Journal of Management Information Systems

Volume 35 Number 4 2018 pp. 1154-1187

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

Ma, Xiao, Khansa, Lara, and Kim, Sung S

ABSTRACT:

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.

Key words and phrases: crowdwork, Amazon Mechanical Turk, Mturk, online communities, crowdworking turnover, turnover intention, two-wave panel, embeddedness, moderated heuristics, co-creation