E
Elkafi Hassini
Researcher at McMaster University
Publications - 73
Citations - 4108
Elkafi Hassini is an academic researcher from McMaster University. The author has contributed to research in topics: Supply chain & Computer science. The author has an hindex of 18, co-authored 59 publications receiving 3228 citations. Previous affiliations of Elkafi Hassini include University of Waterloo.
Papers
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Journal ArticleDOI
Recovery strategies from major supply disruptions in single and multiple sourcing networks
Nader Azad,Elkafi Hassini +1 more
TL;DR: Using a US case study, it is found that a dynamic pricing recovery strategy can improve profits during recovery from major supply disruptions and is more efficient in single-sourcing networks than multi-sourced networks.
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The impact of digital transformation on supply chains through e-commerce: Literature review and a conceptual framework
TL;DR: In this paper , the impact of e-commerce on supply chains has been widely recognized in the literature, but there was no effort to systematically review the literature and conceptualize some of the challenges and propose future research directions.
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Supply Chain Optimization: Current Practices and Overview of Emerging Research Opportunities
TL;DR: This editorial introduces a special issue “Optimization and Simulation Models in Supply Chain Management” and gives a brief overview of the current practice in supply chain optimization and the prospects for future research in this field.
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One-Dimensional Carousel Storage Problems: Applications, Review and Generalizations
TL;DR: A general model is presented that includes the one-dimensional carousel storage location problem as well as other well-known combinatorial optimization problems as special cases.
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Storage space allocation to maximize inter-replenishment times
TL;DR: The results show that the proportion of spaces assigned to a product is not necessarily equal to its demand frequency, and that employing the latter policy would result in inter-replenishment times that are about 24% shorter than the optimal solution.