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Non-cooperative competition among revenue maximizing service providers with demand learning

Changhyun Kwon, Terry L. Friesz, Reetabrata Mookherjee, Tao Yao and Baichun Feng

European Journal of Operational Research, 2009, vol. 197, issue 3, 981-996

Abstract: This paper recognizes that in many decision environments in which revenue optimization is attempted, an actual demand curve and its parameters are generally unobservable. Herein, we describe the dynamics of demand as a continuous time differential equation based on an evolutionary game theory perspective. We then observe realized sales data to obtain estimates of parameters that govern the evolution of demand; these are refined on a discrete time scale. The resulting model takes the form of a differential variational inequality. We present an algorithm based on a gap function for the differential variational inequality and report its numerical performance for an example revenue optimization problem.

Keywords: Revenue; management; Pricing; Demand; learning; Differential; games; Kalman; filters (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (5)

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European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

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