Competition and cooperation for intermodal container transhipment: a network optimization approach
Ziaul Haque Munima, Hercules Haralambidesb,c
aSchool of Business and Law, University of Agder, Norway
bShanghai Maritime University, Shanghai, China
cDalian Maritime University, Dalian, China
This study presents an analysis of cross-border competition and cooperation between ports in Bangladesh and India. Nepal and Bhutan are countries without access to seaports — two landlocked countries in South Asia, depending solely on the Indian port of Kolkata for their international seaborne trade. Alternatives do exist in the Bangladeshi ports of Chittagong and Mongla but these are not exploited, in spite of trade agreements that allow access to a third country’s port, and/or crossing the land of a third, intermediate, country. We formulate a mixed integer linear programming optimization model to find the optimum economic benefit of port users (serving Bhutan, Nepal and Northeast India) and port authorities (Chittagong, Kolkata, Mongla), were Indian and Bangladeshi ports to cooperate in serving intermodal transhipment traffic. Our results show that port users would benefit greatly from such a cooperation, in terms of reduced transportation costs, although Kolkata Port Authority (KPA) would suffer a revenue loss for which it ought to be somehow compensated. Sensitivity analyses considering equal terminal handling charges (THC) for transhipment container at the three ports, as well as different capacity and demand volatilities are also carried out, to establish the robustness of any strategic decisions that might be made on the basis of our findings. Finally, we show that inland transportation costs determine container transhipment demand to distant hinterlands, rather than THC at ports.
Keywords: port cooperation; intermodal freight transport; Mixed Integer Linear Programming; nearest neighbour algorithm; land-locked countries; South Asia
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Cite as: Munim, Z. H., Haralambides, H. (2018). Competition and cooperation for intermodal container transhipment: a network optimization approach. Research in Transportation Business & Management, Vol 26, pp. 87-99, doi.org/10.1016/j.rtbm.2018.03.004 .