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Artificial intelligence and augmented reality are two key tools gaining importance in the digital era due to their wide range of applications in different fields and sectors. Industry 4.0 lays emphasis principally on the technology used to help the business remain competitive and sustainable. Sustainable development goals are another important objective of the UN which has laid responsibility for every business to support addressing the global challenges. Purpose: This chapter essentially aims to present the standpoint of artificial intelligence and augmented reality in meeting the sustainability perspective of organizations. Information about the study is gathered through secondary approaches, critically reviewing published literature, scientific reports, and statistical data accessible through business reports, and corporate websites. Further analyzed to present the perspectives of the authors in the study. Globally artificial intelligence market size is predicted to reach $190 billion by 2025, while the funding for startups doubled during the period 2011–2020 globally. The investment in artificial intelligence is going to reach $500 by 2024 resulting in substantial revenue returns. The augmented reality market size could reach $97 billion by 2028. Artificial intelligence today is increasingly used in many fields and is attracting multiple applications in many sectors such as manufacturing, retail, education, IT, and health care and has also contributed to sustainable development the same time by providing energy conservation options, optimization, and reduction of resources, minimizing wastage, offering timely assistance on maintenance schedules, practices which are enabling organizations to reach closer to sustainability and transformation.

One of the fundamental objectives of adopting digital supply chain (DSC) is to uplift the performance of an organization. Although a wide variety of literature confirms the impact of DSC on performance, it is hard to explore as to which dimensions of the performance is affected by DSC and how much. This chapter undertakes discussion on the impact of DSC on the various organizational performance indicators. The chapter also denotes some major key performance indicators (KPIs) that organization can track to gauge the impact of DSC on performance. A brief discussion on the challenges related to the development, adoption, and continuation of KPIs is also appeared in the later part of the chapter. The chapter concludes by denoting that the utilization of digital technologies (DTs) such as artificial intelligence (AI), the Internet of Things (IoT), and complex analytics in DSC has prospects for enhancing the operational efficiency, transparency, and agility of a supply chain (SC). Organizations that adopt these DTs have experienced better demand forecasting, reduced time order fulfillment time, and higher levels of consumer satisfaction. Nonetheless, the successful use of DSC requires development and implantation of KPIs regularly.

Industry 4.0 and the digital supply chain (DSC) are changing how things are made and moved around the world. This change is all about how smart technologies like the Internet of Things (IoT), artificial intelligence (AI), and blockchain are making supply chains work better. These tools help companies react faster and more clearly to what's needed. By using these new technologies, businesses can get better at guessing what customers want, keeping the right amount of stock, and quickly adjusting to new market trends. With these advanced technologies, companies can see big improvements, like being able to match supply with demand more closely and change their plans fast when things in the market change. It is really important for businesses to get how these tech tools work together as the world of making and selling things keeps changing. This chapter examines the convergence of traditional supply chain systems with Industry 4.0, focusing on the transformative impact of technologies such as the IoT, AI, and blockchain.

This chapter provides an in-depth look at how digital supply chain management (DSCM) can revolutionize supply chains in the post-COVID world. The COVID-19 pandemic exposed the vulnerabilities of traditional supply chains, highlighting the need for resilience and adaptability. The chapter begins by examining these COVID-induced disruptions, setting the foundation for the discussion on DSCM. DSCM, leveraging advanced technologies and data insights, offers a solution to these challenges, promoting agility, transparency, and sustainability in supply chain operations. This represents a significant shift from traditional practices, equipping organizations to cope with the dynamic postpandemic environment. Key capabilities of DSCM, such as resilience, integration, agility, and risk management, are discussed, supported by real-world examples from leading companies. These examples showcase the successful implementation of DSCM and its benefits in navigating the complexities of modern supply chains. However, the adoption of DSCM is not without challenges, including cybersecurity risks and integration difficulties. The chapter suggests strategies to overcome these challenges, emphasizing the importance of technology, collaboration, sustainability, and data-driven decision-making. By embracing these strategies, organizations can effectively manage their supply chains in the evolving global market, leveraging DSCM to withstand future uncertainties.

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.

Purpose: The purpose of this study is to identify the elements that can enhance financial inclusion (FI) in a nation, which in turn promotes economic development and growth.

Need for the Study: FI is crucial in providing people with the skills and resources to manage their money effectively and make informed financial decisions. Accessible, reliable and secure financial services play a significant role in achieving sustainable development goals (SDGs) and fostering economic progress.

Methodology: Data from 571 respondents were collected for analysis. The study utilises Statistical Package for Social Sciences SPSS and Analysis of Moment Structures AMOS software to analyse data and achieve the study’s objectives. The researchers employ these tools to obtain substantial results.

Findings: The findings indicate that FI contributes to economic growth (84%) and helps in accomplishing SDGs. Access, usage, affordability, technology, availability and technology adoption all play a vital role in increasing FI in the nation.

Practical Implications: The study’s outcomes have practical implications for policymakers and stakeholders, emphasising the importance of promoting FI through various measures such as enhancing access, affordability and technological advancements in financial services.

In the present study, we examined how effectively online travel agencies (OTAs) handle negative e-word-of-mouth on social media platforms like Facebook, Twitter, and Instagram. We collected data from 497 participants using survey method. To test the hypotheses formulated from the existing literature, structural equation modeling was adopted in this study. The results from structural equation modeling indicate effective handling of the negative e-word of mouth (e-WOM) on social media websites significantly affects customer satisfaction and repurchase intention. The current research work provides insight into social media recovery efforts and service fairness when handling negative e-WOM. The study recommends that customers can distinguish the differences between general efforts and adaptive complaint-handling efforts, and dissimilarities may influence satisfaction, repurchase intentions, etc. Although empathy, apology, responsiveness, and paraphrasing are considered pioneer strategies in complaint handling, customers' negative e-WOM, and firms' recovery management, but the current study is among a few to categorize OTAs' handling of negative e-WOM and complaint handling efforts in the social media environment.

Purpose: Twenty-first-century leaders operate in an unpredictable and complex business environment. The COVID-19 pandemic highlighted the VUCA (volatility, uncertainty, complexity, and ambiguity) nature of the business milieu and proved to be a real-life test for organisations and their leaders. It brought challenges and losses at personal, organisational, societal, national, and global levels. Nevertheless, some leaders and organisations thrived during and after the pandemic. This research assimilates leadership lessons from extant literature and real-life cases of leadership successes and failures. The authors aim to consolidate leadership strategies valuable in unpredictable, demanding, and complex times like COVID-19.

Methodology: The research relies on an extant literature review and opinions of four c-suite leaders captured through semi-structured interviews. The study uses content analysis to analyse the primary data collected.

Findings: The present research presents its results as a VUCA Leader Toolkit. It consolidates learnings from real-life case studies, extant literature, business reports, and experts’ opinions. It addresses the gap in existing research on VUCA-suited leadership strategies. The outcome of the present study is a clear, adequate, explicit, and well-defined list of VUCA-necessitated leadership strategies.

Originality/value: The research proves its utility in providing the VUCA Leader Toolkit. The outcomes carry usefulness for both present and future business leaders. The business environment today is ever-changing, complex, and uncertain. This unpredictability, uncertainty, complexity, and fuzziness would proliferate in the coming times. Hence, it is imperative to have a list of leadership strategies that may serve as a ready reckoner for leaders.

This chapter investigates the potential of integrating multiple criteria decision-making (MCDM) techniques with decision support systems of digital supply chain management (DSCM) to achieve optimal outcomes. Digital supply chain (DSC) employs digital technologies (DTs) such as artificial intelligence (AI), Internet of Things (IoT), and big data analytics to provide extensive datasets and valuable insights pertaining to supply chain operations. MCDM techniques employ these realizations to facilitate informed decision-making through the assessment of multiple competing criteria. Usually MCDM approaches are used in the academic research with comparatively lesser application in industry. We argue that MCDM methodologies can play an instrumental role in DSCM, specifically in the areas of supplier selection, demand forecasting, and inventory management. Nevertheless, the integration of MCDM like AHP, ANP, DEMATEL, etc., with decision support systems presents several challenges, including concerns regarding the quality of data and the intricate task of assigning weights to various factors.

Purpose: Since its inception in 1987, the literature on the VUCA that represents the volatile, uncertain, complex, and ambiguous nature of the business environment has progressively increased. This study systematically evaluates the vast literature on the VUCA world. Since review-based studies have been criticised as biased, this study uniquely amalgamates bibliometric analysis with content analysis, thereby taking a research triangulation discourse.

Need of the Study: This study was conducted to consolidate the literature about the VUCA environment and uncover the foundational and emerging themes for future research agendas.

Design/Methodology/Approach: This study conducts a performance analysis and science mapping of 193 carefully selected articles (using PRISMA) published in various sources during 2012–2023. Articles for the study were procured from the SCOPUS database. While performance analysis focused on analysing publication and citation evolution, thematic evolution, leading publications, country publication analysis, and most relevant authors and sources. On the other hand, science mapping revealed conceptual structures (keyword plus co-occurrence analysis and thematic maps) and intellectual structures (co-authorship analysis). VOSviewer and Biblioshiny (R-tool for comprehensive science mapping) were used for this study’s choice of application.

Findings: This chapter concludes with future research agendas using content analysis of the ‘scope for the future research’ section of selected publications and bibliographic coupling (to unearth emerging themes).

Practical Implications: The work presented in this chapter will help the researchers gain a structured conceptual, intellectual, and social understanding of the vast literature on the VUCA environment.