Background: Gig economy has shifted working relationships - particularly via digital platforms such as Uber, Upwork, Deliveroo and Fiverr. While gig work is flexible and independent, there are concerns raised by researchers that the experience of gig work could involve income instability, algorithmic control, a distinction between work and leisure, and poor mental health, which may affect the health of workers and their satisfaction.

Research Question: What are the past, empirical and theoretical studies on the work–life balance and job satisfaction of platform-based gig workers, and what are the gaps, inconsistencies and determinants?

Methodology: The method followed in this systematic literature review was the Antecedents–Decisions–Outcomes (ADO) framework, which involved synthesizing and organizing the literature that was found regarding work–life balance and job satisfaction of gig workers. The review was performed with the methodology SPAR-4-SLR and the report followed the PRISMA 2020 guidelines. The supplementary search was conducted in the databases: Literature published between 2016 and 2026 from Scopus, Web of Science, ScienceDirect, Emerald Insight, Taylor & Francis, SpringerLink, Wiley Online Library, Sage Journals and Google Scholar.

Key Findings: Eight themes emerged: flexibility-driven WLB; autonomy and intrinsic motivation strengthening JS; income instability threatening psychological well-being; algorithmic governance leading to technostress and power inequality; burnout due to increased digital surveillance; gendered precarity; occupational insecurity decreasing satisfaction; and psychological well-being as a mediator. The theoretical framework that are most supported within this finding includes the Job Demands–Resources, Self-Determination Theory, Boundary Theory and Spillover Theory.

Implications for research: Future research should integrate JD-R with SDT and integrate longitudinal studies with cross-cultural and gender-balanced designs or samples, particularly on emerging platforms that are based on AI tools, especially in developing economies.

Practical implications: Platform managers to create algorithms, transparency of compensation, prediction tools, mental health programs, and sustainable HR practices that are humane.. Policymakers need to apply the same principles to labor protections in nontraditional jobs as in traditional jobs.

Originality/value: This review is a novel combination of WLB and JS in the gig economy, which spans the various theoretical lines and provides a clear research agenda for future work.....