Abstract

In a port-hinterland service network (PHSN), the occurrence of delays or disruption risks in the ports could impose serious impacts on carriers, nodes in hinterlands, or even the entire port-hinterland service network. To study how such risks are generated, propagated, and effectively controlled in the port-hinterland service network, this paper builds a model for the chained propagation of network risks that is consistent with the characteristics of the port-hinterland service network after analysing the risk factors and the risk-generating path by using the fuzzy analytic hierarchy process (FAHP) framework. On the premise of model stability analysis, the paper analyses the elasticity of carriers and ports to the infected proportion of nodes in the hinterlands, infection rate, and recovery rate in order to obtain the optimal control strategy and control coefficient, and the paper finally validates the model through a simulation analysis under a real case. The research shows that external factors causing delay or disruption risk are more important than internal factors, while the occurrence probability of external factors is lower than that of internal factors. There are four equilibrium points in this system. When the equilibrium conditions are met, the infected proportion of carriers and ports gradually approaches zero or narrows to a fixed ratio, and there is only one no-epidemic point. In the equilibrium conditions, when the infected proportion of inland ports is greater than a certain threshold, the infected proportion of carriers and ports decreases with an increase in the infected proportion of inland ports. Moreover, it is determined that increasing the recovery rate is the most effective and direct control measure. The results of this study provide new insights for the risk control of port-hinterland service network managers and participants.

Highlights

  • Maritime transportation plays a significant role in international trade

  • The advocacy of low carbon emissions and low transportation costs has highlighted the great advantages of nodes in the hinterland, such as distribution centres, logistics parks, and dry ports

  • Nodes in PHSNs with a damaged function can lead to a delay or disruption risk of itself or even the entire service network, Mathematical Problems in Engineering and such an impact might spread and involve other participants in the upstream and downstream service sectors, leading to immeasurable economic losses. erefore, understanding how the risk spreads in the port-hinterland service network based on the key factor analysis for delay or disruption risk and how to control it are valuable lessons for relevant participants and managers

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Summary

Introduction

Maritime transportation plays a significant role in international trade. Approximately, 80% of the international trade volume and 55%–67% of the international trade value are completed through maritime transportation [1]. This paper focuses on a port-hinterland service network consisting of the port, the nodes in the hinterland, and the carrier and aims to establish a model of chained risk propagation based on the classic susceptibleinfected-removed (SIR) model after analysing the delay or disruption risk factors and generating path. 2. Literature Review e literature referred to in this paper is mainly based on three perspectives, namely, studies on the risk factors for a port-hinterland service network, optimization control of port-hinterland service network risks, and research on supply chain risk propagation. We aim to construct a model for chained risk propagation in line with the characteristics of the port-hinterland service network and to conduct research on the risk propagation process and optimized control strategies from systemic and dynamic perspectives

Risk Factor Identification and Analysis in PHSN
The Risk Propagation Model
Optimal Risk Control Strategy Analysis
Optimal Investment Coefficient
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