Harnessing trust and engaging with the online workforce: an examination of crowdworker values

Purpose – This research aims to understand the important values of crowdworkers, and how these values affect their trust and engagement with a crowdwork organization, by examining behavioral intention, value sensitive design and antecedents of trust. Design/methodology/approach – Data was collected from 422 Amazon Mechanical Turk workers. Partial least squares structural equation modeling was then used to uncover the most important values that influence crowdworkers’ trust and intention to return to platforms. Findings – Fair pay, pay transparency, feedback mechanisms and accountability successfully predicted trust and intention to return, while privacy, security and autonomy showed mixed results. Trust was identified as a significant predictor of behavioral intention among crowdworkers. Research limitations/implications – This study contributes to existing research on crowdwork, gig work, value sensitive design, trust and its antecedents and behavioral intention while providing avenues for future research in these areas. Practical implications – Organizations face challenges in attracting, retaining and keeping workers engaged in crowdwork and the gig economy, particularly when designing online systems. This research provides insights into the values that matter most to crowdworkers, which can help organizations better engage this workforce and treat them more equitably. Originality/value – This research addresses the challenges of attracting, retaining and keeping workers engaged in crowdwork, especially in micro-task work, despite millions of businesses tapping into online users to perform work. It identifies specific values that influence trust and engagement in a context where workers can move between jobs, sometimes by choice, but often due to organizations undermining worker rights.