درخت حوزه‌های تخصصی

The study aims to investigate the relationship between the financial incentives of board members and disclosure of corporate risk, emphasizing the levels of corporate performance and risk in Iran. The research sample includes 98 listed firms in Tehran Stock Exchange during 2011-2015 (490 years-firms); the firms have selected by using a systematic removal method. Regarding the aim, the present research is classified as an applied research and concerning its method, it is categorized as a descriptive research. The research hypotheses are examined using the linear regression testing method; Eviews software has employed for data analysis and hypotheses testing. Based on the regression results, financial incentives of board members are effective on the quality and extend of firm’s risk disclosure.

Stock trend forecasting is a one of the main factors in choosing the best investment, hence prediction and comparison of different firms’ stock trend is one method for improving investment process. Stockholders need information for forecasting firm’s stock trend in order to make decision about firms’ stock trading. In this study stock trend, forecasting performs by data mining algorithm. It should mention that this research has two hypotheses. It aimed at being practical and it is correlation methodology. The research performed in deductive reasoning. Hypotheses analyzed based on collected data from 180 firms listed in Tehran stock exchange during 2009-2015. Results indicated that algorithms are able to forecast negative stock return. However, random forest algorithm is more powerful than decision tree algorithm. In addition, stock return from last three years and selling growth are the main variables of negative stock return forecasting.

Nowadays Iran’s position on the international corridors, the loss of Iran's roads accidents and the emergence of environmental and energy issues, have made the development of transportation in Iran a prerequisite. The purpose of this research is to identify the effective factors on the he high speed train technology transfer and provide t its framework. Data collection has been done with library and field studies. After these stages, from 73 extracted indicators, 54 main indicators were selected by the experts of the rail transportation technology field. According to these indices, the research questionnaire was designed and distributed. Finally, after completion of the questionnaires by 37 experts in the technology transfer field, the collected data were analysed using structural equations and PLS Smart software and the research model was fitted. The 49 indicators were accepted in 3 factors and 8 dimensions for the designed model. Also the results indicate that in the selecting and acquiring technology factor,the technology selection ranked first, the technology acquisition ranked second and technology recognition ranked third and in the Deployment factor, the technology adaptation and localization,the technology absorption and analysis and technology exploitation dimensions were ranked first to third respectively and in the maintaining factor, the technology development and improvement and technology diffusion dimensions ranked first and second respectively.

This study analyzes the relationships among quality of life, workaholism and psychological capital. The sample of the study consists of 212 registered employees of Shahid Dr. Beheshtei Hospital in Shiraz. Subjects have been selected using convenience sampling. World Health Organization Quality of life Questionnaire, Luthans psychological capital questionnaire and workaholism analysis questionnaire (Samani and Ahmadi) have been used in the present study. The research shows that there is a significant relationship between psychological capital and quality of life components while workaholism is not related to quality of life components. It is concluded that workaholism cannot predict quality of life components whereas psychological capital components predict quality of life components significantly.