Network Planning and Retail Store Segmentation

Author:

Bermingham Philip1,Hernandez Tony2,Clarke Ian3

Affiliation:

1. Centre for Study of Commercial Activity, Ryerson University, Toronto, ON, Canada

2. Centre for the Study of Commercial Activity, Ryerson University, Toronto, ON, Canada

3. 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.

Publisher

IGI Global

Subject

Earth and Planetary Sciences (miscellaneous),Geography, Planning and Development

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Store Segmentation in Retail Industry Using Clustering Algorithms;Lecture Notes in Networks and Systems;2022

2. Retail analytics: store segmentation using Rule-Based Purchasing behavior analysis;The International Review of Retail, Distribution and Consumer Research;2021-04-29

3. Spatial structure system of land use along urban rail transit based on GIS spatial clustering;European Journal of Remote Sensing;2020-11-14

4. Retail Store Segmentation for Target Marketing;Lecture Notes in Computer Science;2015

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