Meta-analysis of the literature related to SDG 3 and its investment

The government bond (GB) has become the most attractive investment portfolio option, even though many macroeconomic factors affect the bond yield. This paper aims to investigate the determining factor of local currency government bond yield by considering the inflation rate, credit default swap, stock market index, exchange rate, and volatility index. This study used 240 data panel from the Bloomberg stock market in the form of data panel covering Southeast developing countries, namely Indonesia, Thailand, Malaysia, and the Philippines, for five years or sixty months from January 2015 to December 2019. Data analysis used recursive models and multivariate regression techniques using EViews software. The random effect model results revealed that change in the foreign exchange rate and volatility indexes affected, partially and simultaneously, the changes in the stock market index. The result also showed that changes in the stock market index, inflation rate, and credit default swap affected, partially and simultaneously, government bond yield changes. These results suggest that the government bond yield could be managed by controlling volatility index, foreign exchange rate, stock market index, inflation rates, and credit default swaps. This finding could provide an insight into the policymaker and fiscal authority on managing the risk of government bonds under control during high volatility or even making it reasonably lower. This result could contribute to the current research in the field of financial management.

Acknowledgment
It is the author’s pleasure to thank Muhammad Aulia SE MSc CSA® from the Ministry of Finance of Republic Indonesia, for his invaluable contribution to encourage this study and also to share the data required for this paper. He also delivers essential insights into improving the quality of this work. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

The stock market represents complex systems where multiple agents interact. The complexity of the environment in the financial markets in general has encouraged the use of modeling by multi-agent platforms and particularly in the case of the stock market.
In this paper, an agent-based simulation model is proposed to study the behavior of the volume of market transactions. The model is based on the case of a single asset and three types of investor agents. Each investor can be a zero intelligent trader, fundamentalist trader or traders using historical information in the decision making process. The goal of the study is to simulate the behavior of a stock market according to the different considered endogenous and exogenous variables.

Talents play a critical role in achieving organizational strategic goals and a higher level of performance in the healthcare industry. Therefore, the UAE government, which strives to provide world-class healthcare services, encouraged the adoption of talent management strategies and creation of essential capabilities for talent recruitment, development, and retaining. This study explores the talent management strategies, policies, and practices in multiple departments of a public UAE hospital. Moreover, it investigates required skills, competencies, and programs for those departments in the context of Industry 4.0. The study adopted a case study approach and qualitatively surveyed a purposive sample of 13 departmental managers, section heads, and supervisors who are experienced in employee management. The study found that talent management at the studied hospital is undefined and unclear in terms of strategies, policies, and practices. Furthermore, the study highlighted the need for employee encouragement, motivation, and engagement, as well as confirmed the critical role of management and leadership in facilitating talent management in the hospital. Accordingly, a UAE hospital could benefit from this study to develop its talent management policy and strategies that will guide managers in the Industry 4.0 era.

Acknowledgment
The nursing administration, nursing research committee at Tawam hospital and managers who responded to the study survey are acknowledged for the extension of support for the study.