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<p>This work presents a comprehensive multivariate analysis for the strategic design and optimization of large-scale logistics networks. To overcome operational challenges arising from geographic dispersion and technological variability, the framework integrates cluster analysis, factor analysis, MANOVA, and regression modeling to identify optimal regional groupings, simplify complex data, and quantify the effects of key operational variables. The approach is demonstrated through a case study of a Mexican company operating 2500 delivery points nationwide. Analysis showed that consolidating operations into four regional distribution centers can reduce total coverage distance by 80%, significantly lower logistics costs, and improve order fulfillment rates. Scenario simulations and profit modeling further validated the anticipated economic benefits, strongly supporting investment in new centers. These results illustrate how data-driven network redesign can enhance operational efficiency and build lasting competitive advantage in geographically diverse markets.</p>

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Strategic Design and Optimization of Logistics Networks in Mexico: A Multivariate Analysis Approach

  • 期刊论文

  • 发表日期：

    2025年8月25日

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  • Mariángel García-Tarango,
  • José Alejandro Jano-Pérez,
  • Santiago-Omar Caballero-Morales

摘要

This work presents a comprehensive multivariate analysis for the strategic design and optimization of large-scale logistics networks. To overcome operational challenges arising from geographic dispersion and technological variability, the framework integrates cluster analysis, factor analysis, MANOVA, and regression modeling to identify optimal regional groupings, simplify complex data, and quantify the effects of key operational variables. The approach is demonstrated through a case study of a Mexican company operating 2500 delivery points nationwide. Analysis showed that consolidating operations into four regional distribution centers can reduce total coverage distance by 80%, significantly lower logistics costs, and improve order fulfillment rates. Scenario simulations and profit modeling further validated the anticipated economic benefits, strongly supporting investment in new centers. These results illustrate how data-driven network redesign can enhance operational efficiency and build lasting competitive advantage in geographically diverse markets.