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Operationalizing Dynamic Pricing Models
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Dynamic Pricing of services has become the norm for many young service industries especially in todays 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.
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