Spatiotemporal Analysis of Imitation Behavior across New Buyers at an Online Grocery Retailer

Abstract

For Internet retailers, demand propagation varies not only through time but also over space. The authors develop a Bayesian spatiotemporal model to study two imitation effects in the evolution of demand at an Internet retailer. Building on previous literature, the authors allow imitation behavior to be reflected both in geographic proximity and in demographic similarity. As these imitation effects can be time varying, the authors specify their dynamics using a “polynomial smoother” embedded within the Bayesian framework. They apply the model to new buyers at Netgrocer. com and calibrate it on 45 months of data that span all 1459 zip codes in Pennsylvania. The authors find that the proximity effect is especially strong in the early phases of demand evolution, whereas the similarity effect becomes more important with time. Over time, new buyers are increasingly likely to emerge from new zip codes beyond the “core set” of zip codes that produce the early new buyers, and spatial concentration declines. The authors explore the managerial implications stemming from these findings through a hypothetical “seeding” experiment. They also discuss other implications for Internet retailing practice.