Next Article in Journal
The Use of Geographic Databases for Analyzing Changes in Land Cover—A Case Study of the Region of Warmia and Mazury in Poland
Previous Article in Journal
Geospatial Assessment of Soil Erosion Intensity and Sediment Yield Using the Revised Universal Soil Loss Equation (RUSLE) Model
Open AccessArticle

Site Selection Improvement of Retailers Based on Spatial Competition Strategy and a Double-Channel Convolutional Neural Network

1
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
2
Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(6), 357; https://doi.org/10.3390/ijgi9060357
Received: 14 April 2020 / Revised: 9 May 2020 / Accepted: 24 May 2020 / Published: 27 May 2020
The issue of site selection has become a critical challenge in the development of the retail industry with the growth of the Chinese economy and the improvement in the level of household consumption. Previous studies have considered the area of stores as the main factor of retail competition; however, the actual business performance of different stores in these studies was ignored. In addition, few studies have considered the differences in the spatial distribution of the factors of site selection. In this study, we discuss the improvement of site selection of small retail shops. A spatial competition index model was proposed as one of the features in estimating region market potential, and a market demand regression model of a double-channel convolutional neural network (CNN) was constructed based on the spatial correlation range of features. The study area was Guiyang, China. The experiments were based on the monthly sales data of fast-moving consumer goods retail stores in Guiyang. On the basis of the estimated results of the model, 18 sites with high potential for market demand were recommended. The performance of the proposed model was the best among well-known regression methods. Moreover, in comparison with a single-channel CNN, the proposed model decreased the root mean square error by 22.61%. Evaluation results showed that the proposed method could provide effective decision support for the issue of retail site selection. View Full-Text
Keywords: double-channel convolutional neural network; retail site selection; spatial competition; spatial correlation; market demand double-channel convolutional neural network; retail site selection; spatial competition; spatial correlation; market demand
Show Figures

Figure 1

MDPI and ACS Style

Ouyang, J.; Fan, H.; Wang, L.; Yang, M.; Ma, Y. Site Selection Improvement of Retailers Based on Spatial Competition Strategy and a Double-Channel Convolutional Neural Network. ISPRS Int. J. Geo-Inf. 2020, 9, 357.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop