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Supply Chain Resilience in California: Targeted-Efficient Spillover Methodology

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Pubblicato in:International Journal of Combinatorial Optimization Problems and Informatics vol. 16, no. 3 (2025), p. 92-106
Autore principale: Moreno-Baca, Fabricio
Altri autori: Cano-Olivos, Patricia, Martínez-Flores, José Luis, Sánchez-Partida, Diana
Pubblicazione:
International Journal of Combinatorial Optimization Problems & Informatics
Soggetti:
Regional development
Stochastic models
Spatial data
Logistics
Resilience
Graph theory
Supply chains
Externality
Infrastructure
Cooperation
Communication
Optimization
Pandemics
Regions
Taxonomy
Algorithms
Medical supplies
Informatics
Suppliers
Efficiency
Public policy
COVID-19
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Abstract:The world has changed drastically in logistical and economic spheres as a result of the COVID-19 pandemic. This pandemic has caused a global crisis in supply-chain structures, creating regional, national and international impacts of unprecedented magnitude. Accordingly, this research develops a methodology to favour the logistics-resilience framework based on regional externalities and technical-efficiency analysis of the 51 US states, applying a Spatial Data Panel model and a Stochastic Frontier model in conjunction with graph theory (Ford–Fulkerson algorithm). The findings indicate that New York, West Virginia and North Dakota are vital external regions to support California’s logistics resilience. We demonstrate that a region with high technical efficiency does not necessarily constitute a key logistics spillover for a target region. This study represents one of the first attempts to optimise and redirect externalities from one region to another using spatial and logistical mechanisms.
ISSN:2007-1558
DOI:10.61467/2007.1558.2025.v16i2.327
Fonte:Advanced Technologies & Aerospace Database