Operationalizing Dynamic Pricing Models: Bayesian Demand Forecasting and Customer Choice Modeling for Low Cost Carriers

✍ Scribed by Steffen Christ (auth.)

• Publisher: Gabler Verlag
• Year: 2011
• Tongue: English
• Leaves: 362
• Edition: 1
• Category: Library

✦ Synopsis

Dynamic Pricing of services has become the norm for many young service industries – especially in today’s volatile markets. Steffen Christ shows how theoretic optimization models can be operationalized by employing self-learning strategies to construct relevant input variables, such as latent demand and customer price sensitivity. He proves that the development of the necessary forecasting models is indeed possible, i.e., through the usage of real-time data of online sales channels.

✦ Table of Contents

Front Matter....Pages I-XXVII
Front Matter....Pages 1-1
Introduction....Pages 3-13
Motivation and Structure....Pages 15-21
Dynamic Pricing....Pages 23-62
Front Matter....Pages 63-63
Self-Learning Linear Models....Pages 67-95
Demand in Low Cost Markets....Pages 97-130
The Demand Forecasting Model....Pages 131-157
Computational Results and Evaluation....Pages 159-187
Summary and Outlook....Pages 189-197
Front Matter....Pages 199-199
Discrete Customer Choice Analysis....Pages 203-231
Choice Situation in Low-Cost Markets....Pages 233-252
Multinomial Logit Model for Low-Cost Travel Choice....Pages 253-301
Computational Results and Evaluation....Pages 303-318
Summary and Outlook....Pages 319-326
Back Matter....Pages 327-351

✦ Subjects

Operations Research/Decision Theory