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This chapter provides valuable insights around the entrepreneurial landscapes of the twenty-first century, as well as the inherent stressors that may impact entrepreneurial well-being and performance. As the World Health Organization declares stress as the epidemic of the twenty-first century, entrepreneurs face increasingly volatile, uncertain, complex, and ambiguous contexts, or what the Army War College refers to as “VUCA” environments. In these contexts, traditional models of leadership and stress management in entrepreneurship require tapping into new, sometimes previously untapped and underdeveloped resources. Resources such as Psychological Capital (Luthans, Youssef-Morgan, & Avolio, 2007), Algorithmic Leadership (Harms & Han, 2018), and wearable biometric technologies (Tsuji, Sato, Yano, Broad, & Luthans, 2019) that exploit big data analytics powered by artificial intelligence will be invaluable to entrepreneurs as they manage stress, and build and maintain their competitive edges.

This chapter critically examines whether it may be possible to create an AI-based authentic leader, questioning the inherent contradiction between artificial and authentic. The authors pose central research questions: Does the application of AI – even just as a powerful resource – challenge the tenets of authentic leadership? What are the possibilities and limitations of the concept of authenticity in AI-based management systems? Moreover, with the help of three vignettes illustrating practical applications of AI-based systems in leadership and management tasks, the authors illustrate how technology may be used to either control or empower workers and leaders. The authors call for research to assess whether the search for authenticity in AI-based leadership could lead anywhere, warning that it could entrap us in unresolvable existential and conceptual ambiguity, ultimately diverting our focus from the essence of leadership altogether.

Despite widespread interest in the gig economy, academic research on the topic has lagged behind. The present chapter applies organizational theory and research to compose a working model for understanding participation in the gig economy and how gig work may impact worker health and well-being. Drawing from past research this chapter defines the gig economy in all its diversity and advances a framework for understanding why individuals enter into gig economy. Next, the authors discuss how various characteristics of the gig economy and gig workers can be understood as both demands and resources that influence how gig work is likely to be experienced by the individual. To understand how these characteristics are likely to influence worker health and well-being, we draw from past research on alternative work arrangements and entrepreneurship, as well as the limited extant research on the gig economy. Finally, a research agenda is proposed to spur much needed research on the gig economy and its workers.

This paper aims to characterize a sample of Lean Six Sigma (LSS) projects in healthcare settings and discuss some specificities of operational excellence (OPEX) initiatives in hospitals and healthcare organizations in the USA.

A content analysis involving a sample of 23 documents shared by US hospitals was performed in order to achieve the research objectives. Such analysis was based on a conceptual framework developed from the literature review. It was also applied to a quantitative approach, including descriptive statistics, hypothesis testing and correspondence analysis that supported the research.

Most LSSH projects were focused on business transformation and strategic improvements. Simple techniques and tools were predominant such as descriptive statistics, process mapping, 5S and spaghetti charts, usually implemented by Green Belts and Black Belts through the define, measure, analyze, improve and control (DMAIC) method. In addition to the expressive findings reported, these projects' results have been aligned with lead time and operational cost reduction, quality improvement and capacity increase.

The study adds knowledge to the OPEX literature by analyzing the Lean Six Sigma healthcare (LSSH) in hospitals and healthcare institutions in the USA. It also demonstrates that different approaches, such as the kaizen event and DMAIC project show different results according to some techniques and tools applied in the hospital environment.

The empirical evidence presented in this study provides scenery of the LSS practices in the healthcare settings, highlighting the implementation areas, outcomes, tools and techniques mostly used in the North American healthcare institutions.

This chapter considers how social capital is evolving in the era of globalization today especially under COVID-19 pandemic conditions globally. Definitions of social capital have varied: some broad others narrow. The Organisation for Economic Co-operation and Development (OECD), for example, currently has a broad research project on social capital. These researchers have defined social capital as comprising four key areas. These areas are:

• Personal relationships, referring to the structure of people’s social networks.

• Depth and breadth of social network support available to each person in their networks.

• Civic engagement activities such as volunteering and community action.

• Beliefs, attitudes, and action frames of reference such as trust and cooperative norms, of reciprocity.

Personal relationships, referring to the structure of people’s social networks.

Depth and breadth of social network support available to each person in their networks.

Civic engagement activities such as volunteering and community action.

Beliefs, attitudes, and action frames of reference such as trust and cooperative norms, of reciprocity.

Thus, there are tacit as well as explicit aspects of social capital though some of these may seldom if ever be articulated and delineated for others.

As Claridge (2020) indicates, there are distinct, but dynamically interrelated, levels of social capital. These levels range between the micro- or individual level. That is personal “habitus” – which Bourdieu (1977) describes as a person’s “taken-for-granted” – ways of being, thinking, and reacting to events and to other people. Then, the next level above the individual is the meso-level, which is “how things are done here amongst us,” that is, the level of a group’s social capital (such as a team, or an organizational or local community level). Lastly, and wider still, the top level is the macro- or cultural-societal structural level of the nation.

The social capital systems in any location encompasses sets of acceptable or culturally legitimated behavioral norms and rules of engagement between community members which include types of greetings, forms of cooperation, communications, and signaling between diverse members. Thus, social capital may be present in the tacit, or unspoken/taken-for-granted assumptions as much as in explicit or formalized codes of behavior. The forms of social interactions at each of the levels may have norms for specific types communication and address in particular sets of circumstances such as social gatherings at home or in public or when attending communal gatherings or ceremonial occasions, or between people of different social status. Social capital generates trust and social cohesion and some level of cultural and attitudinal consensus and interest, which in turn delivers a stable environment for the local community or larger society, business, or the economy.

• (1)

  Social capital is the development of relationships that help contribute to a more efficient production of goods and services as there is embedded trust, embodied in practice, that is, in behaviors regarded as trustworthy and socially helpful.

• (2)

  There are three types of social capital at each level of interaction – bonding, bridging, and linking. Bridging and linking are similar though they operate in different directions socially. Bonding social capital describes the connections between people in similar social levels or groups of people who share the same characteristic norms and beliefs, whereas linking social capital facilitates connects between different groups.

• (3)

  Social capital can therefore make or break businesses, especially small businesses or start-ups as those with the right kind and amount of social capital, such as good connections and contacts in the trade or profession, can usually thrive as they are able to get work done more quickly, effectively, and efficiently. Conversely, a lack of social capital denoting some distrust between groups can undermine social stability.

Social capital is the development of relationships that help contribute to a more efficient production of goods and services as there is embedded trust, embodied in practice, that is, in behaviors regarded as trustworthy and socially helpful.

There are three types of social capital at each level of interaction – bonding, bridging, and linking. Bridging and linking are similar though they operate in different directions socially. Bonding social capital describes the connections between people in similar social levels or groups of people who share the same characteristic norms and beliefs, whereas linking social capital facilitates connects between different groups.

Social capital can therefore make or break businesses, especially small businesses or start-ups as those with the right kind and amount of social capital, such as good connections and contacts in the trade or profession, can usually thrive as they are able to get work done more quickly, effectively, and efficiently. Conversely, a lack of social capital denoting some distrust between groups can undermine social stability.

The meso- or macro-levels of bridging type social capital ensures acceptance of established social roles locally and linking forms of social capital boost levels of acceptance of other roles such as those of leaders and followers.

All three forms of social capital and the three levels are not mutually exclusive but instead are mutually inclusive and interrelated. That is, they co-evolve, each impacting the other while dynamically interacting with the social capital anchored as it is emerging from the complex and interwoven fields of tacit and explicit norms of social interaction underpinning each of the levels of interaction over time.