Revenue management for low-cost providers

Low-cost providers have emerged as important players in many service industries, the most predominant being low-cost, or the so-called discount airlines. This paper presents models and results leading toward understanding the revenue management outlook for a discount pricing firm. A framework and mo...

Full description

Saved in:
Bibliographic Details
Published inEuropean journal of operational research Vol. 188; no. 1; pp. 258 - 272
Main Authors Marcus, Benjamin, Anderson, Chris K.
Format Journal Article
LanguageEnglish
Published Amsterdam Elsevier B.V 01.07.2008
Elsevier
Elsevier Sequoia S.A
SeriesEuropean Journal of Operational Research
Subjects
Airline industry
Applied sciences
Control theory
Dynamic pricing
Exact sciences and technology
Firm modelling
Operational research and scientific management
Operational research. Management science
Operations research
Pricing policies
Revenue
Revenue management
Stochastic models
Studies
Dynamic pricing
Revenue management
Control theory
Exogenous
Discount
Probabilistic approach
Service industries
Optimal policy
Return rate
Real time
Modeling
Optimal control
Pricing
Randomness
Air transportation
Overhead line
Dynamic programming
Tariffication
Online AccessGet full text

Cover

More Information
Summary:Low-cost providers have emerged as important players in many service industries, the most predominant being low-cost, or the so-called discount airlines. This paper presents models and results leading toward understanding the revenue management outlook for a discount pricing firm. A framework and model is formulated specifically for the airline industry, but is generalizable to low-cost providers in similar revenue management settings. We formulate an optimal pricing control model for a firm that must underprice to capture a segment of exogenous demand. Two specific model formulations are considered: a continuous deterministic version, and a discrete stochastic version. Structural results are derived for the deterministic case, providing insight into the general form of optimal underpricing policies. The stochastic results support the structural insight from the deterministic solution, and illuminate the effect of randomness on the underpricing policies.
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2007.04.010