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This chapter utilizes a network perspective to show how the totality of one’s social connections impacts well-being by providing access to resources (e.g., information, feedback, and support) and placing limits on autonomy. We provide a brief review of basic network concepts and explain the importance of understanding how the networks in which leaders are embedded may enhance or diminish their well-being. Further, with this greater understanding, we describe how leaders can help promote the well-being of their employees. In particular, we focus on four key aspects of workplace networks that are likely to impact well-being: centrality, structural holes, embeddedness, and negative ties. We not only discuss practical implications for leaders’ well-being and the well-being of their employees, but also suggest directions for future research.

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.

Work design has largely overlooked cognitive–emotional interactions in understanding employee motivation and satisfaction. My aim in this chapter is to develop a conceptual model that integrates what we know about these interactions from research on emotions and neuroscience with traditional and emergent work design perspectives. I propose that striving for universal goals influences how a person responds to the work characteristics, such that an event that is personally relevant or “self-referential” will elicit an emotional reaction that must be regulated for optimal performance, job satisfaction, and well-being. A Self-Referential Emotion Regulatory Model (SERM) of work design is presented.

We examine how input- (vs. output-) based performance evaluation and incentive intensity impact employees’ autonomous motivation, thereby influence their proactive work behaviors.

We collected survey responses from 309 employees of different firms. Multi-group Structural Equation Modeling analyses were used to analyze the data.

Input-based evaluation had a positive effect on autonomous motivation and proactive work behaviors when task uncertainty was high, but a negative effect when it was low. Autonomous motivation had a positive effect on proactive work behaviors.

Our results on the moderating effect of task uncertainty provide insights into inconsistencies in earlier studies. Moreover, applying self-determination theory of motivation to incentive research can provide some insights into why sometimes, incentives can negatively affect performance.

The study of proactive work behaviors is important because despite their necessity in the fast-changing business environment, they are relatively unexplored in the incentive literature. Proactivity is especially important for tasks that are high in uncertainty because the exact tasks to achieve those goals are hard to specify.

We investigate the effect of performance management system on proactive work behaviors, mediated by autonomous motivation and moderated by task uncertainty.

Scholars have argued that different forms of proactive behaviors (e.g., career initiative, feedback seeking, and taking charge) all involve employees’ self-initiated and future-focused efforts to bring about change in a situation (Parker et al., 2006). There are at least three important elements that define proactivity: future-focus, change-orientation, and self-initiation (Frese & Fay, 2001; Parker et al., 2006). First, proactive behavior is future-focused, which means that this action is targeted at anticipated problems or at opportunities with a long-term focus. Second, proactive behavior is change-oriented, involving not just reacting to a situation but being prepared to change that situation in order to bring about a different future. Third, and underpinning the prior two elements, proactive behavior is self-initiated, which means that employees initiate a proactive goal without being told to, or without requiring explicit instructions from supervisors. Accordingly, proactivity has also been conceived of as a process in which employees generate and implement, under their own direction, a proactive goal to bring about a different future (Bindl, Parker, Totterdell, & Hagger-Johnson, 2012; Frese & Fay, 2001; Grant & Ashford, 2008).

In this chapter the relationship between job design and older workers is considered. Starting from a conceptual definition of what the concept job and work design is, we consider theoretic approaches to the study of job design over the last decades, including recent frameworks, measurement, and research. We follow this with a specific focus on the topic of job design for older workers. We argue that the rules of “good job design” are not applicable to all workers, focusing specifically on the issues of age and career stage. We next show through a theoretical model and some empirical research that some job characteristics may be more suitable or beneficial for people in older age groups or later stages of their careers (e.g., Truxillo, Cadiz, Rineer, Zaniboni, & Fraccaroli, 2012). Empirical support for the role of age in job design is considered. We conclude by defining some avenues for future research, including the identification of additional factors that may determine how age and job characteristics affect worker behavior, attitudes, and well-being.