Driven by the Algorithm: The Invisible Hand Steering Gig Worker Performance.

Abstract

Technological advances have catalysed the growth of the gig economy, redefining global work patterns by offering flexible freelance engagements, especially in ride-hailing services. This shift holds particular significance for countries like Sri Lanka, where the COVID-19 pandemic has amplified economic challenges and made gig work an attractive alternative. In this digital era, ridehailing drivers are subject to algorithmic control that manages their performance through monitoring, feedback, and automated controls. However, the effect of such digital management on driver performance in non-Western settings remains underexplored. Consequently, our study investigates the influence of algorithmic output control on the work performance of Uber drivers in Sri Lanka, considering the mediating role of challenge technostress. Our results reveal that algorithmic output control alone does not guarantee improved performance; rather, the drivers’ positive interpretation of these controls is essential. When algorithmic directives are perceived as developmental opportunities rather than steady constraints, drivers exhibit higher customer ratings and more reliable operational performance. These findings suggest that digital platform design should improve clarity and transparency to persuade these positive perceptions. PLS-SEM has been utilised to analyse the data collected through a questionnaire, where the sample was drawn through purposive sampling. In summary, our research supports a nuanced view of algorithmic management, highlighting its impact on workers’ performance. Future studies should explore platform interventions, including enhanced feedback systems and digital literacy programs, to promote challenge-oriented technostress and improve overall performance in the gig economy.