Site Selection of Outdoor Advertisement for Home Decoration Brands Based on Multi-source Spatial Big Data

被引：0
|
作者：
Zhang J. [1 ]
Du K. [1 ]
Ren S. [1 ]
Wang R. [1 ]
Guan Q. [1 ]
Chen W. [2 ]
Yao Y. [1 ,3 ]
机构：
[1] School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan
[2] School of Information Engineering, Zhejiang A&F University, Hangzhou
[3] Alibaba Group, Hangzhou
来源：
Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | 2022年 / 47卷 / 09期
基金：
中国国家自然科学基金;
关键词：
block feature set; in-store conversion rate; multi-source data; outdoor advertisement; random forest;
D O I：
10.13203/j.whugis20190468
中图分类号：
学科分类号：
摘要：
Objectives: Outdoor advertisement can attract the attention of target user groups and increase brand influence, and site selection is the most important influencing factor for its effectiveness. Reasonable site selection plays a positive role in improving brand awareness and expanding the market. However, due to the difficulty in obtaining commercial data, previous studies on a macro and rough scales failed to conduct detailed analysis on the actual effects of site selection. Methods: We propose a framework to solve the above problems. Firstly, we extract feature sets from geographical attributes and commercial economic attributes and preprocess them using mathematical statistics and the geographical processing basic method. Then, by coupling of the in-store conversion rate with road network characteristics, point of interest (POI), and other multi-source spatial features, a random forest model is constructed to mine the correlation between them. Finally, the importance of each feature is quantified. Results: We choose Beijing as the study area, and build a prediction model for the in-store conversion rate of a home decoration brand based on this framework. The model shows a good performance (Standard R2=0.758). Then we obtain the spatial distribution and factors influencing the suitability of outdoor advertising for this home decoration brand in Beijing. The in-store conversion rate of the brand is high in the center and is low in the periphery of Beijing, which features the phenomena of strong spatial autocorrelation and high-value aggregation. Meanwhile, the in-store conversion rate has a significant correlation with social economy, commercial politics, and crowd activities. The location of continuous advertising exposure to the same group has a great influence on the in-store conversion rate. Conclusions: The fine mapping results of the model constructed in this study can quantitatively evaluate the advertising effect of each location and maximize the efficiency, which can provide a reference and theoretical basis for relevant studies on the outdoor advertisement or commercial site selection. © 2022 Wuhan University. All rights reserved.
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页码：1406 / 1415
页数：9
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