Using unstable data from mobile phone applications to examine recent trajectories of retail centre recovery.

Urban informatics Pub Date : 2022-01-01 Epub Date: 2022-12-20 DOI:10.1007/s44212-022-00022-0
Patrick Ballantyne, Alex Singleton, Les Dolega
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Abstract

The COVID-19 pandemic has changed the ways in which we shop, with significant impacts on retail and consumption spaces. Yet, empirical evidence of these impacts, specifically at the national level, or focusing on latter periods of the pandemic remain notably absent. Using a large spatio-temporal mobility dataset, which exhibits significant temporal instability, we explore the recovery of retail centres from summer 2021 to 2022, considering in particular how these responses are determined by the functional and structural characteristics of retail centres and their regional geography. Our findings provide important empirical evidence of the multidimensionality of retail centre recovery, highlighting in particular the importance of composition, e-resilience and catchment deprivation in determining such trajectories, and identifying key retail centre functions and regions that appear to be recovering faster than others. In addition, we present a use case for mobility data that exhibits temporal stability, highlighting the benefits of viewing mobility data as a series of snapshots rather than a complete time series. It is our view that such data, when controlling for temporal stability, can provide a useful way to monitor the economic performance of retail centres over time, providing evidence that can inform policy decisions, and support interventions to both acute and longer-term issues in the retail sector.

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利用来自手机应用的不稳定数据,研究零售中心近期的复苏轨迹。
COVID-19 大流行改变了我们的购物方式,对零售和消费空间产生了重大影响。然而,有关这些影响的经验证据,特别是在国家层面上,或者关注大流行后期的证据,仍然明显缺乏。我们利用具有显著时间不稳定性的大型时空流动性数据集,探讨了零售中心从 2021 年夏季到 2022 年的恢复情况,特别考虑了零售中心的功能和结构特征及其区域地理如何决定了这些反应。我们的研究结果为零售中心复苏的多维性提供了重要的实证证据,特别强调了构成、电子复原力和集水区贫困在决定这种轨迹方面的重要性,并确定了似乎比其他地区复苏更快的主要零售中心功能和地区。此外,我们还介绍了具有时间稳定性的流动性数据的使用案例,强调了将流动性数据视为一系列快照而非完整时间序列的好处。我们认为,在控制时间稳定性的情况下,此类数据可以为监测零售中心的长期经济表现提供有用的方法,为政策决策提供依据,并支持对零售业的急性和长期问题进行干预。
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