درخت حوزه‌های تخصصی

According to the study of Fang and his colleagues in 2021, in order to reduce the fall of the stock market, companies pay attention to trading strategies and behavioral financial perspective, which have evaluated the assumptions and goals set in this regard; But there may be a gap in this path that prevents the connection or effect between the above variables, which is discussed in this study. This study aims to determine the effect of quantitative trading strategies on the fall of the stock market according to the perspective of behavioral finance (case study: companies admitted to the Tehran Stock Exchange). In order to analyze the research hypotheses, the statistical population was selected from 2016 to 2021 and for 6 years and included listed companies; the statistical sample was selected by elimination method and 90 companies. The research method used is a descriptive-analytical method and historical research data was collected and classified by referring to the financial statements and financial reports of the companies admitted to the Tehran Stock Exchange. The panel data method was used to analyze the statistical data; And in the analysis section, descriptive statistics, inferential statistics and various relevant tests were performed and data analysis was done using Eviews version 9 software. According to the analysis of the regression model, the findings of the research show that the main hypothesis has been confirmed and it was found that quantitative trading strategies have a negative and significant effect on the fall of the stock market according to the behavioral financial perspective of the companies admitted to the Tehran Stock Exchange. So that in this research, based on the t-statistics, the effectiveness of both special hypotheses (fall-timing and movement-reverse) was determined, and according to the mediating variable of behavioral financial perspective, they can also play a positive and significant role in reducing the fall of the stock market to be.

Healthcare service institutions (HSIs) have sought ways to motivate patient loyalty in response to surging rates of medical tourism. Previous research indicates that Hospital Information System (HIS) is essential for HSIs to gather, measure, and analyze the massive amounts of data required to generate patient loyalty. There is currently no consensus on the factors that comprise HIS specifically geared towards motivating patient loyalty (HISPL). Furthermore, HIS requires full adoption by HSI staff to be effective. Thus, to reduce wastage of HSI resources, it is necessary to predict whether a given HIS specifically geared towards motivating patient loyalty is likely to be adopted. The purpose of this study is to reveal the factors that comprise HISPL and to modify the Unified Theory of Acceptance and Use of Technology (UTAUT) model to help predict the likelihood of an HISPL to be fully adopted by HSI staff. The results revealed that pertinent HISPL factors are capability, configurability, ease of use/help desk availability and competence (EU), and accessibility/shareability (AS). Using these factors, the UTAUT model was modified to fit the specific needs of HISPL. The modifications are theoretical and will have to be validated in future empirical studies.