درخت حوزه‌های تخصصی

This research has been conducted with the aim of investigating the effect of social factors on the development of rural ecotourism entrepreneurship in Dezful tourism villages. This research is a descriptive-correlation type that was conducted using a survey method. Residents of tourism villages of Dezful constitute the statistical population of this research, based on the Cochrane formula and the use of stratified random sampling, 381 households were selected as the research sample.The main tool of this research is a researcher-made questionnaire whose validity and reliability were tested and confirmed. In order to analyze data and test research hypotheses, structural equation modeling with partial least squares approach and PLS Smart software have been used. The findings showed that networking in the village, social participation, education and information, social capital and tourism capacities explain a total of 62.5% of the changes related to the rural ecotourism entrepreneurship. From this research, it can be concluded that social factors are always effective in the growth or retardation of rural ecotourism entrepreneurship according to their collective and cultural potential, and along with economic, historical, cultural and political factors, they can help the development of rural ecotourism entrepreneurship

The main role of financial reporting in capital markets is to provide the necessary conditions for the optimal allocation of resources and making correct and timely decisions. Achieving this goal is possible if the financial statements are consistent with economic realities or even have the slightest deviation from economic performance. However, over the past few decades, fraud detected in corporate financial reporting has increased the risk of financial reporting. Therefore, the current paper aims at investigating the impact of internal control weaknesses on financial reporting risk in companies listed on the Tehran Stock Exchange. In order to achieve the purpose of the research, using the method of systematic elimination of information related to 143 companies among the companies listed on the Tehran Stock Exchange in the period from 2009 to 2019 was collected. A multivariate regression model based on composite data was used to test the research hypothesis. The research findings show the significant positive impact of internal control weaknesses on financial reporting risk. The results indicate that reducing the weaknesses of internal control can reduce the risk of financial reporting and reduce information asymmetry and consequently improve accountability processes.

Many studies have been conducted in the field of bankruptcy prediction; But in most of them only financial ratios are used. However, in Iran, many non-financial factors affect bankruptcy. The main purpose of this study is to develop a mathematical model in which financial and non-financial indicators such as management and economics factors are used to predict bankruptcy. In this study, 44 variables that had the greatest impact on bankruptcy forecast were selected and with confirmatory factor analysis, a questionnaire was developed and sent to experts in the fields of management, accounting and economics to rank the impact of these variables. The statistical sample of the study includes 200 bankrupt and non-bankrupt companies listed in the period 2009-2018. After collecting the questionnaires using the OLS regression estimation method, the variables that had a factor load of less than 0.5 were eliminated and in the final model 9 main variables. The research model identified 95% of bankrupt companies and 93% of non-bankrupt companies with 95.4% confidence. Then, for verification, two hypotheses were developed and the model of this research was compared with two existing models. The ability to distinguish bankrupt companies from non-bankrupt ones by our proposed model was 6% more accurate than the Pourheidari et al. model, and 9.4% more accurate than Altman’s model.

This research, in line with the strategy of the World Customs Organization, order to provide a structural model for improving the ethics and administrative health of employees based on the use of information technology in customs affairs with a combined approach of fundamental theory and interpretive structural modeling to understand how information technology affects ethics and Administrative health and investigating the power of influence and the degree of dependence of the variables of ethics and administrative health of employees in the form of drawing a comprehensive structuring model. In the implementation of this research, a mixed method was used in the qualitative part of the foundation's data theory according to the research needs and structured interviews were used to collect data. To collect data in a qualitative method, with the help of Maxqda software, research findings through the opinions of 13 experts in three stages of open-centered and selective coding in the form of 6 categories affecting the ethics and administrative health of employees in the form of the Strauss paradigm model and Corbin and it was expressed theoretically. After building the theory, in the quantitative stage, interpretive structural modeling has been used in order to understand the relationship between the variables and the leveling of the promotion of ethics and administrative health of Iran Customs. The results of the research show that the variable "use of smart technologies" is the first level variable in the promotion of ethics and health, and the variables "Analysis of the situation of manpower and customs processes, ethical characteristics of employees and laws and management of information technology and human resources" » is the second level variable. And the variables of "conditions and structure of the organization and the requirements and infrastructure of information technology" are the variables of the third level.

The purpose of this study was to present an optimal model Predicting Future Cash Flows optimized neural network with genetic (ANN+GA) and particle swarm algorithms (ANN+PSO). In this study, due to the nonlinear relationship among accounting information, we have tried to predict future cash flows by combining artificial intelligence algorithms. Variables of accruals components and operating cash flows were employed to investigate this prediction; therefore, the data of 137 companies listed in Tehran Stock Exchange during (2009-2017) were analysed. The results of this study showed that both neural network models optimized by genetic and particle swarm algorithms with all variables presented in this study (with 15 predictor variables) are able to provide an optimal model Predicting Future Cash Flows. The results of fitting models also showed that neural network optimized with particle swarm algorithm (ANN+PSO) has lower error coefficient (better efficiency and higher prediction accuracy) than neural network optimized with ge-netic algorithms (ANN+GA).

In the 21st century, the meaning of places is essential to people. Meanings have gained symbolic importance through tourism heritage. Tourism is a powerful force  in shaping the world and our understanding of different cultures, people, and  places. This research investigates the complexities of religious tourism and the  management of religious destinations. It obtains criteria for managing religious  goals with a detailed look and uses the descriptive-analytical method based on  library documents and the opinion of research experts. Then, using research experts  and ISM-PLS hybrid approach, a three-level framework for managing religious  goals in Yazd city has been presented and analyzed. The results showed that the  government's decisions and actions were the most effective criteria. The ultimate  goal was to create a sense of trust and security among religious tourists. It is hoped  that the findings of this research will be a starting point for managing religious  tourism destinations and a guide for examining the complexities of Islamic tourism  destinations and their management.