Revenue Management for Intermodal Transportation: The Role of Dynamic Forecasting

• 成果类型: Article
• 署名作者: Luo, Ting; Gao, Long; Akcay, Yalcin
• 署名单位: University of Texas System; University of Texas Dallas; California State University System; California State University Fullerton; University of California System; University of California Riverside; Koc University
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.12553
• 发表日期: 2016
• 页码: 1658-1672
• 关键词: revenue management; forecasting; Leasing; stochastic comparison; dynamic programming

摘要

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.