Revenue management for container liner shipping services: Critical review and future research directions

Qiang Meng1, Hui Zhao1, Yadong Wang1
1Department of Civil and Environmental Engineering, National University of Singapore, Singapore, 117576, Singapore

Tài liệu tham khảo

Barz, 2016, Air cargo network revenue management, Transp. Sci., 7, 459 Bertsimas, 2005, Simulation-based booking limits for airline revenue management, Oper. Res., 53, 90, 10.1287/opre.1040.0164 Bertsimas, 2003, Revenue management in a dynamic network environment, Transp. Sci., 10.1287/trsc.37.3.257.16047 Bitran, 2003, An overview of pricing models for revenue management, Manuf. Serv. Oper. Manag., 5, 203, 10.1287/msom.5.3.203.16031 Boyd, 2003, Revenue management and e-commerce, Manage. Sci., 49, 1363, 10.1287/mnsc.49.10.1363.17316 Chen, 2016, Pricing and competition in a shipping market with waste shipments and empty container repositioning, Transp. Res. Part B Methodol., 85, 32, 10.1016/j.trb.2015.12.012 Elmaghraby, 2003, Dynamic pricing in the presence of inventory considerations: Research overview, current practices, and future directions, Manage. Sci., 49, 1287, 10.1287/mnsc.49.10.1287.17315 Erdelyi, 2010, A dynamic programming decomposition method for making overbooking decisions over an airline network, INFORMS J. Comput., 22, 443, 10.1287/ijoc.1090.0359 Gallego, 1997, A multiproduct dynamic pricing problem and its applications to network yield management, Oper. Res., 45, 10.1287/opre.45.1.24 Grauberger, 2016, Airline revenue management games with simultaneous price and quantity competition, Comput. Oper. Res., 75, 64, 10.1016/j.cor.2016.05.008 Hellermann, 2006 Kimms, 2006, Simulation of stochastic demand data streams for network revenue management problems, OR Spectr., 29, 5, 10.1007/s00291-005-0020-5 Lee, 2017, Ocean container transport in global supply chains: Overview and research opportunities, Transp. Res. Part B Methodol., 95, 442, 10.1016/j.trb.2016.05.001 Lee, 2015, Fractional price matching policies arising from the ocean freight service industry, Prod. Oper. Manag., 24, 1118, 10.1111/poms.12337 Lee, 2009, A revenue management model for sea cargo, Int. J. Oper. Res., 6, 195, 10.1504/IJOR.2009.026535 Lin, K.Y., Sibdari, S.Y., 2008. Dynamic price competition with discrete customer choices. https://doi.org/10.1016/j.ejor.2007.12.040. Littlewood, 1972, Forecasting and control of passenger bookings, Airl. Gr. Int. Fed. Oper. Res. Soc. Proceedings, 12, 95 Liu, 2015, Joint slot allocation and dynamic pricing of container sea–rail multimodal transportation, J. Traffic Transp. Eng. (English Edition), 2, 198, 10.1016/j.jtte.2015.03.008 Maragos, S., 1994. Yield Management for Maritime Industry. PhD thesis, Massachusetts Institute of Technology, 1994. McGill, 2008, Revenue management: research overview and prospects, Transp. Sci., 33, 233, 10.1287/trsc.33.2.233 McGill, 1999, Revenue management: Research overview and prospects, Transp. Sci., 33, 233, 10.1287/trsc.33.2.233 Meng, 2014, Containership routing and scheduling in liner shipping: overview and future research directions, Transp. Sci., 48, 265, 10.1287/trsc.2013.0461 Moussawi-Haidar, 2014, Optimal solution for a cargo revenue management problem with allotment and spot arrivals, Transp. Res. Part E Logist. Transp. Rev., 72, 173, 10.1016/j.tre.2014.10.006 Munari, F., 2009. Liner shipping, antitrust and the repeal of regulation 4056/86: A new era of global maritime confrontation?. In Competition and Regulation in Shipping and Shipping Related Industries. Brill Nijhoff, pp. 5–25. Pak, 2002, Overview of OR techniques for airline revenue management, Stat. Neerl., 56, 479, 10.1111/1467-9574.00213 Phillips, 2005 Powell, W.B., 2011. Approximate Dynamic Programming: Solving the Curses of Dimensionality: Second Edition, Approximate Dynamic Programming: Solving the Curses of Dimensionality: Second Edition. https://doi.org/10.1002/9781118029176. Song, 2012, Cargo routing and empty container repositioning in multiple shipping service routes, Transp. Res. Part B Methodol., 46, 1556, 10.1016/j.trb.2012.08.003 Soon, 2009, Complementarity demand functions and pricing models for multi-product markets, Eur. J. Appl. Math., 20, 399, 10.1017/S0956792509007918 Subramanian, 1999, Airline yield management with overbooking, cancellations, and no-shows, Transp. Sci., 33, 147, 10.1287/trsc.33.2.147 Talluri, 2004, Revenue management under a general discrete choice model of consumer behavior, Manage. Sci., 50, 15, 10.1287/mnsc.1030.0147 Talluri, 1999, A randomized linear programming method for computing network bid prices, Transp. Sci., 10.1287/trsc.33.2.207 Ting, 2004, An optimal containership slot allocation for liner shipping revenue management, Marit. Policy Manag., 31, 199, 10.1080/0308883032000209553 Wang, 2015, Itinerary provision and pricing in container liner shipping revenue management, Transp. Res. Part E Logist. Transp. Rev., 77, 135, 10.1016/j.tre.2014.06.020 Wang, 2015, Liner container seasonal shipping revenue management, Transp. Res. Part B Methodol., 82, 141, 10.1016/j.trb.2015.10.003 Weatherford, 1992, A taxonomy and research overview of perishable-asset revenue management: Yield management, overbooking, and pricing, Oper. Res., 40, 831, 10.1287/opre.40.5.831 Xu, 2015, Pricing and balancing of the sea–cargo service chain with empty equipment repositioning, Comput. Oper. Res., 54, 286, 10.1016/j.cor.2014.03.001 Yin, 2012, Quantity discount pricing for container transportation services by shipping lines, Comput. Ind. Eng., 63, 313, 10.1016/j.cie.2012.03.008 Zheng, 2017, Effects of risk-aversion on competing shipping lines’ pricing strategies with uncertain demands, Transp. Res. Part B Methodol., 104, 337, 10.1016/j.trb.2017.08.004 Zhou, 2009, Pricing and competition in a transportation market with empty equipment repositioning, Transp. Res. Part B Methodol., 43, 677, 10.1016/j.trb.2008.12.001 Zurheide, 2015, Revenue management methods for the liner shipping industry, Flex. Serv. Manuf. J., 27, 200, 10.1007/s10696-014-9192-0 Zurheide, 2012, A revenue management slot allocation model for liner shipping networks, Marit. Econ. Logist., 14, 334, 10.1057/mel.2012.11