Revenue Management and Pricing Analytics

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Details

  • Addresses the gap between the latest research and established texts in the field - Looks at research in Economics, Marketing, Operations, and Psychology - Strives for readability, with most difficult proofs in Appendix

    Autorentext
    Guillermo Gallego is the Department Head of Industrial Engineering and Decision Analytics, and also the Crown Worldwide Professor of Engineering. Prior to his appointment in January 2016, Prof Gallego was the Liu Family Professor at the Department of Industrial Engineering and Operations Research at Columbia University, where he served as the Department Chairman from 2002-2008. He was named an INFORMS Fellow in 2012, a Manufacturing and Service Operations Management Society (MSOM) Distinguished Fellow in 2013 and has been the recipient of many awards including the Revenue Management Historical Prize (2011), the Revenue Management Practice Prize (2012), the INFORMS Impact Prize (2016) and the Management Science Best Paper Award (2017). Prof Gallego's research interests are Dynamic Pricing and Revenue Optimization, Supply Chain Management, Electronic Commerce, and Inventory Theory. He has published influential papers in the leading journals of his field where he has alsooccupied a variety of editorial positions. His work has been supported by numerous industrial and government grants. In addition to theoretical research, Prof Gallego has developed strong collaboration with global corporations such as Disney World, Hewlett Packard, IBM, Lucent Technologies, Nomis Solutions, and Sabre Airline Solutions. He has also worked with government agencies such as the National Research Council, the National Science Foundation in United States and the Ireland Development Agency. His graduate students are associated with prestigious universities and occupy leading roles in their chosen fields. He spent his 1996-97 sabbatical at Stanford University and was a visiting scientist at the IBM Watson Research Center from 1999-2003. Prof Gallego received both his PhD degree (1988) and MS degree (1987) in Operations Research and Industrial Engineering from Cornell University, and his undergraduate degree in Mathematics (1980) from the University of California in San Diego.
    Huseyin Topaloglu is a professor of operations research in the School of Operations Research and Information Engineering at Cornell University. He joined Cornell in 2002. After working on Cornell's main campus in Ithaca for 13 years, he moved to Cornell's technology-focused campus in New York City in 2015. Professor Topaloglu's research interests are in stochastic optimization and approximation algorithms with applications in revenue management, dynamic pricing and transportation logistics. He serves on the editorial boards of Management Science, Mathematical Programming C, Naval Research Logistics, Operations Research, and Production and Operations Management. He teaches courses on optimization theory, revenue management, and logistics.

    Inhalt

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.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09781493996049
    • Auflage 1st edition 2019
    • Sprache Englisch
    • Genre Allgemeines & Lexika
    • Lesemotiv Verstehen
    • Größe H241mm x B160mm x T25mm
    • Jahr 2019
    • EAN 9781493996049
    • Format Fester Einband
    • ISBN 1493996045
    • Veröffentlichung 15.08.2019
    • Titel Revenue Management and Pricing Analytics
    • Autor Huseyin Topaloglu , Guillermo Gallego
    • Untertitel International Series in Operations Research & Management Science 279
    • Gewicht 699g
    • Herausgeber Springer New York
    • Anzahl Seiten 356

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