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The author addresses the relationship between populism and authenticity in the contemporary era. The author argues that for populists, authenticity is more than an image-building strategy and instead is used strategically to maintain a powerful emotional connection with supporters that extends beyond election campaigns. The chapter also examines the rise of a distinct populist style (ordinariness, provocation, a certain kind of intimacy) that is used in opposition to an established political class. This style is often represented, and celebrated, through social media and increasingly defines what it means to be authentic in the political sphere.

Justice rules are standards that serve as criteria for formulating fairness judgments. Though justice rules play a role in the organizational justice literature, they have seldom been the subject of analysis in their own right. To address this limitation, we first consider three meta-theoretical dualities that are highlighted by justice rules – the distinction between justice versus fairness, indirect versus direct measurement, and normative versus descriptive paradigms. Second, we review existing justice rules and organize them into four types of justice: distributive (e.g., equity, equality), procedural (e.g., voice, consistent treatment), interpersonal (e.g., politeness, respectfulness), and informational (e.g., candor, timeliness). We also emphasize emergent rules that have not received sufficient research attention. Third, we consider various computation models purporting to explain how justice rules are assessed and aggregated to form fairness judgments. Fourth and last, we conclude by reviewing research that enriches our understanding of justice rules by showing how they are cognitively processed. We observe that there are a number of influences on fairness judgments, and situations exist in which individuals do not systematically consider justice rules.

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 literature review is on advanced computer analytics, which is a major trend in the field of Human Resource Management (HRM). The authors focus specifically on computer-assisted text analysis (CATA) because text data are a prevalent yet vastly underutilized data source in organizations. The authors gathered 341 articles that use, review, or promote CATA in the management literature. This review complements existing reviews in several ways including an emphasis on CATA in the management literature, a description of the types of software and their advantages, and a unique emphasis on findings in employment. This examination of CATA relative to employment is based on 66 studies (of the 341) that bear on measuring constructs potentially relevant to hiring decisions. The authors also briefly consider the broader machine learning literature using CATA outside management (e.g., data science) to derive relevant insights for management scholars. Finally, the authors discuss the main challenges when using CATA for employment, and provide recommendations on how to manage such challenges. In all, the authors hope to demystify and encourage the use of CATA in HRM scholarship.

The recent rise of nonperforming loans (NPLs) in some Asian economies calls for close analysis of the determinants, the potential macrofinancial feedback effects, and the implications for financial stability in the region. Using a dynamic panel model, we assess the determinants of the evolution of bank-specific NPLs in Asia and find that macroeconomic conditions and bank-specific factors – such as rapid credit growth and excessive bank lending – contribute to the buildup of NPLs. Further, a panel vector autoregression (VAR) analysis of macrofinancial implications of NPLs in emerging Asia offers significant evidence for feedback effects of NPLs on the real economy and financial variables. Impulse response functions demonstrate that a rising NPL ratio decreases the GDP growth, credit supply and increases the unemployment rate. Our findings underline the importance of considering policy options to swiftly and effectively manage and respond to a buildup of NPLs. The national and regional mechanisms underlying NPL resolution are important for safeguarding financial stability in an increasingly interconnected global financial system.

Behavior problems are common in toddlers and preschoolers. Richman, Stevenson, and Graham (1975) identified difficulties with eating, sleeping, toileting, temper, fears, peer relations, and activity as typical in this young population. While all young children should be expected to experience behavior problems as part of their normal development, an ongoing challenge in the field has been to determine when these “normal” developmental problems rise to the level of being considered “clinical” behavior problems (Keenan & Wakschlag, 2000). For example, when does a two-year-old child's tantrum behavior, a three-year-old's urinary accidents, and a four-year-old's defiance become clinically significant? To answer these questions, clinicians must examine the frequency, intensity, and durability of these difficulties, their potential to cause injury to the child or others, the extent to which they interfere with the child development, and the degree to which they disrupt the lives of their siblings, caregivers, peers, teachers, and others.

Research has consistently shown that the children of business owners are more likely to become business owners themselves. However, what mechanism(s) underlies this intergenerational correlation is still not clear. In this research I assess the importance of several mechanisms proposed to drive the children of business owners to expect to become business owners.

Quantitative analyses of representative data from the 1988 to 1992 National Education Longitudinal Study are employed.

Results are inconsistent with arguments asserting that the children of business owners expect to become business owners because of: the transmission of human capital or financial capital; the expectation of inheriting a business; a heightened awareness of the viability of business ownership; or preferences for having lots of money, leisure time, being successful in work, or steady employment. Findings are consistent with the notion that the intergenerational correlation in business ownership is a result of shared preferences and/or traits, and this effect is particularly strong when accompanied by awareness of paternal business ownership.

Identifying which mechanism underlies the intergenerational transmission may inform how to increase rates of business ownership, particularly among underrepresented groups, which is a matter of increasing policy interest. However, our understanding is limited because: the intergenerational transfer is consistent with numerous mechanisms; and employment outcomes are often used to make inferences about preceding processes. This chapter focuses on expectations that precede outcomes to clarify which mechanism operates in one stage of the transmission process.

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).