Intellectual capital is a type of asset measuring ability of economic agency in order tomake wealth. These assets do not have physical and objective nature and are intangible assets being achieved through utilization of relative assets with human resources, organizational operation and foreign relations from economic agency. Measuring this issue is important from intra-organizational and extra-organizational views. In this paper, we present survey based on Fuzzy TOPSIS to find important factors influencing intellectual capital management. The proposed model of this paper considers different factors, which exist in the literature and prioritize them based on different criteria. The results of our survey identified seven items as the most influencing factors.

One of the most important issues affecting profitability is to determine the impact of different factors influencing purchasing activities. In this paper, we perform an extensive literature survey to detect different purchasing factors influencing customers & apos; behavior. The factors are categorized in three different groups and they are ranked using analytical network process. The results of our survey indicate that three factors of personal, product and situational play important roles in purchasing impulse. The personal item includes different factors where demographic characteristic factors receive the highest ranking (35%) followed by other factors are feelings, excitement and fun, self identify, education and novelty. There are also three sub-factors associated with demographic characteristics including gender, age and race and the weights are 0.46748, 0.42668 and 0.10584, respectively, which means gender is the most important factor followed by age and race. Finally, the other factor is associated with situational factors & apos; group, which includes presence of others, culture, design of store, time available, local market condition, sales staff and self service with the relative importance of 0.04296, 0.08733, 0.12130, 0.22217, 0.05643, 0.15346 and 0.31635, respectively.

Clustering plays an important role on developing industries, since business units can take advantage of many existing industries for trouble shooting or sharing their experiences to increase efficiency. One of the primary concerns for developing clustering is to identify and remove important barriers. In this paper, we gather experts' feedbacks on forming clustering in Iran's industries and, using analytical network process, we prioritize the important factors and provide some necessary guidelines to develop clustering. The results of this paper indicate that the existence of a supplier network is the most important factor, followed by the existence of competition between operational units, existence of high-risk investors, existence of suitable infrastructures. There are also other less important criteria including the existence of flexibility, suitable technology and competition, governmental regularities, social background, trust, etc.

The idea of Science and Technology parks has been widely used in many countries and many innovative plans are initiated in these places. In this paper, we present a multiple criteria decision making plan to prioritize important factors influencing the success of an innovative plan. The study uses fuzzy triangular numbers to gather decision makers & apos; feedback on different criteria and rank them using fuzzy VIKOR method. The results of our survey indicate that it is important to be the first who introduce the idea, the idea must be important for customers and market and it must be scientifically justified. Among other important criteria, the availability of experts to support the ideas and applicability in the area of human and social science are of important criteria. The plan also does not need to have huge amount of investment and a complicated technology and finally it should come to market in short amount of time.

Today automotive companies must pioneer in strategies such as the agile supply chain for competition and various demands of customers. Considering the importance of agile in choosing a supplier at the supply chain, this study tries to identify and evaluate agile activities in SAPCO Company suppliers. Then, using principal component analysis of factor analysis, a number of related activities are divided into smaller groups called factor. The results are used by SAPCO to determine agile patterns in selecting a supplier with emphasis on similarities and differences and create agile portfolio. The study can help SAPCO identify criteria and making decision in the field of agile at suppliers.

Aviation fuel of aircrafts is one of the most important and predominant expenditures in air companies. The recent jump on petroleum price has increased the price of equipments and maintenance. Therefore, many aircraft companies look for different ways to reduce their expenditures as much as they can. In this article, we study effective factors to reduce the fuel consumption. The proposed study of this paper gathers different criteria, which are important for cost reduction plans based on experts & apos; point of view. We take advantages of quantitative and qualitative characteristics of criteria and experts & apos; ideas using fuzzy decision making. Finally, a list of effective factors to reduce the fuel consumption is presented based on order of their importance.

The aim of this research is to present a hybrid model to select auto part suppliers. The proposed method of this paper uses factor analysis to find the most influencing factors on part maker selection and the results are validated using different statistical tests such as Cronbach & apos; s Alpha and Kaiser-Meyer. The hybrid model uses analytical network process to rank different part maker suppliers and fuzzy goal programming to choose the appropriate alternative among various choices. The implementation of the proposed model of this paper is used for a case study of real-world problem and the results are discussed.

Product selection is always one of the troubles that decision makers are facing with it. Correct selection requires having suitable method for this important issue. In this article, we concern to introduce an approach of fuzzy decision making for selection to decision makers. The nature of decision making is usually complex and without structure. Totally, most of qualitative and quantitative factors such as quality, price, and flexibility should be concerned for determining a suitable product. In this study, it is attempted to use recent advances in ranking methods for product selection. The proposed study uses oral preferences language shown in terms of triangular and trapezoid fuzzy numbers. Then, a multi criteria hierarchical decision making is suggested on the basis of fuzzy collection theory for product selection where the proposed fuzzy VIKOR uses different qualitative and quantitative criteria.