Pricing and Revenue Optimization: Second Edition, Edition 2

· Stanford University Press
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This book offers the first introduction to the concepts, theories, and applications of pricing and revenue optimization. From the initial success of "yield management" in the commercial airline industry down to more recent successes of markdown management and dynamic pricing, the application of mathematical analysis to optimize pricing has become increasingly important across many different industries. But, since pricing and revenue optimization has involved the use of sophisticated mathematical techniques, the topic has remained largely inaccessible to students and the typical manager. With methods proven in the MBA courses taught by the author at Columbia and Stanford Business Schools, this book presents the basic concepts of pricing and revenue optimization in a form accessible to MBA students, MS students, and advanced undergraduates. In addition, managers will find the practical approach to the issue of pricing and revenue optimization invaluable.

With updates to every chapter, this second edition covers topics such as estimation of price-response functions and machine-learning-based price optimization. New discussions of applications of dynamic pricing and revenue management by companies such as Amazon, Uber, and Disney, and in industries such as sports, theater, and electric power, are also included. In addition, the book provides current coverage of important applications such as revenue management, markdown management, customized pricing, and the behavioral economics of pricing.

Müəllif haqqında

Robert L. Phillips is Director of Pricing Science at Amazon. He was previously Director of Marketplace Optimization Data Science at Uber Technologies, Professor of Professional Practice at Columbia Business School, Founder and Chief Science Officer at Nomis Solutions, and CEO of Talus Solutions. He is the author of Pricing Credit Products (Stanford, 2018) and the co-editor of The Oxford Handbook of Pricing Management (2014).

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