Formerly considered a curious novelty, platform work is now an established phenomenon in the global labor market and increasingly receives attention, both academically and practically. A central component of platform work is the algorithmic management of supply and demand in the labor marketplace. This involves the algorithmic management of workers. Algorithmic management refers to the use of computerized technologies, typically algorithms, to (partially) automate processes related to decision making and control, enabled through the speeds, scale, and ubiquity of surveillance technologies, data processing and machine learning.
Although algorithmic management is not inherently good or bad. The technologies used to organize and manage work can make work designs better and make them worse. Interestingly, the dominant perspective in academic research is that algorithmic management is more like to generate negative than positive outcomes. We studied the implication of different dimensions of algorithmic management. Specifically, we focused on the impact of algorithmic coordination and algorithmic evaluation on perceived work conditions and meaningful work experience.
Using survey data obtained from 412 platform workers we demonstrate that different aspects of algorithmic management differentially impact work conditions and meaningfulness of work. Specifically, algorithmic coordination has no or a positive impact on perceived work conditions and meaningfulness of work, however, the algorithmic evaluation seems particularly problematic for platform workers’ experienced work conditions. Hence, we show a negative impact of algorithmic evaluation on perceived job conditions and ultimately meaningful work experiences.
These findings are important as they contrast earlier research suggesting that algorithmic management might generate more negative than positive outcomes for workers. We contribute to bridging a gap between emerging research on the implication of algorithmic management and more traditional theories of work design. Evidently, platform workers seem to appreciate the efficiency of algorithmic coordination but are more sceptic towards algorithmic evaluation. Beyond, platform work, the rise of algorithmic systems, leads organizations and human managers to decide what kinds of algorithmic software to implement and what (managerial) functions to allocate to an algorithm. Our findings inform such decisions.