Uncovering traditional retail location competition with machine learning: The role of urban environments in light-asset and capital-intensive formats
- DOI
- 10.1371/journal.pone.0358597
- Published
- 2026-09-21
- Container
- PLOS One
- Publisher
- Public Library of Science (PLoS)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1371/journal.pone.0358597,
title = {Uncovering traditional retail location competition with machine learning: The role of urban environments in light-asset and capital-intensive formats},
author = {Yueyi Tan and Jusheng Song and Guangying Zhao and Yunxi Bai and Yan Li and Xuren Wei},
year = {2026},
journal = {PLOS One},
doi = {10.1371/journal.pone.0358597},
url = {https://doi.org/10.1371/journal.pone.0358597}
}RIS
TY - JOUR TI - Uncovering traditional retail location competition with machine learning: The role of urban environments in light-asset and capital-intensive formats AU - Yueyi Tan AU - Jusheng Song AU - Guangying Zhao AU - Yunxi Bai AU - Yan Li AU - Xuren Wei PY - 2026 JO - PLOS One DO - 10.1371/journal.pone.0358597 UR - https://doi.org/10.1371/journal.pone.0358597 ER -
APA
Tan, Y., Song, J., Zhao, G., Bai, Y., Li, Y., & Wei, X. (2026). Uncovering traditional retail location competition with machine learning: The role of urban environments in light-asset and capital-intensive formats. PLOS One. https://doi.org/10.1371/journal.pone.0358597
Source records
- crossref · retrieved 2026-11-03T12:45:02.684Z