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Most companies struggle to meet the dual goals of sustaining competitive advantage and ensuring high resilience during crises. Those that do, research tells, adapt their operational practices along the crisis cycle, combining an effective cost approach at the start of a crisis, while quickly relaunching their investment to grow ahead of competition, just when they learn that the crisis is peaking, and not too late, when the crisis is over. This cycle alignment is possibly the crucial, but not the only, factor for success. We update early research to show that companies succeeding in this dual objective also take a proactive strategy approach of capturing the complementarities between both performance and resilience during a period of high turbulence. This complementarity relies on exploiting dynamic capabilities common to both resilience and performance, and on leveraging the resilience process as a foundation for strategic renewal going forward.

The research relies on case studies, complemented by an original survey sample, collected just after the peak of the covid-19 pandemic, of 4,000 multinational firms spread across 18 industries termed NACE2, a statistical classification of economic activities in the European Community. This study included 10 countries outside the European Community. The sample collects information on five core enterprise capabilities (agility, innovativeness, active ecosystem play and digital/sustainability maturity, flexible work practices) and uses a variety of quantitative techniques to assess that existence and size of synergies captured by firms.

Companies meeting the dual goal of resilience and performance are more than doubling their rate of profit growth relatively to peers, after the peak of the crisis, by leveraging of synergies between performance and resilience.

The topic is essential for management, given the elevated turbulence. This research confirms that resilience and performance are synergistic and helps make companies using each crisis boost performance forward.

The purpose of this chapter is to determine the basic characteristics of information economy, including consideration of the theoretical features and distinguishing the analytical aspects of functioning of this phenomenon under modern conditions. The authors offer a hypothesis that basic characteristics of information economy are transformed under the influence of digitization and the change in telecommunication interaction.

The following methodological tools were used: analytical introspection (determining estimate phenomena of the studied object with the help of practical materials analysis), theoretical cognition (grouping and synthesis of scientific studies of foreign and Russian scholars in the sphere of information economy), and group evaluation of phenomena (studying the modern regularities of information economy development).

The following conclusions are made: the theory of information economy is based on presenting information as a tool of economy management (information is the main economic value that creates national wealth); the modern idea of information economy is connected to the aspects of digital and telecommunication interaction; the information economy of the twenty-first century is aimed at monetization of information on households; and a new basic direction of information economy is information and program economy.

The sphere of application of the received results is rather wide. They will be of interest for practitioners, government employees, and researchers in the sphere of macro-economic development of the country during the period of transformation of the paradigm of economic growth. The main direction of future research is substantiation of approaches to formation of a new economic thought based on information and digital technologies.

This paper explores whether workers share innovation returns and how the size of innovation returns is affected by market conditions. Using a panel data of Spanish manufacturing firms during the period from 1990 to 1993, we answer affirmatively to both questions. Product and process innovations both generate returns, but such returns are higher for process innovations. The size of innovation returns seems to be affected positively by demand growth, by product standardization, and by low product market concentration. The three empirical results are in agreement with the theoretical predictions, such as Schmoockler’s (1966) theory of demand‐pool innovation, the price‐elasticity of demand effects postulated by Kamien & Schwartz (1970), and the replacement effect suggested by Arrow (1962). At the time of generating returns, process innovations are more affected by market conditions than are other innovations.

Purpose: In recent times, ‘artificial intelligence (AI)’ has been pervasive even in organisations or at home. AI is defined as programming computers or other technological devices to act, react, respond, or assist the same way humans do. AI has undeniably made people’s lives easier. In organisations, the impact of AI is even more visible. The main aim of this chapter is to examine the significant role of future work skill’s (FWS) each component in the field of on-growing automation. The focus will be especially on emotional and social intelligence (ESI) (a key component of FWS) while adopting AI.

Need of the Study: In terms of human resource management (HRM), AI is useful for people management, payroll services, staff monitoring and improving the recruiting network, among other things. Even managers put their organisation’s job openings on the web and get applicant resumes electronically. People and employees in the organisation have become more advanced and innovative due to AI. A device obtains employee attendance, and human resource (HR) can track their employees and their organisation’s workforce data. HR has now been awarded more authority to manage and fix their employee’s problems because of AI. In a rapidly changing world, AI is affecting all aspects. AI is yearning to automate all of the jobs.

Methodology: Now a question arises how we can stay relevant in AI economic development? As humans, we learned that every issue is a problem of optimisation because we simply require human skills to develop, create and innovate new things. Therefore, researchers recognised that adopting sustainable growth skills encourages people to continue learning throughout their lives. Moreover, AI has enabled machines the ability to learn over time. Still, they will never be able to develop new ideas like human intelligence. A machine can use only one fixed data algorithm. Now humans have made significant progress in various fields with the help of FWS; without integrated computer sciences, brain science would not make such an outstanding achievement. On the other hand, human minds are masters of their intelligence, such as creativity, complex problem-solving, cognitive thinking, ESI and communication. Breakthrough human mind are masters of algorithms represented people have to understand new trends of technology around us, and the best way to move forward is to be aware, adapt and update skills.

Practical Implications: However, AI is required because, regardless of technological advancements, AI is leading Industry 4.0. The industry’s transformation is in 4.0, and hopefully, 5.0 will jump on board soon. Undoubtedly, AI should streamline the process and eliminate redundancy or administrative tasks.

Finding: AI can be more effective in organisations if they incorporate other FWS, particularly the soft human ESI skills, whereas AI is present everywhere, we can still not neglect FWS, especially ESI. So, this chapter highlights the important role of soft skills, that is, ESI and FWS, while adapting AI for an effective HRM.

Although Google had a stellar performance in Web search, many of its other services, such as Google Video, were less successful. This case describes how YouTube came to dominate the video market for user-generated content (UGC), while Google Video tried various entry strategies and ultimately failed, ending with the acquisition of YouTube. It also reviews the various competitors in the UGC market, chronicles the entry of established and new players in the area of professionally generated content (PGC), and outlines the key challenges related to monetizing the acquisition of YouTube for Google.

The case discusses when and how to enter winner-take-all markets characterized by very strong network externalities. It focuses on the strategies of new entrants vs. those of incumbents in adjacent industries that seek to leverage their resources and skills. Further, it sheds light on how new industries are created, how convergence is changing competitive forces, how important it is to be a first or late mover in new markets, and how successful entrants may struggle to achieve profitability.

This paper aims to offer a contextualized and multi-stakeholder perspective for creating a learning organization (LO) 2.0.

Based on a systematic review of the critiques of LO in the past three decades, this paper suggests some possible directions for the development of next-generation of LO (e.g. LO 2.0).

It is suggested that LO 2.0 should adopt a contextualized perspective by considering the social, organizational, cultural and industrial contexts to enhance the success of LO implementation and help fine-tune the universal LO model. Accordingly, LO 2.0 should adopt a multi-stakeholder perspective by incorporating multiple stakeholders during the process of design and implementation under the rationales of counteracting managerial dominance of low-power marginalized employees and mitigating the impacts of increased competition and technology advancement.

This paper provides some practical advice to business practitioners regarding how the practices of LO 2.0 can be adopted.

The study adds to the existing LO literature by further supporting and developing a contextualized and multi-stakeholder perspective to create the next generation of LO.