Toward Robust Revenue Management: Competitive Analysis of Online Booking

In this paper, we consider the revenue management problem from the perspective of online algorithms. This approach eliminates the need for both demand forecasts and a risk-neutrality assumption. The competitive ratio of a policy relative to a given input sequence is the ratio of the policy's pe...

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Bibliographic Details
Published in:Operations research Vol. 57; no. 4; pp. 950 - 963
Main Authors: Ball, Michael O, Queyranne, Maurice
Format: Journal Article
Language:English
Published: Hanover, MD INFORMS 01.07.2009
Institute for Operations Research and the Management Sciences
Subjects:
Airline industry
Airlines
Algorithms
Analysis
analysis of algorithms
Applied sciences
Control theory
Determinism
Emergency protective orders
Exact sciences and technology
Firm modelling
Inventory control, production control. Distribution
inventory/production
marketing/pricing
Mathematical sequences
Online transaction processing
Operational research and scientific management
Operational research. Management science
Order quantity
policies
Pricing
Pricing policies
Probability distributions
Regret
Reservation systems
Revenue
Revenue management
Studies
suboptimal algorithms
Wage & price controls
United States
Lower bound
Competitiveness
Booking
Return rate
Real time
analysis of algorithms: suboptimal algorithms
Production management
inventory/production: policies, marketing/pricing
Pricing
Price control
Inventory control
Marketing policy
Tariffication
Algorithm analysis
ISSN:0030-364X, 1526-5463
Online Access:Get full text
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Summary:In this paper, we consider the revenue management problem from the perspective of online algorithms. This approach eliminates the need for both demand forecasts and a risk-neutrality assumption. The competitive ratio of a policy relative to a given input sequence is the ratio of the policy's performance to the offline optimal. Under the online algorithm approach, revenue management policies are evaluated based on the highest competitive ratio they can guarantee. We are able to define lower bounds on the best-possible performance and describe policies that achieve these lower bounds. We address the two-fare problem in greatest detail, but also treat the general multifare problem and the bid-price control problem.
Bibliography:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ISSN:0030-364X
1526-5463
DOI:10.1287/opre.1080.0654