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An extended Huff-model for robustly benchmarking and predicting retail network performance
Affiliation:1. State key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, PR China;2. Collaborative Innovation Center for Geospatial Technology, Wuhan, PR China
Abstract:This study proposes a modified Huff model that takes directly into account spatial competition between stores of the same brand, brand attraction based on actual brand performance and spatially variable substitution. The model uses only publicly available or easily acquirable data as input, whereas model output is extensively validated on various levels. These levels include comparison of modeled and real market shares on block, store and brand level for the Belgian food market. Results show that multi-objective optimization of model parameters yields comparable results on block level to other models in the literature but improved results on store and brand levels, thereby ensuring model robustness. This robustness also enables the application of the model for various business purposes as store location determination, leaflet distribution optimization, store and store concept benchmarking, without loss of spatial generality.
Keywords:Huff model  Retail management  Spatial competition  Multi-objective optimization  Store benchmarking  Turnover prediction
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