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This study aims to investigate the healthcare sector of the United Arab Emirates (UAE) to explore the significance of servant leadership and collaborative culture in fostering social sustainability. The primary objective of this paper is to investigate how servant leadership and a collaborative culture contribute to social sustainability in health care in the UAE. With a focus on promoting well-being within healthcare organizations, the paper aims to uncover the synergies between servant leadership, collaborative culture, and social sustainability.

This paper conducted a multilayer literature review of existing literature on servant leadership, collaborative culture and social sustainability in health care, both globally and specifically in the UAE context, and a conceptual model was proposed.

Servant leadership proves to be a culturally pertinent and effective leadership model within the UAE due to its alignment with cultural values, emphasis on community support, and the robust health-care system that contributes to individual well-being. This combination establishes a solid foundation for fostering a healthy and sustainable society.

Limitations and implications are discussed. The current research has not identified the boundary conditions under which servant leadership and collaborative culture may be more or less effective. This could involve exploring industry-specific influences or contextual factors. Theoretical and practical implications are discussed.

The research seeks to unravel the interconnections between servant leadership, collaborative culture and social sustainability. To the best of the author’s knowledge, none of the studies have explored the interrelationships of these constructs, particularly in the UAE context.

This paper tries to retrospect the mounting application of machine learning (ML) and artificial intelligence (AI) in the human resource management area. The document applies bibliometric analysis and uses relational techniques to explore dimensions of documents in the field. The results highlight publication trends, most impactful authors, countries and institutes in the research area. The science mapping along with co-citation and bibliometric coupling analysis revealed major developments in the field. The thematic mapping and trend analysis highlighted the past and emerging trends towards significant and impactful research in the areas of robotics, big data, AI and data analytics. This paper sets the base for future researchers by coordinating and combining various past researches to help in understanding the evolution of ML and AI in human resource management and expansion of knowledgebase.

Talent management is conducted to maximize an organization's overall performance and efficiency which helps to serve as a competitive advantage. Human resource management is a concept which includes human-related activities, but talent management is a strategy which helps to get new talent, develop their skill sets and provide better employee engagement and experience to retain the top potential employees in an organization. Improvement in recruiting and retention of a workforce results from a well-executed talent acquisition approach. In the 21st century, employee retention has become a primary concern for the organizations specially with work from home and hybrid models.

The workforce for tomorrow is going to be very different from what it has been. Technology is transforming the way people work within organizations. The workplace is rapidly evolving in terms of people and processes and is going through a lot of technological changes. The terminologies such as automation, artificial intelligence, augmented reality and block chain technologies are slowly becoming part of the workplace and everyday activities of the organization.

The challenges are many and especially post-pandemic organizations are going through some major changes such as a mindset shift of employees to take up more remote working opportunities, building virtual teams, increase in the gig economy workers (contractual workers) and a diverse workforce which makes it even more challenging for the organization to manage and retain talent.

This paper aims to examine the connection between digital payments, ownership structure, and bank performance in Jordan, as well as investigate the moderating role of the independent director in the said relationship.

The study uses data from 12 Amman stock exchange-listed commercial banks, covering the period from 2010 to 2023. This paper employs econometric analysis of panel data, including ordinary least squares (OLS) regression as the primary approach, as well as the generalised method of moments, the two-stage least square (2SLS), and the dynamic model to deal with causality and endogeneity issues in the proposed equations. This ensures that the results are valid.

The results indicate that digital payments and ownership structure have a significant positive connection with bank performance. Additionally, the independent director variable appears to play a substantial and positive moderating role in the link between ownership structure (e.g. institutional ownership) and bank performance. These results strengthen and support the claims of agency theory and the information systems success model.

Overall, this research helps stakeholders, bankers, managers, investors, customers, and policymakers, identify the influence of digital payment and ownership structure on bank performance in developing economies such as that of Jordan.

This investigation offers a unique understanding by illuminating how digital payment and ownership structure affect bank performance in a developing country such as Jordan. Additionally, it opens avenues for future research to delve into this literature domain in North African and Middle Eastern nations, with a particular focus on Jordan. This investigation is among the initial explorations in Jordan that aim to elucidate these relationships. On the theoretical level, it adds to the agency theory and IS model. It provides new insights into the dynamics of industry banking in developing nations (i.e. Jordan).