2690-6791ISSN (Online)
2769-786XISSN (Print)
Volume 7 , Issue 2 , PP: 30-39, 2022 | Cite this article as | XML | Html | PDF | Full Length Article
Ahmed M. AbdelMouty 1 *
Doi: https://doi.org/10.54216/JISIoT.070203
The discipline of Supply Chain Management (SCM) is getting more difficult to master. It is necessary to address information silos on the demand and production frontiers of goods in order to execute the de-coupling factor in the preferences of customers who are engaged in a supply chain to optimize business performance, which in today's world has become a difficulty. The so-called "Amazon Effect" has, once again, compelled competitors to rethink their approaches to achieving maximum efficiency. The Analytic Hierarchy Process (AHP), which is part of the Multi-Criteria Decision Making (MCDM) Approaches, has been used to offer the preferences of clients of various criteria versus various features (products). AHP is used to compute the weights of criteria, then rank the various alternatives. The AHP method is used to build the pairwise comparison between criteria to check the importance of these criteria. The AHP method checks the consistency of the experts to ensure all data is consistent.
Cloud Computing , IoT , AHP , Supply Chain Management , Big Data
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