Pricing Structure Optimization in mixed restricted/unrestricted Fare Environments
AbstractIn recent years, many traditional practitioners of revenue management such as airlines or hotels were confronted with aggressive low-cost competition. In order to stay competitive, these firms responded by reducing fare restrictions that were originally meant to fence off customer segments. In markets where traditional practitioners faced low-cost competition, unrestricted fares were introduced. Some markets, including airline long-haul markets, were unaffected. And here restrictions could be maintained. We develop choice-based network revenue management approaches for such a mixed fare environment that can handle both the traditional opening or closing of restricted fare classes as well as handling pricing of the unrestricted fares simultaneously. Due to technical constraints of the reservation system, we have a limit on the number of price points for each unrestricted fare. It is natural to ask then how these price points shall be chosen. To that end, we formulate the problem as a dynamic program and approximate it with a mixed integer linear program (MIP) that selects the best price points out of a potentially large set of price candidates for each unrestricted fare. Numerical experiments illustrate the quality of the obtained price structure and that computational effort is relatively low given that we need to tackle the large-scale MIP with column generation techniques.
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Bibliographic InfoPaper provided by Department of Management Science, Lancaster University in its series Working Papers with number MRG/0014.
Length: 26 pages
Date of creation: Jun 2009
Date of revision: Mar 2010
Publication status: Published in Journal of Revenue & Pricing Management Vol 9 (November 2010), pp 399-418.
revenue management; restriction-free pricing; network; pricing structure;
Find related papers by JEL classification:
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
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