Visual analysis of retailing store location selection
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R E G UL A R P A P E R
Kirlin Li • Yi-Na Li • Hong Yin • Yanpeng Hu • Peng Ye • Changbo Wang
Visual analysis of retailing store location selection
Received: 29 February 2020 / Revised: 13 May 2020 / Accepted: 15 June 2020 The Visualization Society of Japan 2020
Abstract An appropriate location of the retailing store is vital for achieving business success. However, a massive amount of complex information needs to be considered in location selection, such as customer flow, the business environment, and current business performance. Unlike the traditional location recommendation method of statistical sampling, we establish a model of business-district attractiveness based on customer flow. Besides, we build an interactive visual analysis system with a user-friendly interface for an interactive visual query about complex business and environment information. Our system can help users select retailing store locations, support interactive visual queries and display rich information to facilitate managers in decision-making. Keywords Location recommendation Visual analysis system Attractiveness model Customer flow
1 Introduction Choosing an appropriate location for retailing stores has great influences on business success. Population, traffic and accessibility, zoning and neighbors, location cost, existing sales performance, public transit durations and distances, and geographical attributes are essential factors for a manager to choose a place for business (Beatty et al. 1996). Traditional approaches to retailing store location selection based on statistical random sampling and probabilistic inference result in significant deviations because of the volatility of
K. Li H. Yin (&) C. Wang East China Normal University, Zhongshan, China E-mail: [email protected] K. Li E-mail: [email protected] C. Wang E-mail: [email protected] Y.-N. Li University of Techonlogy Sydney, Sydney, Australia E-mail: [email protected] Y. Hu Shanghai Chinafortune Co., Ltd, Langfang, China E-mail: [email protected] P. Ye ChengShu Information Technology, Shanghai, China E-mail: [email protected]
K. Li et al.
Fig. 1 Location recommendation system. a A navigation window provides functions of selection and input. b Statistical analysis view shows flow information, sales information and the market expectation from expert experience. c Location recommendation view provides the solutions and market prosperity. d Business influence view shows the influence area of business districts. e Visual comparison view shows the details and ranking of the solutions
customer flow. Interactive queries and user-friendly interfaces can solve the location selection problem (Fig. 1). Based on the traditional methods, this paper puts forward a convenient and promising method to choose locations for retailing stores. We propose an optimized market attractiveness model based on the analysis of customer flow, which is combined with economic knowledge and experts’ experience (Tretyak and Sloev 2013). It proves customer f
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