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Step by step, this book provides a detailed examination of analytical methods that optimize operational decisions under different types of uncertainty. It discusses stochastic inventory models, introduces uncertainty modeling methods, and explains methods for managing uncertainty. To help readers deepen their understanding, it includes access to various supplementary material including an online interactive tool in Python.
This book is intended for undergraduate and graduate students of supply chain management with a focus on supply chain analytics. It also prepares practitioners to make better decisions in this field.
Step by step, this book provides a detailed examination of analytical methods that optimize operational decisions under different types of uncertainty. It discusses stochastic inventory models, introduces uncertainty modeling methods, and explains methods for managing uncertainty. To help readers deepen their understanding, it includes access to various supplementary material including an online interactive tool in Python.
This book is intended for undergraduate and graduate students of supply chain management with a focus on supply chain analytics. It also prepares practitioners to make better decisions in this field.
Isik Bicer is an Assistant Professor of Operations Management and Information Systems at the Schulich School of Business, York University, Canada. His research focuses on supply chain analytics and supply chain finance. He uses methods from quantitative finance, optimization theory, statistics, and stochastic modeling to develop supply chain models that aim to reduce the mismatches between supply and demand. His research appeared in the top operations management journals, such as Production and Operations Management and Journal of Operations Management, and some practitioner outlets such as Harvard Business Review, California Management Review, and Forbes. The analytical tools developed as the outcome of his research have been implemented in companies in the pharmaceutical, automotive, and agriculture industries.
Introduces a unique risk analysis framework and analytical models to manage supply chain risks
Includes access to various supplementary material including an online interactive tool in Python
Presents the use of analytics from an uncertainty modeling approach
| Erscheinungsjahr: | 2023 |
|---|---|
| Fachbereich: | Management |
| Genre: | Wirtschaft |
| Rubrik: | Recht & Wirtschaft |
| Medium: | Buch |
| Reihe: | Springer Texts in Business and Economics |
| Inhalt: |
xiv
314 S. 16 s/w Illustr. 85 farbige Illustr. 314 p. 101 illus. 85 illus. in color. |
| ISBN-13: | 9783031303463 |
| ISBN-10: | 3031303466 |
| Sprache: | Englisch |
| Ausstattung / Beilage: | HC runder Rücken kaschiert |
| Einband: | Gebunden |
| Autor: | Biçer, I¿¿k |
| Hersteller: |
Springer Nature Switzerland
Springer International Publishing AG Springer Texts in Business and Economics |
| Maße: | 241 x 160 x 24 mm |
| Von/Mit: | I¿¿k Biçer |
| Erscheinungsdatum: | 28.06.2023 |
| Gewicht: | 0,658 kg |
Isik Bicer is an Assistant Professor of Operations Management and Information Systems at the Schulich School of Business, York University, Canada. His research focuses on supply chain analytics and supply chain finance. He uses methods from quantitative finance, optimization theory, statistics, and stochastic modeling to develop supply chain models that aim to reduce the mismatches between supply and demand. His research appeared in the top operations management journals, such as Production and Operations Management and Journal of Operations Management, and some practitioner outlets such as Harvard Business Review, California Management Review, and Forbes. The analytical tools developed as the outcome of his research have been implemented in companies in the pharmaceutical, automotive, and agriculture industries.
Introduces a unique risk analysis framework and analytical models to manage supply chain risks
Includes access to various supplementary material including an online interactive tool in Python
Presents the use of analytics from an uncertainty modeling approach
| Erscheinungsjahr: | 2023 |
|---|---|
| Fachbereich: | Management |
| Genre: | Wirtschaft |
| Rubrik: | Recht & Wirtschaft |
| Medium: | Buch |
| Reihe: | Springer Texts in Business and Economics |
| Inhalt: |
xiv
314 S. 16 s/w Illustr. 85 farbige Illustr. 314 p. 101 illus. 85 illus. in color. |
| ISBN-13: | 9783031303463 |
| ISBN-10: | 3031303466 |
| Sprache: | Englisch |
| Ausstattung / Beilage: | HC runder Rücken kaschiert |
| Einband: | Gebunden |
| Autor: | Biçer, I¿¿k |
| Hersteller: |
Springer Nature Switzerland
Springer International Publishing AG Springer Texts in Business and Economics |
| Maße: | 241 x 160 x 24 mm |
| Von/Mit: | I¿¿k Biçer |
| Erscheinungsdatum: | 28.06.2023 |
| Gewicht: | 0,658 kg |
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