Task performance and platform commitment: the role of job design and worker motivation in microtasking crowdsourcing
Year: 2025
Type: article
Abstract: Introduction This study examines how job design and worker motivation shape task performance and platform commitment in microtasking. Microtasking, a form of crowdsourcing in which work is coordinated by internet platforms and completed in very small units, poses challenges for designing motivating jobs that yield high-quality results. Drawing on the job characteristics model and self-determination theory, we link task and knowledge characteristics, autonomous motivation, and amotivation to quantitative and qualitative performance as well as commitment. Methods We test our model in a free simulation experiment with 558 microtasking workers, combining survey data with objectively assessed performance and self-rated commitment. Results The analysis shows that while certain job characteristics are positively related to autonomous motivation, unexpectedly, the latter does not mediate their effects on performance or commitment. Instead, amotivation plays the central role: certain task and knowledge characteristics are associated with reduced amotivation, which in turn relates to better performance and higher commitment. Discussion This finding indicates that in microtasking, mitigating amotivation is more predictive than fostering autonomous motivation—a significant departure from traditional work motivation theory. The study contributes to theory by highlighting the distinct role of amotivation in platform work and offers practical guidance for designing microtasks that sustain worker engagement and performance.
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,353
OpenAlex ID: W4415588297