Active Community Participation and Crowdworking Turnover: A Longitudinal Model and Empirical Test of Three Mechanisms



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Journal of Management Information Systems


Crowdworkers, such as Mturk workers, face challenging work conditions, including low pay and unfair treatment. To overcome a lack of means to share information with other workers, they often self-organize in independent online communities, for example, TurkerNation. Although prior research has explored both the crowdwork and online community contexts, it has largely ignored crowdworkers’ dual-context roles. This research provides evidence for the dual-context phenomenon. We propose three theory-driven mechanisms―embeddedness, cross-influence, and moderated heuristics―that, together with the conventional model and the sequential-update mechanism, explained up to 72% of key behavioral outcomes in both contexts. Moreover, crowdworkers’ active participation in online communities had a persistent mitigating effect on their desires to quit working in the crowdworking environment. These findings add to a richer understanding of crowdworkers’ integrated and evolving psychology within the dual-context environment. From a managerial perspective, our findings suggest that crowdwork platforms can better retain their workers by facilitating―and actively engaging with―their discussions in an embedded online community.



Crowdwork, Mturk, Online communities, Turnover intention, Amazon Mechanical Turk


Copyright 2018 Journal of Management Information Systems. This is a pre-print version of a published paper available at: Recommended citation: Ma, Xiao, Lara Khansa, and Sung S. Kim. "Active Community Participation and Crowdworking Turnover: A Longitudinal Model and Empirical Test of Three Mechanisms." Journal of Management Information Systems 35, no. 4 (2018): 1154-1187. DOI: 10.1080/07421222.2018.1523587. This item has been deposited in accordance with publisher copyright and licensing terms and with the author's permission.