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

被引：1
|
作者：
Gorman, Michael F. [1 ]
Clarke, John-Paul [2 ]
de Koster, Rene [3 ]
Hewitt, Michael [4 ]
Roy, Debjit [5 ]
Zhang, Mei [6 ]
机构：
[1] Univ Dayton, Dept MIS Operat & Analyt, Sch Business, Dayton, OH USA
[2] Univ Texas Austin, Austin, TX USA
[3] Erasmus Univ, Rotterdam Sch Management, Rotterdam, Netherlands
[4] Loyola Univ Chicago, Quinlan Sch Business, Chicago, IL USA
[5] Indian Inst Management Ahmedabad, Ahmadabad, Gujarat, India
[6] Otis Elevator Co, Farmington, CT USA
来源：
MARITIME ECONOMICS & LOGISTICS | 2023年 / 25卷 / 01期
关键词：
Big data analytics; Data sources; Air freight; Oceanic shipping; Rail; Trucking; DYNAMIC-PROGRAMMING ALGORITHM; SERVICE PROCUREMENT; FLEET MANAGEMENT; SCHEDULE DESIGN; SPOT MARKET; MODEL; TIME; FRAMEWORK; AIRCRAFT;
D O I：
10.1057/s41278-023-00255-z
中图分类号：
U [交通运输];
学科分类号：
08 ; 0823 ;
摘要：
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.
引用
收藏
页码：28 / 60
页数：33
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