Revenue Management and Pricing Analytics

• Κύριοι συγγραφείς: Gallego, Guillermo (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Topaloglu, Huseyin (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: New York, NY : Springer New York : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: International Series in Operations Research & Management Science, 279
• Θέματα: Operations research.; Decision making.; Industrial engineering.; Production engineering.; Production management.; Business logistics.; Macroeconomics.; Operations Research/Decision Theory.; Industrial and Production Engineering.; Production.; Logistics.; Macroeconomics/Monetary Economics//Financial Economics.

 "There is no strategic investment that has a higher return than investing in good pricing, and the text by Gallego and Topaloghu provides the best technical treatment of pricing strategy and tactics available." Preston McAfee, the J. Stanley Johnson Professor, California Institute of Technology and Chief Economist and Corp VP, Microsoft. "The book by Gallego and Topaloglu provides a fresh, up to date and in depth treatment of revenue management and pricing. It fills an important gap as it covers not only traditional revenue management topics also new and important topics such as revenue management under customer choice as well as pricing under competition and online learning. The book can be used for different audiences that range from advanced undergraduate students to masters and PhD students. It provides an in depth treatment covering recent state of the art topics in an interesting and innovative way. I highly recommend it". Professor Georgia Perakis, the William F. Pounds Professor of Operations Research and Operations Management at the Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts. "This book is an important and timely addition to the pricing analytics literature by two authors who have made major contributions to the field. It covers traditional revenue management as well as assortment optimization and dynamic pricing. The comprehensive treatment of choice models in each application is particularly welcome. It is mathematically rigorous but accessible to students at the advanced undergraduate or graduate levels with a rich set of exercises at the end of each chapter. This book is highly recommended for Masters or PhD level courses on the topic and is a necessity for researchers with an interest in the field." Robert L. Phillips, Amazon "This book, written by two of the leading researchers in the area, brings together in one place most of the recent research on revenue management and pricing analytics. New industries (ride sharing, cloud computing, restaurants) and new developments in the airline and hotel industries make this book very timely and relevant, and will serve as a critical reference for researchers." Professor Kalyan Talluri, the Munjal Chair in Global Business and Operations, Imperial College, London, UK. "At last, a serious and comprehensive treatment of modern revenue management and assortment optimization integrated with choice modeling. In this book, Gallego and Topaloglu provide the underlying model derivations together with a wide range of applications and examples; all of these facets will better equip students for handling real-world problems. For mathematically inclined researchers and practitioners, it will doubtless prove to be thought-provoking and an invaluable reference." - Richard Ratliff . 

 Chapter 1. Single Resource Revenue Management with Independent Demands -- Chapter 2. Network Revenue Management with Independent Demands -- Chapter 3. Overbooking -- Chapter 4. Introduction to Choice Modeling -- Chapter 5. Assortment Optimization -- Chapter 6. Single Resource Revenue Management with Dependent Demands -- Chapter 7. Network Revenue Management with Dependent Demands -- Chapter 8. Basic Pricing Theory -- Chapter 9. Dynamic Pricing over Finite Horizons -- Chapter 10. Online Learning -- Chapter 11. Competitive Assortment and Price Optimization.