The study examines the impact of COVID-19 on the economies of Gulf Corporation Council (GCC) member states. The event study methodology was used to analyze Cumulative Abnormal Return (CAR) of GCC member states’ stock indexes: Kuwait Stock Exchange Index (KSE), Dubai Financial Market Index (DFM), Saudi Arabia Tadawul Index (TASI), Qatar Exchange Index (QE), Bahrain All Share Index (BHB), Oman’s Muscat Stock Exchange Index (MSM), Abu Dhabi Stock Exchange Index (ADX) while the S&P GCC Composite Index was used as a reference. Data obtained from 28 July 2019 to 27 July 2020, and 1 March 2020, designated as the event day, abnormal returns (AR) and cumulative average abnormal returns (CAARs) were examined across various time intervals. The findings reveal significant market reactions to the pandemic, characterized by fluctuations in abnormal returns and CAARs. Statistically significant abnormal returns and CAARs during certain time periods underscore the dynamic nature of market responses to the COVID-19 event. These results provide valuable insights for policymakers and market participants seeking to understand and navigate the economic implications of the pandemic on GCC economies. The study recommends that other GCC states, particularly Oman, consider the policies undertaken by Qatar, UAE, and Saudi Arabia, to avoid a long economic crisis.

Pakistan is a leading emerging market as per the recent classification of the International Monetary Fund (MF), and hedging is used as a considerable apparatus for minimizing a firm’s risk in this market. In these markets, investors are customarily unaware about the hedging activities in firms, due to the occupancy of asymmetric environment prevailing in firms. This research paper adds a new insight and vision to the existing literature in the field of behavioral finance by examining the impact of hedging on investors’ sentiments in the presence of asymmetric information. For organizing this research, 366 non-financial firms are taken up as the size sample; all these firms are registered in the Pakistan Stock Exchange. A two-step system of generalized method of moments (GMM) model is implemented for regulating the study. The findings of empirical evidence exhibit that there is a positive relationship between investors’ sentiments and hedging. Investors’ sentiments are negative in relationship with asymmetric information. Due to the moderate presence of asymmetric information, hedging is positively related to investors’ sentiments although this relation is non-significant.

This study investigated the utilization of Artificial Intelligence (AI) in the Recruitment and Selection Process and its effect on the Efficiency of Human Resource Management (HRM) and on the Effectiveness of Organizational Development (OD) in Jordanian commercial banks. The research aimed to provide solutions to reduce the cost, time, and effort spent in the process of HRM and to increase OD Effectiveness. The research model was developed based on comprehensive review of existing literature on the subject. The population of this study comprised HR Managers and Employees across all commercial banks in Jordan, and a census method was employed to gather 177 responses. Data analysis was conducted using Amos and SPSS software packages. The findings show a statistically significant positive impact of AI adoption in the Recruitment and Selection Process on HR Efficiency, which in turn positively impacted OD Effectiveness. Additionally, the study indicated that the ease-of-use of AI technologies played a positive moderating role in the relationship between the Recruitment and Selection Process through AI and HR Efficiency. This study concludes that implementing AI tools in Recruitment is vital through improving HR Efficiency and Organization Effectiveness.