IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v220y2012i2p510-521.html
   My bibliography  Save this article

Approximate nucleolus-based revenue sharing in airline alliances

Author

Listed:
  • Kimms, Alf
  • Çetiner, Demet

Abstract

Alliances allow the airlines to extend their networks and increase the number of destinations they can access. Different from the traditional single airline approach, in an alliance, partner airlines may sell tickets for the same itinerary. In addition, one itinerary may consist of several flight legs, each of which may be operated by a different airline. A major issue that needs to be addressed is how to share the revenue generated from selling a ticket for a product among the individual airlines in a fair way. The fair allocation of the revenue has a critical importance for the long-term stability of the alliance. We model the problem as a cooperative game and show that the core of the game is non-empty. We propose to use a revenue proration scheme based on the concept of the nucleolus. The numerical studies reveal that the revenue shares can effectively be computed even for large alliance networks.

Suggested Citation

  • Kimms, Alf & Çetiner, Demet, 2012. "Approximate nucleolus-based revenue sharing in airline alliances," European Journal of Operational Research, Elsevier, vol. 220(2), pages 510-521.
  • Handle: RePEc:eee:ejores:v:220:y:2012:i:2:p:510-521
    DOI: 10.1016/j.ejor.2012.01.057
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221712000951
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2012.01.057?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. Jos A. M. Potters & Stef H. Tijs, 1992. "The Nucleolus of a Matrix Game and Other Nucleoli," Mathematics of Operations Research, INFORMS, vol. 17(1), pages 164-174, February.
    2. Richa Agarwal & Özlem Ergun & Lori Houghtalen & Okan Orsan Ozener, 2009. "Collaboration in Cargo Transportation," Springer Optimization and Its Applications, in: Wanpracha Chaovalitwongse & Kevin C. Furman & Panos M. Pardalos (ed.), Optimization and Logistics Challenges in the Enterprise, pages 373-409, Springer.
    3. M Butler & H P Williams, 2002. "Fairness versus efficiency in charging for the use of common facilities," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(12), pages 1324-1329, December.
    4. Christopher P. Wright & Harry Groenevelt & Robert A. Shumsky, 2010. "Dynamic Revenue Management in Airline Alliances," Transportation Science, INFORMS, vol. 44(1), pages 15-37, February.
    5. Serguei Netessine & Robert A. Shumsky, 2005. "Revenue Management Games: Horizontal and Vertical Competition," Management Science, INFORMS, vol. 51(5), pages 813-831, May.
    6. Peter Borm & Herbert Hamers & Ruud Hendrickx, 2001. "Operations research games: A survey," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 9(2), pages 139-199, December.
    7. Butler, Martin & Williams, H. Paul, 2002. "Fairness versus efficiency in charging for the use of common facilities," LSE Research Online Documents on Economics 18399, London School of Economics and Political Science, LSE Library.
    8. Kalyan Talluri & Garrett van Ryzin, 1999. "A Randomized Linear Programming Method for Computing Network Bid Prices," Transportation Science, INFORMS, vol. 33(2), pages 207-216, May.
    9. Kalyan Talluri & Garrett van Ryzin, 1998. "An Analysis of Bid-Price Controls for Network Revenue Management," Management Science, INFORMS, vol. 44(11-Part-1), pages 1577-1593, November.
    10. Jeffrey I. McGill & Garrett J. van Ryzin, 1999. "Revenue Management: Research Overview and Prospects," Transportation Science, INFORMS, vol. 33(2), pages 233-256, May.
    11. Jeroen Kuipers & Ulrich Faigle & Walter Kern, 2001. "On the computation of the nucleolus of a cooperative game," International Journal of Game Theory, Springer;Game Theory Society, vol. 30(1), pages 79-98.
    12. Hallefjord, Asa & Helming, Reidun & Jornsten, Kurt, 1995. "Computing the Nucleolus When the Characteristic Function Is Given Implicitly: A Constraint Generation Approach," International Journal of Game Theory, Springer;Game Theory Society, vol. 24(4), pages 357-372.
    13. Potters, J.A.M. & Tijs, S.H., 1992. "The nucleolus of a matrix game and other nucleoli," Other publications TiSEM ae3402e7-bd19-494b-b0a1-f, Tilburg University, School of Economics and Management.
    14. SCHMEIDLER, David, 1969. "The nucleolus of a characteristic function game," LIDAM Reprints CORE 44, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. de Boer, Sanne V. & Freling, Richard & Piersma, Nanda, 2002. "Mathematical programming for network revenue management revisited," European Journal of Operational Research, Elsevier, vol. 137(1), pages 72-92, February.
    16. Graf, M. & Kimms, A., 2011. "An option-based revenue management procedure for strategic airline alliances," European Journal of Operational Research, Elsevier, vol. 215(2), pages 459-469, December.
    17. Wen-Chyuan Chiang & Jason C.H. Chen & Xiaojing Xu, 2007. "An overview of research on revenue management: current issues and future research," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 1(1), pages 97-128.
    18. Jerome W. O'Neal & Michael S. Jacob & Adam K. Farmer & Kristi G. Martin, 2007. "Development of a Codeshare Flight-Profitability System at Delta Air Lines," Interfaces, INFORMS, vol. 37(5), pages 436-444, October.
    19. Lori Houghtalen & Özlem Ergun & Joel Sokol, 2011. "Designing Mechanisms for the Management of Carrier Alliances," Transportation Science, INFORMS, vol. 45(4), pages 465-482, November.
    20. Drechsel, J. & Kimms, A., 2010. "Computing core allocations in cooperative games with an application to cooperative procurement," International Journal of Production Economics, Elsevier, vol. 128(1), pages 310-321, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li, Tingting & Xie, Jinxing & Lu, Shengmin & Tang, Jiafu, 2016. "Duopoly game of callable products in airline revenue management," European Journal of Operational Research, Elsevier, vol. 254(3), pages 925-934.
    2. Karaca, Orcun & Delikaraoglou, Stefanos & Hug, Gabriela & Kamgarpour, Maryam, 2022. "Enabling inter-area reserve exchange through stable benefit allocation mechanisms," Omega, Elsevier, vol. 113(C).
    3. Guajardo, Mario & Jörnsten, Kurt, 2015. "Common mistakes in computing the nucleolus," European Journal of Operational Research, Elsevier, vol. 241(3), pages 931-935.
    4. Minhyuk Sur & Deok-Joo Lee & Kyung-Taek Kim, 2019. "Optimal revenue sharing in platform markets: a Stackelberg model," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(4), pages 317-331, August.
    5. Yuntong Wang, 2016. "Revenue Sharing in Airline Alliance Networks," Working Papers 1605, University of Windsor, Department of Economics.
    6. Li, Deng-Feng, 2012. "A fast approach to compute fuzzy values of matrix games with payoffs of triangular fuzzy numbers," European Journal of Operational Research, Elsevier, vol. 223(2), pages 421-429.
    7. Çetiner, D. & Kimms, A., 2013. "Assessing fairness of selfish revenue sharing mechanisms for airline alliances," Omega, Elsevier, vol. 41(4), pages 641-652.
    8. Mehmet Onur Olgun, 2022. "Collaborative airline revenue sharing game with grey demand data," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(3), pages 861-882, September.
    9. Grauberger, W. & Kimms, A., 2014. "Computing approximate Nash equilibria in general network revenue management games," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1008-1020.
    10. Grauberger, Waldemar & Kimms, Alf, 2016. "Revenue management under horizontal and vertical competition within airline alliances," Omega, Elsevier, vol. 59(PB), pages 228-237.
    11. Miguel A. Ortiz Acuña & Adiel T. Almeida Filho & Francisco S. Ramos, 2024. "Modelling the triple helix system innovation of the main economies from Latin America: a coalitional game theory approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 3245-3270, June.
    12. Clempner, Julio B., 2020. "Penalizing passenger’s transfer time in computing airlines revenue," Omega, Elsevier, vol. 97(C).
    13. Luo, Chunlin & Zhou, Xiaoyang & Lev, Benjamin, 2022. "Core, shapley value, nucleolus and nash bargaining solution: A Survey of recent developments and applications in operations management," Omega, Elsevier, vol. 110(C).
    14. Lütkemeyer, Daniel & Heese, H. Sebastian & Wuttke, David A., 2021. "Overcoming inefficiencies in the development of personalized medicine," European Journal of Operational Research, Elsevier, vol. 290(1), pages 278-296.
    15. W. Grauberger & A. Kimms, 2018. "Computing pure Nash equilibria in network revenue management games," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(2), pages 481-516, March.
    16. An, Qingxian & Wen, Yao & Ding, Tao & Li, Yongli, 2019. "Resource sharing and payoff allocation in a three-stage system: Integrating network DEA with the Shapley value method," Omega, Elsevier, vol. 85(C), pages 16-25.
    17. Bin Zhang & Qingyao Xin & Min Tang & Niu Niu & Heran Du & Xiqiang Chang & Zhaohua Wang, 2022. "Revenue allocation for interfirm collaboration on carbon emission reduction: complete information in a big data context," Annals of Operations Research, Springer, vol. 316(1), pages 93-116, September.

    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. Nicolas Houy & François Le Grand, 2015. "The Monte Carlo first-come-first-served heuristic for network revenue management," Working Papers halshs-01155698, HAL.
    3. Grauberger, Waldemar & Kimms, Alf, 2016. "Revenue management under horizontal and vertical competition within airline alliances," Omega, Elsevier, vol. 59(PB), pages 228-237.
    4. Nicolas Houy & François Le Grand, 2015. "Financing and advising with (over)confident entrepreneurs : an experimental investigation," Working Papers 1514, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    5. Grauberger, W. & Kimms, A., 2014. "Computing approximate Nash equilibria in general network revenue management games," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1008-1020.
    6. Hans Buhl & Robert Klein & Johannes Kolb & Andrea Landherr, 2011. "CR 2 M—an approach for capacity control considering long-term effects on the value of a customer for the company," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 22(2), pages 187-204, December.
    7. Andris Möller & Werner Römisch & Klaus Weber, 2008. "Airline network revenue management by multistage stochastic programming," Computational Management Science, Springer, vol. 5(4), pages 355-377, October.
    8. Çetiner, D. & Kimms, A., 2013. "Assessing fairness of selfish revenue sharing mechanisms for airline alliances," Omega, Elsevier, vol. 41(4), pages 641-652.
    9. Clempner, Julio B., 2020. "Penalizing passenger’s transfer time in computing airlines revenue," Omega, Elsevier, vol. 97(C).
    10. Dimitris Bertsimas & Sanne de Boer, 2005. "Simulation-Based Booking Limits for Airline Revenue Management," Operations Research, INFORMS, vol. 53(1), pages 90-106, February.
    11. Drechsel, J. & Kimms, A., 2010. "Computing core allocations in cooperative games with an application to cooperative procurement," International Journal of Production Economics, Elsevier, vol. 128(1), pages 310-321, November.
    12. Meissner, Joern & Strauss, Arne, 2012. "Improved bid prices for choice-based network revenue management," European Journal of Operational Research, Elsevier, vol. 217(2), pages 417-427.
    13. Mehmet Onur Olgun, 2022. "Collaborative airline revenue sharing game with grey demand data," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(3), pages 861-882, September.
    14. Guerriero, Francesca & Miglionico, Giovanna & Olivito, Filomena, 2012. "Revenue management policies for the truck rental industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 202-214.
    15. Chan Seng Pun & Diego Klabjan & Fikri Karaesmen & Sergey Shebalov, 2016. "Itinerary-based nesting control with upsell," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 15(2), pages 107-137, April.
    16. Gabriel Bitran & René Caldentey, 2003. "An Overview of Pricing Models for Revenue Management," Manufacturing & Service Operations Management, INFORMS, vol. 5(3), pages 203-229, August.
    17. Lori Houghtalen & Özlem Ergun & Joel Sokol, 2011. "Designing Mechanisms for the Management of Carrier Alliances," Transportation Science, INFORMS, vol. 45(4), pages 465-482, November.
    18. Meissner, Joern & Strauss, Arne, 2012. "Network revenue management with inventory-sensitive bid prices and customer choice," European Journal of Operational Research, Elsevier, vol. 216(2), pages 459-468.
    19. Kalyan Talluri & Garrett van Ryzin, 2000. "Revenue management under general discrete choice model of consumer behavior," Economics Working Papers 533, Department of Economics and Business, Universitat Pompeu Fabra, revised Oct 2001.
    20. Mohammad Vardi & Ali Salmasnia & Ali Ghorbanian & Hadi Mokhtari, 2016. "A bi-objective airline revenue management problem with possible cancellation," International Journal of Applied Management Science, Inderscience Enterprises Ltd, vol. 8(1), pages 20-37.

    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:eee:ejores:v:220:y:2012:i:2:p:510-521. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.