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Revenue Management for Intermodal Transportation: The Role of Dynamic Forecasting
Author(s) -
Luo Ting,
Gao Long,
Akçay Yalçın
Publication year - 2016
Publication title -
production and operations management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.279
H-Index - 110
eISSN - 1937-5956
pISSN - 1059-1478
DOI - 10.1111/poms.12553
Subject(s) - revenue management , volatility (finance) , revenue , dynamic pricing , demand forecasting , demand management , context (archaeology) , scarcity , operations research , value (mathematics) , computer science , economics , microeconomics , operations management , econometrics , finance , paleontology , machine learning , biology , engineering , macroeconomics
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 levers—forecasting, 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.