Mattering in Digital Labor

Abstract

Purpose: Online gig labor platforms bring together a global and fast-growing workforce to complete highly granular, remote and decontextualized tasks. While these environments might be empowering to some workers, many others feel disenfranchised and removed from the final product of their labor. To better understand the antecedents of continued participation in forms of crowdsourced digital labor, we explore the relationship between worker’s ability to create a narrative of their work mattering regardless, and their continued work engagement in these work setups. Design: We approach the relationship between individual mattering and digital work engagement through a longitudinal study among workers on the crowdworking platform Amazon Mechanical Turk. We further provide qualitative insight into individual perceptions of mattering based on essay data. Findings: We develop a measure of mattering in crowdworking with four dimensions: reliance, social recognition, importance, and interaction. Reliance is the most pronounced dimension, followed by interaction, importance and social recognition. In the final longitudinal model, only importance affects work engagement positively, while the other three mattering dimension do not have a significant effect. Originality: The findings indicate that individuals who feel that they themselves and their work ‘count’ and ‘make a difference’ will be more engaged in their digital labor. By clarifying the dimensionality of mattering in crowdwork and studying its differentiated effect on work engagement, the paper makes a contribution to research on crowdwork and the future of work. Beyond the theoretical contributions, the finding that perceived importance fosters work engagement has important implications for task and platform design.

Mattering in Digital Labor