A revenue management problem with a choice model of consumer behaviour in a random environment

Modeling consumer behavior is a relevant and growing research area in revenue management. Single-resource (single-leg) capacity control problems comprising consumer choice modeling constitute the backbone of more complicated models. In existing models, the distribution of demand is assumed to be ind...

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Bibliographic Details
Published in:OR Spectrum 2015-03, Vol.37 (2), p.457-473
Main Authors: Özkan, Can, Karaesmen, Fikri, Özekici, Süleyman
Format: Article
Language:English
Subjects:
Business and Management
Calculus of Variations and Optimal Control
Optimization
Consumer behavior
Demand (economics)
Dynamic programming
Economics
Fluctuation
Logistics
Management
Marketing
Markov analysis
Mathematical models
Operations research
Operations Research/Decision Theory
Optimization
Pricing policies
Probability
Regular Article
Revenue management
Revenues
Role models
Studies
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Summary:Modeling consumer behavior is a relevant and growing research area in revenue management. Single-resource (single-leg) capacity control problems comprising consumer choice modeling constitute the backbone of more complicated models. In existing models, the distribution of demand is assumed to be independent of external factors. However, in reality demand may depend on the current external environment which represents the prevailing economic, financial or other factors that affect customer behavior. We formulate a stochastic dynamic program that comprises a discrete choice model of consumer behavior in a randomly fluctuating demand environment with a Markovian structure. We derive some structural results on the optimal policy for capacity control. The model and the results generalize earlier work of Talluri and van Ryzin (Revenue management under a general discrete choice model of consumer behavior. Manag Sci 50(1):15–33 2004b ). In particular, the concept of an efficient set of products plays an important rule but such sets may depend on the particular external environment. We also present some computational results which illustrate the structural properties and explore the benefits of explicitly modeling the external environment.
ISSN:0171-6468
1436-6304
DOI:10.1007/s00291-014-0380-9