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The fourth industrial revolution and digital transformation have caused paradigm changes in the procedures of goods production and services through disruptive technologies, and they have formed new methods for business models. Health and medicine fields have been under the effect of these technology advancements. The concept of smart hospital is formed according to these technological transformations. The aim of this research, other than explanation of smart hospital components, is to present a model for evaluating a hospital readiness for becoming a smart hospital.

This research is an applied one, and has been carried out in three phases and according to design science research. Based on the previous studies, in the first phase, the components and technologies effecting a smart hospital are recognized. In the second phase, the extracted components are prioritized using type-2 fuzzy analytic hierarchical process based on the opinion of experts; later, the readiness model is designed. In the third phase, the presented model would be tested in a hospital.

The research results showed that the technologies of internet of things, robotics, artificial intelligence, radio-frequency identification as well as augmented and virtual reality had the most prominence in a smart hospital.

The innovation and originality of the forthcoming research is to explain the concept of smart hospital, to rank its components and to provide a model for evaluating the readiness of smart hospital. Contribution of this research in terms of theory explains the concept of smart hospital and in terms of application presents a model for assessing the readiness of smart hospitals.

This chapter addresses one of the most crucial areas for critical thinking: the morality of turbulent markets around the world. All of us are overwhelmed by such turbulent markets. Following Nassim Nicholas Taleb (2004, 2010), we distinguish between nonscalable industries (ordinary professions where income grows linearly, piecemeal or by marginal jumps) and scalable industries (extraordinary risk-prone professions where income grows in a nonlinear fashion, and by exponential jumps and fractures). Nonscalable industries generate tame and predictable markets of goods and services, while scalable industries regularly explode into behemoth virulent markets where rewards are disproportionately large compared to effort, and they are the major causes of turbulent financial markets that rock our world causing ever-widening inequities and inequalities. Part I describes both scalable and nonscalable markets in sufficient detail, including propensity of scalable industries to randomness, and the turbulent markets they create. Part II seeks understanding of moral responsibility of turbulent markets and discusses who should appropriate moral responsibility for turbulent markets and under what conditions. Part III synthesizes various theories of necessary and sufficient conditions for accepting or assigning moral responsibility. We also analyze the necessary and sufficient conditions for attribution of moral responsibility such as rationality, intentionality, autonomy or freedom, causality, accountability, and avoidability of various actors as moral agents or as moral persons. By grouping these conditions, we then derive some useful models for assigning moral responsibility to various entities such as individual executives, corporations, or joint bodies. We discuss the challenges and limitations of such models.

This study is a radical interactionist analysis of family conflict. Drawing on both a negotiated order perspective and Athen's theory of complex dominative encounters, this study analyzes the role that domination plays in conflicts among intimates. As the family engages in repeated conflicts over roles, the family also engages in negotiations over the family order, what role each party should play, interpretations of past events, and plans for the future. These conflicts take place against a backdrop of patriarchy that asymmetrically distributes power in the family to determine the family order. The data from this study come from a content analysis of mothers with substance use problems as depicted in the reality television show Intervention. The conflicts in these families reveal that these families develop a grinding family order in which families engaged in repeated conflict but also continued to operate as and identify as a family. These conflicts are shaped by and reinforce patriarchal expectations that mothers are central to family operation. The intervention at the end of each episode offered an opportunity for the family to engage in a concerted campaign to try to force the mother into treatment and reestablish the family order.

Using a GED-GARCH model to estimate monthly data from January 1990 to February 2022, we test whether gold acts as a hedge or safe haven asset in 10 countries. With a downturn of the stock market, gold can be viewed as a hedge and safe haven asset in the G7 countries. In the case of inflation, gold acts as a hedge and safe haven asset in the United States, United Kingdom, Canada, China, and Indonesia. For currency depreciation, oil price shock, economic policy uncertainty, and US volatility spillover, evidence finds that gold acts as a hedge and safe haven for all countries.

Homelessness has many causes and also is stigmatized in the United States, leading to much misunderstanding of its causes and what policy solutions may ameliorate the problem. The problem is of course getting worse and impacting many communities far removed from the West Coast cities the authors examine in this study. This analysis examines the socioeconomic variables influencing homelessness on the West Coast in recent years. The authors utilize a panel fixed effects model that explicitly includes measures of healthcare access and availability to account for the additional health risks faced by individuals who lack shelter. The authors estimate a spatial error model (SEM) in order to better understand the impacts that systemic shocks, such as the COVID-19 pandemic, have on a variety of factors that directly influence productivity and other measures of welfare such as income inequality, housing supply, healthcare investment, and homelessness.