The algorithmic management of gig work on digital platforms is both similar to and distinct from Taylorist forms of organising work. Drawing on interviews with over 300 gig workers on ride-hailing, food delivery, home service and other platforms in India in 2023, this paper argues that algorithmic management reduces worker control over the outcomes (in work allocation, wage, disciplinary action) and routines (volume, hours and location) of work. Further, this decline in control stemming partially from algorithmic management is compounded by the specific forms of alienation that gig workers face from platform management at one end and customers at the other.

Focusing on the Chinese context, this investigation addresses digital labor platforms that mediate interactions between workers and clients as specific instances of social media. This article addresses the evolving landscape of domestic labor in contemporary China, specifically focusing on female internal migrant workers - commonly referred to as “Ayi’s” - in the gig economy. More specifically, by employing a feminist intersectional lens, we analyze how digital labor platforms broker migrant Ayi’s subjectivities and address how these rural-to-urban migrants may create a new narrative for themselves. Based on in-depth interviews with 15 female migrant workers alongside a walkthrough study of three digital labor platforms, Ayi’s are found to represent themselves by branding themselves. This form of self-marketing offers the potential to transform their visibility in public from perceived low-skilled laborers to “pre-packaged” professionals. While enhancing visibility, and thereby improving the standing of some, the representational practices of Ayi’s also offer insights into newly emergent forms of vulnerability and marginalization, shaped by gender, migrant status, and socioeconomic class.

Platforms play an increasingly prominent role in today’s economy. As big tech companies like Alphabet, Meta and Alibaba leverage their size and access to large amounts of data to provide value for their users and shareholders, platforms have begun to emerge within the gig economy. The gig economy is where individuals rent out their labour, and has rapidly grown in recent years. This paper focuses on Fiverr, an online freelancing platform in the gig economy that allows individuals to sell their services to anyone who can access it. We undertake a longitudinal case study, exploring and analysing how Fiverr has developed its business to provide a number of services that facilitate the operation of the platform. We explain growth drivers, innovation strategies and show how they favour the buyer, which has created tensions in the operation of the platform. Additionally, we contextualize Fiverr, and online freelancing more generally, within two major socio-technical developments in recent years, namely the Covid-19 pandemic and the rise of generative AI, showing the turbulent times such platforms are currently facing.

The intersection of gender dynamics and platform-based gig work emerges as a pivotal, albeit under-researched, domain in contemporary scholarship. This article seeks to bridge this gap by looking into the gendered dimensions of the food delivery sector in China’s gig economy. By adopting "friction" as an analytical lens, this study aims to illuminate the nuanced encounters, challenges, and systemic barriers female delivery workers face within the predominantly male-oriented food delivery industry. We examine how control operates through various social structures—family, workplace, and societal environment—creating friction in the daily work experiences of female platform workers. We reveal that the gendered division of labor within families limits women's commitment to platform work, putting them at a disadvantage against algorithmic control favoring stable workers. Female food delivery riders, in particular, face gendered segregation during breaks, hindering camaraderie and knowledge exchange with male counterparts. Their gender becomes a salient identity, subjecting them to sexist slurs and suspicion from security guards. Different from existing studies on solidarity and resistance among gig workers, these female riders view platform work as a means to enhance economic independence but face constant setbacks thanks to their female gender. We argue that these frictions women workers experience in the platform economy are not only shaped by algorithmic control but conditioned with long-existing social structures, which further marginalize and isolate women in gig worker mobilization and resistance.