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
- Container
- PloS one
- Publisher
- Not recorded
- Open access
- yes
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limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
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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 = {Tan Y and Song J and Zhao G and Bai Y and Li Y and Wei X},
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 - Tan Y AU - Song J AU - Zhao G AU - Bai Y AU - Li Y AU - Wei X PY - 2026 JO - PloS one DO - 10.1371/journal.pone.0358597 UR - https://doi.org/10.1371/journal.pone.0358597 ER -
APA
Y, T., J, S., G, Z., Y, B., Y, L., & X, W. (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
- pubmed · retrieved 2026-09-25T03:33:15.696Z