Weighted Centrality and Retail Store Locations in Beijing, China: A Temporal Perspective from Dynamic Public Transport Flow Networks

Cong Liao,Tiantian Ding,Pengfei Zhao,Teqi Dai

doi:10.3390/app11199069

Cong Liao, Tiantian Ding + Show 2 more

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https://doi.org/10.3390/app11199069

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Journal: Applied Sciences	Publication Date: Sep 29, 2021
Citations: 5	License type: CC BY 4.0

Affiliation: Beijing Normal University, Peking University

Abstract

The spatial relationship between transport networks and retail store locations is an important topic in studies related to commercial activities. Much effort has been made to study physical street networks, but they are seldom empirically discussed with considerations of transport flow networks from a temporal perspective. By using Beijing’s bus and subway smart card data (SCD) and point of interest (POI) data, this study examined the location patterns of various retail stores and their daily dynamic relationships with three weighted centrality indices in the networks of public transport flows: degree, betweenness, and closeness. The results indicate that most types of retail stores are highly correlated with weighted centrality indices. For the network constructed by total public transport flows in the week, supermarkets, convenience stores, electronics stores, and specialty stores had the highest weighted degree value. By contrast, building material stores and shopping malls had the weighted closeness and weighted betweenness values, respectively. From a temporal perspective, most retail types’ largest correlations on weekdays occurred during the after-work period of 19:00 to 21:00. On weekends, shopping malls and electronics stores changed their favorite periods to the daytime, while specialty stores favored the daytime on both weekdays and weekends. In general, the higher store type level of the shopping malls correlates more to weighted closeness or betweenness, and the lower-level store type of convenience stores correlates more to weighted degree. This study provides a temporal analysis that surpasses previous studies on street centrality and can help with urban commercial planning.

Highlights

Location is a key factor for the commercial success of retail stores, as consumers tend to patronize stores that have higher access advantages [1,2]
As this study addresses public transport flows and retail activity, the analysis is conducted in the urban area of Beijing
Among the densities of the six types of retail stores, building material stores have the largest average density, which is followed by specialty stores, convenience stores, supermarkets, electronics stores, and shopping malls

Summary

Introduction

Location is a key factor for the commercial success of retail stores, as consumers tend to patronize stores that have higher access advantages [1,2]. Many factors may affect the location retail stores, which made it a complex and multi-dimensional problem [12]. Among these factors, transportation is often regarded as a key element for retail locations. The multiple centrality assessment (MCA) model, which groups several indices together, has been applied to examine the relationship between street centrality and the spatial distributions of retail stores [17]. Different cities around the world have been examined, and the findings indicate that the centralities of the physical street network may well explain the retail distributions [18,19,20,21].

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