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Using unstable data from mobile phone applications to examine recent trajectories of retail centre recovery
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 mob...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Nature Singapore
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9763087/ https://www.ncbi.nlm.nih.gov/pubmed/36569988 http://dx.doi.org/10.1007/s44212-022-00022-0 |
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author | Ballantyne, Patrick Singleton, Alex Dolega, Les |
author_facet | Ballantyne, Patrick Singleton, Alex Dolega, Les |
author_sort | Ballantyne, Patrick |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9763087 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Nature Singapore |
record_format | MEDLINE/PubMed |
spelling | pubmed-97630872022-12-20 Using unstable data from mobile phone applications to examine recent trajectories of retail centre recovery Ballantyne, Patrick Singleton, Alex Dolega, Les Urban Inform Original Article 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. Springer Nature Singapore 2022-12-20 2022 /pmc/articles/PMC9763087/ /pubmed/36569988 http://dx.doi.org/10.1007/s44212-022-00022-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Ballantyne, Patrick Singleton, Alex Dolega, Les Using unstable data from mobile phone applications to examine recent trajectories of retail centre recovery |
title | Using unstable data from mobile phone applications to examine recent trajectories of retail centre recovery |
title_full | Using unstable data from mobile phone applications to examine recent trajectories of retail centre recovery |
title_fullStr | Using unstable data from mobile phone applications to examine recent trajectories of retail centre recovery |
title_full_unstemmed | Using unstable data from mobile phone applications to examine recent trajectories of retail centre recovery |
title_short | Using unstable data from mobile phone applications to examine recent trajectories of retail centre recovery |
title_sort | using unstable data from mobile phone applications to examine recent trajectories of retail centre recovery |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9763087/ https://www.ncbi.nlm.nih.gov/pubmed/36569988 http://dx.doi.org/10.1007/s44212-022-00022-0 |
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