Market Area Analysis and Intelligence Through Geoweb Map Segmentation

Abstract

Segmentation is of particular interest in market area analysis and intelligence. A generalized Voronoi influence model provides a flexible framework for segmenting diverse business cases and market tessellations. In this article, we propose a Voronoi influence model-based computational framework for mining various user-supplied business and market data sets from a GeoWeb model, in particular from Yahoo Local. The market area analysis and intelligence provided by the generalized Voronoi model can be effectively used for various market intelligence and strategy decision support. The advantages of using this computational model from the GeoWeb framework is the access to enormous amounts of participation-driven information on businesses and services available on the Internet. The proposed model supports weighted analysis, order-k analysis (k-nearest neighbor analysis), various metrics modeling different scenarios, complex modeling data types representing complex real-world situations, and obstacles modeling real-world barriers through a series of generalized Voronoi diagrams. We provide a series of cases studies that demonstrate the usefulness and practicability of the proposed model.