Performance measurement plays an essential role on accelerating the efficiency of any organization. There are literally different methods for measuring the relative performance of a particular unit and many of them are involved considering various criteria. In this paper, we propose 360° feedback system for performance measurement of all employees who work for municipality of the city of Tabas located in east part of Iran. The proposed model of this paper also uses hierarchical method to cluster different attributes based on various characteristics and implements analytical hierarchy process to find the relative importance of all items. The survey uses five personal characteristics including cognitive, technical, personal and human skills and for each major item, the proposed model considers various sub-criteria. The results indicate that technical and cognitive skills are the most important personal characteristics followed by human and personal characteristics. The results of this survey show that responsibility and quality of work are the most important employee characteristics.

During the past five decades, there have been tremendous efforts to offer different methods for portfolio management. The primary objective of many of these methods is to provide a trade-off between risk and reward. The proposed study of this paper uses analytical hierarchy process (AHP) and grey relational analysis to offer a method for portfolio management. The proposed method of this paper uses a statistical sample consists of 16 firms whose shares were trading during the fiscal year of 2010 on Tehran Stock Exchange. The study uses AHP and gray relational analysis to assign weight to each firm. We also use a linear programming technique to model the resulted problem by considering some realistic constraints.

Measuring organization performance plays an important role for developing better strategic plans. In today & apos; s competitive environment, organizations attempt for the product quality or offering the service, delivery, reliability capability and the customer satisfaction. These properties are not measurable only by traditional financial criteria and we need a method, which could consider non-financial factors as well. The present study of this paper proposed a hybrid of balanced score card (BSC) and data envelopment analysis (DEA) method for an empirical study of banking sector. The study proposes a model for assessing the Tose`eTa`avon bank performance, which is an example of governmental credit and financial services institutes. The study determines different important factors associated with each four components of BSC and uses analytical hierarchy process to rank the measures. In each part of BSC implementation, we use DEA for ranking different units of bank and efficient and inefficient units are determined.

Information technology (IT) plays a vital role on developing different markets. In this paper, we study the impact of IT on developing businesses located mainly on free zones or in the borders of countries using analytical hierarchy process. The proposed study of this paper gathered the relative importance of five important factors influencing IT implementation. There are 12 experts and we use pairwise comparison to gather their insight and using Expert Choice we implement AHP for ranking the factors. The results indicate that management is the most important factor, followed by cultural and social items. The other factors including technical, investment and organization items are in lower degree of importance.

These days, one of primary concerns for residence of big cities is associated with the access on shopping centers. People prefer to live in places, which are close to their works, shopping centers and schools. Local governments also prefer to find the most appropriate places in an attempt to reduce unnecessary travels and traffic jams. In this paper, we present an empirical investigation to determine the most important factors influencing facility location for fruit and vegetable market in city of Tehran, Iran. The study has implemented two methods of analytical hierarchy process (AHP) and factor analysis for the investigation. The implementation of AHP has considered two main criteria including Geographic location of market and market, amenities and existing infrastructures. In terms of Geographic location of market, cost saving and public infrastructure are found to be the most important factors while in terms of market based factors, Space and availability of parking are the most important factors. We also use factor analysis and the results of our survey have indicated that Space and Ease of access were two most important factors, which must be considered for facility location.

Project selection is considered as the first essential part of project portfolio management. Project selection is also considered as a process to evaluate each project idea and chooses the one with the biggest priority. Project selection plays an essential role in the entire life cycle of different projects. This paper presents a survey for project selection using multiple criteria decision mak-ing techniques. The study considers 60 papers from over the period 1980-2017. The results of the survey have indicated that integration of Order of Preference by Similarity to Ideal Solution (TOPSIS) and analytical hierarchy process/analytical network process was the most popular techniques for project selection followed by VIKOR method.

Service quality plays an important role in health care systems since hospitals are responsible for people & apos; s lives. This study presents an effective approach for evaluating and comparing service qualities of four hospitals. Service quality consists of different attributes and many of them are intangible and difficult to measure. Therefore, we propose a fuzzy method to resolve the ambiguity of the concepts, which are associated with human judgments. SERVQUAL model is used to evaluate the respondents & apos; judgments of service quality and multi attribute decision making approach is implemented for the comparison among hospitals. The paper use analytical hierarchy process (AHP) for obtaining criteria weight and TOPSIS for ranking the cases.

One of the primary concerns on many countries is to determine different important factors affecting economic growth. In this paper, we study some factors such as unemployment rate, inflation ratio, population growth, average annual income, etc to cluster different countries. The proposed model of this paper uses analytical hierarchy process (AHP) to prioritize the criteria and then uses a K-mean technique to cluster 59 countries based on the ranked criteria into four groups. The first group includes countries with high standards such as Germany and Japan. In the second cluster, there are some developing countries with relatively good economic growth such as Saudi Arabia and Iran. The third cluster belongs to countries with faster rates of growth compared with the countries located in the second group such as China, India and Mexico. Finally, the fourth cluster includes countries with relatively very low rates of growth such as Jordan, Mali, Niger, etc.

Analytic Hierarchy Process (AHP) is one of the most popular approaches in the area of multiple attribute decision making (MADM). However, it is not practical any more if input information are fuzzy. In this paper, we propose a new method for fuzzy AHP which is especially useful to make decisions for multiple attribute problems. The method is developed by applying preference ratio concept which makes it practical since it assigns crisp weights and crisp scores to different alternatives. Two algorithms are proposed in this paper: The first one defines crisp and normalized weight by pairwise comparison with fuzzy data while the second one calculates fuzzy consistency ratio. The proposed method is applied to prioritize different short courses in a management school.