Data-Guided Gravity Model for Competitive Facility Location

In this paper we introduce a data analytics approach for specifying the gravity model as applied to competitive facility location. The gravity model is used primarily by marketers to estimate the market share attracted by competing retail facilities. Once the market share is computed, various solution techniques can be applied for finding the best locations for one or more new facilities. In competitive facility location research, various parametrized gravity models have been proposed such as the power and the exponential distance decay specifications. However, parameterized approaches may not be robust to slight data inconsistency and possibly leading to inaccurate market share predictions. As the volume of data available to support managerial decision making is growing rapidly, non-parametric (data-guided) approaches are naturally attractive alternatives as they can mitigate parametric biases. We introduce a unified gravity model that encompasses practically all existing parametric gravity models as special cases. We provide a statistical framework for empirically estimating the proposed gravity models focusing on shopping malls data involving shopping frequency.