Competitive Location Modeling with a Rank Proportional Allocation

Abstract

Competitive location modeling deals with a strategic spatial decision which seeks to identify optimal locations for new facilities among existing competing facilities. The capture of customers by a new facility essentially depends on customer-choice behaviors. In this paper, we introduce a competitive location model incorporating a rank proportional choice rule. Also, we explore how the competitive location model with a ranking system differs from other models with two more-typical choice rules—deterministic and probabilistic choices. To do so, we present a numerical example and an illustrative application in the broadband market context, focusing on customer-capture patterns. Our analytical findings reveal that the different choice rules in modeling significantly influence customer-capture and market-share estimates. In particular, a competitive location model with a rank proportional allocation captures fewer customers than other models with different allocation rules, given a fixed number of few facilities.