inputs of our proposed DEA model include capital, employment and importance coefficient and outputs are exports, ecological effects and added value. In addition, exports, value added and environmental investment are used as outputs of DEA method. Since the results of DEA may consider more than one efficient unit, so we implement Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique to rank efficient units. In our case study, there were 15 different sectors from various industries and the implementation of DEA technique recommends 8 efficient units. The implementation of TOPSIS among these efficient units has suggested that Chemical industry could be considered as the most attracting industry for investment.

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.