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Open Access Journal Article

Big Data Analytics in Operations and Logistics

by James White 1,*
1
James White
*
Author to whom correspondence should be addressed.
ORS  2019 1(1):3; https://doi.org/10.69610/j.ors.20191030
Received: 31 July 2019 / Accepted: 30 September 2019 / Published Online: 30 October 2019
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Abstract

Big Data Analytics in Operations and Logistics is a crucial field that has gained significant attention in recent years. This paper explores the integration of big data analytics techniques within the operations and logistics sectors, aiming to enhance efficiency, reduce costs, and improve decision-making processes. The study delves into the various applications of big data analytics, including supply chain optimization, predictive maintenance, inventory management, and route planning. By utilizing advanced analytical tools and techniques, companies can gain valuable insights from vast amounts of data, leading to better resource allocation and customer satisfaction. The paper discusses the challenges and opportunities associated with big data analytics in the operations and logistics domain, emphasizing the importance of data quality, privacy concerns, and the need for skilled professionals. Furthermore, it highlights the potential future developments in this field and the impact they may have on the industry.

Keywords: Big Data Analytics; Operations Management; Logistics; Supply Chain Optimization; Predictive Maintenance.;
Copyright: © 2019 by White. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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APA Style
White, J. (2019). Big Data Analytics in Operations and Logistics. Operations Research and Statistics, 1(1), 3. doi:10.69610/j.ors.20191030
ACS Style
White, J. Big Data Analytics in Operations and Logistics. Operations Research and Statistics, 2019, 1, 3. doi:10.69610/j.ors.20191030
AMA Style
White J. Big Data Analytics in Operations and Logistics. Operations Research and Statistics; 2019, 1(1):3. doi:10.69610/j.ors.20191030
Chicago/Turabian Style
White, James 2019. "Big Data Analytics in Operations and Logistics" Operations Research and Statistics 1, no.1:3. doi:10.69610/j.ors.20191030

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ACS Style
White, J. Big Data Analytics in Operations and Logistics. Operations Research and Statistics, 2019, 1, 3. doi:10.69610/j.ors.20191030
AMA Style
White J. Big Data Analytics in Operations and Logistics. Operations Research and Statistics; 2019, 1(1):3. doi:10.69610/j.ors.20191030
Chicago/Turabian Style
White, James 2019. "Big Data Analytics in Operations and Logistics" Operations Research and Statistics 1, no.1:3. doi:10.69610/j.ors.20191030
APA style
White, J. (2019). Big Data Analytics in Operations and Logistics. Operations Research and Statistics, 1(1), 3. doi:10.69610/j.ors.20191030

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