Stepwise capacity integration in port cluster under uncertainty and congestion

Abstract

Port capacity integration is important for mitigating port overinvestment and preventing the waste of coastline resources and port assets. In this paper, we study the port capacity integration problem in port cluster under uncertainty and congestion. The optimal investment and exit decisions for individual ports under uncertainty are first derived based on real option theory. A capacity stepwise investment and exit integration model with the aim of achieving maximum discounted expected payoff is developed for the problem and the corresponding solution algorithm is proposed. Empirical studies regarding the individual ports and the Bohai Rim port cluster in China are conducted to demonstrate and verify the model and methods. The results indicate that the port cluster has achieved great benefits from port integration compared to the scenario without integration and the capacity utilization of the port cluster has increased over 30% at the end of the integration process. Furthermore, the policy implications for guiding the port capacity integration in port cluster (including unified port governance institution, adjustment mechanism of port price, and transfer payment) are proposed based on the empirical results.