Microtargeting control: Explicating algorithmic control and nudges in platform-mediated cab driving in India

Abstract

We discuss algorithmic control and nudges prevalent in the gig economy in relation to extant management control literature. We draw on an analysis of archival data and interviews with drivers and executives of app-based cab companies in India. Comparing algorithmic control with direct control, we explain the increase in the scale and scope of automation that enables detailed driver profiling and segmentation, which is crucial for microtargeting control mechanisms and controlling driver earnings. Explaining nudges vis-a-vis indirect control, we highlight the role of mental processes and clarify the labelling of control mechanisms as nudges. Furthermore, we show how nudges are interwoven into algorithmic control as they capitalise on and feed into it. We also substantiate the discussions on information asymmetry by explicating the calculative apparatus that underlies the asymmetry.