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Network Planning and Retail Store Segmentation: A Spatial Clustering Approach

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  • Philip Bermingham

    (Centre for Study of Commercial Activity, Ryerson University, Toronto, ON, Canada)

  • Tony Hernandez

    (Centre for the Study of Commercial Activity, Ryerson University, Toronto, ON, Canada)

  • Ian Clarke

    (Newcastle University Business School, New Castle University, Newcastle upon Tyne, UK)

Abstract

Store segmentation aims to divide a network of stores into meaningful groups, typically based on a combination of operational, site and trading environment characteristics. It is an increasingly important component within network planning activities of major retail chains due to the significant capital investment that is physically grounded in their large store networks. The paper outlines findings from case study research that has focused on developing spatial decision support tools that enable decision makers to explore, construct and visualize store segments. An integrated spatial statistical approach to store segmentation is detailed and associated benefits and shortfalls discussed. The paper highlights the potential to develop customised geospatial tools to support network planning decision making activities. It is argued that geospatial decision support tools need to be designed to accommodate the varying GIS skill-levels of potential end-users and that fundamentally more emphasis needs to be placed on creating tools that can be used by decision-makers as opposed to analysts.

Suggested Citation

  • Philip Bermingham & Tony Hernandez & Ian Clarke, 2013. "Network Planning and Retail Store Segmentation: A Spatial Clustering Approach," International Journal of Applied Geospatial Research (IJAGR), IGI Global, vol. 4(1), pages 67-79, January.
    • Handle: RePEc:igg:jagr00:v:4:y:2013:i:1:p:67-79
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