Emerging practices and research issues for big data analytics in freight transportation

Michael F. Gorman, John-Paul Clarke, René Koster, Michael Hewitt, Debjit Roy () and Mei Zhang
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Michael F. Gorman: University of Dayton School of Business
John-Paul Clarke: The University of Texas at Austin
René Koster: Erasmus University Rotterdam
Michael Hewitt: Quinlan School of Business at Loyola University Chicago
Debjit Roy: Indian Institute of Management Ahmedabad
Mei Zhang: Otis Elevator Company

Maritime Economics & Logistics, 2023, vol. 25, issue 1, No 2, 28-60

Abstract: Abstract Freight transportation has been experiencing a renaissance in data sources, storage, and dissemination of data to decision makers in the last decades, resulting in new approaches to business and new research streams in analytics to support them. We provide an overview of developments in both practice and research related to big data analytics (BDA) in each of the major areas of freight transportation: air, ocean, rail, and truck. In each case, we first describe new capabilities in practice, and avenues of research given these evolving capabilities. New data sources, volumes and timeliness directly affect the way the industry operates, and how future researchers in these fields will structure their work. We discuss the evolving research agenda due to BDA and formulate fundamental research questions for each mode of freight transport.

Keywords: Big data analytics; Data sources; Air freight; Oceanic shipping; Rail; Trucking (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1057/s41278-023-00255-z

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