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The nature of technologies that are recognised as Artificial Intelligence (AI) has continually changed over time to be something more advanced than other technologies. Despite the fluidity of understanding of AI, the most common theme that has stuck with AI is ‘human-like decision making’. Advancements in processing power, coupled with big data technologies, gave rise to highly accurate prediction algorithms. Analytical techniques which use multi-layered neural networks such as machine learning and deep learning have emerged as the drivers of these AI-based applications. Due to easy access and growing information workforce, these algorithms are extensively used in a plethora of industries ranging from healthcare, transportation, finance, legal systems, to even military. AI-tools have the potential to transform industries and societies through automation. Conversely, the undesirable or negative consequences of AI-tools have harmed their respective organisations in social, financial and legal spheres. As the use of these algorithms propagates in the industry, the AI-based decisions have the potential to affect large portions of the population, sometimes involving vulnerable groups in society. This chapter presents an overview of AI’s use in organisations by discussing the following: first, it discusses the core components of AI. Second, the chapter discusses common goals organisations can achieve with AI. Third, it examines different types of AI. Fourth, it discusses unintended consequences that may take place in organisations due to the use of AI. Fifth, it discusses vulnerabilities that may arise from AI systems. Lastly, this chapter offers some recommendations for industries to consider regarding the development and implementation of AI systems.

Industry 4.0 has been identified as a key cornerstone to modernise economies where man and machines complement each other seamlessly to achieve synergies in decision-making and productivity for contributing to SDG 8: Decent Work and Economic Growth and SDG 9: Industry, Innovation and Infrastructure. The integration of Industry 4.0 remains a challenge for the developing world, depending on their current status in the industrial revolution journey from its predecessors 1.0, 2.0 and 3.0. This chapter reviews reported findings in literature to highlight how robotics and automated systems can pave the way to implementing and applying the principles of Industry 4.0 for developing countries like Mauritius, where data collection, processing and analysis for decision-making and prediction are key components to be integrated or designed into industrial processes centred heavily on the use of artificial intelligence (AI) and machine learning techniques. Robotics has not yet found its way into the various industrial sectors in Mauritius, although it has been an important driver for Industry 4.0 across the world. The inherent barriers and transformations needed as well as the potential application scenarios are discussed.

The chapter looks at two recent acquisitions by Chinese companies of German firms operating in the automotive sector. In both cases it was the target firm that initiated the process, intentionally selling to a Chinese strategic investor. The main purpose of the chapter is to examine the main motivations that induce developed country MNEs to deliberately search for a buyer in China.

The chapter uses a case-study approach. Interviews were conducted with the managers that followed the entire process of sale and who were responsible for the search and the selection of a strategic investor in China.

Empirical findings show that major drivers in opting for Chinese investors are the potential synergies generating from resource redeployment, the ability of the acquired firm to maintain its autonomy and the opportunity to expand into the Chinese market.

The cases analysed show that developed country firms may take a proactive role in China in order to address their institutional-based disadvantages and to reduce and eliminate the liability of foreignness they may confront there. What is important is strong core competitiveness on their side, which can ensure their operational autonomy, such as technological leadership and superior quality and solid development. The policy implications are relevant, because in the current particular situation where many companies in Europe turn for sources of capital to emerging market firms, Chinese investors can facilitate target companies’ growth, with a positive impact for the local economy.

This chapter proposes a new architecture to address challenges to security and the privacy in e-healthcare under Industry 5.0. With the growing needs for high-quality medical treatment and the continuously growing costs of treating global medical problems, systems and web-based medical care are regarded as innovative solutions. In particular, the new progress in Internet of Things (IoT) has led to the development of Internet of Medical Things (IoMT). The patient history data is handled and processed remotely in real-time rather than visiting any clinic and then having that data transferred for subsequent use to third parties, such as data that gets saved in the cloud. This patient data faced security threats and it is observed as major limitations of using such systems in Industry 5.0. This chapter analyzes the security and secrecy challenges, together with the necessities, the danger involved and proposed secured blockchain-based framework which is capable of future research scope in Industry 5.0. The study has described an Eye Hospital case study that stores the eye donors’ details. With such critical scenario, this study addresses healthcare scenario with poverty-led agenda and social developmental features.

As the size of the population is growing and the capacity of the planet Earth is limited, human beings are searching for sustainable and technology-enabled solutions to support society, ecology and economy. One of the solutions has been developing smart sustainable cities. Smart sustainable cities are cities as systems, where their infrastructure, different subsystems and different functional domains are virtually connected to the information and communication technologies (ICT) and internet via sensors and devices and the Internet of Things (IoT), to collect and process real-time Big Data and make efficient, effective and sustainable solutions for a democratic and liveable city for its various stakeholders. This chapter explores the concepts and practices of sustainable smart cities across the globe and explores the use of technologies such as IoT, Blockchain technology and Cloud computing, etc. their challenges and then presents a view on business models for sustainable smart cities.

In the effort to procure solutions to emerging challenges faced in the construction industry, construction stakeholders implemented the use of several technologies in construction operations from the onset of project planning to completion. Cyber technology introduced into construction brought about the inclusion of wearable technology, mobile devices, apps, project management software, drones, 3D printers, robotics, etc. to enhance output as the industry tends towards that which is sustainable. This chapter identified benefits, barriers and other related cyber technology interactions within the scope of delivering projects that are of standard, budget and quality at the same time. The conclusion gave a summary of the whole chapter for further comprehension.