Stay or Leave: Investigating Factors Impact Crowd-Based Workers’ Platform-Based Justice Perceptions and Turnover Intentions

Crowdsourcing has emerged as a transformative business model, harnessing collective intelligence to tackle complex tasks efficiently. However, the impact of crowd-based platforms on workers’ justice perceptions is still understudied. This research delves into organizational justice perceptions among crowd-based workers, focusing on platform features that influence these perceptions as well as workers’ subsequent turnover intentions. Drawing on data collected from 364 workers across multiple platforms, findings indicate that equitable compensation policies, participative evaluation, interactive and considerate communication, and rule-based evaluation can enhance procedural, distributive, and interactional justice perceptions, which in turn, significantly reduce turnover intentions. Moreover, media richness moderates part of these relationships, strengthening the mitigating effects of justice perceptions on turnover intentions. The study contributes to understanding the dynamics of organizational justice in crowdsourcing contexts and provides insights for platform management strategies to enhance worker retention.

Authors

Publication Details

Journal
Journal of Applied Business and Economics
Published
2024-10-12
DOI
https://doi.org/10.33423/jabe.v26i5.7295
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
0.00
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article

Stay or Leave: Investigating Factors Impact Crowd-Based Workers’ Platform-Based Justice Perceptions and Turnover Intentions

Xiaochuan Song
Journal of Applied Business and Economics
Impact of AI and Big Data on Business and Society
article

Stay or Leave: Investigating Factors Impact Crowd-Based Workers’ Platform-Based Justice Perceptions and Turnover Intentions

Xiaochuan Song
article en

Abstract

Crowdsourcing has emerged as a transformative business model, harnessing collective intelligence to tackle complex tasks efficiently. However, the impact of crowd-based platforms on workers’ justice perceptions is still understudied. This research delves into organizational justice perceptions among crowd-based workers, focusing on platform features that influence these perceptions as well as workers’ subsequent turnover intentions. Drawing on data collected from 364 workers across multiple platforms, findings indicate that equitable compensation policies, participative evaluation, interactive and considerate communication, and rule-based evaluation can enhance procedural, distributive, and interactional justice perceptions, which in turn, significantly reduce turnover intentions. Moreover, media richness moderates part of these relationships, strengthening the mitigating effects of justice perceptions on turnover intentions. The study contributes to understanding the dynamics of organizational justice in crowdsourcing contexts and provides insights for platform management strategies to enhance worker retention.

Journal of Applied Business and EconomicsVol. 26(5)
Openalex Percentile: Top 77%
Impact of AI and Big Data on Business and Society
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