Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-29T04:03:02.920Z Has data issue: false hasContentIssue false
  • English
  • Français

Optimal Bilateral Cooperative Slot Allocation for Two Liner Carriers under a Co-Chartering Agreement

Published online by Cambridge University Press:  17 April 2017

Jihong Chen ,
Xiang Liu ,
Xiaohua Zhang ,
Junliang He  and
Lihua Luo
Jihong Chen
Affiliation:
(College of Transport and Communications, Shanghai Maritime University, China)
Xiang Liu*
Affiliation:
(Department of Civil and Environmental Engineering, Rutgers, The State University of New Jersey, USA)
Xiaohua Zhang
Affiliation:
(Logistics Engineering College, Shanghai Maritime University, China)
Junliang He
Affiliation:
(Engineering Research Center of Container Supply Chain Technology, Ministry of Education, Shanghai Maritime University, China)
Lihua Luo
Affiliation:
(College of Transport and Communications, Shanghai Maritime University, China)
*
(E-mail: xiang.liu@rutgers.edu)
Get access Rights & Permissions [Opens in a new window]

Abstract

The container liner shipping industry has stepped into an era of international strategic alliances. Important to these liner alliances is the sharing and allocation of container slots between its member carriers. This paper optimises planning of container ship capacity sharing and co-allocation under a co-charting agreement. First, we explain the concept of this business agreement and its implications on maritime operations. Then, we identify key influencing factors that may affect the decisions of cooperative slot co-allocation. The slot co-allocation problem is modelled as an Integer Programming problem and solved using data from two routes between the United States and Asia. The model determines the optimal slot co-allocation strategies between shipping alliance carriers along allied shipping routes. Computational results indicate that the proposed method is effective in obtaining optimal, cooperative slot sharing strategies that can maximise the total system revenue.

Keywords

ContainerSlot co-allocationLiner shippingCo-chartering
Type
Research Article
Information
The Journal of Navigation , Volume 70 , Issue 5 , September 2017 , pp. 1170 - 1182
Copyright
Copyright © The Royal Institute of Navigation 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Agarwal, R. and Ergun, Ö. (2010). Network design and allocation mechanisms for carrier alliances in liner shipping. Operations Research, 58(6), 1726–1742.Google Scholar
Benacchio, M., Ferrari, C. and Musso, E. (2007). The liner shipping industry and EU competition rules. Transport Policy, 14(1), 1–10.Google Scholar
Caschili, S., Medda, F., Parola, F. and Ferrari, C. (2014). An analysis of shipping agreements: the cooperative container network. Networks and Spatial Economics, 14(3–4), 357–377.Google Scholar
Chen, J. and Yahalom, S. (2013). Container slot co-allocation planning with joint fleet agreement in a round voyage for liner shipping. Journal of Navigation, 66(4), 589–603.Google Scholar
Conforti, M., Cornuéjols, G., and Zambelli, G. (2014). Integer programming. Berlin: Springer.Google Scholar
Dong, J.X., Lee, C.Y. and Song, D.P. (2015). Joint service capacity planning and dynamic container routing in shipping network with uncertain demands. Transportation Research Part B: Methodological, 78, 404–421.Google Scholar
Feng, C.M. and Chang, C.H. (2008). Optimal slot allocation in intra-asia service for liner shipping companies. Maritime Economics & Logistics, 10(3), 295–309.CrossRefGoogle Scholar
Fransoo, J.C. and Lee, C.Y. (2013). The critical role of ocean container transport in global supply chain performance. Production and Operations Management, 22(2), 253–268.Google Scholar
Gao, Z. and Yoshida, S. (2013). Analysis on Industrial Structure and Competitive Strategies in Liner Shipping Industry. Journal of Management and Strategy, 4(4), 12–20.Google Scholar
Kuno, T. (2002). A branch-and-bound algorithm for maximizing the sum of several linear ratios. Journal of Global Optimization, 22(1–4), 155–174.Google Scholar
Lewandowski, K. (2015). Alliance of Marine Container Carriers-Back to the Cartels. Logistics and Transport, 26(2), 21–32.Google Scholar
Lu, H.A., Cheng, J. and Lee, T.S. (2006). An evaluation of strategic alliances in liner shipping–an empirical study of CKYH. Journal of Marine Science and Technology, 14(4), 202–212.CrossRefGoogle Scholar
Lu, H.A., Chen, S.L. and Lai, P. (2010). Slot exchange and purchase planning of short sea services for liner carriers. Journal of Marine Science and Technology, 18(5), 709–718.CrossRefGoogle Scholar
Meng, Q., Wang, S., Andersson, H. and Thun, K. (2013). Containership routing and scheduling in liner shipping: overview and future research directions. Transportation Science, 48(2), 265–280.Google Scholar
Midoro, R. and Pitto, A. (2000). A critical evaluation of strategic alliances in liner shipping. Maritime Policy & Management, 27(1), 31–40.CrossRefGoogle Scholar
Narendra, P.M. and Fukunaga, K. (1977). A branch and bound algorithm for feature subset selection. Computers, IEEE Transactions on, 100(9), 917–922.Google Scholar
Panayides, P.M. and Cullinane, K. (2002). Competitive advantage in liner shipping: a review and research agenda. International Journal of Maritime Economics, 4(3), 189–209.Google Scholar
Panayides, P.M. and Wiedmer, R. (2011). Strategic alliances in container liner shipping. Research in Transportation Economics, 32(1), 25–38.Google Scholar
Papadimitriou, C.H. (1981). On the complexity of integer programming. Journal of the ACM (JACM), 28(4), 765–768.CrossRefGoogle Scholar
Parola, F., Satta, G. and Panayides, P.M. (2015). Corporate strategies and profitability of maritime logistics firms. Maritime Economics & Logistics, 17(1), 52–78.Google Scholar
Ryoo, D.K. and Thanopoulou, H.A. (1999). Liner alliances in the globalization era: a strategic tool for Asian container carriers. Maritime Policy & Management, 26(4), 349–367.CrossRefGoogle Scholar
Slack, B., Comtois, C. and McCalla, R. (2002). Strategic alliances in the container shipping industry: a global perspective. Maritime Policy & Management, 29(1), 65–76.Google Scholar
Song, D.W. and Panayides, P.M. (2002). A conceptual application of cooperative game theory to liner shipping strategic alliances. Maritime Policy & Management, 29(3), 285–301.CrossRefGoogle Scholar
Ting, S.C. and Tzeng, G.H. (2004). An optimal containership slot allocation for liner shipping revenue management. Maritime Policy & Management, 31(3), 199–211.Google Scholar
Tran, N.K. and Haasis, H.D. (2013). Literature survey of network optimization in container liner shipping. Flexible Services and Manufacturing Journal, 27(2–3), 139–179.CrossRefGoogle Scholar
UNCTAD. (2015). Review of Maritime Transportation. In Paper Presented at the United Nations Conference on Trade and Development, New York and Geneva; Available online: http://unctad.org/en/publicationslibrary/rmt2015_en.pdf (accessed on 26 September 2016).Google Scholar
Wang, M. (2015). The formation of shipping conference and rise of shipping alliance. International Journal of Business Administration, 6(5), 22–36.CrossRefGoogle Scholar
Wu, W.M. (2012). Capacity utilization and its determinants for a container shipping line: theory and evidence. Applied Economics, 44(27), 3491–3502.Google Scholar
Yang, D., Liu, M. and Shi, X. (2011). Verifying liner shipping alliance's stability by applying core theory. Research in Transportation Economics, 32(1), 15–24.Google Scholar
Yap, W.Y. (2014). P3 alliance and its implications on contestability in major gateway ports in north America. Transportation Journal, 53(4), 499–515.Google Scholar
Zheng, J., Gao, Z., Yang, D. and Sun, Z. (2015). Network design and capacity exchange for liner alliances with fixed and variable container demands. Transportation Science, 49(4), 886–899.CrossRefGoogle Scholar
Zurheide, S. and Fischer, K. (2012). A revenue management slot allocation model for liner shipping networks. Maritime Economics & Logistics, 14(3), 334–361.CrossRefGoogle Scholar