Journal of Global Economics

The COVID-19 pandemic has presented unprecedented challenges to organizations worldwide, impacting various aspects of their operations, including Human Resource Management (HRM). This paper explores the critical role of information systems in enhancing the effectiveness of HRM during the on-going pandemic. The integration of technology and HR practices has become imperative to navigate the complexities brought about by remote work, workforce management, and employee well-being. This comprehensive analysis delves into the key strategies and tools that organizations can leverage to adapt their HRM practices, ensuring continuity and resilience in the face of the pandemic. The COVID-19 pandemic has reshaped the landscape of business operations, compelling organizations to rethink their approaches to Human Resource Management (HRM). In this context, information systems play a pivotal role in facilitating efficient and effective HRM strategies. This paper examines the challenges posed by the pandemic and explores how information systems can be leveraged to address these challenges and promote resilient HRM practices.

This research explores the intricate web of nonlinear interdependence and overflows between global economic variables and currency markets. The study employees advanced econometric techniques to analyse the dynamic relationships that exist beyond linear correlations, shedding light on the complexities inherent in the contemporary global financial landscape. By investigating the feedback loops, spill over effects and non-linearities, this research aims to enhance our understanding of how various economic factors influence currency markets and vice versa. The findings provide valuable insights for policymakers, investors, and researchers grappling with the challenges of an interconnected and rapidly evolving global economy.

Understanding complex dynamics is crucial in various scientific disciplines, ranging from physics and biology to economics and social sciences. In this paper, we propose a novel statistical complexity measure to assess and characterize regular patterns in dynamic systems. The measure aims to capture intricate structures and regularities, providing a comprehensive analysis of complex dynamics. Through theoretical development and practical applications, we demonstrate the effectiveness and versatility of the proposed measure. This contribution enhances our ability to quantify and comprehend the underlying regularities in complex systems, leading to valuable insights across diverse domains. Understanding the intricate dynamics of complex systems is a fundamental challenge in various scientific disciplines. Whether it is the behavior of biological networks, the fluctuations in financial markets, or the evolution of social systems, identifying and characterizing regular patterns in dynamic processes is essential for meaningful analysis. This paper introduces a novel statistical complexity measure designed to provide a robust and comprehensive assessment of regularities in complex systems.

Sustainable Public-Private Partnership (PPP) initiatives play a pivotal role in the socio-economic development of developing nations. As these nations strive for progress, effective risk management becomes crucial in ensuring the success and longevity of PPP projects. This paper aims to provide a comprehensive analysis of the risk severity matrix for sustainable PPP initiatives in developing nations. By examining various dimensions of risk and their impacts, we seek to offer valuable insights and guidelines for policymakers, investors, and stakeholders involved in such initiatives. The matrix presented herein integrates diverse risk factors, categorizing them based on severity, to enhance decision-making processes and promote the sustainability of PPP projects.