Big Data in Logistics

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Published: 2025-12-27
DOI: https://doi.org/10.51699/g4yvks28
Keywords:
big data, big data analytics, big data applications, logistics, supply chain, transportation

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Matthew N. O. Sadiku
Roy G. Perry College of Engineering, Prairie View A&M University, Prairie View, TX, USA
Uwakwe C. Chukwu
Department of Engineering Technology, South Carolina State University, Orangeburg, SC, USA
Janet O. Sadiku
Juliana King University, Houston , TX, USA

Abstract

The logistics sector involves complex operations that require a high level of precision and efficiency. In recent years, the use of big data has revolutionized the logistics industry, providing companies with valuable insights and analytics that can help improve their operations. Logistics companies generate massive amounts of data daily, including shipment tracking, inventory levels, delivery schedules, and customer feedback. In logistics, big data analytics involves leveraging extensive and complex data sets to derive insights, make informed decisions, and enhance transportation processes. The goal is to extract valuable information and patterns from this data to improve operational efficiency, reduce costs, enhance customer service, and enable strategic decisions. The impact of big data on logistics is hard to overestimate. This paper will discuss the role of big data analytics in the logistics sector.

Article Details

Issue

Vol. 3 No. 12 (2025): Innovative: International Multi-disciplinary Journal of Applied Technology

Section

Articles

How to Cite

Big Data in Logistics. (2025). Innovative: International Multidisciplinary Journal of Applied Technology (2995-486X), 3(12), 96-110. https://doi.org/10.51699/g4yvks28

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