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Reliability Engineering & System Safety Volume ��, January ��, Pages ��-��

Analysis of vulnerabilities in maritime supply chains

Liu Honglu , Tian Zhihong , Huang Anqiang , Yang Zaili

https://doi.org/��.��/j.ress.��.��.��

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Abstract

This paper aims to analyze the different concepts of “vulnerability” used in maritime supply chains, and to develop a

novel framework with supporting models to identify and analyze the relevant vulnerabilities in the chains. A real case

of the Maersk shipping line in its Asia-Europe route is studied to demonstrate the applicability of the proposed

framework. We find that the investigated network has stronger robustness against random failures than that when

facing deliberate attacks. Furthermore, to identify vulnerable nodes (i.e. ports) of the network, two different types of

analysis are undertaken through a multi-centrality model and a robustness analysis model, respectively. Consequently,

the vulnerabilities estimated through robustness analysis can ascertain those by the classical centrality methods when

they appear on both analysis results. More importantly, the similarity between the two outcomes can help gain more

confidence on the accuracy in terms of the identification of the vulnerabilities in the system, while the difference (if

any) such as those identified by the robustness analysis but not by the centrality analysis (or vice versa) can trigger a

further investigation to find the comprehensive vulnerable nodes against different threats/hazards. It will aid rational

decision on design and operation of resilient and robust maritime supply chains.

Introduction

With the fast development of container transportation, maritime supply chains become one of the largest complex

networks in the world. Random failures and deliberate attacks on a single element (node or edge) in the network may

cause a cascading breakdown of the whole system. Foci of investigating the risks associated with the chains are moving

from classical cause-consequence analysis at a local component level to a network vulnerability study from a global

system perspective. Complex network theories and methods, including Social Network Analysis (SNA) and system

simulation, are therefore playing increasingly important roles in the vulnerability analysis of maritime supply chains

[6], [12], [22].

A careful literature review on maritime and supply chain vulnerabilities reveals three main research challenges in

previous studies. First, the maritime sector received little attention in terms of both complex networks and resilience

and vulnerability research, compared to other transportation networks [17]. Most of existing risk studies in maritime

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transport networks are from safety and security perspectives (e.g. [32], [33], [34], [35]). Secondly, the concept of the

term “vulnerability” used in this field significantly varies with regards to different research contexts, requiring the new

development of a consolidated definition and a systematic research framework. Thirdly, from a theoretical perspective,

vulnerability of complex networks were analyzed by using either centrality measures in SNA or robustness analysis

approaches, but not in a combined way yet. Comparative analysis using both methods are scanty, requiring

investigation to explore the associated potential benefits. To fill such research gaps, this paper aims to analyze the

different concepts of “vulnerability” used in maritime supply chains, and to develop a novel framework with

supporting models to identify and analyze the relevant vulnerabilities in maritime supply chains. The research findings

from both SNA and robustness analysis approaches will be compared to provide useful insights for ship lines to identify

the vulnerable nodes in their network for accident prevention.

The remaining part of this paper is organized as follows. In Section 2, the relevant literature on “vulnerability” is

reviewed. In Section 3, a new methodology for the vulnerability analysis of maritime supply chains is developed while

maritime network modeling, and its basic topology features are analyzed in Section 4. In Section 5, a model of two

indexes, global and local network efficiency, is built to evaluate the network robustness. In Section 6, multi-centrality

models based on the Borda Count method and robustness analysis approaches are developed to identify vulnerable

ports in maritime networks through the evaluation of the relative drop of the network efficiency. Finally, Section 7

describes the research implications and discusses, while Section 8 concludes the paper by highlighting its contributions

and limits.

Section snippets

Literature review

According to the literature study, the concepts of the term “vulnerability” vary within different research contexts. There

are three main kinds of relevant definitions.

(1) First, the network vulnerability is the opposite perspective of the concept “network robustness”, which denotes how

the network topology (or further one, e.g., the network performance, usually including global and local connection

properties) is affected by the elimination of a finite number of links and/or nodes. In other…

…

Methodology

According to the above definition of vulnerability, the methodology proposed in this work is developed based on the

measurement instruments in the complex network theory. The first step is to use data sources to build the maritime

supply network under investigation. Next, the measures using centrality and robustness analysis are carried out to

analyze vulnerability in the network. Last, when more information about the network is acquired, an in-depth

(focused) analysis will be conducted. The…

Degree metrics and their distributions

The above Fig. 2 only shows the network topology. It is necessary to use statistical methods to further investigate the

feature of the network topology. In statistics, the topology structure of a network can be analyzed by distribution

functions. The spread in the number of edges of a node, i.e., node degree, is characterized by a distribution function

P(k), which describes the probability that a random selected node i has exactly k edges. Emergence of a power-law in

the degree distribution P(k…

Network robustness

Network robustness denotes the capacity to resist the effect of a random or selected removal of nodes or edges. From

the definition, it can be seen that network robustness could be analyzed from two perspectives of random failures of

and deliberate attacks to ports.

From the above node degree and strength analysis, the investigated network is obviously heterogeneous. In general, a

heterogeneous network has stronger robustness against random failures but weaker robustness against deliberate…

Identification of important ports

Identification of important nodes presents the most practical purpose of this research for the analysis of maritime

network vulnerability. It is carried out by both a multi-centrality model and a robustness analysis model. By

incorporating a robustness analysis model into the identification of important nodes can complement the results by

using a classical multi-centrality model only. Therefore, in practice it can provide more insights for a rational decision

making.…

Research implications and discussions

It should be well noted that by using the two models, i.e., multi-centrality model and robustness analysis model, this

study can provide more insightful analysis, including:

(1) Cross reference. The above two different approaches focus on different perspectives of node importance. The multi-

centrality model focuses on the position of node and relations with other nodes from a local node/component level.

Unlike that, the method based on relative drop of network efficiency focuses on the impact of a…

…

Conclusion

There are scanty studies on vulnerability analysis of maritime supply chains from a complex network perspective in

the current literature. Our work is a study of multi-disciplinary nature incorporating science relating to complex

network, vulnerability analysis and maritime transportation operations. The findings reveal that the proposed

methodology is capable of providing insights on the identification of vulnerability in maritime supply chains.

Based on related works, different concepts of…

Acknowledgements

This research has been supported by grants from the National Natural Science Foundation of China under Grants

71540018, EU FP7 Marie Curie IRSES ENRICH project (PIRSES-GA-2013-(612546)) and the Fundamental Research Funds

for the Central Universities (Grant No. B15JB00040). The authors would also like to thank the four anonymous

reviewers for their constructive suggestions.…