Piovani, D;
Zachariadis, V;
Batty, M;
(2017)
Quantifying Retail Agglomeration using Diverse Spatial Data.
Scientific Reports
, 7
, Article 5451. 10.1038/s41598-017-05304-1.
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Abstract
Newly available data on the spatial distribution of retail activities in cities makes it possible to build models formalized at the level of the single retailer. Current models tackle consumer location choices at an aggregate level and the opportunity new data offers for modeling at the retail unit level lacks an appropriate theoretical framework. The model we present here helps to address these issues. Based on random utility theory, we have built it around the idea of quantifying the role of floor-space and agglomeration in retail location choice. We test this model on the inner area of Greater London. The results are consistent with a super linear scaling of a retailer's attractiveness with its floorspace, and with an agglomeration effect approximated as the total retail floorspace within a 300 m radius from each shop. Our model illustrates many of the issues involved in testing and validating urban simulation models involving spatial data and its aggregation to different spatial scales.
| Type: | Article |
|---|---|
| Title: | Quantifying Retail Agglomeration using Diverse Spatial Data |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1038/s41598-017-05304-1 |
| Publisher version: | http://dx.doi.org/10.1038/s41598-017-05304-1 |
| Language: | English |
| Additional information: | Open Access: This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
| Keywords: | Applied mathematics, Civil engineering, Nonlinear phenomena, Scientific data |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1567692 |
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