Finding meaning in crowdwork: An analysis of algorithmic management, work characteristics, and meaningfulness
基于412名众包工人的调查数据，分析算法协调和算法量化对工作条件及工作意义的不同影响，发现算法协调有正面或中性作用，而算法量化则与较差的工作条件和较低的工作意义相关。
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.