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Purpose of This Chapter: This study examines the relationship of ambidextrous leadership with employee voice behaviour, underscoring the intervening role of employee thriving.

Design / Methodology / Approach: This study proposes a conceptual framework based on an extensive literature review using the conservation of resource theory, social exchange theory, and the broaden-and-build theory of positive emotions.

Findings: This study demonstrates that employee thriving act as an underlying mechanism explaining the relationship between ambidextrous leadership and employee voice behaviour.

Research Limitations: Being a conceptual study, the proposed framework lacks empirical validation.

Practical Implications: Organizations should focus on leaders with flexible behaviours who understand situational necessities to adopt diverse leadership styles and contribute to employee thriving.

Originality: This is one of the first studies to propose the role of ambidextrous leadership in impacting and enhancing change in employee voice through employee thriving at work. By introducing a framework that delves into the unexplored territory of ambidextrous leadership, acting as a catalyst for enhancing employee voice via the lens of employee thriving. This study provides a fresh perspective and adds value to the evolving conversations around employee voice behaviour.

Purpose: The study discusses various concepts for human resources (HR) executives for effective decision making in VUCA times, talent management, hybrid work business model, creativity and innovation in HR practices, diversity, equity, and inclusion (DEI) in HR practices, and flexibility in HR policies.

Need for the Study: The driving truth of this study is to approach a successful dynamic critical model for HR leaders in the IT Industry in Chennai city during VUCA times. Volatility, Uncertainty, Complexity, and Ambiguity are the four main components of VUCA.

Methodology: The essential information was gathered with Google Structures, and testing methods were embraced to review the Snowball Examining Procedure. The 211 reactions were settled for the concentrate after deficient reactions. The auxiliary information was gathered from sources like Papers, Business Magazines, Industry Reports, Articles, and Reading material. The information was dissected with measurable programming SPSS 25 and AMOS 23. The validity check, t-test, correlation analysis, regression analysis, and structural equation modeling (SEM) are the statistical methods used in the study.

Findings: The review results that the free factor is the ability of The board, Crossbreed Work Plan of action, Imagination and development in HR rehearses, Variety, Value and Consideration in HR practices, and adaptability in HR strategies altogether affect the reliant variable viable decision making during VUCA times.

Practical Implications: The study identifies hybrid work models and flexible HR policies as crucial parameters in VUCA times.

This article reconstructs the conditions under which displaced persons are integrated into their workplaces with their hosts. It identifies the characteristics of this pathway and provides guidance on the support that should be provided to these people. This support is part of social responsibility. Theories on professional integration/labour market integration (LMI) have been categorised and then arranged in a logical order to determine the stages of this integration. Theories on professional integration support for refugees were also reviewed and examined in relation to this categorisation. Six stages characterise professional integration: getting a job, its sustainability and its wage adequacy, its security and sustainability, career continuity and employability, the fact of being a full and equal participant and being an integrated part of the workforce and the meaningfulness of that job. The level of professional integration marks the quality of this integration. Each level encompasses the previous levels. Displaced persons should be supported throughout their careers to go beyond technical and behavioural skills and take a more holistic view of their tasks to find meaning in their work. While most research focuses on getting a job as a characteristic of occupational integration, this study found five other characteristics that were ordered. It also links vocational integration with social responsibility and provides guidance on how to help displaced people reach the final stage of this integration.

Several studies have been conducted on social inequalities. Despite highlighting inequalities between the rich and poor, researchers often overlook the fact that disabled people in Africa are marginalised more than their counterparts elsewhere. Using critical discourse analysis (CDA) as a theory and data analysis method, this study sought to answer two questions: (1) What is reported about the inclusion of disabled people in using digital media? (2) How is it reported? Twenty-two articles were purposively sampled: 15 from Newsday and 7 from The Herald published between 20 November 2017 and 24 September 2022. Findings indicate that the two papers exposed marginalisation of disabled people in an educative and informative way and had erudite analysis from disabled columnists. This was successful because the papers relied on the disabled community as sources of information and contributors of published material. The papers also engaged stakeholders such as corporates, government and civil society organisations. It is recommended that other newspapers and many forms of mass communication provide a representation of people with different forms of disabilities. Future studies could seek the views of disabled communities about their presentation in the digital media through disabled writers and providers of information.

There is a growing interest in the use of HR-based Industry 4.0 technologies for equality, diversity, and inclusion (EDI) issues yet the emerging trends of Industry 4.0 in EDI implementations and interventions are not fully covered. This chapter investigates the emerging themes regarding EDI and Industry 4.0 interaction through Google-based big data that show the actual interest in Industry 4.0 and EDI. Drawing on a web analytics method that tracks the real click behaviours of web users through querying combined sets of keywords, the study explores the trends and interactions between Industry 4.0 technologies and EDI-related HR practices. Our search engine results page (SERP) analyses find a high volume of queries and a significant interest between EDI elements and artificial intelligence (AI) only. In contrast to the suggestions of the extant literature, no significant user interest in other Industry 4.0 applications for EDI implementations was observed. The authors suggest that other Industry 4.0 technologies such as machine learning (ML) and natural language processing (NLP) for EDI implementations are in their early stages.

Artificial Intelligence (AI) has revolutionised the tourism industry, offering personalised experiences and streamlining operations. AI provides customised recommendations for travellers through data analysis and machine learning, making their journeys more meaningful. It has also improved efficiency through automated processes, chatbots and enhanced security measures. AI's ability to analyse large volumes of data enables tourism organisations to make data-driven decisions and target their marketing strategies effectively. One of the most notable contributions of AI in tourism is its ability to offer personalised recommendations. By analysing vast travel history, preferences and online behaviour, AI systems can provide tailored suggestions for destinations, accommodations, activities and dining options. This level of customisation enhances the overall travel experience, making it more relevant and satisfying for individual travellers. AI has also greatly improved operational efficiency within the tourism sector. Chatbots, powered by natural language processing, are increasingly being deployed by hotels, airlines and travel agencies to provide instant customer support and assistance. These chatbots can answer queries, offer recommendations and handle booking processes, reducing waiting times and enhancing customer satisfaction. In addition, facial recognition technology allows for quick and accurate identity verification at airports, hotels and other travel-related facilities. This improves security and provides travellers with a seamless and efficient experience. As technology advances, we expect AI to play a more prominent role in augmented reality, voice recognition and virtual assistants, further enhancing the travel experience and facilitating seamless interactions. In conclusion, AI has transformed the tourism industry by providing personalised recommendations, improving operational efficiency, enhancing security measures and enabling data-driven destination management.