مطالب

investors and managers are always faced with uncertainty in the information environment, which uncertainty can be due to factors such as the synchronization of stock returns, extraordinary fluctuations in stock returns and the number of equations. The purpose of this study is to investigate the political uncertainty caused by the size of the firm under the influence of risky information environment, the irregular behavior of accruals anomaly and the anomaly behavior of the cost of normal stock equity of companies. For this purpose, the data of 99 companies listed on the Tehran Stock Exchange and Iran TSETMC during the years 2009 to 2019 were examined and tested through combined data. The results showed that the political uncertainty caused by the firm size affected the concurrency stock returns with the optional accrual anomaly behavior and the cost of normal stock equity behavior of companies has a positive and signification relationship. The results also showed that the political uncertainty caused by the firm size is affected by the extraordinary fluctuation of stock returns with the optional accrual anomaly behavior and the cost of normal stock equity behavior of companies has a positive and signification relationship. In addition, the political uncertainty caused by the firm size is affected by the number of equations with the optional accrual anomaly behavior and the cost of normal stock equity behavior of companies has a positive and signification relationship.

The Analytic visualization suggests representing knowledge during a visual type that may be charts, graphs, lists, or maps. The COVID 19 detection and analysis of spreading is very important for countries. Database management with respect to virus deep analysis is a critical task to the researcher through conventional algorithms. The RNA, DNA, and biological data are helping to the bio-inspired algorithm but its implementation can be complex by software tools. Therefore, an effective technique is required to cross over the above limitations. So that covid 19 pandemic data analysis is performed through FCNN (Fully conventional Neural Network) pre-training network. The dataset is collected from social media, Kaggle, and GitHub databases. At 1st stage, the auto stack encoding process is applied later same data is processed with FCNN deep learning classifier. In this research work, covid-pandemic affects parameters like infected persons, deaths, active cases, and recovering cases. The FCNN is take care of feature extraction, training, testing, and classification. Finally using a confusion matrix accuracy of 98.34%, sensitivity 97.63%, Recall 98.26%, and F measure 98.83% had been estimated.

Greenwashing is considered as a deliberate and conscious deception of the consumer in relation to the environmental activities of an organization or the environmental benefits of a product, which has adverse consequences for various groups, including consumers, stakeholders and the environment, therefore, the purpose of this article was to analyze the different angles of greenwashing in the real context of the companies active in the dairy industry, as well as to identify and explain this phenomenon. The philosophy of this research is interpretive, its approach is qualitative, and the strategy used is grounded theory based on the emergent approach. The studied community included managers and activists of the dairy industry and related organizations, 15of whom were selected through purposive sampling until reaching theoretical saturation, and the research data was collected through semi-structured interviews. In order to check the strength of the research, the four criteria of reliability, transferability, reliability and verifiability have been used. The relevant data analysis has been done using MAXQDA software and open, central and selective coding processes, and during continuous comparison, 427codes, 27concepts, 11categories and 2categories have been obtained. which has led to the emergence of the final model of research around the central category under the title of "companies greenwashing actions" model. The mentioned model includes the causes and results related to the central category of the research. In general, this study, by explaining the greenwashing measures theory, has provided the necessary platform for understanding this category of measures as well as their control and prevention.

Home businesses play a positive role in economic growth and development. Therefore, the development of the capabilities of these businesses is an important issue in economic success. The purpose of this research was to investigate the impact of entrepreneurial knowledge on the structure and performance of home businesses. In this research, the indirect effect of the structure of home businesses on the performance of these types of businesses has been investigated. The data used in the analysis of this study were collected from 139home business owners using a questionnaire. Data analysis was done using structural equation modeling method with PLS approach and questionnaire constructs show good validity and reliability. Previous knowledge of home business owners has a positive (β=0.392) and significant (T=2.289, >1.96) effect on business structure performance. Therefore, the first research hypothesis is supported. Previous knowledge of home business owners has a positive (β=0.597) and significant (T=6.310, >1.96) effect on the performance structure of home businesses. And therefore, the second hypothesis of the research is supported. The structure of home businesses has a positive (β=0.4) and significant (T=2.124, >1.96) effect on business performance. And therefore, the third hypothesis of the research is also supported.