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Optimal decision making process of transportation service providers in maritime freight networks

  • Transportation Engineering
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KSCE Journal of Civil Engineering Aims and scope

Abstract

The paper presents a bi-level modeling approach for capturing hierarchical relationships among major carriers and finding carrier decision-making processes in maritime freight networks. Carriers are transportation service providers and generally include OC (Ocean Carrier), LC (Land Carrier) and PTO (Port Terminal Operator). They make pricing and routing decisions at each part of the intermodal freight system and have sequential relationships. OCs are considered as the leaders in maritime shipping markets since they generally choose both PTOs and LCs. The individual carrier group determines the optimal service cost and route that give the greatest profit. Hierarchical interactions between OCs and PTOs/LCs are captured in a bi-level model. The concept of multi-leaderfollower game is applied to the bi-level game, assuming multiple and competitive leaders.

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References

  • Agrawal, B. B. and Ziliaskopoulos, A. (2006). “Shipper-carrier dynamic freight assignment model using a variation linequality approach.” Transportation Research Record, vol. 1966, no. 8, pp. 60–70, DOI: 10.3141/1966-08.

    Article  Google Scholar 

  • Bureau of Transportation Statistics (2010). World maritime container traffic 1995-2009.

    Google Scholar 

  • Cheng, T. C. E. and Wu, Y. N. (2006). “A multiproduct, multi-criterion supply demand network equilibrium.” Operations Research, vol. 54, no. 3, pp. 544–554, DOI: 10.1287/opre.1060.0284.

    Article  MathSciNet  MATH  Google Scholar 

  • Dafermos, S. and Narguney, A. (1987). “Oligopolistic and competitive behavior of spatially separated markets.” Regional Science and Urban Economics, vol. 17, pp. 245–254, DOI: 10.1016/0166-0462(87)90048-2.

    Article  Google Scholar 

  • Fernandez, J. E., De Cea, J., and Soto, A. O. (2003). “A multi-modal supply-demand equilibrium model for predicting intercity freight flows.” Transportation Research Part B, vol. 37, no. 7, pp. 615–640, DOI: 10.1016/S0191-2615(02)00042-5.

    Article  Google Scholar 

  • Friesz, T. L., Gottfried, J. A., and Morlok, E. K. (1986). “A sequential shipper-carrier network model for predicting freight flows.” Transportation Science, vol. 20, no. 2, pp. 80–91, DOI: 10.1287/trsc.20.2.80.

    Article  Google Scholar 

  • Guelat, J., Florian, M., and Crainic, B. C. (1990). “Amulti mode multiproduct network assignment model for strategic planning of freight flows.” Transportation Science, vol. 24, no. 1, pp. 25–49, DOI: 10.1287/trsc.24.1.25.

    Article  MATH  Google Scholar 

  • Harker, P. T. (1985). “The state of the art in the predictive analysis of freight transport systems.” Transport Reviews, vol. 5, no. 2, pp. 143–164. DOI: 10.1080/01441648508716591.

    Article  Google Scholar 

  • Harker, P. T. (1988). “Multiple equilibrium behaviors on network.” Transportation Science, vol. 22, no. 1, pp. 39–46, DOI: 10.1287/trsc.22.1.39.

    Article  MathSciNet  MATH  Google Scholar 

  • Harker, P. T. and Friesz, T. L. (1986a). “The use of equilibrium network models in logistics management: with application to the U.S. coal industry.” Transportation Research Part B, vol. 18, no. 5, pp. 457–470, DOI: 10.1016/0191-2615(85)90058-X.

    Google Scholar 

  • Harker, P. T. and Freisz, T. L. (1986b). “Prediction of intercity freight flows: theory.” Transpn. Res., Vol. 20B, No. 2, pp. 139–153, DOI: 10.1016/0191-2615(86)90004-4.

    Article  Google Scholar 

  • Harker, P. T. and Freisz, T. L. (1986c). “Prediction of intercity freight flows: mathematical formulations.” Transpn. Res., Vol. 20B, No. 2, pp. 155–174, DOI: 10.1016/0191-2615(86)90005-6.

    Article  Google Scholar 

  • Hurley, W. J. and Petersen, E. R. (1994). “Nonlinear tariffs and freight network equilibrium.” Transportation Science, vol. 28, no. 3, pp. 236–245, DOI: 10.1287/trsc.28.3.236.

    Article  MATH  Google Scholar 

  • Kim, G. S. and Kim, T. S. (2010). “Functional networking of logistics port cities in Northeast Asia.” International Journal of Urban Sciences, vol. 14, no. 1, pp. 73–85, DOI: 10.1080/12265934.2010.9693665

    Article  Google Scholar 

  • Kim, E. M., Park, D. J., Kim, C. S., and Lee, J. Y. (2010). “A new paradigm for freight demand modeling: The physical distribution channel choice approach.” International Journal of Urban Sciences, vol. 14, no. 3, pp. 240–253, DOI: 10.1080/12265934.2010.9693682.

    Article  Google Scholar 

  • Kim, J. J., Rho, J. H., and Park, D. J. (2009). “On-line estimation of departure time-based link travel times from spatial detection system.” International Journal of Urban Sciences, vol. 13, no. 1, pp. 63–80, DOI: 10.1080/12265934.2009.9693646.

    Article  Google Scholar 

  • Kuroda, K., Takebayashi, M. and Tsuji, T. (2005). “International container transportation network analysis considering port-panamaxclass container ships.” Transportation Economics, vol. 13, no. 5, pp. 369–391, DOI: 10.1016/S0739-8859(05)13016-9.

    Article  Google Scholar 

  • Lee, H., Boile, M. and Theofanis, S (2014a). “Modeling carrier interactions in an international freight transportation system.” Journal of Information Systems and Supply Chain Management, vol. 7, no. 1, pp. 15–39, DOI: 10.4018/ijisscm.2014010102.

    Article  MATH  Google Scholar 

  • Lee, H. S., Boile, M., Theofanis, S., and Choo, S. (2014b). “Game Theoretical Models of the Cooperative Carrier Behavior.” KSCE Journal of Civil Engineering, KSCE, vol. 18, no. 5, pp. 1528–1538, DOI: 10.1007/s12205-014-0337-1.

    Article  Google Scholar 

  • Lee, H., Song, Y., Choo, S., Chung, K., and Lee, K. (2014c). “Bi-level optimization programming for the shipper-carrier Network Problem.” Cluster Computing, vol. 17, no. 3, pp. 805–816, DOI: 10.1007/s10586-013-0311-6.

    Article  Google Scholar 

  • Lee, H., Boile, M., Theofanis, S., Choo, S., and Lee, K. (2014d). “A freight network planning model in oligopolistic shipping markets.” Cluster Computing, vol. 17, no. 3, pp. 835–847, DOI: 10.1007/s10586-013-0314-3.

    Article  Google Scholar 

  • Miller, T. C., Tobin, R. L., and Friesz, T. L. (1991). “Stackelberg games on a network with Cournot-Nash oligopolistic competitors.” Journal of Regional Science, vol. 31, no. 4, pp. 435–454, DOI: 10.1111/j.1467-9787.1991.tb00159.x.

    Article  Google Scholar 

  • Min, H. and Guo, Z. (2010). “Developing bi-level equilibrium models for the global container transportation network from the perspectives of multiple stakeholders.” International Journal of Logistics Systems and Management, vol. 6, no. 4, pp. 362–379, DOI: 10.1504/IJLSM.2010.032942.

    Article  Google Scholar 

  • Nagurney, A. (1999). Network economics: A variational inequality approach, Dordrecht/Boston/London: Kluwer Academic Publishers.

    Book  Google Scholar 

  • Wang, Y. (2001). A bi-level programming approach for the shippercarrier network problem, Ph.D Thesis, New Jersey Institute ofof Technology.

    Google Scholar 

  • Xiao, F. and Yang, H. (2007). “Three-player game-theoretic model over a freight transport network.” Transportation Research Part C, vol. 15, no. 4, pp. 209–217, DOI: 10.1016/j.trc.2006.08.005.

    Article  Google Scholar 

  • Xu, N. and Holguin-Veras, J. A. (2009). “Dynamic model of integrated production-transportation operations.” Presented at the Transportation Research Board 2009 Annual Meeting.

    Google Scholar 

  • Yang, H., Zhang, X., and Meng, Q. (2007). “Stackelberg games and multiple equilibrium behavior on networks.” Transportation Research Part B, vol. 41, no. 8, pp. 841–861, DOI: 10.1016/j.trb.2007.03.002.

    Article  Google Scholar 

  • Zan, Y. (1999). “Analysis of container port policy by the reaction of an equilibrium shipping market.” Maritime Policy & Management, vol. 26, no. 4, pp. 367–381, DOI: 10.1080/030888399286808.

    Article  MathSciNet  Google Scholar 

  • Zhang, T., Zhao, Q., and Wu, W. (2008) “Bi-level programming model of container port game in the container transport supernetwork.” Journal of Applied Mathematics and Computing, vol. 31, no. 1, pp. 13–32, DOI: 10.1007/s12190-008-0188-3.

    Google Scholar 

  • Zhang, X., Zhang, H. M., Huang, H., Sun, L. J., and Tan, T. Q. (2011). “Competitive, cooperative and Stackelberg congestion pricing for multiple regions in transportation networks.” Transportmetrica, vol. 7, no. 4, pp. 297–320, DOI: 10.1080/18128602.2010.502547.

    Article  MATH  Google Scholar 

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Correspondence to Sangho Choo.

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Lee, H., Choo, S. Optimal decision making process of transportation service providers in maritime freight networks. KSCE J Civ Eng 20, 922–932 (2016). https://doi.org/10.1007/s12205-015-0116-7

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