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The estimates by both Russian and foreign authoritative organizations show the signs of the transition from stagnation to moderate growth, and this process should be accounted for by the largest transnational corporations (TNCs) traditionally active in Russia, such as Coca-Cola, Nestle, Adidas, and others. However, despite the optimistic predictions of many analysts, macroeconomic (and geopolitical) situation in the world remains unstable. Russia is aiming at the trajectory of economic growth in the face of continuing pressure from the macroeconomic, foreign policy, and internal institutional factors. In response to this strain, the government has intensified efforts to implement the strategy of import substitution, which objectively affects the interests of TNCs at the Russian markets. The objective process of import substitution creates both challenges and opportunities for TNCs. Problems are connected with a direct displacement of their traditional products and brands due to both administrative restrictions and a change in consumer attitudes and preferences (“Buy Russian” approach gaining momentum). However, the opportunities lie within the participation in the future satiation of demand and fulfilling the consumer expectations during the upcoming revival of the positive economic dynamics. It can generally be noted that the TNCs should integrate into a specific project of import substitution in the postcrisis environment despite the variety of their corporate policies. This relatively new situation for TNCs in the context of general economic and geopolitical instability requires scenario modeling of the possible strategies of TNCs depending on both the overall macroeconomic and political situation in the country, as well as the internal factors affecting various commodity markets in Russia.

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.

The origins of the SCS can be traced to the civil service established by the English East India Company (EIC) in 1786, when the EIC began its operations in Malaya with the acquisition of Penang as a settlement from the Sultan of Kedah (Tilman, 1964, p. 40; Jones, 1953, p. 7). The EIC used the term “civil service” to distinguish its civilian employees from those working in the military, maritime, and ecclesiastical organizations. There were three types of civil servants then: those who were covenanted, i.e., occupying senior positions requiring a bond of 500 British pounds as security to ensure the performance of their duties; those who were uncovenanted; and extra-covenanted officers who were granted covenants locally because of their exceptional administrative capabilities (Blunt, 1937, pp. 1–2).

This chapter discusses some of the internationalisation (e.g. mergers and acquisitions, networks and strategic alliances) of household names into Africa – especially in the aftermath two simultaneous events – that is, the African Continental Free Trade Area and British exit from the European Union (Brexit) with or without a trade deal. This chapter also touches upon the need for inter-functional integration in driving forward Africa’s creative industries – notably the intersections between entrepreneurship and innovation within which business models in digital publishing and software development, as well as localisation of animation and games in Africa have been seen.

Engagement, motivation, and persistence are usually associated with positive outcomes. However, too much of it can overtax our psychophysiological system and put it at risk. On the basis of a neuro-dynamic personality and self-regulation model, we explain the neurobehavioral mechanisms presumably underlying engagement and how engagement, when overtaxing the individual, becomes automatically inhibited for reasons of protection. We explain how different intensities and patterns of engagement may relate to personality traits such as Self-directedness, Conscientiousness, Drive for Reward, and Absorption, which we conceive of as functions or strategies of adaptive neurobehavioral systems. We describe how protective inhibitions and personality traits contribute to phenomena such as disengagement and increased effort-sense in chronic fatigue conditions, which often affect professions involving high socio-emotional interactions. By doing so we adduce evidence on hemispheric asymmetry of motivation, neuromodulation by dopamine, self-determination, task engagement, and physiological disengagement. Not least, we discuss educational implications of our model.

In this chapter, we apply APPNIE to two case studies, BIOerg srl and LiMiX srl, which are innovative start-ups born in the Marche Region in Italy. The choice to analyse two companies in the same region is based on the fact that the surrounding ecosystem of innovation and entrepreneurship has a strong impact on the birth and subsequent development of innovative start-ups. Using these two case studies, this chapter shows the differences between SWOT and APPNIE analyses.