Understanding customers’ behavior normally helps planning better marketing strategies, which could lead to an increase in market share and profitability. Loyal customers are always considered as the most important assets for any firm. This paper presents a survey to detect factors influencing the formation of loyal customers’ mental image. The proposed study uses factor analysis to determine these factors by designing a questionnaire and distributing among some loyal customers who do banking business in Bank Melli Iran located in city of Tehran, Iran. The results indicate that there were eight important factors influencing customer loyalty including social status, business identity, brand strength, the contract role, organizational benefit, consumer rights, organizational image and supporting power.

Brand loyalty is one of the most important factors influencing on the success of retail stores. Many retail stores in the field of sport shoes in city of Tehran, Iran are facing tight competition and there seems to be that only stores with loyal customers could survive. In this paper, we present an exploration study to find out important factors influencing retail stores selling one of well-known sport shows such as Adidas, Nike, etc. in city of Tehran, Iran. The proposed study designs a questionnaire in Likert scale and distributes among 265 regular customers of these stores and analyze them using factor analysis. The results indicate that there were four important factors influencing customer loyalty including brand identification, brand promotion, brand loyalty and characterization of stores.

A very challenging issue in robot navigation or path planning in an unknown environment is to find a globally optimal path from the start to the target point at the same time avoid collisions. This paper presents a new sensor-based online method for generating collision-free optimal path for mobile robots to take a target amidst static obstacles. It is assumed that, target is static and the location of obstacles is completely unknown for robot and all of these materials will be calculated online. Although the area that is under vision of robot’s sensor is confined, we have to consider an inevitable assumption that target is detectable by robot in everywhere. Proposed algorithm to avoid colliding the obstacles in its way toward target, detects a short and feasible paths by utilizing an innovative and effective method. Following that, shortest of them to will be chosen for navigation. There are different important factors which are considered in robot motion planning problems. First, required time for robot’s action in unpredicted circumstances that the running time of the used algorithm plays a major role in this term. Second, the length of traveled path from start point to target point that represents the efficiency of exploited algorithm for leading the robot. The presented algorithm of this paper has proved its efficiency in both of mentioned issues. Simulation results show that traveled path has the least length and the running time is remarkably less than other presented algorithms until now. In addition, the effectiveness of presented algorithm in complex situation is discernible. These results prove that the presented novel and effective robot navigation algorithm is very suitable for real-time navigation in complex environments.

The evaluation of the most appropriate flexibility in the manufacturing sector is one of the strategic issues that may affect the Flexibile Manufacturing System (FMS). In this paper, a Multiple Attribute Decision Making Method (MADM) methodology is structured to resolve this problem. The two decision making methods, which are Simple Additive Weighting (SAW) and Weighted Product Method (WPM), are integrated with Analytical hierarchy process (AHP) in order to get the best use of information available. The aim of using AHP is to give the weights of the attributes and these weights are used in SAW & WPM method for ranking of flexibility in FMS. Furthermore, the method uses fuzzy logic to change the qualitative attributes into the quantitative attributes. 15 factors are taken to evaluation of 15 flexibility. In this report, we concluded that Product Flexibility has the most impact in 15 flexibilities and Programme Flexibility has the least impact in these 15 flexibilities by this methodology.

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.

There is an ongoing change on customers’ needs on selecting customers’ needs, which may influence requirements on designing products and services as well as export sale and company’s market shares in domestic and international market. In the present study, through descriptive approach with qualitative method and case study, we investigate important key factors influencing on new product development and products’ successive factors at overseas nutritional market. In addition by presenting a new model in accordance with the present condition of the organization we explore the closest product development model and affective factors influencing them. The study investigates 36 factors and extracts six important ones, which influence product development including intelligent information, process research and development, strategy introduced, participation strategy, market survey and differentiation strategy.

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.

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.

Ranking various alternatives has been under investigation and there are literally various methods and techniques for making a decision based on various criteria. One of the primary concerns on ranking methodologies such as analytical hierarchy process (AHP) is that decision makers cannot express his/her feeling in crisp form. Therefore, we need to use linguistic terms to receive the relative weights for comparing various alternatives. In this paper, we discuss ranking different alternatives based on the implementation of preference relation matrix based on intuitionistic fuzzy sets.