Article Correctness Is Author's Responsibility: How do instrumental and expressive network positions relate to turnover? A meta-analytic investigation.

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Although social network methods have proven valuable for predicting employee turnover, an informed use of network methods for turnover management requires an integration and extension of extant networks-turnover research. To that end, this article addresses two relatively neglected issues in the networks-turnover literature: the lack of integration of turnover process models into networks-turnover research and the differential influence of "network content" (i.e., instrumental vs. expressive network resources) on turnover processes. To address these issues, we draw from social capital and turnover theories as a basis for investigating how turnover antecedents (i.e., work attitudes, job alternatives, and job performance) mediate the associations between instrumental and expressive degree centrality and turnover. We test a theoretical model using meta-analytic path analysis based on the results of random-effects meta-analyses (64 independent samples of working adults) of instrumental and expressive degree centrality in relation to job satisfaction, organizational commitment, job alternatives, job performance, and employee turnover. We found that both instrumental and expressive degree centrality relate to employee turnover, but through different mediating processes; instrumental degree centrality decreased the likelihood of turnover via job performance and organizational commitment, whereas expressive degree centrality decreased the likelihood of turnover via job satisfaction and organizational commitment. Furthermore, expressive degree centrality (as compared to instrumental degree centrality) had a negative association with turnover after accounting for these prominent turnover antecedents. These findings illustrate the importance of distinguishing between instrumental and expressive network positions in the turnover process as well as the value of leveraging employee networks for employee retention. (PsycINFO Database Record (c) 2019 APA, all rights reserved)