Price Elasticity Variations across Locations, Time and Customer Segments: An Application to the Self-Storage Industry
33 Pages Posted: 9 Dec 2018 Last revised: 6 Feb 2024
Date Written: January 24, 2024
Abstract
The demand for services such as self-storage varies across locations, over time, and across customer segments. Service providers try to leverage these variations and maximize profits by adopting dynamic pricing policies. Implementing such policies requires accurate estimates of price elasticities at a granular level. Using data from a leading self-storage retailer in Europe, we estimate a Bayesian Dynamic Hierarchical Linear Model (DHLM) to obtain price elasticities across 67 stores, for 21 bi-weeks, and high-valuation vs. low-valuation customer segments. Our estimation procedure accounts for price endogeneity, which is essential when using the estimated price elasticities to set dynamic pricing policy. We find evidence of different price elasticities between stores and over time, which supports the practice of local dynamic price setting, and also strong differences between customer segments. Overall, high-valuation customers are more price-sensitive than low-valuation customers. Further, while the price elasticity of high-valuation customers remains stable, low-valuation customers become less price sensitive over time. This suggests a markup policy for low-valuation customers and a stable pricing regime for high-valuation customers. We show our model's benefits over a benchmark model with time-invariant price elasticities in determining pricing policy, and discuss how it can be applied to other industries practicing revenue management.
Keywords: Price Elasticity, Bayesian Models, Endogeneity, Revenue Management, Retailing
JEL Classification: C11, C32, M31
Suggested Citation: Suggested Citation