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Title: Locating a shopping centre by considering demand disaggregated by categories
Authors: Suárez-Vega, Rafael 
Gutiérrez-Acuña, José Luis
Rodríguez-Díaz, Manuel 
UNESCO Clasification: 12 Matemáticas
Keywords: Geographically Weighted Regression
Competitive Facility Location
General Framework
Gis Tools
Models, et al
Issue Date: 2018
Journal: IMA Journal Management Mathematics 
Abstract: We model a shopping centre. The demand for goods and services in shopping centres is classified in four different categories: food, leisure, household goods and clothing. As some of these sectors do not provide essential goods and services, a Huff customer-choice model is applied that sets a parameter absorbing any lost demand when there is a shortfall in customer attraction. For each category, the parameters for the Huff model are estimated both globally (by means of ordinary least squares, assuming the same effect for the parameters throughout the entire market), and locally (using geographically weighted regression, considering that parameters depend on the customers’ location). The proposed model was applied to a real data case on the island of Gran Canaria (Spain) to determine the best location for a shopping centre selling all four categories of goods. Finally, a study is conducted to determine how robust the solution is with respect to the lost demand parameter, and a comparison is made between the solutions obtained, using both global and local calibration methods.
ISSN: 1471-6798
DOI: 10.1093/imaman/dpx006
Source: IMA Journal Management Mathematics [ISSN 1471-6798], v. 29 (4), p. 435–456
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