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.

Supplier selection is one of the most important decisions made in supply chain management. Supplier evaluation problem has been in the center of supply chain researcher’s attention in these years. Managers regard some of these studies and methods inappropriate due to simple, weight scoring methods that generally are based on subjective opinions and judgments of decision maker units involved in the supplier evaluation process yielding imprecise and even unreliable results. This paper seeks to propose a methodology to integrate data envelopment analysis (DEA) and group analytical hierarchy process (GAHP) for evaluating and selecting the most efficient supplier. We develop a methodology, which consists of 6 steps, one by one has been introduced in lecture and finally applicability of proposed method is indicated by assessing 12 suppliers in a numerical example.

Tourism industry is one of the most important low carbon industries and it can provide good opportunities for developing countries to take advantage of their natural attractions such as historical monuments, culture, etc. to create value added. However, there are always some barriers in front of developing this industry and a good strategy could help it develop faster. There are different methods for strategic planning and SWOT matrix is one of the most popular one. In this paper, we present an empirical survey to find the most important and strategic items for developing tourism industry in Iran. The proposed study designed a questionnaire and distributed it among 384 tourists who were visiting Iran in a three months period of year 2011. The information gathered were analyzed using factor analysis and structural equation modeling. There are seven important factors involved in developing tourism industry. The first factor, price and having sufficient infrastructures, is the most important factor according to our survey representing 14.623 percents of the changes. The second factor is associated with political and international affairs, which represents 13.926 percents of the changes. The third factor is associated with culture and civilization attractiveness representing 9.342 percent of changes on tourism. The fourth factor is natural attractiveness representing 6.691 percent of the changes. The fifth factor is related to economical factor representing 5.632, the sixth factor, human resources, represents 5.353 percent of the changes and finally the last factor is related to diversity of creatures, which represents 4.749. These factors include 60.3 percent of the success of tourism.

The purpose of this paper is to study the effect of "emotional intelligence" on "organizational learning" among employees who work for Jihad Agriculture organization of Isfahan. The statistical population includes 500 employees of the organization and a sample of 217 people are selected from these people using Morgan statistical tables for a period of 6 months of second half of 2011. Therefore, the research method is descriptive- survey, the type of correlation. For data collection the Wesinger Emotional Intelligence Questionnaire and organizational learning questionnaire was used. Validity of the questionnaire was confirmed by a number of university professors. The reliability was obtained with Cronbach & apos; s alpha coefficient for the first questionnaire, 0.813 and for the second questionnaire, 0.786. By using Correlation coefficient and multiple Regressions by SPSS software the data were analyzed. Results in a significant level of 99% showed that emotional intelligence had a significant effect on organizational learning.

Every day in workplaces, continues events occur that cause death and injury. These accidents usually happen because of lack of exploring the potential hazards and lack of training of employees. Hence, with exploring and evaluating the hazards of workplace and utilizing the suitable procedures, it is possible to prevent from many of these hazardous incidents. Exploring, evaluating and controlling the potential hazards have been the initial stages of scientific safety assurance in every system. Preliminary hazard analyzing is the first effort in analyzing hazards. In this method, usual hazards in sighted job are explored, using the usual hazards table for developing the basis of PHA, the PHA checklist is prepared and at last the PHA table completed and the appropriate suggestions are given. In this paper, we present an implementation of PHA method in one of industries located in city of Tehran, Iran. The proposed study uses 15 explored hazards, where 2 are unacceptable, 9 are undesirable and 4 are acceptable with need of revisal. By eliminating and reducing each hazards risk, some controlling solutions are suggested. The most important of these solutions are utilizing and using the regulations of the welding with electrical archer.

This paper presents an empirical study on measuring the effects of fiscal policy in terms of government spending on private consumption in both recession and booms over the period of 1965-2010. The proposed study uses Hodric-Prescott filter to find the cycle of recessions and booms. Then, we use autoregressive distributed lag model to estimate the changes. The results of this survey indicate that, in long term, an increase on government expenditures normally impacts private sector positively in both recessions and booms. The impact in short terms is positive during the recessions but during the booming session, there is no meaningful relationship between government spending and private spending.

Quality Function Deployment (QFD) as one of the quality engineering methods; originates from market study and product or service customers identification, where by determining their needs; tries to involve them in all stages of product or service development. This study uses QFD method to apply customers’ criteria in production of Coach Plasma in Mashhad`s Sahateb Company. Coach Plasma is used for healthy bloodletting. The proposed study of this paper designed and distributed a questionnaire, which includes identification & determination of customers’ needs and investigation of their satisfaction of manufactured products, while looking for technical and engineering characteristics related to their needs. The Coach Plasma costumers are categorized into two groups of local and external customers. Data collection was done based on available documents, experts opinions, structured interview with managers and questionnaire. Customers’ needs were studied in QFD teams. Collecting essential information such as needs importance degree and competitive benchmarking of customer`s needs, the weight of each need has been evaluated. In this research, House of Quality was used from first matrix of QFD leading to estimation of engineering & technical characteristics in order to enter to the quality deployment matrix. Take a look at obtained results, we could mention the role of each of these external factors in satisfaction of Sahateb Company customers and technical characteristics of the company in providing these factors and the prioritization of the customer & apos; s needs.

This study examines the relationship between earnings management and information asymmetry based on some companies listed in Tehran Stock Exchange over the period of 2005-2010. The study only uses qualified samples by taking into account all limitations and necessary criteria. Based on the results of this survey, we can conclude that there is not a significant relationship between earning management and information asymmetry in Tehran Stock Exchange. There is also not a significant relationship between low or high earning management and information asymmetry. Estimated dividend announcement has information content and it can influence on information asymmetry. Finally, in Tehran Stock Exchange, there is information asymmetry and after dividend announcement, its value is more than before.

Ranking insurance firms plays an important role on choosing the most appropriate company for receiving appropriate services especially long term insurances such as life insurances. The proposed model of this paper uses two well-known methods of CAMELS and RBC to rank 18 active private and governmental insurance firms in Iran over the period of 2009-2011. The results of Spearman test imply that there is no meaningful difference between these two methods for year 2010 and year 2011 and according to Freedman test, there is not meaningful difference between these two methods in any three years of 2009, 2010 and 2011. In summary, we can conclude that the results of both methods could be used in practice.

Autoregressive moving average (ARMA) process and dynamic neural networks namely the nonlinear autoregressive moving average with exogenous inputs (NARX) are compared by evaluating their ability to predict financial time series; for instance the S & P500 returns. Two classes of ARMA are considered. The first one is the standard ARMA model which is a linear static system. The second one uses Kalman filter (KF) to estimate and predict ARMA coefficients. This model is a linear dynamic system. The forecasting ability of each system is evaluated by means of mean absolute error (MAE) and mean absolute deviation (MAD) statistics. Simulation results indicate that the ARMA-KF system performs better than the standard ARMA alone. Thus, introducing dynamics into the ARMA process improves the forecasting accuracy. In addition, the ARMA-KF outperformed the NARX. This result may suggest that the linear component found in the S & P500 return series is more dominant than the nonlinear part. In sum, we conclude that introducing dynamics into the ARMA process provides an effective system for S & P500 time series prediction.