4.6 Article

Assessing the Relative and Combined Effects of Network, Demographic, and Suitability Patterns on Retail Store Sales

期刊

LAND
卷 12, 期 2, 页码 -

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MDPI
DOI: 10.3390/land12020489

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network analysis; regression; artificial intelligence; site selection; spatial analysis; retail

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Despite challenges in acquiring proprietary sales data, there is a wealth of literature using different types of data to understand or represent drivers of retail store sales. This study analyzes the relative influence of road networks, demographic, and suitability variables on store sales and demonstrates that road network patterns have a greater impact than demographic and suitability variables in predicting store sales. The analysis builds on previous research estimating consumer spending and incorporates spatial interaction models and other unique criteria typically used in isolation, showing the critical role of network patterns in retail store sales.
Despite challenges associated with acquiring proprietary sales data, there exists a wealth of literature using different types of data (e.g., spending, demographic, geographic) to understand or represent different drivers of retail store sales. We contribute to the spatial analysis of drivers of retail store sales by analyzing the relative influence of road networks, demographic, and suitability variables on retail store sales within the home-improvement sector. Results demonstrate that the inclusion of variables describing the road network pattern is more influential in predicting store sales than demographic and suitability variables with linear models (e.g., ordinary- and partial-least squares regression) as well as with a non-linear mathematical model derived using artificial intelligence. The analysis builds on previous research estimating consumer spending and a big-data suitability analysis for site selection that incorporates spatial interaction models, location quotient, and other unique criteria that are typically used in isolation. The overarching contribution of our results is the demonstration that network patterns can play a critical role in retail store sales, especially when regressions, analogs, and other simple methods for site selection are used.

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