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Additive manufacturing (AM) has the potential to transform the organisation of all the activities carried out by firms. The growing diffusion of these technologies is increasingly challenging multinational enterprises to reinvent their businesses. Accordingly, many scholars argue that AM may reduce countries’ participation in global value chains (GVCs) or, at least, affect GVCs’ geography, length and further developments. However, so far, the lack of available data on the real worldwide diffusion of these technologies has precluded the possibility to study this phenomenon from an empirical standpoint.

This study investigates AM technologies, with a particular focus on their possible impact on GVCs, in the framework of the current debate in international business. In order to examine this relationship and overcome the lack of adoption data, the authors identify a potential proxy of AM diffusion – that is, patenting activity. Coherently, the authors employ this proxy and a country-level measure of GVC participation (i.e., the Share of Re-Exported Inputs on Total Imported Inputs) to empirically investigate the role of AM in influencing countries’ participation to GVCs. This country-level analysis is focussed on three specific industries and the aggregate economy in 58 countries for the period 2000–2014.

The results show that AM decreases a country’s participation in GVCs, both at the country level and, in particular, in the sectors which are more likely to be affected by AM technologies. This evidence suggests that this phenomenon might be induced by a decreasing reliance on intermediates processed abroad, hence an increasing importance of domestic goods, manufactured via AM.

The digital economy has significantly altered the way business is conducted and financial information is communicated. A rapidly growing number of organizations are conducting business and publishing business and financial reports online and in real-time. Real-time financial reporting is likely to necessitate continuous auditing to provide continuous assurance about the quality and credibility of the information presented. The audit process has, by necessity, evolved from a conventional manual audit to computer-based auditing and is now confronted with creating continuous electronic audits. Rapidly emerging information technology and demands for more timely communication of information to business stakeholders requires auditors to invent new ways to continuously monitor, gather, and analyze audit evidence. Continuous auditing is defined here as “a comprehensive electronic audit process that enables auditors to provide some degree of assurance on continuous information simultaneously with, or shortly after, the disclosure of the information.” This paper is based on a review of related literature, innovative continuous auditing applications, and the experiences of the authors. An approach for building continuous audit capacity is presented and audit data warehouses and data marts are described. Ever improving technology suggests that the real-time exchange of sensitive financial data will place constant pressure on auditors to update audit techniques. Most of the new techniques that will be required will involve creation of new software and audit models. Future research should focus on how continuous auditing could be constantly improved in various auditing domains including assurance, attestation, and audit services.

Internet of things (IoT) and Big Data, which are among the pioneers of Industry 4.0 technologies, have gained great importance in recent years. Within the scope of Industry 4.0, organizations are trying to undertake digital transformation by adapting these two important technologies to their business processes. Undoubtedly, while this transformation provides great advantages for organizations in terms of management, organization, and marketing, it also carries disadvantages such as difficulties and complexity regarding the privacy of the collected data and systems. However, IoT and Big Data Analytics play a role as restructuring factors for products, services, and especially business processes. This study discusses the impact of IoT and Big Data Analytics on the digital transformation of organizations from the perspective of corporate culture, marketing, and management. Simultaneously, the effects of the COVID-19 epidemic that the world has experienced recently, on the business of institutions, are also discussed. By adopting IoT and Big Data Analytics, the attitudes, benefits, and challenges of the institutions that are or are not willing to realize digital transformation during the epidemic process are examined, and a projection is tried to be made to the post-COVID-19 period. While the study specifically highlights the positive effects of IoT and Big Data Analytics on the business, it sheds light on available opportunities and provides useful implications for managers and marketers.

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.

Digitalisation has become a central theme in the current economic and policy debate. Large digital and tech multinational enterprises (MNEs) are gaining an outsized role in the global economy. Also, the adoption of advanced digital technologies across all industries is fundamentally changing production processes. Both these (interrelated) phenomena have profound implications for economic structures, employment, inequality and development and industrialisation opportunities. This chapter analyses the international production and investment (i.e., foreign direct investment [FDI]) implications of the digital economy. First, it empirically documents significant differences in internationalisation patterns between the largest digital MNEs and traditional MNEs; particularly, the tendency of digital MNEs to exhibit an asset-light international footprint. Second, it argues that the powerful transformational forces related to digital adoption and the new industrial revolution have the potential to change international production more broadly, favouring a shift towards internationalisation models characterised by decentralised production, accelerated servicification and extended disintermediation. The chapter concludes with investment policy implications and a number of questions for future research.

The growing turbulence of the external environment has progressively led to the necessity by organizations of exploiting new opportunities provided by data-driven approaches for supporting the even more complex decision-making processes. The new digital environment has led to the development and adoption of innovative approaches; also in the urban context which has always been characterized by different, interconnected, and dynamic dimensions. Urban governance models have been enhanced by smart technologies, which act as enablers of advanced services and foster connections between citizens, public and private organizations, and decision-makers. In this context, the objective of this chapter is to examine the role of data-driven approaches in the urban context during the chaotic and high variable circumstances related to the diffusion of the Coronavirus disease 2019 (Covid-19). Thanks to the adoption of the co-evolutionary perspective, a cycle in urban governance decision-making approach based on digital technologies is depicted and its contribution for managing the ongoing Covid-19 is traced. The results of the analysis highlight how the data-driven approach supports urban decision-making process and shed light on the co-evolutionary perspective as heuristic device to map the interactions settled in the networks between local governments, data-driven technologies, and citizens. In this sense, this chapter offers interesting insights, potentially capable of generating useful implications for both researchers and professionals in the public sector.