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Although a significant body of work has amassed that explores the antecedents, correlates, and consequences of employee turnover in organizations, little is known about how employees go about quitting once they have made the decision to leave. That is, after the decision to voluntarily quit their job is made, employees must then navigate through the process of planning for their exit, announcing their resignation, and potentially working at their company for weeks after their plans to resign have been made public. Our lack of understanding of the resignation process is important as how employees quit their jobs has the potential to impact the performance and turnover intentions of other organizational members, as well as to harm or benefit the reputation of the organization, overall. Moreover, voluntary turnover is likely to increase in the coming decades. In this chapter, we unpack the resignation process. Specifically, drawing from the communication literature and prior work on employee socialization, we develop a three-stage model of the resignation process that captures the activities and decisions employees face as they quit their jobs, and how individual differences may influence how they behave in each of these three stages. In doing so, we develop a foundation upon which researchers can begin to build a better understanding of what employees go through after they have decided to quit but before they have exited their organization for the final time.

The purpose of this paper is to estimate the strength of the relationship between job performance and intentions to quit (ITQ), identify moderators to this relationship, and calculate the direct and indirect effects that job performance has on ITQ and turnover.

Data from 65 studies (n=17,918) were meta‐analyzed to estimate the performance‐ITQ relationship. This overall sample was separated into subgroups for moderator analyses. Meta‐analytic path analysis was used to test the hypothesized model of turnover.

Supervisor ratings of performance had the strongest relationship with ITQ (ρ=−0.16), followed by self‐ratings (ρ=−0.14), and objective measures (ρ=−0.02). Employee nationality and job type also acted as moderators. Poor performers are more likely to quit even after controlling for job satisfaction and turnover intentions, indicating that they are more apt to engage in unplanned quitting. Good performers were slightly more likely to intend to quit after controlling for job satisfaction.

Limitations on the number and type of studies available prevented a test of how performance level acts as a moderator to the job performance‐turnover relationship and may cause some of the moderator analyses to be unstable.

The findings provide for a better understanding of how employees' job performance affects their turnover decisions and how organizations can control turnover.

This is the first meta‐analysis to estimate the relationship between performance and ITQ and to test a meta‐analytic path model of the job performance‐job satisfaction‐ITQ‐turnover relationships.

Research on employee mobility has proliferated in the past four decades across four research traditions: Economics, sociology, management, and organizational behavior/human resource management. Despite significant overlap in interest and focus, these four streams of research have evolved independent from each other, resulting in a structural divide. We provide a detailed account of the research on employee mobility and the structural divide across disciplines. We document that the payoff from this profusion of research and increasing interest has been disappointing, as reflected in the limited number of cross-disciplinary citations, even among common topics of interest. However, our analysis also provides some encouraging signs in the form of specific journals and individuals who provide a bridge for cross-disciplinary fertilization.

The reported inquiry-based learning (IBL) study was designed in 2012–2013 for the highest achieving undergraduate students at a research-intensive university in the United Kingdom (U.K.). In 2005, the University received national funding from the U.K. Higher Education Academy (HEA) to develop an innovative model of IBL to be used in a multidisciplinary context (Tosey, 2006). As a consequence, IBL was an obvious tool when, in 2012, the authors set out to design learning interventions to improve the teamwork and leadership skills of high-attaining students. In the process of exploring the application of IBL to this task, the need to ensure the intervention allowed for development in the conative domain was considered important. Historically, IBL practice at the University had catered well for cognitive and affective learning but had not been focussed to develop conation. A conative-heavy element was therefore purposefully designed into the latest IBL intervention.