Overview
- Provides a framework for the study of inventory models in which customers have heterogeneous price and delivery-time requirements and derive the optimal inventory management policy for firms to respond to incoming customer demand in real- time and determine the inventory replenishment quantities accordingly
- Draws upon real-world practices of automobile dealerships to shed light on how firms should employ delivery-time-based market segmentation strategy to improve their inventory utilization and achieve profit maximization
- Investigates extensions to the basic model such as different fulfilment-priority strategies and applications to problems of similar nature such as the group-buying mechanism
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Operations Management (BRIEFSOPERMAN)
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Table of contents (7 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book develops a modeling framework to analyze the problem of inventory management with alternative delivery times. The general context considered here is that a seller replenishes its inventory in fixed intervals and, between replenishments, allocates the limited inventory to satisfy customers who are both price and delivery-time sensitive. On the demand side, customers have heterogeneous delivery-time requirements and choose either spot or late delivery. This theoretical modeling captures the essence of real-world business practices such as the delivery time market segmentation strategy adopted by automobile dealerships in China and many other similar examples. The book focuses on the seller’s optimal inventory replenishment and demand fulfillment policies, and our results provide managerial insights into the merits of flexible delivery-time options. Similar applications such as the group-buying mechanism are also examined. The main mathematical tool used in theoretical analysis is dynamic programming. This book is written for students, researchers, and practitioners in the areas of operations management and industrial engineering who are interested in understanding the rationale of flexible delivery times and designing successful applications.
Authors and Affiliations
About the authors
Xiaoying Liang received his B.Eng. degree from Tsinghua University in 2003 and his Ph.D. degree in Systems Engineering and Engineering Management from the Chinese University of Hong Kong in 2010. He is currently a senior research assistant at the City University of Hong Kong. His research interests include revenue management, operations management/marketing interface, and network effects.
Lijun Ma is currently Associate Professor of Operations Management and the Associate Department Head of Department of Management Science in the College of Management at Shenzhen University. He received his B.S. and M.S. degrees from the University of Science and Technology of China and his Ph.D. degree in Systems Engineering and Engineering Management from the Chinese University of Hong Kong in 2007.
He has published over 70 journal articles, conference papers and book chapters on inventory management, supply chain management, and transportation management. His publications appear in journals such as European Journal of Operational Research, Annals of Operations Research, Operations Research Letters, Transportation Research Part E: Logistics and Transportation Review, International Journal of Production Economics, International Journal of Production Research and Journal of the Operational Research Society. He also consulted for manufacturing and logistics companies such as SF Express on issues spanning from business process re-engineering to supply chain management. He is a member of INFORMS, POMS and ORSC.
Haifeng Wang received his B.Eng. and Ph.D. degrees in Automation from Tsinghua University in 2003 and 2009, respectively. He is currently the founder and CEO of Fengyuan Innovation Technology Co., Ltd. He has previously worked at IBM and Hanergy and has extensive experience in the renewable energy industry. He has authored dozens of journal and conference papers and holds several patents.
Houmin Yan is Chair Professor of Management Sciences and Dean of the College of Business at the City University of Hong Kong. Prior to joining CityU, he served as Professor at the Chinese University of Hong Kong, and as Associate Director and Science Advisor for the Hong Kong R&D Center for Logistics and Supply Chain Management Enabling Technologies. He has also worked as a tenured Associate Professor at the School of Management, University of Texas at Dallas.
His main research areas are stochastic models, simulations, and supply chain management. He has published in journals such as Operations Research, Manufacturing and Service Operations Management, IIE Transactions, Production and Operations Management, Journal of Optimization: Theory and Applications, and IEEE Transactions. He consulted for a number of manufacturing and logistics companies, such as Motorola, Freescale, Kappa and Citic Global Logistics, on issues spanning from forecasting, supply chain management to business process re-engineering.
He received his B.S. and M.S. degrees from Tsinghua University and his Ph.D. degree from the University of Toronto. He is a member of INFORMS.
Bibliographic Information
Book Title: Inventory Management with Alternative Delivery Times
Authors: Xiaoying Liang, Lijun Ma, Haifeng Wang, Houmin Yan
Series Title: SpringerBriefs in Operations Management
DOI: https://doi.org/10.1007/978-3-319-48635-2
Publisher: Springer Cham
eBook Packages: Business and Management, Business and Management (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2017
Softcover ISBN: 978-3-319-48633-8Published: 05 December 2016
eBook ISBN: 978-3-319-48635-2Published: 24 November 2016
Series ISSN: 2365-8320
Series E-ISSN: 2365-8339
Edition Number: 1
Number of Pages: XI, 106
Number of Illustrations: 6 b/w illustrations, 6 illustrations in colour
Topics: Operations Management, Engineering Economics, Organization, Logistics, Marketing, Transportation