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

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.

Dr. Steffen Christ wrote his dissertation at the Institute of Statistics and Mathematical Economics of Prof. Dr. Robert Klein at the University of Augsburg.