IDEAS home Printed from https://ideas.repec.org/a/spr/sumafo/v28y2020i1d10.1007_s00550-020-00496-z.html
   My bibliography  Save this article

Model-based long-term pricing in maritime container shipping

Author

Listed:
  • Jörn Schönberger

    (Technische Universität Dresden)

Abstract

This article reports the development and the assessment of a freight rate optimization approach based on mathematical modeling and optimization. It exploits the functional interdependency between the price of a (service) product and the quantity of the product using this price. Solving the proposed model enables a differentiated and shipper-specific rate determination accompanied by the allocation of the transport capacity provided by the carrier to different shippers. This bilateral pricing between carrier and shippers considers market-based reference rates typically available in the maritime container shipping industry. Herewith, we integrate market-based pricing with demand-based pricing. We validate the proposed model in computational experiments for an artificial pricing scenario. An analysis of the achieved results demonstrates that missing overcapacities will lead to reduced revenues if spot market prices are too low.

Suggested Citation

  • Jörn Schönberger, 2020. "Model-based long-term pricing in maritime container shipping," NachhaltigkeitsManagementForum | Sustainability Management Forum, Springer, vol. 28(1), pages 1-11, June.
  • Handle: RePEc:spr:sumafo:v:28:y:2020:i:1:d:10.1007_s00550-020-00496-z
    DOI: 10.1007/s00550-020-00496-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00550-020-00496-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00550-020-00496-z?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Doostizadeh, Meysam & Ghasemi, Hassan, 2012. "A day-ahead electricity pricing model based on smart metering and demand-side management," Energy, Elsevier, vol. 46(1), pages 221-230.
    2. Dimitris Bertsimas & Ioana Popescu, 2003. "Revenue Management in a Dynamic Network Environment," Transportation Science, INFORMS, vol. 37(3), pages 257-277, August.
    3. Gustavo Vulcano & Garrett van Ryzin & Wassim Chaar, 2010. "OM Practice--Choice-Based Revenue Management: An Empirical Study of Estimation and Optimization," Manufacturing & Service Operations Management, INFORMS, vol. 12(3), pages 371-392, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Syed Asif Raza & Rafi Ashrafi & Ali Akgunduz, 2020. "A bibliometric analysis of revenue management in airline industry," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(6), pages 436-465, December.
    2. Dan Zhang & Larry Weatherford, 2017. "Dynamic Pricing for Network Revenue Management: A New Approach and Application in the Hotel Industry," INFORMS Journal on Computing, INFORMS, vol. 29(1), pages 18-35, February.
    3. Moussawi-Haidar, Lama & Nasr, Walid & Jalloul, Maya, 2021. "Standardized cargo network revenue management with dual channels under stochastic and time-dependent demand," European Journal of Operational Research, Elsevier, vol. 295(1), pages 275-291.
    4. Flores, Alvaro & Berbeglia, Gerardo & Van Hentenryck, Pascal, 2019. "Assortment optimization under the Sequential Multinomial Logit Model," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1052-1064.
    5. Jun Li & Serguei Netessine & Sergei Koulayev, 2018. "Price to Compete … with Many: How to Identify Price Competition in High-Dimensional Space," Management Science, INFORMS, vol. 64(9), pages 4118-4136, September.
    6. Escobari, Diego, 2014. "Estimating dynamic demand for airlines," Economics Letters, Elsevier, vol. 124(1), pages 26-29.
    7. Thomas W. M. Vossen & Dan Zhang, 2015. "Reductions of Approximate Linear Programs for Network Revenue Management," Operations Research, INFORMS, vol. 63(6), pages 1352-1371, December.
    8. Li, Xiao Hui & Hong, Seung Ho, 2014. "User-expected price-based demand response algorithm for a home-to-grid system," Energy, Elsevier, vol. 64(C), pages 437-449.
    9. Jalali, Hamed & Carmen, Raïsa & Van Nieuwenhuyse, Inneke & Boute, Robert, 2019. "Quality and pricing decisions in production/inventory systems," European Journal of Operational Research, Elsevier, vol. 272(1), pages 195-206.
    10. Gupta, Vishal Kumar & Ting, Q.U. & Tiwari, Manoj Kumar, 2019. "Multi-period price optimization problem for omnichannel retailers accounting for customer heterogeneity," International Journal of Production Economics, Elsevier, vol. 212(C), pages 155-167.
    11. Guillermo Gallego & Robert Phillips, 2004. "Revenue Management of Flexible Products," Manufacturing & Service Operations Management, INFORMS, vol. 6(4), pages 321-337, January.
    12. Jun Li & Nelson Granados & Serguei Netessine, 2014. "Are Consumers Strategic? Structural Estimation from the Air-Travel Industry," Management Science, INFORMS, vol. 60(9), pages 2114-2137, September.
    13. Chevalier, Philippe & Lamas, Alejandro & Lu, Liang & Mlinar, Tanja, 2015. "Revenue management for operations with urgent orders," European Journal of Operational Research, Elsevier, vol. 240(2), pages 476-487.
    14. Boukettaya, Ghada & Krichen, Lotfi, 2014. "A dynamic power management strategy of a grid connected hybrid generation system using wind, photovoltaic and Flywheel Energy Storage System in residential applications," Energy, Elsevier, vol. 71(C), pages 148-159.
    15. Li, Haitao & Womer, Norman K., 2015. "Solving stochastic resource-constrained project scheduling problems by closed-loop approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 246(1), pages 20-33.
    16. Chiou, Yu-Chiun & Liu, Chia-Hsin, 2016. "Advance purchase behaviors of air passengers: A continuous logit model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 474-484.
    17. Davarzani, Sima & Pisica, Ioana & Taylor, Gareth A. & Munisami, Kevin J., 2021. "Residential Demand Response Strategies and Applications in Active Distribution Network Management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    18. Thomas Spengler & Stefan Rehkopf, 2005. "Revenue Management Konzepte zur Entscheidungsunterstützung bei der Annahme von Kundenaufträgen," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 16(2), pages 123-146, June.
    19. Yuhang Ma & Paat Rusmevichientong & Mika Sumida & Huseyin Topaloglu, 2020. "An Approximation Algorithm for Network Revenue Management Under Nonstationary Arrivals," Operations Research, INFORMS, vol. 68(3), pages 834-855, May.
    20. Felipe Caro & Victor Martínez-de-Albéniz & Paat Rusmevichientong, 2014. "The Assortment Packing Problem: Multiperiod Assortment Planning for Short-Lived Products," Management Science, INFORMS, vol. 60(11), pages 2701-2721, November.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sumafo:v:28:y:2020:i:1:d:10.1007_s00550-020-00496-z. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.