Paper Info
Title
Site Selection of Retail Shops Based on Spatial Accessibility and Hybrid BP Neural Network.
Abstract
The increase of consumer income has resulted in the rapid development of the retail industry in China, which provides high market potential for retail companies worldwide. However, site selection for retail shops has been a confusing business issue in practical business decisions. In this study, a two-step hybrid model in site selection for small retail shops was proposed. The two steps were spatial accessibility evaluation and market potential estimation. The spatial accessibility of target regions was evaluated based on the improved gravity model to determine regions that lack retail shops. Then, a PCA (principal component analysis)-BP (backpropagation network) model was established to estimate the market potential in the target regions. The two-step model could determine sites with the most market potential and low competition. We conducted the experiment in Guiyang, China and considered 18 socioeconomic factors to make the site selection convincing. Through the experiment, 42 locations were determined with high business value; the locations were recommended to the new retail shops. The accuracy of the PCA-BP model was then proven satisfactory by comparing it with other regression methods. The proposed model could guide retail chains in enhancing business location planning and formulating regional development policies.
Year
DOI
Venue
2018
10.3390/ijgi7060202
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
Keywords
Field
DocType
PCA-BP,retail shops,spatial accessibility,site selection
Market potential,Business value,Retail industry,Site selection,Gravity model of trade,Industrial organization,Artificial neural network,Backpropagation,Principal component analysis,Business
Journal
Volume
Issue
ISSN
7
6
2220-9964
Citations 
PageRank 
References 
0
0.34
7
Authors
3
Name
Order
Citations
PageRank
Luyao Wang144.20
Hong Fan2114.96
Yankun Wang311.03