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Author Jeff Resnick explores the vulnerability of firms whose executives fail to manage the perceptions of their company – indeed, their corporate reputation – with as much rigor as they apply to managing financial, operational or technology risk. Mr Resnick offers up a snapshot of current attitudes towards managing corporate reputation, including research underscoring CEOs perception that it has become far more important than it was several years ago, and juxtaposes this with data that indicates US investors remain as distrustful of corporate ethics today as they were in the heated moment of corporate scandals. Mr Resnick then presents a provocative case for better managing reputation – a company’s most critical important intangible asset – in a more strategic manner. Finally, he provides readers with steps for effectively monitoring reputational risk. His monitoring system focuses on a multi‐stakeholder measurement approach that more fully informs executives’ decisions concerning their corporate reputation. Critical to making his case, Mr Resnick uses examples from recently completed reputational research, focusing on the electric power industry and conducted by an independent reputation‐rating agency.

This chapter uses Goffman’s concept of total institutions in a comparative case study approach to explore the role of psychotropic drugs in the process of transinstitutionalization.

This chapter interprets psychotropic drug use across four institutionalized contexts in the United States: the active-duty U.S. military, nursing homes and long-term care facilities, state and federal prisons, and the child welfare system.

This chapter documents a major unintended consequence of transinstitutionalization – the questionable distribution of psychotropics among vulnerable populations. The patterns of psychotropic use we synthesize suggest that total institutions are engaging in ethically and medically questionable practices and that psychotropics are being used to serve the bureaucratic imperatives for social control in the era of transinstitutionalization.

Psychotropic prescribing practices require close surveillance and increased scrutiny in institutional settings in the United States. The flows of mentally ill people through a vast network of total institutions raises questions about the wisdom and unintended consequences of psychotropic distribution to vulnerable populations, despite health policy makers’ efforts regulating their distribution. Medical sociologists must examine trans-institutional power arrangements that converge around the mental health of vulnerable groups.

This is the first synthesis and interpretive review of psychotropic use patterns across institutional systems in the United States. This chapter will be of value to medical sociologists, mental health professionals and administrators, pharmacologists, health system pharmacists, and sociological theorists.

Assessment is used to describe the process of gathering information to make judgments about how well someone has performed, how much progress has been made, and how much potential someone has. In other words, gathering information and forming judgments are both indispensable to good teaching. Educational institutions, government agencies, and professional associations are placing increasing emphasis on assessing performance in relevant areas of their domains. In this chapter, several issues important to the establishment of appropriate assessment procedures and the potential uses of both traditional and innovative assessment techniques are discussed. Finally, the limitations of traditional assessment techniques are considered, followed by the future perspectives on assessment techniques.

The authors use experiential learning theories to examine college students’ acquisition of tax knowledge and tax literacy. Tax knowledge is important because taxation affects virtually all adults, college students are often employed and subject to individual taxation, and understanding taxation and tax planning has both current and future implications for individuals’ financial well-being. Further, taxation is a key policy issue, and college student voters have the potential to impact tax policy choices. The results of this study show that real-world experiences improve college students’ understanding of tax concepts; this relationship holds for overall understanding and for understanding both current tax issues and tax issues that will have an impact in the future. The authors predict and find that a student’s socioeconomic status is positively related to understanding of tax concepts. The authors also find that the level of understanding of tax concepts is still limited; many students do not have a strong knowledge of tax concepts. The relatively low levels of understanding may have implications for structuring college curricula to improve tax literacy.

Certain elements of Hayek’s work are prominent precursors to the modern field of complex adaptive systems, including his ideas on spontaneous order, his focus on market processes, his contrast between designing and gardening, and his own framing of complex systems. Conceptually, he was well ahead of his time, prescient in his formulation of novel ways to think about economies and societies. Technically, the fact that he did not mathematically formalize most of the notions he developed makes his insights hard to incorporate unambiguously into models. However, because so much of his work is divorced from the simplistic models proffered by early mathematical economics, it stands as fertile ground for complex systems researchers today. I suggest that Austrian economists can create a progressive research program by building models of these Hayekian ideas, and thereby gain traction within the economics profession. Instead of mathematical models the suite of techniques and tools known as agent-based computing seems particularly well-suited to addressing traditional Austrian topics like money, business cycles, coordination, market processes, and so on, while staying faithful to the methodological individualism and bottom-up perspective that underpin the entire school of thought.

Addressing occupational stress and fostering employee wellness helps meet a host of organizational stakeholder expectations including high quality of work life (employees), reasonable return on investment (investors), increased productivity (management), and competitiveness (owners). Despite being dynamic in nature, stress and wellness are often studied using a static perspective. One reason for the scarcity of dynamic empirical research is the limited knowledge and use of the tools available to assess change over time. To address this limitation, four tools used to assess change and dynamics of occupational stress and well-being are described: growth models, latent change score models, spectral analysis, and computational modeling. First, we begin by discussing growth curve models and then transition to latent change score models. We then expand into spectral analysis, a tool used to determine cycles of ups and downs that repeat regularly. Last, computational modeling is discussed, where computers and simulations are used to understand a dynamic process. For each tool, we give examples of how they have been used, make recommendations for future use, and provide readers with suggestions and references for how to complete analyses in software and programs, most of which are freely available (i.e., R, Vensim).

The applications of artificial intelligence (AI), natural language processing and machine learning in e-commerce are growing. Recommender systems (RSs) are interaction-based technologies based on AI that can offer recommendations for products for use or of interest to a potential consumer. Curiosity, focused immersion and temporal dissociation are often treated as the dimensions of cognitive absorption, so exploring them separately can provide valuable insights into their dynamics. The paper aims to determine the effect of the cognitive absorption dimensions namely focused immersion, temporal dissociation and curiosity independently on RSs continuous use intention.

A quantitative research design was used to explore the effect of dimensions of cognitive absorption on AI-driven RSs continuous use intention in e-commerce. Data were gathered from 452 active users of Amazon through an online cross-sectional survey and were analysed using partial least squares structural equation modelling.

The findings indicated that curiosity and focused immersion directly affect RSs continuous use intention, but temporal dissociation does not affect RSs continuous use intention.

The current research focused on Amazon’s RSs that use AI and machine learning techniques. The research aimed to empirically explore the effects of the dimensions of cognitive absorption separately on AI-driven RSs continuous use intention in e-commerce. This research may be of interest to executives working in both public and private industries to better harness the potential of recommendations driven by AI to maximize RSs’ reuse and to enhance customer loyalty.