Administrative Sciences (Nov 2020)

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

  • Xiaochuan Song,
  • Graham H. Lowman,
  • Peter Harms

DOI
https://doi.org/10.3390/admsci10040093
Journal volume & issue
Vol. 10, no. 4
p. 93

Abstract

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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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