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The COVID-19 pandemic has disrupted the ‘real’ world and substantially impacted the virtual world and thus the Internet ecosystem. It has caused a significant exogenous shock that offers a wealth of natural experiments and produced new data about broadband, clouds, and the Internet in times of crisis. In this chapter, we characterise and evaluate the evolving impact of the global COVID-19 crisis on traffic patterns and loads and the impact of those on Internet performance from multiple perspectives. While we place a particular focus on deriving insights into how we can better respond to crises and better plan for the post-COVID-19 ‘new normal’, we analyse the impact on and the responses by different actors of the Internet ecosystem across different jurisdictions. With a focus on the USA and Europe, we examine the responses of both public and private actors, with the latter including content and cloud providers, content delivery networks, and Internet service providers (ISPs). This chapter makes two contributions: first, we derive lessons learned for a future post-COVID-19 world to inform non-networking spheres and policy-making; second, the insights gained assist the networking community in better planning for the future.

This chapter is based on the findings of the empirical material gathered in Finland and Sweden through interviews with education and audiovisual (AV) media actors and policymakers in 2017–2018. The aim of the chapter is to discuss the innovation systems of the education sector and Finland and Sweden in general, compare the sectoral innovation models of the two sectors, and conclude with discussing the resulting challenges for policymakers. Our results show that a new EdTech sector employing the competences of the education, information and communication technology, and AV media sectors has begun to emerge and actors in the both countries have eagerly taken actions to boost its development as a business and export field. We discuss the reasons and consequences of this development.

This study aims to focus on a reinforcement supplier’s efforts to diffuse solutions, more or less innovative, in the construction sector to gain understanding of what facilitates and complicates innovation diffusion from a supplier perspective.

The interpretative research presented builds on 28 semi-structured interviews with the supplier and its customers and document studies. The research emphasizes dynamics in the diffusion process and rests on the assumption that the innovation content, innovation context and the innovation process interacts in the diffusion process.

The findings and the contribution from the study provide significant details concerning how the dimensions interact and how the diffusion process may unfold over time, but also that different solutions interact to push diffusion forward.

The study relates to one supplier’s work and the interplay implies uniqueness in different cases. Studies in other contexts could, therefore, also be suitable to develop findings and their transferability.

The study provides understanding for suppliers diffusing innovations in construction on how to act.

A major contribution from the study is that it puts emphasis on how the diffusion process proceeds in interaction with its content and context and problematizes this dimension. Furthermore, the importance of nuancing sub-contexts to display decisive factors in the diffusion process is emphasized.

Organizations across industries are increasingly using Artificial Intelligence (AI) systems to support their innovation processes, supply chains, marketing and sales and other business functions. Implementing AI, firms report efficiency gains from automation and enhanced decision-making thanks to more relevant, accurate and timely predictions. By exposing the benefits of digitizing everything, COVID-19 has only accelerated these processes. Recognizing the growing importance of AI and its pervasive impact, this chapter defines the “social value of AI” as the combined value derived from AI adoption by multiple stakeholders of an organization. To this end, we discuss the benefits and costs of AI for a business-to-business (B2B) firm and its internal, external and societal stakeholders. Being mindful of legal and ethical concerns, we expect the social value of AI to increase over time as the barriers for adoption go down, technology costs decrease, and more stakeholders capture the value from AI. We identify the contributions to the social value of AI, by highlighting the benefits of AI for different actors in the organization, business consumers, supply chain partners and society at large. This chapter also offers future research opportunities, as well as practical implications of the AI adoption by a variety of stakeholders.

This chapter focuses on clarifying the cooperation and convergence between tourism and audiovisual (AV) sectors in Hamburg and Riga. In light of increasingly easier and more accessible travel, the tourism sector is a growing trend in most countries and regions. To what extent does this affect cooperation with the AV sector? The chapter gives an overview of different types of cooperation in these regions and brings out the main obstacles for innovation. When describing the innovation systems, focus is put on institutional frameworks in these two regions. We end by arguing that raising the demand for innovation in the tourism sector is a real challenge and demonstrating that the public sector plays an important role in driving the cross-innovation processes between the observed sectors.

In times of converging and diversifying audiovisual (AV) industries, digitising health sector and the increasing phenomenon of cross-sectoral innovation, the question arises about the state of affairs between the health and AV sectors. The chapter aims to explore what the main modes of cross-sectoral cooperation between the health and AV sectors are and what supports and hinders the emergence of a related cross-innovation system. The chapter introduces two case studies carried out in Estonia and the wider Aarhus region (Midtjylland) in Denmark. At each site representatives of the main stakeholders of both sectors were interviewed – policy makers, entrepreneurs, educators and professionals. The results demonstrate the crucial role of path-dependencies – in terms of both hindering and enabling cross-sectoral dialogues – and also the importance of effective coordination in supporting cross-innovation.

This chapter establishes the conceptual and analytic framework for the book. It relates not only to much of the existing work in evolutionary and institutional economics, but also to work in cultural science and cultural semiotics domains as well as in media convergence and transmedia studies. The central concept it first deploys is ‘innovation systems’ as applied in national, regional, international and sectoral contexts. It then builds on the general theory of economic evolution by Kurt Dopfer and Jason Potts and reviews the tools this theory provides to carry out a meso-level analysis of industries co-innovating and converging. It then proposes a new concept – ‘cross-innovation’ – to refer to the emergence of new structures and ‘rules’ at the boundaries of existing industries.

Digital technologies have fundamentally changed organizations, industries, and even the society. Although institutional theory provides rich array of perspectives to both the content and dynamics of such changes, research at the intersection of institutional scholarship and digitalization has remained scarce. In this essay, I draw on the institutional logics perspective to elaborate digitalization as involving a new set of interconnected managerial beliefs and norms, organizational practices, and diverse material and social structures that together complement and challenge the established logics in organizations and institutional fields. I draw attention to two central organizing principles in the logic of digitalization: the pursuit of digital omniscience – the efforts to represent and conceive the world through digital data – and digital omnipotence – the efforts to bring activities inside and outside organizations under the control of information systems. I conclude the essay by elaborating how the institutional logics perspective can help understand organization-level efforts to leverage digitalization by incumbent corporations and new digital-native companies.

This chapter highlights how implementing circular economy principles can help companies working with sustainability to move from a reductionist and waste management approach to marketing competitive circular value propositions that intentionally design out waste (e.g. emissions and pollution) by rethinking, reinventing and redesigning the value chain. Schijvens, a Dutch family-owned corporate fashion textile company, acts as a case for exemplifying successful implementation of circular economy principles as a marketing strategy in a sector that struggles with finding solutions to the ethical challenges of producing and marketing textile fashion. The textile industry has, for many years, been accused of production that is based on environmentally harmful processes and conditions that are not socially fair. Circular economy principles provide a range of suggestions to address the ethical challenges occurring from covering the human needs of having clothes to wear. Yet, implementing circular economy principles is not a panacea. It is not only a question of delivering a technological quick fix but also a question of managing the new processes and human mindset guiding the actions in the value chain. This chapter, therefore, outlines reasons for a different perspective on the traditional linear value chain and related implications managers face when undertaking a journey from sustainability based on a reductionist approach to a closed-loop approach. It is argued that implementing circular economy principles by pro-actively managing the value chain processes based on eco-centric dynamic capabilities can provide even more radical changes than the incremental reductionist approach often associated with being a green sustainable company.

Smart industry initiatives focus on intelligent and interconnected cyber-physical systems. These initiatives develop complex technical architectures that integrate heterogenous technologies, causing significant organizational complexity. Tapping into the digital capabilities of distant partners while capturing profit from such innovation is demanding. Furthermore, firms often need to establish and orchestrate inter-organizational collaborations without prior relations or established trust. As a result, smart industry initiatives bring together disparate organizational forms and institutional environments, distinctive knowledge bases, and geographically dispersed organizations. We conceptualize this organizational capability as ‘distant capabilities integration’. This research explores the governance mechanisms that support such integration and their relation to value capture. We analyse 11 IoT case studies organized in three categories (process, product and technologies) of smart industry initiatives. Building on existing literature, we consider different ways to describe distance, including knowledge heterogeneity and organizational, geographical, institutional, cultural and cognitive distance. Finally, we describe the governance mode appropriate for upstream (developing foundational technologies) and downstream (leveraging existing distant technologies) smart industry initiatives.