Big geo-data unveils influencing factors on customer flow dynamics within urban commercial districts

IF 7.6 Q1 REMOTE SENSING
Xia Peng , Yue-yan Niu , Bin Meng , Yingchun Tao , Zhou Huang
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引用次数: 0

Abstract

Commercial districts, as the epicenters of urban commerce and economic activity, largely reflect an area’s prosperity through their customer flow. However, previous research, which often relied on statistical and survey data, has typically not captured the full scope of customer flow dynamics throughout urban commercial districts and has not adequately measured the specific impacts of business district locations and their surrounding communities on customer flow. To bridge these gaps, this study utilizes multidimensional big geo-data resources, including mobile phone signaling data, Points of Interest (POI) data, and transportation network data, to uncover the underlying factors that influence customer flow within urban commercial districts. The findings suggest that several factors—the size of the commercial district, the diversity of business formats, the convenience of parking, the working and residential population in surrounding communities, and the proximity to urban centers—significantly influence the customer flow. Consumers show a preference for larger-scale, centrally-located commercial districts that offer convenient parking options, while a homogenized and uncharacteristic business format may reduce a commercial district’s appeal. Furthermore, the study reveals that industrial parks and mixed-use complexes within the 15-minute living circle surrounding the commercial district have a stronger attraction to customer flow than residential neighborhoods do. The insights from this research not only guide the strategic placement of new commercial centers but also provide a robust framework for enhancing the layout of urban commercial spaces and for the revitalization and advancement of established commercial districts.
大地理数据揭示城市商业区客流动态的影响因素
商业区作为城市商业和经济活动的中心,其客流在很大程度上反映了一个地区的繁荣程度。然而,以往的研究往往依赖于统计和调查数据,通常无法全面捕捉整个城市商业区的客流动态,也无法充分衡量商业区位置及其周边社区对客流的具体影响。为了弥补这些不足,本研究利用多维大地理数据资源,包括手机信号数据、兴趣点(POI)数据和交通网络数据,揭示了影响城市商业区客流的潜在因素。研究结果表明,商业区的规模、业态的多样性、停车的便利性、周边社区的工作人口和居住人口以及与城市中心的距离等因素对客流产生了重要影响。消费者偏好规模较大、位置集中、停车方便的商业区,而同质化、缺乏特色的商业业态则会降低商业区的吸引力。此外,研究还显示,商业区周围 15 分钟生活圈内的工业园区和综合体比住宅区对客流的吸引力更大。这项研究的见解不仅为新商业中心的战略布局提供了指导,也为加强城市商业空间的布局、振兴和提升现有商业区提供了一个强有力的框架。
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来源期刊
International journal of applied earth observation and geoinformation : ITC journal
International journal of applied earth observation and geoinformation : ITC journal Global and Planetary Change, Management, Monitoring, Policy and Law, Earth-Surface Processes, Computers in Earth Sciences
CiteScore
12.00
自引率
0.00%
发文量
0
审稿时长
77 days
期刊介绍: The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.
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