Content area

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.

Details

Title
Supply Chain Resilience in California: Targeted-Efficient Spillover Methodology
Volume
16
Issue
3
Source details
Guest Editors
Pages
92-105
Number of pages
15
Publication year
2025
Publication date
2025
Section
Articles
Publisher
International Journal of Combinatorial Optimization Problems & Informatics
Place of publication
Jiutepec
Country of publication
Mexico
Publication subject
e-ISSN
20071558
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-07-14
Milestone dates
2025-07-14 (Issued); 2022-12-03 (Submitted); 2025-07-14 (Created); 2025-07-14 (Modified)
Publication history
 
 
   First posting date
14 Jul 2025
ProQuest document ID
3233470578
Document URL
https://www.proquest.com/scholarly-journals/supply-chain-resilience-california-targeted/docview/3233470578/se-2?accountid=208611
Copyright
Copyright International Journal of Combinatorial Optimization Problems & Informatics 2025
Last updated
2025-08-26
Database
ProQuest One Academic