Location effects: Geo-spatial and socio-demographic determinants of sales dynamics in brick-and-mortar retail stores |
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Affiliation: | 1. School of Marketing and International Business, Victoria University of Wellington, PO Box 600, Wellington, New Zealand;2. College of Business Zayed University Abu Dhabi Campus, P.O. Box 144534, Abu Dhabi, United Arab Emirates;3. College of Business Administration, American University in the Emirates, Dubai, United Arab Emirates;4. School of Business Administration, American University of Sharjah, PO Box 26666, Sharjah, United Arab Emirates;1. Deputy Director, Incheon International Airport Corporation, Incheon, South Korea;2. Professor, Graduate School of Logistics, Inha University, Incheon, South Korea;1. Graduate School of Economics, Keio University, 2-15-45 Mita, Minato-ku, Tokyo, 108-8345, Japan;2. Faculty of Economics, Keio University, 2-15-45 Mita, Minato-ku, Tokyo, 108-8345, Japan;3. RIKEN Center for Advanced Intelligence Project, Nihonbashi 1-chome Mitsui Building, 15th Floor, 1-4-1 Nihonbashi, Chuo-ku, Tokyo, 103-0027, Japan |
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Abstract: | For brick-and-mortar retail operators, store location is an essential prosperity factor, affecting the volume and structure of sales. Understanding the complexity of location effects on sales dynamics and utilizing such information may be the key element of corporate success in a competitive market environment. In general, store locations can be characterized by representative sets of geo-spatial and socio-demographic features. Nowadays, multiple sources of location-related data are available from public authorities and other open sources. However, using such data may be a complex task: distinct location factors can have divergent effects on sales of different types of products. Hence, our objective is to quantify the effects of different measures of location on sales dynamics over a wide range of product categories. For this purpose, we introduce a methodology combining econometric modeling and cluster analysis. The presented empirical analysis is performed using data on 479 brick-and-mortar shops of a major drugstore chain operating in Czechia (2019 data are used to avoid distortions due to COVID-19). Besides estimating location effects on sales at the product-category level, we identify and evaluate groups (clusters) of product categories with similar sales dynamics. Both the methodology proposed and the empirical results presented can be utilized by different retail chains to assess and plan brick-and-mortar store locations. Also, the research presented can be instructive for academic researchers and other stakeholders in the fast-moving consumer goods sector. |
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Keywords: | Store location Location planning Location effect Sales dynamics |
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