(1) Background: Our study aims to explore the impact of abusive management and self-efficacy on corporate performance in the context of artificial intelligence-based human–machine interaction technology in enterprise performance evaluation. (2) Methods: Surveys were distributed to 578 participants in selected international companies in Turkey, Taiwan, Japan, and China. To reduce uncertainty and errors, the surveys were rigorously evaluated and did not show a normal distribution, as it was determined that 85 participants did not consciously fill out the questionnaires, and the questionnaires from the remaining 493 participants were used. By using the evaluation model of employee satisfaction based on a back propagation (BP) neural network, we explored the manifestation and impact of abusive management and self-efficacy. Using the listed real estate businesses as an example, we proposed a deep learning BP neural network-based employee job satisfaction evaluation model and a human–machine technology-based employee performance evaluation system under situational perception, according to the design requirements of human–machine interaction. (3) Results: The results show that the human–machine interface can log in according to the correct verbal instructions of the employees. In terms of age and education level variables, employees’ perceptions of leaders’ abusive management and self-efficacy are significantly different from their job performances, respectively (p < 0.01). (4) Conclusions: artificial intelligence (AI)-based human–machine interaction technology, malicious management, and self-efficacy directly affect enterprise performance and employee satisfaction.
There has been a rise in recent studies on behavioral finance. According to Fama (1970) all information is priced, so it cannot be said about the undervalued stock. However, behavioral finance asserts that there are many anomalies in the market. The effects of days of the week, January effect and religious days on the returns and volatility of the stock markets were examined in the literature. In the case of Turkey, aforementioned anomalies are tested using returns and volatility of BIST100 and KAT30 indices. As a result, days of the week, January effect and Ramadan effect have no any effect on returns and volatility of both conventional and unconventional stock indices. The result has strengthened the assumption that Turkish market is more efficient in this sense and in line with Fama's EMH. It has been observed that timing does not have a significant effect on the strategies of Turkish investor.
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