Finding meaning in crowdwork: An analysis of algorithmic management, work characteristics, and meaningfulness

Abstract In this study we investigate the implications of different aspects of algorithmic coordination and algorithmic quantification for perceived work conditions and the meaningfulness of crowdwork. Using survey data obtained from 412 crowdworkers, our analysis shows that work conditions and the meaningfulness of work are impacted differently by algorithmic coordination and the feeling of being quantified by an algorithm. Specifically, it shows that algorithmic coordination has either a positive or null impact on perceived work conditions and meaningfulness of work. However, negative associations between algorithmic quantification and perceived work conditions, suggest that the algorithmic quantification seems particularly problematic for crowdworkers’ experienced work conditions. Furthermore, algorithmic coordination is positively associated with the meaningfulness of work, while algorithmic quantification is negatively associated with the perceived meaningfulness of work. Using work design theory, the findings also provide insights into the mechanisms explaining these relationships.