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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Christ, Steffen (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Wiesbaden : Gabler, 2011.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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520 |a 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. 
650 0 |a Business. 
650 0 |a Marketing. 
650 0 |a Operations research. 
650 0 |a Decision making. 
650 1 4 |a Business and Management. 
650 2 4 |a Marketing. 
650 2 4 |a Operation Research/Decision Theory. 
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