Distributed coping under algorithmic HRM: extending the Transactional Model of Stress and Coping in platform-based online freelancing

Purpose This study investigates how platform-based online freelancers navigate algorithmically mediated stressors through distributed coping and extends the Transactional Model of Stress and Coping (TMSC) under algorithmic HRM. Design/methodology/approach Drawing on 41 semi-structured interviews with Sri Lankan freelancers delivering creative and professional services via global platforms, this study employs an abductive, Gioia-guided analysis within a theory-elaboration approach. TMSC is treated as a sensitising framework, while the analysis remains open to emergent dynamics that extend beyond its original scope. Findings The findings identify four key extensions to the TMSC: (1) Primary appraisal is reconceptualised as socially distributed rather than individual, emerging through collective sensemaking under conditions of algorithmic opacity; (2) Secondary appraisal is shown to be structurally delimited by platform governance in the absence of institutional resource pathways; (3) Coping generates paradoxical outcomes, sustaining short-term functioning while reinforcing conditions of chronic precarity; and (4) Coping resources are assembled through a distributed ecology spanning platform affordances/induced behaviours, peer networks, clients, families, and AI tools. Practical implications Platforms should enhance algorithmic transparency and provide structured worker support. Policymakers should invest in digital infrastructure and portable social protections. Worker collectives and educational institutions can formalise distributed support mechanisms and build algorithmic literacy. Originality/value This study advances TMSC by identifying four theoretically grounded extensions that reposition the model to explain how workers appraise and cope with algorithmic HRM stressors in the Global South, highlighting the collective and paradoxical nature of coping in algorithmically governed labour markets.