Data-Driven Revenue Management for Air Cargo

TL;DR

This paper introduces a data-driven revenue management approach tailored for the air cargo industry, addressing demand volatility, capacity uncertainty, and routing flexibility, and demonstrates its effectiveness through simulation results.

Contribution

It presents a novel data-driven revenue management algorithm specifically designed for air cargo, outperforming other strategies in simulation tests.

Findings

The proposed algorithm outperforms other strategies with over 3% revenue improvement.

Simulations show effective handling of demand volatility and capacity uncertainty.

Independent weight and volume bid price generation yields the best revenue results.

Abstract

It is well-recognized that Air Cargo revenue management is quite different from its passenger airline counterpart. Inherent demand volatility due to short booking horizon and lumpy shipments, multi-dimensionality and uncertainty of capacity as well as the flexibility in routing are a few of the challenges to be handled for Air Cargo revenue management. In this paper, we present a data-driven revenue management approach which is well-designed to handle the challenges associated with Air Cargo industry. We present findings from simulations tailored to Air Cargo setting and compare different scenarios for handling of weight and volume bid prices. Our results show that running our algorithm independently to generate weight and volume bid prices and summing the weight and volume bid prices into price optimization works the best by outperforming other strategies with more than 3% revenue gap.