Supply Chain Analytics: Concepts, Techniques and Applications

ISBN-13: 9783030922238 / Angielski / Miękka / 2022 / 400 str.

Kurt Y. Liu

Spis treści

Chapter 1: Introduction.- Chapter 2: Data-drive Supply Chains & Intro to Python.- Chapter 3: Data Manipulation.- Chapter 4: Data Visualization.- Chapter 5: Customer Management.- Chapter 6: Supply Management.- Chapter 7: Warehouse & Inventory Management.- Chapter 8: Demand Management.- Chapter 9: Logistics Management.

O autorze

Kurt Y. Liu is an Associate Professor of Supply Chain Analytics at the Adam Smith Business School, University of Glasgow. He teaches Executive, MBA, graduate and undergraduate students on supply chain, logistics and operations management. His main research interests include supply chain analytics, supply network configuration and sustainable SCM. Kurt was educated in New Zealand, Australia, the US and the UK. He has taught in China, Dubai, Singapore and the UK.

Blurb

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.