Research Summary: Forced volatility: earnings and incentives for gig work in quick commerce

The rapid growth of India's quick commerce sector, driven by platforms like Blinkit, Zepto, and Swiggy Instamart, has significantly expanded the gig economy. This expansion relies on a large, flexible delivery workforce, yet it raises critical issues regarding worker earnings, working conditions, and social security. Platforms utilize opaque algorithms to determine pay and task allocation, leading to variable and unpredictable earnings for workers and creating significant information asymmetry.

Why it matters

This development highlights the evolving operational models in high-growth digital sectors and their societal impact. The interplay between algorithmic management, workforce flexibility, and worker welfare presents a complex challenge that could influence regulatory frameworks and public perception of the gig economy globally.

Key insights

• India's quick commerce sector is experiencing explosive growth, significantly contributing to the national gig economy.
• The sector relies on extensive networks of 'dark stores' and a flexible delivery workforce for rapid grocery and essential deliveries.
• Pressing concerns exist regarding wages, working conditions, and social security for gig workers in this sector.
• Platform operations are characterized by opaque algorithms that dictate worker pay, task assignments, and performance evaluations.
• Worker earnings are subject to unpredictable fluctuations based on factors like weather and availability, without clear explanation.
• A significant information asymmetry prevents workers from understanding how their pay is calculated or how it varies.

Source

arXiv — Computers and Society — https://arxiv.org/abs/2609.13178