Abstract
Workforce shortages during the COVID-19 pandemic and the recent threat of railroad strike in the United States have generated greater public awareness of how freight flow disruptions can harm society. Unlike highways, trains often do not have the ability to take alternative routes that directly connect major metropolitan areas; hence railroad networks are vulnerable to disruptions like accidents. This study developed a data mining workflow to rank commodity movements that are at the highest risk of disruption from railroad accidents and other types of regional disasters that can affect railroad operations. A key finding is that five U.S. metropolitan areas are at least five times more likely than others to experience a railroad accident. Those five areas account for more than 40% of the monetary value in alcoholic beverages, raw meats, gasoline, plastic-based products, and rubber-based products moved by rail. Hence, any disruption in those five areas can lead to widespread shortages of those commodities. The implication is that decision makers should focus risk mitigation and resiliency strategies in those five metropolitan areas and on the top commodity categories at risk.
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The data that support the findings of this study are openly available at the sources cited within the manuscript.
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The authors conducted this work with support from North Dakota State University and the Mountain-Plains Consortium, a University Transportation Center funded by the U.S. Department of Transportation.
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RB: conceptualization, methodology, software, data curation, formal analysis, writing—original draft preparation. DT: supervision, resources, funding acquisition, project administration, validation, writing—reviewing and editing.
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Bridgelall, R., Tolliver, D.D. Quantifying freight flow disruption risks from railroad accidents. Qual Quant 58, 1993–2007 (2024). https://doi.org/10.1007/s11135-023-01727-3
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DOI: https://doi.org/10.1007/s11135-023-01727-3