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Enhancing the supply chain responsiveness through cloud manufacturing

conference contribution
posted on 21.09.2017, 10:49 by Mihalis Giannakis, Konstantina Spanaki, Masoud Fakhimi
With the substantial advances of Information Technology (IT) and digital communication platforms over the past decade, there is a growing awareness among stakeholders that their success is heavily dependent on early adoption of such technologies throughout their supply chain. The objective of this paper is to develop the computer architecture of a cloud based supply chain system and to explore the effect that its utilization has on supply chain responsiveness (SCR). SCR is conceptualized in terms of the level of visibility a company can in the supply chain, supply chain flexibility, and rapid detection and reaction to changes. The potential benefits that cloud can yield are discussed through a comprehensive literature review and compared to existing mature supply chain management (SCM) systems and solutions, in terms of several IT enabled supply chain capabilities. The detailed architecture of a cloud-based SCM (C-SCM) system is then developed, with the use of mature modules, to ensure its compatibility with existing technologies. The effect of the utilization of the cloud based SCM system on SCR is explored with case based scenarios, using data of a retail fashion company’s supply chain operations. Our findings suggest that the proposed system improves all the dimensions of SCR. Implications for supply chain practice and how companies can migrate to a cloud supply chain are drawn.

History

School

  • Business and Economics

Department

  • Business

Published in

EurOMA

Citation

GIANNAKIS, M., SPANAKI, K. and FAKHIMI, M., 2017. Enhancing the supply chain responsiveness through cloud manufacturing. Presented at the 24th EurOMA 2017 conference, Edinburgh, UK, 1st-5th July.

Publisher

EurOMA

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

30/04/2017

Publication date

2017

Notes

This paper is closed access.

Publisher version

Language

en

Location

Edinburgh