Optimal Retail Location: Empirical Methodology Application to Practice
Operations, Information, & Decisions Department; Faculty Advisers: Santiago Gallino, Antonio Moreno
The food industry has undergone considerable change in an effort to improve the convenience and efficiency of the shopping experience. Online ordering together with food delivery apps have streamlined the experience for consumers looking to reduce time by ordering their groceries in advance.
For her research, Chloe partnered with an online grocer that offers customers two services: 1) delivery to their door at a cost, and 2) free pick-up from a third-party location, which changes depending on the day, at a specified time.
Focusing on the free pick-up option, Chloe has created a maximization model as a function of r (the revenue from operating location i at date t), s (spatial cannibalization on location i attributed to location j at time t), and t (temporal cannibalization on location i). Using this model, Chloe creates a heat map of an area to predict the revenue at each pick-up location, and determine which locations, after accounting for spatial and temporal cannibalization, will maximize revenue. Using this information, Chloe has identified which areas are over- or under-saturated and can make recommendations for retailers to reconfigure their pick-up locations in a select area.
Publications, Presentations & Awards
Kim Glaeser, Chloe, Marshall Fisher and Xuanming Su (2017), “Optimal Retail
Location: Empirical Methodology and Application to Practice,” Working Paper.