Bulletin’s strike map has documented a total of 567 collective actions among food delivery riders, and more than 170 cases among ride-hailing drivers, which represents at best a tip of the iceberg.
To date, existing studies to understand this dialect of precarity and resistance tend to take the labour process approach (Burawoy, 1979; Gandini, 2019; Smith & Thompson, 1998) and locate platform workers’ precarity in the realm of the immediate labour process. It has been argued that algorithmic management is the main factor behind platform worker precarity. By algorithmic management scholar denote an algorithmic system that is constantly fed by labour process and user data to automate workforce direction, evaluation and discipline (Kellogg et al., 2020; van Doorn & Chen, 2021). Main mechanisms of algorithmic management include automated order dispatching, automated evaluation and rating, dynamic pricing and information asymmetries, among others. The goal is to produce just-in-time and just-in-place labour. In addition, customers are invariably granted organizational power of direction, monitoring and evaluation over workers to laundering control (Y Zhou, 2020), further supplemented by subcontractors or third-party labour intermediaries (Li, 2021). Finally, these control mechanisms evolve over time, depending on the platform’s desire to increase profit margin, the changing institutional environment and the expectations of financial capital. All these arrangements are found to be able to socially, legally, spatially individualize workers, thus accounting for various forms of precarity outlined earlier.
In the meantime, this largely technology-enabled, dispersed form of labour process arrangement and individualization paradoxically also offer platform workers free space to associate, through both social media and offline interactions. As a result, like platform workers in Europe, in China they have strong associational power (Joyce et al., 2023; Zhou & Pun, 2024). Apart from mild forms of mutuality and contingent agency, riders and drivers also resort to more confrontational collective actions. Insofar as platforms rely on riders and drivers to deliver orders, this very simple fact gives them strong workplace bargaining power against the platform and third-party agencies. In moments of resurgence, platform workers’ strong associational power can translate into strong collective workplace bargaining power, to pressure management and government concession. Research further noted that the very marketplace flexibility platforms tap into, also gives riders stronger marketplace bargaining power, i.e. even though when the unemployment rate is high, workers can still switch between different platforms easily, thus reducing their reliance on certain platforms while enhancing their collective power of resistance (Liu & Friedman, 2021; Zhao & Luo, 2023).
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