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Constructive deviance has received increasing attention across the last 20 years. However, because the distinction between constructive and traditional forms of deviance (i.e., destructive) is based on the intent behind the behaviors, it can be difficult to determine which acts are constructive. As an umbrella construct consisting of several forms of deviant acts (e.g., whistle-blowing, employee voice, necessary evils), research into constructive deviance has largely remained focused on the individual behaviors to date. While advancements have been made, this focus has limited the consideration of an overarching understanding of constructive deviance in the workplace. Further, constructs like constructive deviance that straddle the bounds between beneficial and detrimental necessitate the exploration into their antecedents as determined by the employees (i.e., apples), their environments (e.g., barrels), or some combination of the two. The author seeks to advance the research in constructive deviance by proposing a testable model. In which, the author develops an interactionist perspective of the antecedents to reposition constructive deviance as the acts of good employees in restrictive or negative environments. In doing so, the author considers how various aspects of individuals, their organizational environments, and the influence of their leaders interact. The author then develops a multi-stakeholder approach to the outcomes of constructive deviance to consider how the various parties (i.e., organization, coworkers, customers) are expected to respond and how these responses impact the more distal outcomes as well as the likelihood of engaging in future constructive deviance.

This paper investigates effective human-robot collaboration (HRC) and presents implications for Human Resource Management (HRM). A brief review of current literature on HRM in the smart industry context showed that there is limited research on HRC in hybrid teams and even less on effective management of these teams. This book chapter addresses this issue by investigating factors affecting intention to collaborate with a robot by conducting a vignette study. We hypothesized that six technology acceptance factors, performance expectancy, trust, effort expectancy, social support, organizational support and computer anxiety would significantly affect a users' intention to collaborate with a robot. Furthermore, we hypothesized a moderating effect of a particular HR system, either productivity-based or collaborative. Using a sample of 96 participants, this study tested the effect of the aforementioned factors on a users' intention to collaborate with the robot. Findings show that performance expectancy, organizational support and computer anxiety significantly affect the intention to collaborate with a robot. A significant moderating effect of a particular HR system was not found. Our findings expand the current technology acceptance models in the context of HRC. HRM can support effective HRC by a combination of comprehensive training and education, empowerment and incentives supported by an appropriate HR system.