Archive | 2019
A Fuzzy Base Classifier for Fuzzy Data Included Location Segmentation
Abstract
Location Segmentation has several strategic and tactical implications in marketing products and services. Despite hard clustering methods having several weaknesses, they remain widely applied in marketing studies. Alternative segmentation methods such as fuzzy methods are rarely adapted to understand consumer location visiting tendency. In this study, we propose a strategy of analysis, by combining Adaboost algorithm and the fuzzy decision tree methodology for fuzzy data. The results emphasis on the heterogeneity in consumers’ place preferences and implications for marketing are offered.