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Related Experiment Video

Updated: Nov 15, 2025

New Variations for Strategy Set-shifting in the Rat

New Variations for Strategy Set-shifting in the Rat

Published on: January 23, 2017

Robust pricing for airlines with partial information.

Bo Feng¹, Jixin Zhao¹, Zheyu Jiang²

¹School of Business and Research Center for Smarter Supply Chain, Soochow University, Suzhou, 215021 China.

Annals of Operations Research

|March 3, 2021

Summary

This summary is machine-generated.

Airlines can use robust pricing strategies to manage air cargo demand uncertainty with partial information. This method helps set optimal prices, even with limited data, ensuring profitability and easier implementation.

Keywords:

Air cargo Distributional robust stochastic programming Partial information Robust pricing

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Area of Science:

Operations Research
Aviation Management
Econometrics

Background:

Airlines face demand uncertainty in air cargo pricing.
Accurate demand distribution estimation is challenging.
Dynamic pricing is crucial for managing capacity.

Purpose of the Study:

To develop a dynamic pricing model for airlines with partial demand information.
To minimize expected regret under distributional uncertainty.
To provide practical insights for airline revenue management.

Main Methods:

Distributional robust stochastic programming framework.
Reformulation of a non-convex model for closed-form solutions.
Design of an efficient algorithm for robust pricing strategies.

Main Results:

Well-structured closed-form formulae for maximal expected regret.
Characterization of robust pricing strategies in polynomial time.
Numerical analysis yielding managerial insights for pricing and information collection.

Conclusions:

The proposed method offers a practical and efficient approach to dynamic pricing for air cargo.
Additional demand information enhances, rather than compromises, pricing strategy viability.
Airlines can strategically collect data to optimize capacity pricing.