Operationalizing Dynamic Pricing Models [electronic resource] : Bayesian Demand Forecasting and Customer Choice Modeling for Low Cost Carriers /
Christ, Steffen.author.
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.
Description based upon print version of record.
Dissertation--University of Augsburg, 2009.
Includes bibliographical references.
pt. 1. Dynamic pricing in the airline industry -- pt. 2. Forecasting latent demand -- pt. 3. Estimating price sensitivity.
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.
Marketing.
Operations research.
Decision making.
Marketing.
Operations Research/Decision Theory.