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

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.