The Algorithmic Precarity of 'Ojol' Drivers: Investigating the Gig Economy and Digital Resistance in Southeast Asia’s Largest Market

Abstract

The rise of ride-hailing platforms like Gojek and Grab has transformed Indonesia into one of the world’s largest laboratories for the gig economy. However, beneath the promise of "flexible work" lies a growing phenomenon of algorithmic precarity. This paper investigates how digital platforms exercise "soft control" over drivers through opaque rating systems, incentive structures, and automated suspensions. Employing a mixed-methods approach—comprising digital ethnography in driver Telegram groups and semi-structured interviews—this study maps the forms of "digital resistance" emerging among ojek (motorcycle taxi) drivers. These include the use of "tutor" apps to bypass GPS restrictions and the formation of informal grassroots unions to demand transparency. The findings indicate that the algorithm functions as a digital panopticon that shifts operational risks from the corporation to the individual worker. This research contributes to global labor sociology by demonstrating that despite the lack of formal employee status, gig workers in the Global South are developing sophisticated counter-narratives and collective strategies to challenge technological hegemony.