dc.contributor.author | Gorman, Michael | |
dc.contributor.author | Clarke, John-Paul | |
dc.contributor.author | Koster, René de | |
dc.contributor.author | Hewitt, Michael | |
dc.contributor.author | Roy, Debjit | |
dc.contributor.author | Zhang, Mei | |
dc.date.accessioned | 2023-02-14T04:51:26Z | |
dc.date.available | 2023-02-14T04:51:26Z | |
dc.date.issued | 2023-02-09 | |
dc.identifier.citation | Gorman, M. F., Clarke, J.-P., René De Koster, ·, Hewitt, M., Roy, D., & Zhang, · Mei. (2023). Emerging practices and research issues for big data analytics in freight transportation. Maritime Economics & Logistics 2023, 1–32. https://doi.org/10.1057/S41278-023-00255-Z | en_US |
dc.identifier.issn | 1479-294X | |
dc.identifier.uri | http://hdl.handle.net/11718/26072 | |
dc.description.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. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Springer | en_US |
dc.relation.ispartof | Maritime Economics & Logistics | en_US |
dc.subject | Big data analytics | en_US |
dc.subject | Data sources | en_US |
dc.subject | Air freight | en_US |
dc.subject | Oceanic shipping | en_US |
dc.subject | Rail | en_US |
dc.subject | Trucking | en_US |
dc.title | Emerging practices and research issues for big data analytics in freight transportation | en_US |
dc.type | Article | en_US |