درخت حوزه‌های تخصصی

This study aimed to test the conceptual model on the causal relationship of motivation and consumption intention. To this end, 390 spectators who were present at the stadium, were randomly selected using stratified random sampling. They voluntarily completed Funk’s Motivation Scale and spectators’ consumption intention questionnaire. Structural Equation findings indicted a significantly positive relationship between the motivation and the consumption intentions among the spectators of Iran’s Premier Football League. There is a positive relationship between motivation and the components of consumption intention, including re-attendance, recommendation to others, purchase of team goods, and media consumption. The indices confirmed the optimal fit of the model. According to the results of the study, the authorities holding the Premier League matches as well as the clubs are recommended to have a detailed planning to enhance the motivation of the spectators as it had the greatest impact on re-attendance.

In this paper, a fractional multi- objective multi- product solid transportation problem with interval costs, supply, demand, and conveyances is investigated based on fuzzy programming approach. To minimize the problem, the order relations that represent the decision maker's (DM) performance between interval costs, supply, demand and conveyances are defined by the right limit, and the left limit. Through the deterministic problem is obtained, a fuzzy programming approach is applied by defining membership functions. A linear membership function is being used for obtaining optimal compromise solution. Finally, a numerical example is given to the utility of the approach.

The rapid development of communication technologies and information and online computers and their usage in processes of the industrial production have facilitated simultaneous monitoring of multiple variables (characteristics) in a process. In this work, we applied boosted decision tree and Monte Carlo simulation to propose an efficient method for detecting in-control and out-of-control states in multivariate control processes.In this work, four classifiers (methods) - , , , – are used for detecting the process control states. Then, with converting detection results these four classifiers, the boosted decision tree is made and provides the ultimate result as the in-control or the out-of-control states. To show how the proposed model works and the superiority of this method over , , , and methods, we run it on a standardized trivariate normal process. To compare and evaluate the performance of classifiers, we used ARL functions and the evaluation measures including Accuracy (ACC), Sensitivity (TPR), Specificity (SPC), and Precision (PPV). The findings not only showed the superiority of the proposed method over the tradition Chi-square but also confirmed former results on the efficiency of decision tree for rapid detecting of mean shifts in multivariate processes in which data are gathered automatically.

The present study is conducted to identify the components of the establishment of an ethical marketing system based on the Islamic-Iranian approach with emphasis on the food industry.In terms of its purpose it is a descriptive analytic type, and collects statistical data using a library methodology for research literature and Delphi method based on an expert opinion survey. In order to achieve the purpose, through an applied approach and through a survey method, a researcher-made questionnaire. Then, through the Delphi technique, which is a reliance on thought and use of expert knowledge and views and after three stages, the agreement and consensus of the Delphi group have reported on the components for the establishment of the ethical marketing system based on Islamic-Iranian approach. In order to consider the scientific and technical aspects, 30 experts in marketing system (marketing professors and experts in food industry marketing) were determined. Data analysis has been done with a mixed approach based on deep and structured studies and through content analysis. The results showed that social norms, organizational norms, green norms, individual norms, 4 ps norms and religious norms are among the requirements of establishing an ethical marketing system based on the Islamic-Iranian approach with emphasis on food industry. Standards and ethics in marketing approach is one of the most pressing issues for the review of the development and prosperity of Islamic countries. Adherence to such ethical practices can help to elevate the standards of behavior and thus of living, of traders and consumers alike. Selected key marketing issues are examined from an Islamic perspective which, it is argued, if adhered to, can help to create a value-loaded global ethical marketing framework for MNCs in general, and establish harmony and meaningful cooperation between international marketers and Muslim target markets in particular.

The purpose of this research was to provide a "Structural Equations Modeling Template" for the role of Human resources (HR) strategies on occupational performance development of colligate personnel. The current study is an applied research in terms of purpose, and a descriptive-analytical sample in terms of research method. The statistical population of this research included all employees Islamic Azad University of Shiraz Branch. The sampling method was "Random Classification". The standard questionnaire was used for data collection. By applying SMART PLS software, the research hypothesizes were made based on structural equations modeling & factor analysis .Findings showed that, there is a positive and significant relation between human resources development strategies and occupational performance of employees. Meanwhile, the HR development strategy, and employees' recruitment strategy have the greatest and the least impact on employees' occupational performance, respectively. The research findings showed importance of human resources strategies in evaluating occupational performance of employees. Therefore, HR strategies should be considered in Islamic Azad university of Shiraz.

Nowadays, organizational agility is a subject that its study has a significant impact on the growth and improvement of organizations. Present research in terms of purpose is applied and in terms of methodology is descriptive-exploratory. According to the theoretical hypotheses explained in the research, organizational, strategic, human, and technological factors were identified in this research as the factors explaining the organizational agility development model. The results obtained from the statistical analysis at the descriptive level demonstrated that average of organizational agility, human, organizational and strategic factors are greater than the average level and average of technological factors is at the average level. At the inferential level, which used confirmatory factor analysis, the results indicated that organizational, human, strategic, and technological factors are influential on the organizational agility development.

The main goal of this paper is to propose a new approach for efficiency measurement and ranking of stocks. Data envelopment analysis (DEA) is one of the popular and applicable techniques that can be used to reach this goal. However, there are always concerns about negative data and uncertainty in financial markets. Since the classical DEA models cannot deal with negative and imprecise values, in this paper, possibilistic range directional measure (PRDM) model is proposed to measure the efficiencies of stocks in the presence of negative data and uncertainty with input/output parameters. Using the data from insurance industry, this model is also implemented for a real case study of Tehran stock exchange (TSE) in order to analyse the performance of the proposed method.

Because in the theory of economics, the value of a company is based on the current value of future cash flows and profit is used as a substitute for cash flows, profit forecasting is of particular importance. In the research, the effect of rounding and revision in predicting earnings per share on the investors' attention in Iran has been investigated. After designing the investors' attention assessment indexes, the transaction information was collected from the Stock Exchange in the five-year period of 2011-2015. The statistical sample consists of 120 companies selected by systematic elimination method and totally obtained 600 year-firm. In this research, linear regression and correlation were used to investigate the hypotheses of the research and Eviews software was used to analyze the data and test the hypotheses. What can be said in the summing up and conclusion of the test of research hypotheses is that predicting the earning per share influences investors 'attention, as well as the revision of the earnings per share influences the investors' attention. On the other hand, research studies show that the rounding in interaction with the revision in predicting earnings per share can also affect the investors' attention.

Optimal working capital management can positively effect on the Firm performance, but this relationship can be affected by major characteristics of the firm, making an important subject for research. This research investigates the moderating role of firm characteristics on the relation between working capital management and financial performance of the firms listed in TSE during 2008 – 2017 period. Based on existing researches, three characters are considered as moderating variables in this research include firm size, debt ratio, and Governmental ownership. Financial performance and working capital management are measured using return on assets (ROA) and cash conversion cycle (CCC), respectively. We use from multivariate regression model with panel data for test of research hypotheses. The Results of this study show that, firm size affects the Relation between CCC (as a measure of working capital management) and ROA (as a measure of firm performance). However, debt ratio and Governmental ownership don’t any significant effect on the relationship between working capital management and financial performance of firms

Venture capital companies play an important role in the economy of countries and greatly influences economic and employment growth. VC is the provision of capital for companies and entrepreneurs that is prone to leaping and growing value and, of course, a lot of risk. However, the volume of venture capital in our country is far less than the economic capacity. Many of analysts consider having no model for venture capital in our country as the main reason for this. Therefore, the present study by the qualitative method aims to design decision-making native model for selecting venture capital investment in emerging companies. To achieve this goal, by collecting qualitative data through literature reviews and having deep interview with experts and venture capital firms, a native decision-making model for selecting venture capital in emerging companies is presented. The methodology of this research based on purpose, is fundamental and through the qualitative methods, thematic analysis method is used. Purposeful sampling method is used and interviewing experts continued to theoretical saturation level that means the number of selected samples includes 16 elites. The native decision-making model for selecting venture capital in emerging companies presented in this research has 16 main themes and 86 sub-themes.

Improving return forecasting is very important for both investors and researchers in financial markets. In this study we try to aim this object by two new methods. First, instead of using traditional variable, gold prices have been used as predictor and compare the results with Goyal's variables. Second, unlike previous researches new machine learning algorithm called Deep learning (DP) has been used to improve return forecasting and then compare the results with historical average methods as bench mark model and use Diebold and Mariano’s and West’s statistic (DMW) for statistical evaluation. Results indicate that the applied DP model has higher accuracy compared to historical average model. It also indicates that out of sample prediction improvement does not always depend on high input variables numbers. On the other hand when using gold price as input variables, it is possible to improve this forecasting capability. Result also indicate that gold price has better accuracy than Goyal's variable to predicting out of sample return.