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This final chapter delves into the future of digital supply chain management (DSCM) amid today's dynamic business environment, shaped by technological advancements and factors like automation, artificial intelligence (AI), sustainability, and resilience. It emphasizes the crucial role of digital technologies (DTs) such as AI, the Internet of Things (IoT), Industrial IoT, and the Internet of Everything (IoET), along with blockchain, in revolutionizing supply chain operations. These technologies enable agility, flexibility, efficiency, and responsiveness, crucial for supply chains to proactively adapt to market changes. The chapter explores the trends in DSCs, focusing on real-time data analytics, end-to-end visibility, sustainability, and resilience. It highlights the growing importance of transparency in supply chains, driven by consumer demand for sustainable practices and product origins. DSCM is identified as pivotal for prioritizing sustainability, leading organizations toward green practices. Despite the opportunities in DSCM, challenges like cybersecurity, data management complexities, geopolitical uncertainties, and talent shortages are acknowledged. To overcome these, the chapter stresses strategic foresight in DSCM and the importance of robust process management, risk management, and talent development. The future-readiness of supply chain professionals is discussed, highlighting the need for change management, development of social and deep work skills, collaboration, and ethical practices. The chapter concludes by underscoring the transformative potential of DTs in the digital era, urging organizations to embrace innovation, transparency, and sustainability in their supply chains, recognizing that the future of DSC is an imminent reality.

The supply chain is undergoing a significant digital transformation to adapt to the increasingly digitalized and globalized business environment. To remain competitive in this evolving market, businesses must seamlessly integrate digital technologies throughout the supply chain, spanning all stages from procurement to distribution. This chapter delves into models and methodologies critical to digital supply chain (DSC) transformation, with a focus on advanced techniques such as the Internet of Things (IoT), artificial intelligence (AI), blockchain, and data analytics to boost the resilience and agility of supply chain operations. By leveraging practical examples and case studies, the chapter highlights the myriad enhancements digital transformation can introduce across diverse supply chain stages, including sourcing and after-sales service. Additionally, the chapter examines the complexities of cybersecurity, data integrity, and change management within the digital transformation framework, proposing strategies to address these challenges. The insights offered in this chapter will serve as a thorough guide for both practitioners and scholars in the supply chain field, equipping them to adeptly navigate the multifaceted arena of digital transformation.

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.

Purpose: The COVID-19 pandemic has been a good example of a Volatility, Uncertainty, Complexity, and Ambiguity (VUCA) world. Higher educational institutions (HEIs) have faced a massive hit because the jobs in this industry have become unexpected. Considering the most valuable assets ‘Teachers’ crunched in the VUCA crisis, the study intends to determine if personal harmony (PH) and organisational citizenship behaviour (OCB) would enhance teachers’ job satisfaction (JS).

Design/methodology/approach: Data are collected from the teachers of Indian HEIs and teachers who have experienced the impact of the COVID-19 catastrophe (VUCA). Considering the pandemic restrictions, data have been collected through an online survey (N = 364).

Practical Implications: PH is an individual’s internal quality and attribute that cannot be developed on force or situational need. Even in an uncertain situation, teachers have tried their best to contribute through professional service. Hence, people who possess PH contribute their best even though unsatisfied with their jobs.

Originality/value: This study has focused on finding the relationship between two different variables, PH and OCB (which has not been explored in Asian countries, majorly in India, where it has a vast cultural diversity and structure influencing the educational policies) that hinders the factors influencing JS, where these two variables are highly influenced by hygiene factors such as values, culture, ethical standards, personal belief, leadership styles, and fair treatment showcased by the organisations/institutions.

The purpose of this chapter is to explore the challenges of health emergency communication as presented in the COVID-19-related research articles in the fields of organisational communication, strategic communication and public relations published between 2020 and mid-2022. A qualitative literature review consisting of two rounds of data selection and ATLAS.ti-assisted content analysis was conducted. The data include 67 articles published in quality journals of communication studies, with a focus on the abstract, results and discussion sections. The findings emphasise the need for emotional support, empathy and both vertical and horizontal informal communication in uncertainty reduction during a major health emergency. The limitations of the study include that the data are limited to the first published journal articles concerning the consequences of COVID-19 and that it comprises publications in communication studies but not related fields, such as health, psychology or management. However, it provides an overview of the research findings and offers guidelines for managers and communication professionals for the development of communication practices under the threat of a major health crisis. Moreover, it proves the importance of healthy and trustful workplace relationships as a prerequisite for coping with uncertainty. All in all, the study provides a good basis for further studies of organisational communication and health emergencies.

This study developed a new analytical model to quantify the influence of business intelligence (BI) adoption on bank performance. An in-depth review of academic literature revealed a significant research gap exists in investigating BI's performance impacts, especially in the under-studied Indian banking context. Additionally, customer relationship management (CRM) was incorporated as a moderating variable given banks' large customer databases.

A survey was administered to 413 employees across leading Indian banks to collect empirical data for evaluating the conceptual model. Relationships between variables were analysed using partial least squares structural equation modelling (PLS-SEM). This technique is well-suited for theory building with smaller sample sizes and non-normal data.

Statistical analysis supported the hypothesised positive effect of BI adoption on bank performance dimensions including growth, internal processes, customer satisfaction, and finances. Furthermore, while CRM did not significantly moderate this relationship, its inclusion represents an incremental contribution to the limited academic literature on BI in Indian banking.

The model provides a quantitative basis for strategies leveraging BI's performance benefits across the variables studied. Moreover, the literature review revealed an important knowledge gap and established a testable framework advancing BI theory in the Indian banking context. Significant future research potential exists through model replication, expansion, and empirical verification.

This research thoroughly reviewed existing academic literature to develop a novel testable model absent in prior studies. It provides a robust conceptual foundation and rationale for ongoing scholarly investigation of BI's deployment and organisational impacts.