Algorithmic Pricing and Transparency in the Gig Economy

Daniel Chen, PhD Candidate at the Wharton School, and Gad Allon, Operations, Information and Decisions, The Wharton School

Abstract: Algorithms control pricing and match customers and workers in the gig economy. However, algorithms face several critiques: they lack transparency, can be biased, and can be inefficient. We empirically analyze these issues and show that algorithms lose efficiency from two sources: competition between platforms and misaligned worker incentives. We model workers’ strategic responses to variation in pricing and estimate counterfactuals on the effects of minimum wage and transparent pricing policies.