IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v205y2010i2p448-458.html
   My bibliography  Save this article

Cost allocation in collaborative forest transportation

Author

Listed:
  • Frisk, M.
  • Göthe-Lundgren, M.
  • Jörnsten, K.
  • Rönnqvist, M.

Abstract

Transportation planning is an important part of the supply chain or wood flow chain in forestry. There are often several forest companies operating in the same region and collaboration between two or more companies is rare. However, there is an increasing interest in collaborative planning as the potential savings are large, often in the range 5-15%. There are several issues to agree on before such collaborative planning can be used in practice. A key question is how the total cost or savings should be distributed among the participants. In this paper, we study a large application in southern Sweden with eight forest companies involved in a collaboration. We investigate a number of sharing mechanisms based on economic models including Shapley value, the nucleolus, separable and non-separable costs, shadow prices and volume weights. We also propose a new allocation method, with the aim that the participants relative profits are as equal as possible. We use two planning models, the first is based on direct flows between supply and demand points and the second includes backhauling. We also study how several time periods and geographical distribution of the supply and demand nodes affect the solutions. Better planning within each company can save about 5% and collaboration can increase this about another 9% to a total of 14%. The proposed allocation method is shown to be a practical approach to share the overall cost/savings.

Suggested Citation

  • Frisk, M. & Göthe-Lundgren, M. & Jörnsten, K. & Rönnqvist, M., 2010. "Cost allocation in collaborative forest transportation," European Journal of Operational Research, Elsevier, vol. 205(2), pages 448-458, September.
    • Handle: RePEc:eee:ejores:v:205:y:2010:i:2:p:448-458
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(10)00023-8
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

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

    Other versions of this item:

    References listed on IDEAS

    as
    1. Tijs, S.H. & Driessen, T.S.H., 1986. "Game theory and cost allocation problems," Other publications TiSEM 376c24c5-c95d-4d29-96b6-4, Tilburg University, School of Economics and Management.
    2. 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).
    3. Lemaire, Jean, 1984. "An Application of Game Theory: Cost Allocation," ASTIN Bulletin, Cambridge University Press, vol. 14(1), pages 61-81, April.
    4. S. H. Tijs & T. S. H. Driessen, 1986. "Game Theory and Cost Allocation Problems," Management Science, INFORMS, vol. 32(8), pages 1015-1028, August.
    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. M. Fiestras-Janeiro & Ignacio García-Jurado & Manuel Mosquera, 2011. "Cooperative games and cost allocation problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 19(1), pages 1-22, July.
    2. Rene van den Brink & Youngsub Chun & Yukihiko Funaki & Zhengxing Zou, 2021. "Balanced Externalities and the Proportional Allocation of Nonseparable Contributions," Tinbergen Institute Discussion Papers 21-024/II, Tinbergen Institute.
    3. Benjamin R. Auer & Tobias Hiller, 2021. "Cost gap, Shapley, or nucleolus allocation: Which is the best game‐theoretic remedy for the low‐risk anomaly?," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(4), pages 876-884, June.
    4. van den Brink, René & Chun, Youngsub & Funaki, Yukihiko & Zou, Zhengxing, 2023. "Balanced externalities and the proportional allocation of nonseparable contributions," European Journal of Operational Research, Elsevier, vol. 307(2), pages 975-983.
    5. Skovsgaard, Lise & Jensen, Ida Græsted, 2018. "Recent trends in biogas value chains explained using cooperative game theory," Energy Economics, Elsevier, vol. 74(C), pages 503-522.
    6. Gao, Evelyn & Sowlati, Taraneh & Akhtari, Shaghaygh, 2019. "Profit allocation in collaborative bioenergy and biofuel supply chains," Energy, Elsevier, vol. 188(C).
    7. Grigoriev, Alexander & Jung, Verena & Peeters - Rutten, Marianne & Vredeveld, Tjark, 2017. "On the Acceptance of Gain Sharing Methods in Supply Chain Collaboration," Research Memorandum 024, Maastricht University, Graduate School of Business and Economics (GSBE).
    8. Juan Aparicio & Joaquín Sánchez-Soriano, 2008. "Depreciation games," Annals of Operations Research, Springer, vol. 158(1), pages 205-218, February.
    9. Salant, David J, 2007. "Formulas for fair, reasonable and non-discriminatory royalty determination," MPRA Paper 8569, University Library of Munich, Germany.
    10. Zhang, Ranran & Ma, Weimin & Si, Hongyun & Liu, Jinjin & Liao, Le, 2021. "Cooperative game analysis of coordination mechanisms under fairness concerns of a green retailer," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    11. Florian Kellner & Andreas Otto, 2012. "Allocating CO 2 emissions to shipments in road freight transportation," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 22(4), pages 451-479, January.
    12. Homburg, Carsten & Scherpereel, Peter, 2008. "How should the cost of joint risk capital be allocated for performance measurement?," European Journal of Operational Research, Elsevier, vol. 187(1), pages 208-227, May.
    13. Massol, Olivier & Tchung-Ming, Stéphane, 2010. "Cooperation among liquefied natural gas suppliers: Is rationalization the sole objective?," Energy Economics, Elsevier, vol. 32(4), pages 933-947, July.
    14. Basso, Franco & Guajardo, Mario & Varas, Mauricio, 2020. "Collaborative job scheduling in the wine bottling process," Omega, Elsevier, vol. 91(C).
    15. Defryn, Christof & Sörensen, Kenneth & Cornelissens, Trijntje, 2016. "The selective vehicle routing problem in a collaborative environment," European Journal of Operational Research, Elsevier, vol. 250(2), pages 400-411.
    16. Kellner, Florian & Schneiderbauer, Miriam, 2019. "Further insights into the allocation of greenhouse gas emissions to shipments in road freight transportation: The pollution routing game," European Journal of Operational Research, Elsevier, vol. 278(1), pages 296-313.
    17. Ramaekers, Katrien & Verdonck, Lotte & Caris, An & Meers, Dries & Macharis, Cathy, 2017. "Allocating collaborative costs in multimodal barge networks for freight bundling," Journal of Transport Geography, Elsevier, vol. 65(C), pages 56-69.
    18. DEFRYN, Christof & SÖRENSEN, Kenneth & CORNELISSENS, Trijntje, 2015. "The selective vehicle routing problem in a collaborative environment," Working Papers 2015006, University of Antwerp, Faculty of Business and Economics.
    19. Mehmet Onur Olgun & Erdal Aydemir, 2021. "A new cooperative depot sharing approach for inventory routing problem," Annals of Operations Research, Springer, vol. 307(1), pages 417-441, December.
    20. Lozano, S. & Moreno, P. & Adenso-Díaz, B. & Algaba, E., 2013. "Cooperative game theory approach to allocating benefits of horizontal cooperation," European Journal of Operational Research, Elsevier, vol. 229(2), pages 444-452.

    More about this item

    Keywords

    Transportation OR in natural resources Supply chain management Logistics Economics Group decisions and negotiations Linear programming Backhauling;

    JEL classification:

    • L91 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Transportation: General
    • Q21 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Demand and Supply; Prices
    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry

    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:eee:ejores:v:205:y:2010:i:2:p:448-458. 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.