Encouraging virtue or enforcing control? Ethical impacts of PickMe’s algorithmic management

Purpose This study aims to investigate how Algorithmic Management (AM) within Sri Lanka’s PickMe ride-hailing platform shapes the ethical conduct, autonomy and professional agency of autorickshaw drivers. Drawing on MacIntyrean Virtue Ethics (MacIntyre, 2007), this research examines whether PickMe’s algorithmic governance fosters genuine ethical dispositions or primarily enforces compliance through digital control. Design/methodology/approach The study uses a qualitative case study design grounded in critical realism. Data was collected through 25 semistructured interviews with PickMe drivers, senior managers and one frequent customer. Using the GIOIA methodology, interview transcripts were coded to identify first-order concepts, second-order themes and aggregate dimensions related to algorithmic surveillance, nudging and ethical behavior. Findings The analysis reveals that PickMe’s algorithmic systems, particularly data surveillance, automated ratings and performance-based nudging, successfully promote professionalism and accountability among drivers. However, these same mechanisms constrain ethical agency by limiting transparency, reducing autonomy and embedding opaque decision-making processes into everyday work. Drivers experience both empowerment through structure and disempowerment through algorithmic opacity, reflecting broader tensions in gig economy labor governance. Originality/value This study contributes to emerging scholarship on AM by examining a South Asian ride-hailing platform that explicitly integrates ethical training with algorithmic oversight. It extends Gal et al. (2020) by demonstrating how algorithmic nudging and workplace datafication influence virtue cultivation in informal labor markets. The findings highlight the need for more transparent, participatory and ethically aligned algorithmic governance models.