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Talent management process makes sure that the organization has sufficient supply of talented employees to meet the organizational goals. However, this aspect is important for organizations especially in the wake of the ever-changing business environmental factors such as political, social and economic factors. To undertake a critical examination of the changing dynamics in the field of talent management, the following research focuses on an analysis of the impact of political, economic and socio-cultural changes on the talent management process in oil and gas companies in GCC. As such, the main objective of the research is to undertake an analysis of the practices of talent management adopted in the oil and gas sector in GCC region and analyze the changing dynamics of the Talent Management process to suggest strategies to manage talent to improve the industry performance. Despite the advanced in the human resource management field, the talent landscape in the GCC region faces challenges in the talent management process such as talent acquisition, talent retention, and talent development. The following research focuses on the use of an empirical quantitative approach towards data collection and interpretation of the obtained data. The research advanced three hypotheses, which are tested in the research. The findings of the research provide evidence that the economic, social and political factors have a significant influence on talent management practices in this region. And it is important to consider the business environmental factors in managing talent by aligning organizational strategy with talent management strategy of the company. The implantation of technology by means of Artificial intelligence, HR analytics and automation will reduce the dependency on more employees and improving the value of HR in the organization by enlightening organizational performance and productivity with few talented employees in line with dynamic business environmental factors.

Purpose This paper aims to study the roles of Muslim CEO, Muslim Chairman and Muslim board of directors in mitigating earnings management via real activities manipulation. Design/methodology/approach In total, 656 firm year-observations from 2007 to 2014 of Malaysian Top 100 firms listed on Bursa Malaysia is used to examine the relationship between real earnings management (REM) and the religious ethical values of Muslim top leadership of the firms. Findings The study provides evidence that there was no significant relationship between ethical values and REM measures among Muslim top corporate leaders. However, through additional analysis on sub-sample firms, this study finds that Muslim CEO and Muslim Chairman have a significant and negative association with proxies of REM: RCFO and RPC. Research limitations/implications The results show that Muslim CEO and Muslim Chairman are the actors that contribute more control in limiting REM especially in family-owned firms in Malaysia. Originality/value This is the first published paper that focuses on Islamic ethical values of corporate top leadership and REM in Malaysia, as previous studies have focused more on accruals earnings management.

-External auditor is one of the governance mechanisms in mitigating corporate managerial misconduct and thereby enhance the credibility of accounting information. Thus, the main objective of this study is to develop machine learning prediction model on auditor choice of the firm which signal the quality of auditing and financial reporting processes.This paper presents the fundamental knowledge on the design and implementation of machine learning model based on four selected algorithms tested on the real dataset of 2,262 firm-year observations of companies listed on Malaysian stock exchange from 2000 to 2007. The performance of each machine learning algorithm on the auditor choice dataset has been observed based on three groups of features selection namely firm characteristics, governance and ownership. The findings indicated that the machine learning models present better accuracy performance with ownership features selection mainly with the Naïve Bayes algorithm. Keywords-Auditor Choice, Machine Learning, Prediction

This study examines the association between government-linked investment companies’ (GLICs’) shareholdings and real earnings management activities in Malaysia. Consistent with prior research, this study uses three proxies to measure real earnings management; abnormal cash flow from operations (RCFO), abnormal production costs (RPC), and abnormal discretionary expenses (RDE). This study segregates GLICs’ shareholdings into two categories; Federal Government Pension Investment Funds (FGPIF) and other GLICs (OFGLIC). Using a sample of 213 firm-year observations of Malaysian government-linked companies from 2010 to 2015, this study finds that FGPIF is a more effective monitoring mechanism than OFGLIC in limiting real earnings management. The findings also show that there is a significant and negative relationship between Employee Provident Fund (EPF), Khazanah Nasional Berhad (Khazanah), Permodalan Nasional Berhad (PNB) and RCFO and RPC. The evidence suggests that these three are the most effective government institutional investors in promoting corporate governance, which in turn limit real earning management activities in Malaysia. In general, the findings support the incentive alignment hypothesis, which argues that companies with government intervention are normally better governed.