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Inicio  /  Administrative Sciences  /  Vol: 10 Par: 4 (2020)  /  Artículo
ARTÍCULO
TITULO

Justice for the Crowd: Organizational Justice and Turnover in Crowd-Based Labor

Xiaochuan Song    
Graham H. Lowman and Peter Harms    

Resumen

Crowd-based labor has been widely implemented to solve human resource shortages cost-effectively and creatively. However, while investigations into the benefits of crowd-based labor for organizations exist, our understanding of how crowd-based labor practices influence crowd-based worker justice perceptions and worker turnover is notably underdeveloped. To address this issue, we review the extant literature concerning crowd-based labor platforms and propose a conceptual model detailing the relationship between justice perceptions and turnover within the crowd-based work context. Furthermore, we identify antecedents and moderators of justice perceptions that are specific to the crowd-based work context, as well as identify two forms of crowd-based turnover as a result of justice violations: requester and platform turnover. In doing so, we provide a novel conceptual model for advancing nascent research on crowd-based worker perceptions and turnover.

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