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基于网络的零售商店商业类别及最佳位置预测。

Network-based predictions of retail store commercial categories and optimal locations.

作者信息

Jensen Pablo

机构信息

Laboratoire de Physique, CNRS UMR 5672, Ecole Normale Supérieure de Lyon, 46 Allée d'Italie, 69364 Lyon Cedex 07, France.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2006 Sep;74(3 Pt 2):035101. doi: 10.1103/PhysRevE.74.035101. Epub 2006 Sep 8.

DOI:10.1103/PhysRevE.74.035101
PMID:17025686
Abstract

I study the spatial organization of retail commercial activities. These are organized in a network comprising "antilinks," i.e., links of negative weight. From pure location data, network analysis leads to a community structure that closely follows the commercial classification of the U.S. Department of Labor. The interaction network allows one to build a "quality" index of optimal location niches for stores, which has been empirically tested.

摘要

我研究零售商业活动的空间组织。这些活动是在一个包含“反链接”(即负权重链接)的网络中组织起来的。从纯粹的位置数据来看,网络分析得出的社区结构与美国劳工部的商业分类密切相关。互动网络使人们能够构建一个针对商店的最佳选址利基的“质量”指数,该指数已得到实证检验。

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