This paper presents the application of the new method in the process of making the decisions on the scooters selection. The Fuzzy AHP method was used to obtain the weight coefficients of criteria, on the basis of which the alternatives were evaluated. The selection of criteria for evaluating scooters was based on an analysis of available manufacturer website. The evaluation and selection of scooters was carried out using a new multi-criteria decision making (MCDM) method. The present study tries to identify the attributes like kerb weight, mileage, top speed, fuel tank capacity and price playing prominent role in the buying behavior of the working women while purchasing scooters. Fuzzy-AHP method has been used to obtain the relative weights of the criteria, on the basis of which the alternatives are evaluated using new MCDM. The TOPSIS and MABAC methods were tested under the same conditions. The stability of the result obtained by this method is established through a sensitivity analysis.

One of the primary concerns in banking industry is to measure the relative importance of banking industry using popular multi criteria decision making (MCDM) techniques such as data envelopment analysis (DEA) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In this paper, we use these two MCDM techniques to measure the relative efficiencies of 16 private and governmental banks in terms of electronic payment. There are three inputs with DEA methods including the number of issued cards, the number of ATM machines and the number of POSs and there are two outputs including the number of successful ATMs and the number of successful POSs transactions. The proposed study of this paper uses the necessary data of one of Iranian provinces and the results of the implementation of DEA and TOPSIS have indicated that 9 out of 16 banks were efficient. Our study also indicates that mean of relative efficiency for private banks was 82% while this number was 75% for governmental banks.

Decisions related to acceptance or rejection of orders play an important role in companies engaged in make-to-order production. The incoming orders have a specific delivery date by which the customer expects the due date to be met and the order delivered. In some cases the level of input orders exceeds beyond the existing capacity. In such situations the main concern is to decide which orders must be accepted and which ones rejected taking into account the available production capacity. This paper prioritises the input orders according to a comprehensive and systematic multi criteria decision making (MCDM) model. It then proceeds with making decisions to either accept or reject orders according to the calculated prioritises and production constraints. Ultimately the optimum list of orders for acceptance is determined. The proposed model is a combination of two techniques of Fuzzy Analytical Hierarchy Process (FAHP) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). In this model FAHP is used to determine the weights of criteria and TOPSIS is used for prioritizing the orders. Finally the proposed model is tested for its efficiency by application to a real case.

Decision-making process is an integral part of every sporting event across the globe. This process uses inputs from single to multi-decision makers. To make a sporting event a success, appropriate decision making needs to be made starting from hosting-right to the end of the event. Thus, this study presents a framework that scientifically determines the hosting-right for a sporting event. The framework is based on techno-economic analysis of potential hosting locations for a sporting event. Techno-economic criteria are analysed using fuzzy TOPSIS (technique for order preference by similarity to ideal solution) method. The analysis of the hosting-right is also performed through technical, economic, techno-economic and cost-benefit ratio perspectives. A case study of national sports festival in Nigeria is used to demonstrate the applicability of the proposed framework. Twelve technical and eight economic criteria are considered in the proposed framework. Six loca-tions are considered during the implementation of the proposed framework. The results obtained show that the issue of hosting-right award depends on the evaluation criteria that are considered by decision-makers.

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.

For years, tangible assets used to be the most important precious wealth of organizations. However, the recent advances in technology has changed this concept and today, intangible assets such as human resources, customers, processes are playing essential roles on making strategies. In this paper, we present a study to setup appropriate strategies using the implementation of balanced score card in four perspectives of customers, processes, learning and financial. The proposed study of this paper gathers important factors through three different brainstorming sessions and prioritize them using TOPSIS method. Based on the results of MCDM technique, selecting appropriate target market for penetration is the number one priority followed by having good accounting system and preparing for more diversified production. These are the most important items influencing strategic planning. Therefore, the study uses BSC for the first two important strategies and discusses possible actions for productivity improvement.

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).

One of the primary questions in asset management is to find good combinations of different assets and this has been an interesting area of research for over half a century. The proposed model of this paper uses decision makers & apos; feedbacks based on multiple criteria decision making technique to find an appropriate portfolio. We first select some important financial criteria and then using decision makers & apos; opinions and by implementation of some fuzzy network analysis we find appropriate weights of the asset. The proposed model uses two multiple criteria techniques namely TOPSIS and VIKOR and the model is examined for some real-world data from Tehran Stock Exchange. The results of the implementation of the proposed model have been examined against Markowitz traditional model. The preliminary results indicate that the proposed model of this paper performs reasonably well compared with alternative method.

In this study, the efficiency of integration between Taguchi and TOPSIS in multi-response optimi-zation of powder mixed electrical discharge machining (PMEDM) process was evaluated. The in-put parameters, such as workpiece and tool electrode material, polarity, pulse on time (ton), pulse off time (toff), Current (I) and powder concentration have been selected to optimize two responses; namely surface roughness (Ra) and surface hardness (HV). The results show that titanium powder mixed dielectric fluid improves multi-response optimization efficiency in PMEDM. In addition, machining conditions, such as tool electrode material, powder concentration, pulse on time, polarity, current density, A×G and B×G interactions play a very important role on S/N ratio of C* whereby powder concentration has the strongest influence. TOPSIS -Taguchi is a potential method for multi-response optimization in PMEDM. However, the optimal results using ANOVA analysis show that there is a necessity to have more studies in TOPSIS-Taguchi to improve the in-tegration efficiency between two methods for optimizing multiple responses in PMEDM.