Dynamic Pricing and Demand Volatility: Evidence from Restaurant Food Delivery

Abstract

Pricing technology that allows firms to rapidly adjust prices has two potential benefits. Prices can respond more rapidly to demand shocks, leading to higher revenues. On the other hand, time-varying prices can be used to smooth out demand across periods, reducing costs in markets with capacity constraints. Using data from the staggered adoption of a pricing algorithm, we measure the impacts of time-varying pricing in the context of restaurant food delivery. On average, the pricing algorithm reduced prices, though it led to substantial variation in prices within and across days. We find that the adoption of time-varying pricing reduced demand volatility, resulting in a relative increase in the share of transactions occurring during low-demand periods. Consumers appear to strategically time purchases at high frequencies and also across days of the week. We estimate that the volatility semi-elasticity, which we define to reflect the relationship between time-series variation in quantities and prices, is -1.96. Our results point to the potential efficiency gains of time-varying pricing when firms face capacity constraints.

Keywords: Pricing Algorithms, Dynamic Pricing, Demand Volatility, Delivery Services

JEL Classification: D4, L1, L81, L86