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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.

Sustainability has become the topic of the era, and the world is moving toward a circular economy. As part of it, companies are also integrating sustainability in supply chain management. Therefore, this study conducts a technology-empowered systematic literature review to examine the state of the literature on the technologies in the sustainable supply chain. The review reveals that limited studies have been conducted in the area. There is still scope for the researchers to explore new innovative technologies, many clusters in author collaboration, and involve more sectors in the study. Future studies can enrich the field by employing other methodologies like meta-analysis review.

Introduction: The insurance sector provides security to society by pooling resources to manage risks. Insurers’ improved ability to analyse risks by examining vast amounts of granular data has considerably refined this technique. Compiling and analysing the fine data sets is now transformed into the ‘Big Data’ technique. The introduction of big data analytics (BDA) is transforming the insurance industry and the role data plays in insurance.

Purpose: This chapter will attempt to examine the applications and role of big data in the insurance sector and how big data affects the different insurance segments like health insurance, property and casualty, and travel insurance. This chapter will also describe the disruptive impact of big data on the insurance market.

Methodology: Systematic research is carried out by analysing case studies and literature studies, emphasising how BDA is revolutionary for the insurance market. For this purpose, various articles and studies on BDA in the insurance market are selected and studied.

Findings: The execution of big data is continuously increasing in the insurance sector. The performance of big data in the insurance market results in cost reduction, better access to insurance services, and more fraud detection that benefits the customers and stakeholders. Therefore, big data has revolutionised the insurance market and assisted insurers in targeting customers more precisely.

Digital disruption no longer ensures the security or longevity of established firm structures and business models. Instead, it necessitates that firms reinvent their business models, including business processes, people, and technologies that align with the organizational goals. Despite the exponential growth of digital disruption, prior literature indicates that the concept of business model innovation is poorly understood in developing economies. Furthermore, little is known about how low-tech firms in developing economies should adapt and reinvent their business models to cope with and shape digital disruption as it unfolds. Grounded in two overarching theoretical frameworks, namely the theory of disruptive innovation and the resources–processes–values (RPV) framework, this chapter addresses this void in prior literature. Based on multiple case study analyses of 10 low-tech firms in diverse industries in Sri Lanka, the findings indicate that successful disruptive business model innovation in low-tech firms in Sri Lanka is predicated on an effective technology management strategy, suitable organizational structure, compatible organizational culture, and devoted corporate governance. Moreover, external influences like changing market dynamics, competition, and shifts in consumer behavior also significantly influence disruptive business model innovation of selected firms. This chapter acts as a springboard for future researchers by extending the theory of disruptive innovation and RPV framework to low-tech industries in developing economies.

In this paper, we investigate how digital technology disruptors and the incumbents who stand to be disrupted by them frame their arguments to transform or sustain existing institutional frameworks to enable or deter the market entry of these technologies. Using a longitudinal, comparative case analysis of three digital technologies – namely, voice over Internet protocol (VoIP), cloud antenna, and over-the-top (OTT) technologies – we explore how stakeholders use public interest frames for this purpose. We find that entrepreneurs use three specific frames to drive institutional change for the successful adoption of digital technologies in the presence of established incumbents and powerful regulators: frames that emphasize the broad public appeal of the new digital technology; frames that emphasize efficiency, democracy, and technological advancement; and frames that emphasize present as well as future benefits to the public. We find that constructing interpretations of what serves the public interest is the primary tactic used by disruptors to gain market entry, and an equally popular weapon for incumbents to block the entry of new digital technologies. These interpretations lead to a framing contest aimed at influencing regulators and obtaining a more favorable institutional environment. Our empirical findings illustrate that new digital technologies themselves are not the sole contributors to institutional change. Rather, institutional outcomes associated with the introduction of new digital technologies are shaped by how disruptors and incumbents use public interest frames and how regulators react to these frames.

In recent years, scholarly focus has shifted towards exploring the applications of disruptive technologies in professional services. These studies emphasise the need for further research in this domain. This research aims to comprehensively review the existing literature on the uses of blockchain, artificial intelligence (AI) and machine learning (ML) algorithms in professional services such as higher education, healthcare, financial securities firms and smart energy consulting. The rapid innovation and advancement in technology have led to substantial improvements in work efficiency and productivity. As industries transition towards sustainability and digitalisation, the role of energy-efficient systems becomes important in shaping smart factory designs and in further implementations. The uses of AI and other disruptive technologies for business operations not only boost production efficiency but also enhance customer satisfaction. Central to this transformation are strategies like deep learning and data/text mining, which facilitate the shift from conventional manufacturing practices to smart manufacturing. Apart from smart energy systems, the fields of higher education, healthcare and financial securities are witnessing a surge in the applications of AI, ML algorithms and blockchain technology and their contributions in emerging service economy. This study undertakes a comprehensive investigation into various factors associated with the application of disruptive technologies, evaluating their impact on the operational efficiency of professional service firms (PSFs). Through this research, we aim to identify gaps in the current literature and will suggest the directions for future research.

The objective of this chapter is to identify the key characteristics of Global Services businesses that will thrive and achieve success in the future. These factors are integrated into three main pillars, which we refer to as the Triple-Win. The first and most obvious pillar is technology as a tool. The second pillar is the design and sustainability of the business model, without which the previous factor would be merely a cost and not an investment. And last but not the least, there is the purpose which gives meaning to the proposal, focusing on the human being and their environment. The DIDPAGA business model sits at the intersection of these three elements.