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  5. Big Data Analytics in Supply Chain Management

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Chapter in a book
English
2020

Big Data Analytics in Supply Chain Management

0 Datasets

0 Files

English
2020
CRC Press eBooks
DOI: 10.1201/9780367816384-1

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Amir Gandomi
Amir Gandomi

University of Techology Sdyney

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Iman Rahimi
Amir Gandomi
M. Ali Ülkü
+1 more

Abstract

The study of big data ("5V" concept consisting of Volume, Velocity, Variety, Veracity, and Value) is constantly expanding, and the new age of supply chain analytics has been provided by efforts that create more technology aimed at collecting data at different steps of the supply chain. By using big data, organization can achieve mastery over their supply chains. In this chapter, a short analysis on big data analytics in supply chain management is addressed. The chapter presents a scientometric analysis of "Big Data Analytics in Supply Chain Management" for the time period between 2000 and 2020. In this chapter, keywords analysis and citation analysis with VOSviewer software have been used, and the commonly used keywords have been identified. The analysis included keywords, organization, country, coauthor, and cocitation analyses that were investigated in this chapter. The conclusion and discussion along with recommendation for the future studies are addressed in the last section.

How to cite this publication

Iman Rahimi, Amir Gandomi, M. Ali Ülkü, Simon Fong (2020). Big Data Analytics in Supply Chain ManagementBig Data Analytics in Supply Chain Management. CRC Press eBooks, pp. 1-7, DOI: 10.1201/9780367816384-1,

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Publication Details

Type

Chapter in a book

Year

2020

Authors

4

Datasets

0

Total Files

0

Language

English

DOI

10.1201/9780367816384-1

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