Revenue management for intermodal transportation: the role of dynamic forecasting

Abstract

We study a joint capacity leasing and demand acceptance problem in intermodal transportation. The model features multiple sources of evolving supply and demand, and endogenizes the interplay of three leversforecasting, leasing, and demand acceptance. We characterize the optimal policy, and show how dynamic forecasting coordinates leasing and acceptance. We find (i) the value of dynamic forecasting depends critically on scarcity, stochasticity, and volatility; (ii)traditional mean-value equivalence approach performs poorly in volatile intermodal context; (iii) mean-value-based forecast may outperform stationary distribution-based forecast. Our work enriches revenue management models and applications. It advances our understanding on when and how to use dynamic forecasting in intermodal revenue management.