Skip to main content
SpringerLink
Log in

Revenue management methods for the liner shipping industry

  • Published:
Flexible Services and Manufacturing Journal Aims and scope Submit manuscript

Abstract

Due to changes in the industry which have led to opportunities for new market segmentations, revenue management (RM) methods have gained in importance for liner shipping companies in the recent past. Therefore, possible market segmentations of the liner shipping market and suitable RM methods are discussed in this work. Based on a slot allocation model for container bookings, three different booking acceptance strategies are studied and compared with respect to their applicability in liner shipping and their performance regarding profit and capacity utilization. Especially, a new bid-price (BP) strategy is developed and compared to previously presented booking limit strategies. A simulation approach is used to evaluate the strategies for different scenarios. The simulation study reveals large differences in the impact the strategies can have, e.g. depending on the booking forecast quality. As the new BP strategy shows very promising results for many different realistic scenarios, it can be highly recommended for application in liner shipping.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Acciaro M (2011) Service differentiation in liner shipping: advance booking and express services. Int J Shipping Trans Log 3(4):365–383

    Article  Google Scholar 

  • Bertsimas D, Popescu I (2003) Revenue management in a dynamic network environment. Trans Sci 37:257–277

    Article  Google Scholar 

  • Bingzhou L (2008) A stochastic model for dynamic capacity allocation of container shipping two-dimensional revenue management. International conference on service systems and service management 2008:1–7

    Google Scholar 

  • Brooks MR (2000) Sea change in liner shipping. Pergamon, Oxford

    Google Scholar 

  • Brooks MR, Button KJ (1994) Yield management: A phenomenon of the 1980s and 1990s? Int J Trans Econ 21(2):177–196

    Google Scholar 

  • Brouer BD, Pisinger D, Spoorendonk S (2011) Liner shipping cargo allocation with repositioning of empty containers. INFOR Inf Syst Operat Res 49(2):109–124

    Google Scholar 

  • Demirag O, Swann J (2007) Capacity allocation to sales agents in a decentralized logistics network. Naval Res Log (NRL) 54(7):796–810

    Article  MATH  MathSciNet  Google Scholar 

  • European Commission (2006) Council regulation (ec) no 1419/2006 of 25 September 2006. http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2006:269:0001:01:EN: HTML, Accessed 5 Aug 2013

  • Feng CM, Chang CH (2008) Optimal slot allocation in intra-asia service for liner shipping companies. Marit Econ Log 10:295–309

    Article  Google Scholar 

  • Feng CM, Chang CH (2009) Optimal slot allocation with empty container reposition problem for asia ocean carriers. Int J Ship Trans Log 2(1):22–43

    Article  Google Scholar 

  • Hanke J, Wichern D (2009) Business forecasting. Pearson/Prentice Hall, New Jersey

    Google Scholar 

  • Hapag Lloyd (2013) Services from North Europe to Asia. http://www.hapag-lloyd.com/en/products_and_services/services_between_north_europe_and_asia.html, Accessed 5 Aug 2013

  • Hellermann R (2006) Capacity options for revenue management: theory and applications in the air cargo industry. Springer, Berlin

    Google Scholar 

  • Leach PT (2011) Maersk to charge fees for no-show containers. http://www.joc.com/maritime-news/international-freight-shipping/maersk-charge-fees-no-show-containers_20110623.html, Accessed 5 Aug 2013

  • Lee LH, Chew EP, Sim MS (2007) A heuristic to solve a sea cargo revenue management problem. OR Spectrum 29(1):123–136

    Article  MATH  MathSciNet  Google Scholar 

  • Lee LH, Chew EP, Sim MS (2009) A revenue management model for sea cargo. Int J Operat Res 6:195–222

    Article  MathSciNet  Google Scholar 

  • Lu HA, Chu CW, Che PY (2010) Seasonal slot allocation planning for a container liner shipping service. J Mar Sci Technology 18(1):84–92

    Google Scholar 

  • Maersk Line (2010) Its in your hands. Weekly highlights January 26th

  • Maersk Line (2011a) Daily maersk—press kit. http://www.dailymaersk.com/html/pdf/PressKit_A4_2.pdf, Accessed 5 Aug 2013

  • Maersk Line (2011b) The new normal—a manifesto for changing the way we think about shipping

  • Maragos S (1994) Yield management for maritime industry. PhD thesis, Massachusetts Institute of Technology

  • Salisbury M (2011) The JOC top 50 world container ports. J Commerce 12:32–38

    Google Scholar 

  • Simpson RW (1989) Using network flow techniques to find shadow prices for market and seat inventory control. Flight transportation laboratory memorandum M89–1. MIT, Cambridge

  • Talluri KT, van Ryzin G (1998) An analysis of bid-price controls for network revenue management. Manag Sci 44(11):1577–1593

    Article  MATH  Google Scholar 

  • Talluri KT, van Ryzin GJ (2004) The theory and practice of revenue management. Springer, New York

    Book  MATH  Google Scholar 

  • Ting SC, Tzeng GH (2004) An optimal containership slot allocation for liner shipping revenue management. Marit Policy Manag 31(3):199–211

    Article  Google Scholar 

  • UNCTAD (2008) Review of maritime transport 2008. Tech. rep., United Nations Conference in Trade and Development.

  • Williamson EL (1992) Airline network seat control. PhD thesis, MIT, Cambridge

  • Xiangzhi B, Rongqiu C, Li L (2007) Container slot allocation model with liner shipping revenue management. In: Proceedings of ICM 2007 The 6th international conference on management, pp. 130–137

  • Zou H, Ding J (2008) Analysis of capacity allocation for sea cargo based on revenue management. In: International conference on service operations and logistics, and informatics 2008, vol 1, pp 1399–1402

  • Zurheide S, Fischer K (2011) A simulation study for evaluating a slot allocation for a liner shipping network. In: Böse JW, Hu H, Jahn C, Shi X, Stahlbock R, Voß S (eds) Proceedings of the 2nd international conference on computational logistics, LNCS 6971. Springer, Berlin, pp 354–369

    Google Scholar 

  • Zurheide S, Fischer K (2012a) A nested booking limit algorithm for liner shipping slot allocation. In: Applied mathematical optimization and modelling (APMOD 2012), pp 334–338

  • Zurheide S, Fischer K (2012b) A revenue management slot allocation model for liner shipping networks. Marit Econ Log 14(3):334–361

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to thank the editors and two anonymous referees for their helpful comments on a first version of this paper

Author information

Authors and Affiliations

  1. Institute for Operations Research and Information Systems, Hamburg University of Technology, Hamburg, Germany

    Sebastian Zurheide & Kathrin Fischer

Authors
  1. Sebastian Zurheide
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kathrin Fischer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sebastian Zurheide.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zurheide, S., Fischer, K. Revenue management methods for the liner shipping industry. Flex Serv Manuf J 27, 200–223 (2015). https://doi.org/10.1007/s10696-014-9192-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10696-014-9192-0

Keywords

Search

Navigation