Mattering in digital labor.

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, the purpose of this paper is to explore the relationship between worker's ability to create a narrative of their work mattering regardless, and their continued work engagement (WE) in these work setups. Design/methodology/approach: The authors approach the relationship between individual mattering and digital WE through a longitudinal study among workers on the crowdworking platform Amazon Mechanical Turk. The authors further provide qualitative insight into individual perceptions of mattering based on essay data. Findings: The authors 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 WE positively, while the other three mattering dimensions do not have a significant effect. Originality/value: 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 WE, the paper makes a contribution to research on crowdwork and the future of work. Beyond the theoretical contributions, the finding that perceived importance fosters WE has important implications for task and platform design. [ABSTRACT FROM AUTHOR]