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Offers a case study describing how the Fossil and Hydro Power (F&HP) Organization of the Tennessee Valley Authority ‐ a finalist for the 1995 Presidential Award for Quality ‐ has taken information from feedback reports and other sources, and developed a strategy for implementing areas of opportunity into its core business. The strategy expands the plan‐do‐check‐act logic into a plan‐do‐knowledge‐act model which couples assessment information with theory ‐ in the form of the conceptual guidelines of the Baldrige criteria ‐ to create knowledge. Details how the model has been implemented at F&HP over the past three years, and describes the resulting accomplishments.

Patriotism is often described as the “love of country” that individuals display in the acclamation of their national community. Despite the prominence of this sentiment in various societies around the world, organizational research on patriotism is largely absent. This omission is surprising because entrepreneurs, human resource (HR) divisions, and firms frequently embrace both patriotism and patriotic organizational practices. These procedures include (among other interventions) national symbol embracing, HR practices targeted toward military members and first responders, the adulation of patriots and celebration of patriotic events, and patriotic-oriented corporate social responsibility (CSR). Here, the authors argue that research on HR management and organization studies will likely be further enhanced with a deeper understanding of the national obligation that can spur employee productivity and loyalty. In an attempt to jumpstart the collective understanding of this phenomenon, the authors explore the antecedents of patriotic organizational practices, namely, the effects of founder orientation, employee dispersion, and firm strategy. It is suggested that HR practices such as these lead to a patriotic organizational image, which in turn impacts investor, customer, and employee responses. Notably, the effect of a patriotic organizational image on firm-related outcomes is largely contingent on how it fits with the patriotic views of other stakeholders, such as investors, customers, and employees. After outlining this model, the authors then present a thought experiment of how this model may appear in action. The authors then discuss ways the field can move forward in studying patriotism in HR management and organizational contexts by outlining several future directions that span multiple levels (i.e., micro and macro). Taken together, in this chapter, the authors introduce a conversation of something quite prevalent and largely unheeded – the patriotic organization.

Having a child with Autism Spectrum Disorder (ASD) can cause significant professional strain for parents. Compared to parents of typically developing children or children with other types of special needs, parents of children with ASD report being underemployed, having more difficulty accomplishing important work tasks or taking on new work assignments, and being viewed less favorably by supervisors. They also may be more likely to perceive themselves as stigmatized by coworkers, negatively impacting their abilities to develop or maintain meaningful relationships with others at work. All of these factors lead to parents of children with ASD earning less annual income than other types of parents and being more likely to experience loss of workplace motivation or lower overall job satisfaction. The negative career experiences of parents of children with ASD may also impact employers. Employees experiencing lower levels of motivation are less productive and more likely to quit their jobs, resulting in increased turnover expense. Because the number of working parents of children with ASD continues to grow as ASD rates increase, organizations would benefit from supporting parents of children with ASD through adopting flexible work–life balance policies, encouraging leaders to promote values of diversity and inclusiveness, and implementing workplace programs designed to support parents and educate coworkers.

This paper considers the finite-sample distribution of the 2SLS estimator and derives bounds on its exact bias in the presence of weak and/or many instruments. We then contrast the behavior of the exact bias expressions and the asymptotic expansions currently popular in the literature, including a consideration of the no-moment problem exhibited by many Nagar-type estimators. After deriving a finite-sample unbiased k-class estimator, we introduce a double-k-class estimator based on Nagar (1962) that dominates k-class estimators (including 2SLS), especially in the cases of weak and/or many instruments. We demonstrate these properties in Monte Carlo simulations showing that our preferred estimators outperform Fuller (1977) estimators in terms of mean bias and MSE.

This chapter reviews the methods available to hospitality and tourism researchers to perform moderation analysis with continuous variables in partial least squares structural equation modeling (PLS-SEM), with the objective of enhancing understanding and encouraging the use of these techniques in future papers. The product term method is presented first, followed by an empirical example/application in the context of hospitality and tourism. Two extensions, namely the two-stage approach that can help cope with formative and higher-order constructs, and the orthogonalizing approach that can help generate more accurate results and overcome multicollinearity among tourism variables in the presence of a continuous moderator variable, are then presented and discussed. The chapter concludes by presenting guidelines and recommendations for improving the use of interaction effects in analyses of tourism variables, as well as highlighting ongoing developments in both the product term method and PLS-SEM software.

Statistical methods of spatial analysis are often successful at either prediction or explanation, but not necessarily both. In a recent paper, Dearmon and Smith (2016) showed that by combining Gaussian Process Regression (GPR) with Bayesian Model Averaging (BMA), a modeling framework could be developed in which both needs are addressed. In particular, the smoothness properties of GPR together with the robustness of BMA allow local spatial analyses of individual variable effects that yield remarkably stable results. However, this GPR-BMA approach is not without its limitations. In particular, the standard (isotropic) covariance kernel of GPR treats all explanatory variables in a symmetric way that limits the analysis of their individual effects. Here we extend this approach by introducing a mixture of kernels (both isotropic and anisotropic) which allow different length scales for each variable. To do so in a computationally efficient manner, we also explore a number of Bayes-factor approximations that avoid the need for costly reversible-jump Monte Carlo methods.

To demonstrate the effectiveness of this Variable Length Scale (VLS) model in terms of both predictions and local marginal analyses, we employ selected simulations to compare VLS with Geographically Weighted Regression (GWR), which is currently the most popular method for such spatial modeling. In addition, we employ the classical Boston Housing data to compare VLS not only with GWR but also with other well-known spatial regression models that have been applied to this same data. Our main results are to show that VLS not only compares favorably with spatial regression at the aggregate level but is also far more accurate than GWR at the local level.

Scholars who study humility tend to think of it in highly individualized terms, such as an absence of vanity or an accurate self-assessment. Individuating definitions can lead to such jarring concepts as the “humble white supremacist” (Roberts & Wood, 2007). Qualitative sociological research in the (predominantly North American) evangelical movement to accept and affirm lesbian, gay, bisexual, trans, queer, and intersex (LGBTQI) identities, same-sex marriage, and sex/gender transition reveals that humility is not simply the awareness that “I could be wrong.” That awareness is rooted in what we have found to be humility’s defining element, concern to foster relationship. These findings prompt us to define humility as a fundamentally social disposition, as concern to protect the kinds of intimate connection with others that can transform the self. Recognizing the social nature of humility reveals why humility is incompatible with injustice.

There has been a sustained interest over the past couple of decades in developing sophisticated leak detection techniques (LDTs) that are economical and reliable. Majority of current commercial LDTs are acoustics based and they are not equally suitable to all pipe materials and sizes. There is also limited knowledge on the comparative merits of such acoustics-based leak detection techniques (ALDTs). The purpose of this paper is to review six commercial ALDTs based on four decisive criteria and subsequently develop guidance for the optimal selection of an ALDT.

Numerous publications and field demonstration reports are reviewed for evaluating the performance of various ALDTs in this study to inform their optimal selection using an integrated multi-criteria decision analysis (MCDA) framework. The findings are validated using interviews of water utility experts.

The study approach and the findings will have a broad impact on the water utility industry by identifying a suite of suitable ALDTs for a range of typical application scenarios. The evaluated ALDTs include listening devices, noise loggers, leak-noise correlators, free-swimming acoustic, tethered acoustic, and acoustic emissions. The evaluation criteria include cost, reliability, access requirements, and the ability to quantify leakage severity. The guidance presented in this paper will support efficient decision making in water utility management to minimize pipeline leakage.

This study attempts to address the problem of severe dearth of performance data for pipeline inspection techniques. Performance data reported in the published literature on various ALDTs are appropriately aggregated and compared using a MCDA, while the uncertainty in performance data is addressed using the Monte Carlo simulation approach.

In response to the worsening environmental crisis, there have been multiple calls for sustainable supply chain management (SSCM) scholars and practitioners to adopt a “business-not-as-usual” approach based on justice, fairness, equity and sustainability. We add to this literature by proposing environmental justice (EJ) as a key concept for the theory and practice of SSCM.

This conceptual article builds SSCM theory on EJ and contributes to supply chain justice research and practice by introducing the concept of the “environmentally just supply chain” and presenting pathways for operationalizing it in practice.

Three pathways are proposed to leverage transformative SSCM to create environmentally just supply chains: human rights due diligence, resilience thinking and coproduction of environmentally just supply chains.

The three pathways can be used by actors within a supply chain to create environmentally just supply chains.

This article extends transformative, non-instrumental perspectives on environmental sustainability within SSCM scholarship to provide insights into how supply chains can be transformed through EJ. Not only does the article show the relevance of EJ for SSCM theory and practice, but it elaborates pathways for moving from harm reduction to transformative sustainability actions.