International Journal of Supply Chain Management
Vol 10, No 1 (2021): International Journal of Supply Chain Management (IJSCM)

Applying Data Mining Tools in Transportation : Data-Driven Supply Chain View

Islam, Sanjida Binte (Unknown)
Habib, Md. Mamun (Unknown)

Article Info

Publish Date
26 Feb 2021

Abstract

Despite the big data research and relevance of data analysis there has been limited empirical research and implication of data-driven supply chain networks. This paper explores the effect of data-driven supply chain capabilities on transportation (train based). In order to illustrate the shortest path calculation, London Underground Transportation open source data have been analysed through implementing different data mining tools and using programming language Python and R. The findings indicate that a data-driven supply chain has a significant time efficient effect on the logistics support. Coordination, using available data, and supply chain responsiveness are positively and significantly related to time and cost efficient performance. This system can be implemented in train based logistic support to consider the route selection.

Copyrights © 2021




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Journal Info
International Journal of Supply Chain Management
Website

Abbrev

IJSCM

Publisher

ExcelingTech

Subject

Decision Sciences, Operations Research & Management Engineering Environmental Science Industrial & Manufacturing Engineering Transportation

Description

International Journal of Supply Chain Management (IJSCM) is a peer-reviewed indexed journal, ISSN: 2050-7399 (Online), 2051-3771 (Print), that publishes original, high quality, supply chain management empirical research that will have a significant impact on SCM theory and practice. Manuscripts ...