Spatial Pattern and Influencing Factor Analysis of Parcel Lockers in London
When carriers deliver goods to customers, last-mile delivery is one of the supply chain’s most costly and environmentally damaging components [1]. In recent years, a growing number of scholars have investigated parcel lockers as a solution to the problems of last-mile delivery [2]. The goal of this...
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EDP Sciences
2025-01-01
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| Series: | E3S Web of Conferences |
| Online Access: | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/17/e3sconf_eeupd2024_02004.pdf |
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| author | Kang Xinwei |
| author_facet | Kang Xinwei |
| author_sort | Kang Xinwei |
| collection | DOAJ |
| description | When carriers deliver goods to customers, last-mile delivery is one of the supply chain’s most costly and environmentally damaging components [1]. In recent years, a growing number of scholars have investigated parcel lockers as a solution to the problems of last-mile delivery [2]. The goal of this work is to satisfy urban consumers’ demand for online shopping while lowering CO2 emissions. However, few studies have focused on the parcel locker itself. Therefore, for the first time, this paper introduces clustering methods into the study of last-mile delivery on parcel lockers; moreover, it builds a methodology to analyse the spatial distribution of parcel lockers and identifies parcel locker clustering based on the DBSCAN algorithm. This study employs Ordinary Least Squares Regression and Geographically Weighted Regression models with data on the socioeconomic, built environment and public transportation to quantify the relationship between the degree of parcel locker clustering in London and these factors at the global and local levels. The study’s findings indicate that parcel lockers are spatially clustered in London, with a significant degree of clustering in central London. Fufrthermore, the degree of parcel locker clustering is affected by population density, restaurant density, supermarket density, underground station density and bus stop density. However, the influence of these factors on the degree of parcel locker clustering at different sites is varied. Based on this, we propose that the government and businesses collaborate to establish various renovation projects and strategies for various MSOAs to improve the spatial distribution of parcel lockers, helping London achieve its goal of becoming a zero-carbon city by 2050. |
| format | Article |
| id | doaj-art-86e4f471e8cb4d1a8b0fb401fd9d86ca |
| institution | DOAJ |
| issn | 2267-1242 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | E3S Web of Conferences |
| spelling | doaj-art-86e4f471e8cb4d1a8b0fb401fd9d86ca2025-08-20T03:16:19ZengEDP SciencesE3S Web of Conferences2267-12422025-01-016170200410.1051/e3sconf/202561702004e3sconf_eeupd2024_02004Spatial Pattern and Influencing Factor Analysis of Parcel Lockers in LondonKang Xinwei0Centre for Advanced Spatial Analysis, UCLWhen carriers deliver goods to customers, last-mile delivery is one of the supply chain’s most costly and environmentally damaging components [1]. In recent years, a growing number of scholars have investigated parcel lockers as a solution to the problems of last-mile delivery [2]. The goal of this work is to satisfy urban consumers’ demand for online shopping while lowering CO2 emissions. However, few studies have focused on the parcel locker itself. Therefore, for the first time, this paper introduces clustering methods into the study of last-mile delivery on parcel lockers; moreover, it builds a methodology to analyse the spatial distribution of parcel lockers and identifies parcel locker clustering based on the DBSCAN algorithm. This study employs Ordinary Least Squares Regression and Geographically Weighted Regression models with data on the socioeconomic, built environment and public transportation to quantify the relationship between the degree of parcel locker clustering in London and these factors at the global and local levels. The study’s findings indicate that parcel lockers are spatially clustered in London, with a significant degree of clustering in central London. Fufrthermore, the degree of parcel locker clustering is affected by population density, restaurant density, supermarket density, underground station density and bus stop density. However, the influence of these factors on the degree of parcel locker clustering at different sites is varied. Based on this, we propose that the government and businesses collaborate to establish various renovation projects and strategies for various MSOAs to improve the spatial distribution of parcel lockers, helping London achieve its goal of becoming a zero-carbon city by 2050.https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/17/e3sconf_eeupd2024_02004.pdf |
| spellingShingle | Kang Xinwei Spatial Pattern and Influencing Factor Analysis of Parcel Lockers in London E3S Web of Conferences |
| title | Spatial Pattern and Influencing Factor Analysis of Parcel Lockers in London |
| title_full | Spatial Pattern and Influencing Factor Analysis of Parcel Lockers in London |
| title_fullStr | Spatial Pattern and Influencing Factor Analysis of Parcel Lockers in London |
| title_full_unstemmed | Spatial Pattern and Influencing Factor Analysis of Parcel Lockers in London |
| title_short | Spatial Pattern and Influencing Factor Analysis of Parcel Lockers in London |
| title_sort | spatial pattern and influencing factor analysis of parcel lockers in london |
| url | https://www.e3s-conferences.org/articles/e3sconf/pdf/2025/17/e3sconf_eeupd2024_02004.pdf |
| work_keys_str_mv | AT kangxinwei spatialpatternandinfluencingfactoranalysisofparcellockersinlondon |