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Drawing on Bandwidth Fidelity Theory (Cronbach, 1970; Cronbach & Gleser, 1965), this chapter argues for more specificity with regard to conceptualizing and measuring variables in the field of behavioral ethics. We provide an example of how this might be accomplished, by building on recent work on organizational support that emphasizes more specific facets of perceived organizational support (POS). We introduce the concept of perceived organizational support for ethics (POS-E) and test its predictive power on a sample of 4,315 employees from manufacturing and technology firms. We find support for our assertions that ethics-specific support is a better predictor of ethics-related outcomes (e.g., pressure to violate ethical standards, preparedness to handle ethical violations) and general support (POS) is a better predictor of more general organizational outcomes (i.e., job satisfaction). Theoretical and practical implications of these results and the importance of moving toward more specific versus general constructs in the field of behavioral ethics are discussed.

This response addresses the central issues raised by the commentaries on our earlier chapter. The intent here is to clarify issues that may have been insufficiently explicated in our original treaties. These include the distinction between core and other employee groups, the importance of horizontal fit among the human resources management (HRM) practices, and the importance of job analysis principles when considering innovative activities throughout firms.

The ability for learners to interact online via their avatars in a 3-D simulation space means that virtual worlds afford a host of educational opportunities not offered by other learning technology platforms, but their use also raises several pertinent issues that warrant consideration. This chapter reviews the educational use of virtual worlds from a design perspective. Virtual-world definitions are explored, along with their key educational characteristics. Different virtual-world environments are briefly contrasted, including Second Life, Active Worlds, Open Sim, and Minecraft. A wide variety of virtual-world uses in schools and universities are examined so as to understand their versatility. Key educational benefits of virtual worlds are distilled from the literature, such as the ability to facilitate 3-D simulations, role-plays, construction tasks, and immersive learning. Emergent issues surrounding the use of virtual worlds are also analyzed, including cognitive load, safety, and representational fidelity. One higher education and one school level vignette are provided in order to offer more detailed insight into the use of virtual worlds in practice. Recommendations for learning design and implementation are presented, based on the thematic analysis of contemporary virtual-worlds research.

The diffusion and adoption (D&A) of innovation propels today's technological landscape. Crisis situations, real or perceived, motivate communities of people to take action to adopt and diffuse innovation. The D&A of innovation is an inherently human activity; yet, artificially intelligent techniques can assist humans in six different ways, especially when operating in fifth generation ecosystems that are emergent, complex, and adaptive in nature.

Humans can use artificial intelligence (AI) to match solutions to problems, design for diffusion, identify key roles in social networks, reveal unintended consequences, recommend pathways for scaling that include the effects of policy, and identify trends for fast-follower strategies. The stability of the data that artificially intelligent systems rely upon will challenge performance; nevertheless, the research in this area has positioned several promising techniques where classically narrow AI systems can assist humans. As a result, human and machine interaction can accelerate the D&A of technological innovation to respond to crisis situations.

To date, the literature on quantile regression and least absolute deviation regression has assumed either explicitly or implicitly that the conditional quantile regression model is correctly specified. When the model is misspecified, confidence intervals and hypothesis tests based on the conventional covariance matrix are invalid. Although misspecification is a generic phenomenon and correct specification is rare in reality, there has to date been no theory proposed for inference when a conditional quantile model may be misspecified. In this paper, we allow for possible misspecification of a linear conditional quantile regression model. We obtain consistency of the quantile estimator for certain “pseudo-true” parameter values and asymptotic normality of the quantile estimator when the model is misspecified. In this case, the asymptotic covariance matrix has a novel form, not seen in earlier work, and we provide a consistent estimator of the asymptotic covariance matrix. We also propose a quick and simple test for conditional quantile misspecification based on the quantile residuals.

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.

This chapter focuses on visualization. Seeing the humanities differently is one of the amazing benefits of working with tools mentioned within this category. Whether it be more traditional visualizations like images or video or that which is considered a bit more advanced like augmented or virtual reality, the enhanced perspective gained through the use of these tools offers digital humanities scholars unprecedented disciplinary perspectives while helping to shape new research areas, questions, and understanding of humanity and culture. In addition to visualization and issues related to it, this chapter also examines gaming and how games and play are impacting the digital humanities in exciting ways.