The home-field disadvantage refers to the disadvantage inherent in research that takes a particular cultural group as the starting point or standard for research, including cross-cultural research. We argue that home-field status is a serious handicap that often pushes researchers toward deficit thinking, however good the researchers' intentions may be. In this article, we aim to make this home-field bias more explicit and, in doing so, more avoidable. We discuss three often-overlooked disadvantages that result from this home-field status: the problem of marked versus unmarked culture, the problem of homogenous versus heterogeneous culture, and the problem of regression toward the mean. We also recommend four interventions researchers can apply to avoid the home-field disadvantage or, at the least, attenuate its deleterious effects.

There has been a recent upsurge of research on moral judgment and decision making. One important issue with this body of work concerns the relative advantages of calculating costs and benefits versus adherence to moral rules. The general tenor of recent research suggests that adherence to moral rules is associated with systematic biases and that systematic cost-benefit analysis is a normatively superior decision strategy. This article queries both the merits of cost-benefit analyses and the shortcomings of moral rules. We argue that outside the very narrow domain in which consequences can be unambiguously anticipated, it is not at all clear that calculation processes optimize outcomes. In addition, there are good reasons to believe that following moral rules can lead to superior consequences in certain contexts. More generally, different modes of decision making can be seen as adaptations to particular environments.

Purpose During the past decade, the coworking concept has expanded and evolved along with the industry associated with it, so that references to coworking often refer to notions quite distinct from the original conception. The purpose of this paper is to establish a classification of contemporary coworking environments and clarify the scholarly, as well as the industry usage of a coworking model. Design/methodology/approach The paper reviews popular and scientific literature and the authors’ field experience in the industry to derive three defining features of coworking and distinct categories that help clarify the concept and can be used to identify and evaluate coworking spaces. Findings The main finding behind the following paper is the taxonomy of contemporary coworking spaces that takes into account the broad spectrum of shared workspaces that commonly receive the coworking label, specifies the features required to warrant that label and provides a framework for understanding the defining factors of a coworking model. The taxonomy showcases four unalike types of coworking spaces and the three types of non-coworking shared offices that are repeatedly and somewhat mistakenly labeled as coworking environments. Originality/value Understanding the core differentiation between unalike models would enable scholars to guide and structure the study to evolve in coworking research. The taxonomy can be seen as a base for further research in the field of coworking that helps ensure scholars are sufficiently specific and distinctive in the shared subject of their research, suggests a roadmap for future coworking research and provides a tool to evaluate real-world examples of work environments concerning the degree they fit the coworking concept.

Objectives: This paper summarizes the fast-and-frugal-heuristics (FFH) approach to judgment and decision making, particularly as it applies to sports. The aim is to provide a framework through which current sports psychologists may apply this approach to better understand sports decision making. Methods: FFH are studied using a variety of methods, including (1) computer simulations and mathematical analysis of heuristic performance as it depends on environmental structure (what we call the ecological rationality of heuristics); (2) empirical analysis of the heuristics, performance in naturally occurring environments; and (3) experimental research examining whether people actually use the identified heuristics. Results: Simulations and analysis have shown that FFH can perform as well as complicated optimizing models while using less information and without integrating this information. Furthermore, in many cases FFH are more robust than optimizing models, outperforming these models when generalizing to new cases. Conclusion: FFH depart from many models of human decision making in that they set a reasonable standard of rationality based on real-world constraints such as (a) limited time, information, and cognitive capacity, (b) decision tasks that may have no calculable optimal solution, and (c) the structured environments within which humans have learned and evolved. These simple heuristics are particularly