مطالب

This study aims to present a model for the role of disclosure quality in the relationship between innovation and financial performance. The present study seeks to determine whether disclosure quality improve the relationship between innovation and financial performance or not? This study is a correlation study. Data is analyzed using structural equation modeling. The statistical population comprised of companies listed on the Tehran Stock Exchange. Y exerting the systematic elimination 140 companies were selected from 2015 to 2022. Result of the first hypothesis showed a significant and positive relationship between Innovation criteria and financial performance indices. This means that innovation improves financial performance. The results of the second hypothesis showed a significant and positive relationship between innovation criteria and disclosure quality indices. This means that innovation enhances the quality of disclosure. The third hypothesis's results showed a significant and positive relationship between financial performance criteria and disclosure quality indices. This means that financial performance improves disclosure quality. The results of the fourth hypothesis showed that disclosure quality indicators have a moderating role between Innovation criteria and financial performance indicators. This means that disclosure quality causes innovation to improve financial performance in the Tehran Stock Exchange and provide these companies with better disclosure quality.

INTRODUCTION: Considering the significant contribution of public education to the reduction of damages incurred by disasters and crises in the country, the identification of all the components and dimensions of public education can be of great help to policymakers in this field in order to adopt a correct policy and decision. The current research aimed to investigate public education in natural disasters with the meta-synthesis method based on the seven-step model of Sandelowski and Barroso (2007). METHODS: The current qualitative research was conducted based on a meta-synthesis approach. The statistical population of the research included articles related to the research from 2000 until now. A number of 175 articles were retrieved, and after examining the title of the research, 105 articles were removed, and 70 papers were reviewed, out of which 36 papers were removed, and 34 articles entered the final stage for full analysis. Articles were searched in databases, such as Scopus, Emerald, Science Direct, Springer, Google Scholar, and Scientific Information Database (SID). FINDINGSThe selected sources were analyzed using Maxqda software, and the research findings were coded. In the open coding stage, 100 primary codes were extracted from 34 articles, and after extracting the primary codes, to categorize the concepts, axial coding was used, yielding 5 dimensions, 12 components, and their sub-components. CONCLUSIONAs evidenced by the obtained results, to reduce vulnerability, the responsible institutions can adopt appropriate measures that lead to learning and changes in the audience's behavior by using the presented model and considering the determined components and indicators in the process of public education. This model includes the stages of analysis, educational design, preparation and development, implementation, and evaluation.

Choosing the proper investment mechanism is one of the main tasks of any investor that requires careful analysis and research on all available information. Since no investor exactly knows whether his or her expectations for a particular stock return will be met, they need to build their strategy in such a way as to eliminate as much damage as possible in the event of an adverse outcome. This study aims to predict the optimal portfolio using Algorithm Analysis Systems. In this regard, 98 firms listed on the Tehran Stock Exchange were examined in 2015-2019. Then, random portfolios were selected to test the research hypotheses by separating value stocks and growth stocks. For analysis, two algorithms of Support Vector Machines and an Adaptive Neuro-Fuzzy Inference System were used to select the most desirable portfolio. According to the support vector machine algorithm analysis, the results confirm the difference between the Sortino and Marquitz portfolios. To build their portfolios, decision-makers often rely on growth stocks which can boost their expected returns. Therefore, recognizing the analytical nature of portfolio formation in specialized areas can help improve investment analysis and pave the way for higher returns.