Evolution of inland container distribution among the cluster of ports in the Greater Pearl River Delta

Abstract

Goal programming (GP) is applied to obtain the cargo distribution ratio from hinterland to port cluster in the absence of statistical data. Non-parametric test techniques and correlation analysis are used to analyze the stability of cargo distribution and ordinal preference in port selection. A case study for the inland container distribution in the Greater Pearl River Delta (GPRD) of China shows that most hinterland districts maintain a stable port selection pattern except for Shenzhen, in which many ports are located and which is also close to Hong Kong, another important port in the region. Although Hong Kong is important for international logistics and is one of the busiest and most efficient container ports, it does not provide great advantages for attracting cargoes from the GPRD. In the long run, the best strategy is cooperation rather than competition, which will maximize the overall benefit of the container port cluster in the GPRD.

Keywords:

• Greater Pearl River Delta
• Port cluster
• Hinterland
• Container distribution
• Goal programming
• Non-parametric test
• Correlation analysis
• Port selection

Acknowledgement

This research is supported by 2011 Founded Project of National Natural Science Foundation of China (71171084), 2011 Research Fund for the Doctoral Program of Higher Education of China (20110172110010), and The Fundamental Research Funds for the Central Universities (2012, x2gsD2117850). The authors wish to thank the Companie Maritime d'Affertment–Companie General Maritime (CMA–CGM) for providing necessary data for our research. The authors also acknowledge the Charlesworth Group for improving and polishing the language.

Notes

*Statistical Package for the Social Sciences (SPSS) statistics is a software package used for statistical analysis. Long produced by SPSS inc. located in Chicago, United States, it was acquired by IBM (Armonk, New York, United State) in 2009. SPSS is a widely used program for statistical analysis in social science. It is also used by market researchers, health researchers, survey companies, government, data miners, and others.

† A Mathematical Programming Language (AMPL) is a comprehensive and powerful algebraic modeling language for linear and nonlinear optimization problems in discrete or continuous variables, It was developed at Bell Laboratories, with headquarters in Madison, Wisconsin, United States. For more detailed information, see the website http://www.ampl.com/.

‡ CPLEX is one of the most powerful commercially available solvers, capable of using several CPUs in parallel calculations. Problem types that CPLEX can handle include LP, mixed integer linear programming (MILP), quadratic programming (QP), quadratically constrained quadratic programming (QCQP), and second-order cone programming (SOCP), among others.