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New Book Explores Uncertainty Modeling Approach in Supply Chain Analytics

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  • July 13, 2023

    New Book Explores Uncertainty Modeling Approach in Supply Chain Analytics

    Professor Isik Bicer

    A new book written by a Schulich professor emphasizes the application of uncertainty modeling approach (a convolutional optimization technique) to supply chain management problems and focuses on evolutionary demand models to quantify the value of operational improvements and the cost of supply chain risks.

    Supply Chain Analytics: An Uncertainty Modeling Approach, written by Professor Isik Bicer, is an outcome of several company projects and academic collaborations. The book includes 9 chapters:

    • Chapter 1 introduces a unified supply chain framework and links it to operational and financial risks.
    • Chapter 2 reviews fundamental quantitative methods.
    • Chapter 3 covers inventory management models.
    • Chapter 4 focuses on uncertainty models within the context of supply chain management. Some parts of this chapter are based on the author’s collaboration with GSK Vaccines.
    • Chapter 5 presents the techniques to improve supply chain responsiveness. Some parts of this chapter are based on the author’s article that was later adapted into a cost assessment tool by the US Department of Commerce.
    • Chapter 6 covers methods to manage product variety. This chapter is based on the author’s collaboration with Kordsa.
    • Chapter 7 focuses on the modeling of supply risks: (1) supply disruption and (2) delivery shortfall risks. The disruption model is motivated by the problems faced by a big pharmaceutical company, and the delivery shortfall model is based on the author’s collaboration with one of the largest European crop processors.
    • Chapter 8 presents four important supply chain finance methods: (1) Early payment scheme, (2) reverse factoring, (3) letter of credits, and (4) dynamic discounting. It emphasizes the use of both reverse factoring and the market mechanism of dynamic discounting (invented by C2FO) to maximize the returns from treasury operations.
    • Chapter 9 features the trajectory of AI and its future trends that would impact the supply chain management world.

    There are many Python applications for each chapter and a supplementary web application on Python Dash. One appendix also introduces the reader to the introductory concepts of Python programming. Additional information about the book and some explanatory videos can be found on the book webpages: (1-Yorku) https://www.yorku.ca/research/areas/supplychainanalytics/ and (2-Springer) https://link.springer.com/book/10.1007/978-3-031-30347-0/.

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