Supply chain analytics: concepts, techniques and applications

By:

Liu, Kurt Y

Material type: Text

TextPublication details: Palgrave Macmillan Switzerland 2022Description: xix, 377 pISBN:

9783030922238

Subject(s):

DDC classification:

658.70285 LIU

Summary: This innovative new core textbook, written by an experienced professor and practitioner in supply chain management, offers a business-focused overview of the applications of data analytics and machine learning to supply chain management. Accessible yet rigorous, this text introduces students to the relevant concepts and techniques needed for data analysis and decision making in modern supply chains and enables them to develop proficiency in a popular and powerful programming software. Suitable for use on upper-level undergraduate, postgraduate and MBA courses in supply chain management, it covers all of the major supply chain processes, including managing supply and demand, warehousing and inventory control, transportation and route optimization. Each chapter comes with practical real-world examples drawn from a range of business contexts, including Amazon and Starbucks, case study discussion questions, computer-assisted exercises and programming projects. (https://link.springer.com/book/10.1007/978-3-030-92224-5#about-this-book)

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Operations Management & Quantitative Techniques	658.70285 LIU (Browse shelf(Opens below))	1	Checked out	04/16/2024	005277

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Previous	658.7 WIS Principles of supply chain management: a balanced approach	658.701 SNY Fundamentals of supply chain theory	658.70282 VAN Data science for supply chain forecasting	658.70285 LIU Supply chain analytics: concepts, techniques and applications	658.70285 ROS The digitalization of the 21st century supply chain	658.70285 TIP Supply chain analytics and modelling:	658.70285 VYA Blockchain and the supply chain: concepts, strategies and practical applications	Next

This innovative new core textbook, written by an experienced professor and practitioner in supply chain management, offers a business-focused overview of the applications of data analytics and machine learning to supply chain management. Accessible yet rigorous, this text introduces students to the relevant concepts and techniques needed for data analysis and decision making in modern supply chains and enables them to develop proficiency in a popular and powerful programming software. Suitable for use on upper-level undergraduate, postgraduate and MBA courses in supply chain management, it covers all of the major supply chain processes, including managing supply and demand, warehousing and inventory control, transportation and route optimization. Each chapter comes with practical real-world examples drawn from a range of business contexts, including Amazon and Starbucks, case study discussion questions, computer-assisted exercises and programming projects.

(https://link.springer.com/book/10.1007/978-3-030-92224-5#about-this-book)

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