The Chinese U. of Hong Kong, Shenzhen, United States
Existing research has extensively examined injunctive and descriptive norms in traditional work settings. However, little is known about how gig workers respond to norms shaped by algorithms. We conceptualize “algorithmic norm,” defined as people’s perception of behavioral patterns shaped explicitly or implicitly by the logic embedded in algorithm(s) adopted by digital platforms. Using a dataset of 1,470 doctors and 225,766 responses collected over 472 days from a digital health platform in China, along with six vignette-based experiments involving 1,164 doctors, we investigate how and why the algorithmic norm supersedes descriptive and injunctive norms to impact web doctors’ compassion expression. Drawing on the focus theory of normative conduct, we predict that prior to algorithm adoption, web doctors conform to the descriptive norm to seek social approval from peers. However, post-algorithm implementation, their focus gradually shifts towards the algorithmic norm, motivated by a desire for system approval. Results across all studies support these predictions. Additionally, we find the enduring independent influence of injunctive norms in shaping individual online behavior. Our findings thus extend the focus theory into a bi-focal framework. This research underscores the significance of theorizing and examining the algorithmic norm as a key driver of worker behavior in the gig economy.
