Given the extensive research on the topic of voluntary employee turnover in the past decade as well as new managerial approaches to employee retention, labor market dynamism, and evolution in research methodology and technology, it is important that researchers evaluate the current state of the field. In 232 • The Academy of Management Annals this chapter, we critically review prior research to provide a solid foundation and clear perspective to guide future research. Some of the major trends of the past decade include: (1) new individual difference predictions of turnover (e.g., personality, motivating forces); (2) increased emphasis on contextual variables with an emphasis on interpersonal relationships (e.g., leadermember exchange, interpersonal citizenship behaviors); (3) enhanced focus on factors looking specifically at staying (e.g., organizational commitment and job embeddedness); and (4) dynamic modeling of turnover processes with the consideration of time (e.g., changes in job satisfaction). We believe these trends point to a number of important issues to consider in the next decade, including the influence of social networks, differences across cultures, temporal aspects (e.g., early vs. late turnover), consequences of turnover, multi-level investigations of turnover and other types of withdrawal (e.g., retirement).

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Recent narrative reviews (e.g., Hom, Mitchell, Lee, and Griffeth, 2012;Hom, Lee, Shaw, and Hausknecht, 2017) advise that it is timely to assess the progress made in research on voluntary employee turnover so as to guide future work. To provide this assessment, we employed a three-step approach. First, we conducted a comprehensive meta-analysis of turnover predictors, updating existing effect sizes and examining multiple new antecedents. Second, guided by theory, we developed and tested a set of substantive moderators, considering factors that might exacerbate or mitigate zeroorder meta-analytic effects. Third, we examined the holistic pattern of results in order to highlight the most pressing needs for future turnover research. The results of Step 1 reveal multiple newer predictors and updated effect sizes of more traditional predictors, which have received substantially greater study. The results of Step 2 provide insight into the context-dependent nature of many antecedentturnover relationships. In Step 3, our discussion takes a bird's-eye view of the turnover "forest" and considers the theoretical and practical implications of the results. We offer several research recommendations that break from the traditional turnover paradigm, as a means of guiding future study.