Editors:
Offers best-in-class industry cases with detailed descriptions of leading companies' segmentation journeys
Provides in-depth discussion of the current practical and theoretical background of supply chain segmentation
Includes practical lessons learned and success factors for planning and implementating a supply chain segmentation
Includes supplementary material: sn.pub/extras
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Table of contents (8 chapters)
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Front Matter
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Back Matter
About this book
This book addresses the challenges companies face when different customer value propositions require them to pursue a differentiated supply chain strategy. It provides practical insights on how to achieve successful supply chain segmentation and presents the benefits this can yield for companies on the basis of best-in-class industry case studies from Gardena, Philips Luminaire, Siemens Healthcare and Volvo Construction Equipment. Drawing on these examples, it provides recommendations and solutions on how to define supply chain segmentation, and how to set up and implement a transformation program. Furthermore, it presents an in-depth discussion of the current theoretical background of supply chain segmentation and introduces the current trends and available frameworks.
Offering readers specific, pragmatic guidance on the main challenges and opportunities and proposing ways to effectively measure efficiency and performance, the book concludes with the do’s, don’ts and most important aspects to keep in mind when considering an end-to-end segmentation.Editors and Affiliations
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Department SCM & MS, University of Cologne, Cologne, Germany
Margarita Protopappa-Sieke, Ulrich W. Thonemann
About the editors
Margarita Protopappa-Sieke is Associate Professor for Supply Chain Management at the University of Cologne, Germany. She started her academic career as an Assistant Professor at European Business School, Wiesbaden, Germany and as an Assistant Professor at the University of Cologne. She holds a Doctoral Degree from École Polytechnique Fédéral de Lausanne, Switzerland, a Master in Industrial Systems Engineering from Georgia Tech, Atlanta, USA, and a diploma in Production Engineering and Management from Technical University of Crete, Chania, Greece. Her research focusses on Supply Chain Management and Financial Supply Chain Management.
e="font-size: 11pt; line-height: 115%; font-family: Calibri, sans-serif; background-image: initial; background-position: initial; background-size: initial; background-repeat: initial; background-attachment: initial; background-origin: initial; background-clip: initial;">Ulrich Thonemann is Professor for Supply Chain Management at the University of Cologne, Germany, and Director of the Department of Supply Chain Management. He started his academic career as a Professor for Supply Chain Management at Stanford University and also holds Master and PhD degrees from Stanford. Before joining academia, he worked as a management consultant at McKinsey & Company in Cologne. His publications appeared in journals such as Management Science, Operations Research, Harvard Business Manager, and the European Journal of Operations Research. His current research focusses on Supply Chain Management, Service Management, and Behavioral Operations and the application of state-of-the-art approaches in industry.Bibliographic Information
Book Title: Supply Chain Segmentation
Book Subtitle: Best-in-Class Cases, Practical Insights and Foundations
Editors: Margarita Protopappa-Sieke, Ulrich W. Thonemann
DOI: https://doi.org/10.1007/978-3-319-54133-4
Publisher: Springer Cham
eBook Packages: Business and Management, Business and Management (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-54132-7Published: 16 March 2017
Softcover ISBN: 978-3-319-85327-7Published: 09 May 2018
eBook ISBN: 978-3-319-54133-4Published: 09 March 2017
Edition Number: 1
Number of Pages: VII, 74
Number of Illustrations: 20 illustrations in colour
Topics: Supply Chain Management, Engineering Economics, Organization, Logistics, Marketing, Production, Operations Research/Decision Theory