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.
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Oner, S.C., Oztaysi, B. (2020). A Fuzzy Base Classifier for Fuzzy Data Included Location Segmentation. In: Kahraman, C., Cebi, S., Cevik Onar, S., Oztaysi, B., Tolga, A., Sari, I. (eds) Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making. INFUS 2019. Advances in Intelligent Systems and Computing, vol 1029. Springer, Cham. https://doi.org/10.1007/978-3-030-23756-1_22
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DOI: https://doi.org/10.1007/978-3-030-23756-1_22
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