Invisible inequalities: Gender, safety, and income disparities in India’s platform economy

Abstract

Purpose: This study investigates the contemporary transformation of urban labour markets via digital platform mediation, focusing specifically on the gendered structural frameworks governing participation, monthly compensation structures, occupational environments, and operational satisfaction metrics within Mumbai's expanding gig economy. Methodology: Utilizing an explanatory sequential mixed-methods framework, the empirical architecture evaluates primary data compiled from a stratified convenience sample of 200 active digital platform laborers (120 male, 80 female) across key operational segments including ride-hailing, logistical fulfillment, domestic services, and on-demand personal beauty services. The quantitative configuration evaluates systematic dependencies through multivariate OLS linear regressions, Pearson product-moment correlations, and non-parametric Chi-square test frameworks, coupled with descriptive contextual validations. Key Findings: OLS econometric estimations establish that independent of aggregated weekly labor allocations, explicit institutional disparities and implicit gender structures persist. Women workers encounter compressed monthly compensation thresholds (Mean = ₹15,300) relative to male counterparts (Mean = ₹24,800), compounded by a restricted capacity to leverage incremental working hours (β = 350, p < 0.01). Furthermore, non-parametric assessments identify a significant structural covariance between gender categories and operational satisfaction indices, heavily depressed by critical safety exposures, systemic domestic care burdens, and implicit algorithmic task-allocation asymmetries.