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The advent of the digital technologies (DTs), coincided with the pandemic and global conflicts, has proven to be an unprecedented and transformative era for supply chain management (SCM). DTs are reshaping the way organizations plan, execute, and optimize their SC operations. Throughout this book, we posit that the adoption of digital supply chain management (DSCM) has become essential for staying competitive and responsive in a rapidly evolving business environment. However, amid technological advancements and digital solutions, there exists a critical factor that often goes overlooked – the significance of intangible assets, specifically intellectual capital (IC). This chapter comprehensively explores the role of an organization's IC in the adoption and performance of DSCM. We employ a comprehensive analytical approach, drawing upon existing literature from various sources to elucidate the relationship between IC and DSCM. Synthesizing insights from the literature, the chapter shows how each constituent of IC contributes to the adoption, operation, and performance improvement of DSCM. The discussion in the chapter shows that human capital (HC) forms foundations, as the knowledge, skills, and abilities (KSAs) of the employees are prerequisites essential for understanding, adopting, and capitalizing on DTs in SCM. The analysis also reveals that SC, which represents organizational processes, digital tools, and knowledge repositories, supports the seamless integration of DTs within SCs. Similarly, RC, by nurturing trust, open communication, and collaborative networks, plays an instrumental role in establishing ecosystems that help the adoption and effective functioning of DSCM. This chapter makes a convincing case to consider IC as the strategic component while DSCM adoption and performance.

Disruptive technologies are accelerating global growth. Artificial intelligence (AI) has the potential to transform the idea of delivering value to end users. On the other hand, the growth of Industry 5.0 has given rise to the concept of humanizing technology, and AI is a promising technology with the potential to contribute to business success. Nevertheless, the idea of value creation in the field of AI is novel, so it is necessary to define the meaning of value by understanding the context of AI applicability in different environments and industries. In this chapter, the author uses the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) procedure to conduct an SLR that provides interesting insights into the focus, industries, and methodologies and approaches used in existing research. Following the initial literature review on the state of the art of AI and value creation, the author also offers a reflection on the strategic implications of AI in the field of marketing, postulating a macrovalue creation framework that addresses the existence of implications on three different levels: emerging markets, Sustainable Development Goals, and adoption issues. Therefore, this chapter examines the value creation perspectives of AI to understand the current research focus and future directions.

Artificial intelligence (AI) is revolutionizing businesses and daily life, with AI-powered technologies like personal assistants and medical diagnostic systems transforming how we interact and make decisions. However, the ethical implications of these technologies cannot be ignored. AI systems can produce biased results and decisions if not designed to be fair and unbiased. Corporate digital responsibility (CDR) provides a valuable framework for addressing these ethical dilemmas. Service organizations need to navigate CDR issues across the data and technology life-cycle stages (e.g., their creation, operation, refinement, and retention) and across its digital service ecosystem (including its external business partners). Despite the risks associated with poor CDR practices, companies may adopt them to benefit from data monetization, enhanced customer experience, and productivity improvement. To mitigate these risks and build a strong CDR culture, organizations need to establish ethical norms, prioritize customer privacy, and ensure equitable power dynamics with business partners. The emergence of generative AI poses enhanced CDR challenges, such as AI complexity, monitoring, accountability, and workforce changes. Going forward, CDR is a crucial framework for firms to address the needs of their multiple stakeholders and to ensure sustainable business practices in the increasingly digital service world.

Innovation is critical to the tourism industry. Living Labs (LLs) are innovation ecosystems which are becoming popular in tourism. LLs are a model of open innovation characterized by a networked approach to innovation. Local communities and businesses are usually excluded from processes of decision-making concerning the management of tourism. LLs enable local communities' participation in the sustainable development of tourism, thereby providing them the opportunity to increase their share of benefits. This chapter focuses on a case study of an LL recently created in Portugal and discusses LLs as an environment for tourism innovation where the local community is stimulated to explore competencies to cocreate value.

This beginning chapter offers a comprehensive overview of community development, tracing its historical roots and societal implications. It underscores community development’s role in fostering social cohesion and positive change. Beginning with its foundational principles of collective action, participation, and empowerment, the chapter delves into its evolution in response to industrialization and urbanization. It explores diverse scales, contexts, tools, and strategies used in community development and its broader societal impact. The chapter advocates for inclusivity and active engagement of community members, emphasizing tailored solutions that address unique challenges. It acknowledges complexities like ethical dilemmas, power imbalances, and cultural sensitivities, underscoring the importance of integrity and local context understanding in community development.

The very essence of internationalisation, which depends heavily on academic mobility and cross-border interactions, has been adversely affected due to the COVID-19 pandemic and has been associated with a significant decline in student and staff mobility in South Africa and around the world. Nonetheless, it has also catalysed innovation and inspired new approaches to teaching and learning that have the potential to transform the future of higher education. In the aftermath of the COVID-19 pandemic, higher education institutions are grappling with a fundamental question that goes beyond the practicalities of internationalisation: How can we re-envision the concept of internationalisation to meet the challenges of the new normal? This question calls for a deeper reflection on the nature of internationalisation itself. How can we ensure that cross-border interactions and exchanges continue to foster a sense of global community and intercultural understanding, even in a world that is physically distanced? This chapter seeks to explore the profound implications of the pandemic on the internationalisation of higher education (IHE) in South Africa. It aims to critically examine the present challenges to internationalisation and the strategies that have been developed to address them in the context of the post-pandemic world. The chapter employs a critical reflection approach through the use of qualitative research, systematic literature review, and document analysis. By utilising these methodologies, it seeks to delve deeper into the implications of the pandemic on the IHE in South Africa.

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.

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.