An integrated fuzzy risk assessment for seaport operations http://researchonline.ljmu.ac.uk/id/eprint/1787/ Article LJMU has developed LJMU Research Online for users to access the research output of the University more effectively.Abstract Seaport operations are characterised by high levels of uncertainty, as a result their risk evaluation is a very challenging task. Much of the available data associated with the system's operations is uncertain and ambiguous, requiring a flexible yet robust approach of handling both quantitative and qualitative data as well as a means of updating existing information as new data becomes available. Conventional risk modelling approaches are considered to be inadequate due to the lack of flexibility and inappropriate structure for addressing the system's risks. This paper proposes a novel fuzzy risk assessment approach to facilitating the treatment of uncertainties in seaport operations and to optimize its performance effectiveness in a systematic manner. The methodology consists of a fuzzy analytical hierarchy process, an evidential reasoning (ER) approach, fuzzy set theory and expected utility. The fuzzy analytical hierarchy process is used to analyse the complex structure of seaport operations and determine the weights of risk factors while ER is used to synthesise them. The methodology provides a robust mathematical framework for collaborative modelling of the system and allows for a step by step analysis of the system in a systematic manner. It is envisaged that the proposed approach could provide managers and infrastructure analysts a flexible tool to enhance the resilience of the system in a systematic manner. Keywords: Seaport operations; evidential reasoning approach; fuzzy set theory; fuzzy analytical hierarchy process 2. Literature Review CMI systems are faced with high operational constraints due to the dynamic interactions among their interrelated components. The level of interdependences and complexity of the system's operations can be acknowledged through its description by the US Department of Homeland Security "as all areas and things of, on, under, relating to, adjacent to, or bordering on a sea, ocean, or other navigable waterway, including all maritime related activities, infrastructure, people, cargo, vessels and other conveyances" [8]. Analysing the systems in terms of their interdependences which include infrastructure characteristics, operational relationships, environmental impacts, technical efficiency, failure types and state of operation provides insight into their complexity, enabling collaborative modelling to be undertaken. Modern seaports, which are an integral component of CMI systems, focus their operations on continuous handling of flows and efficient transport. Meersman [9], as shown in Figure 1, revealed that these systems progressed from performing cargo handling, stacking and distribution functions to being a complex transportation hub in logistic chains. A vessel operator controls a fleet of vessels with a set of characteristics; the land si...

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In the North West of England the issue of a perceived infrastructure gap is of increasing concern. Investment needs to be made to improve the transport infrastructure of the region if it is to be expected to promote the development of its own regional logistics gateway. Funding tools have been set up to address the challenges arising from the imbalance in infrastructure development that exists between regions in the north of the United Kingdom and those in the south. For regions with well developed economies the outlook is promising as the availability of modern transport infrastructure looks set to improve. However, some sources believe that the development of new transport infrastructure will have a negative impact upon sustainable development. It is expected that this will occur in a range of both direct and indirect ways. As a result, it is critical that planning for the creation of new intermodal transport infrastructure, or the upgrading of that which already exists, takes into account the impact that these developments will have on the sustainable development of the host region. A scenario based development methodology is proposed in this paper. It was developed to provide a way to identify potential scenarios that may arise within a given region as a result of transport infrastructure projects. To create significant scenarios the methodology is dependent on the availability of a sufficient quantity of quality data. For this paper that data was collected through a focus group composed of stakeholders from the region in question. This was further supported by the performance of an impact survey using the same group of stakeholders

Purpose Unforeseen events can disrupt the operational process and negatively impact emergency resources optimization and its supply chain. A limited number of studies have addressed risk management issues in the context of emergency supply chains, and this existing research lacks inbuilt and practical techniques that can significantly affect the reliability of risk management outcomes. Therefore, this paper aims to identify and practically analyze the specific risk factors that can most likely disrupt the normal functioning of the emergency supply chain in disaster relief operations. Design/methodology/approach This paper has used a three-step process to investigate and evaluate risk factors associated with the emergency supply chain. First, the study conducts a comprehensive literature review to identify the risk factors. Second, the research develops a questionnaire survey to validate and classify the identified risk factors. At the end of this step, the study develops a hierarchical structure. Finally, the research investigates the weighted priority of the validated risk factors using the fuzzy-analytical hierarchy process (FAHP) methodology. Experts were required to provide subjective judgments. Findings This paper identified and validated 28 specific risk factors prevalent in emergency supply chains. Based on their contextual meanings, the research classified these risk factors into two main categories: internal and external risk factors; four subcategories: demand, supply, infrastructural and environmental risk factors; and 11 risk types: forecast, inventory, procurement, supplier, quality, transportation, warehousing, systems, disruption, social and political risk factors. The most significant risk factors include war and terrorism, the absence of legislative rules that can influence and support disaster relief operations, the impact of cascading disasters, limited quality of relief supplies and sanctions and constraints that can hinder stakeholder collaboration. Therefore, emergency supply chain managers should adopt appropriate strategies to mitigate these risk factors. Research limitations/implications This study will contribute to the general knowledge of risk management in emergency supply chains. The identified risk factors and structural hierarchy taxonomic diagram will provide a comprehensive risk database for emergency supply chains. Practical implications The research findings will provide comprehensive and systemic support for respective practitioners and policymakers to obtain a firm understanding of the different risk categories and specific risk factors that can impede the effective functioning of the emergency supply chain during immediate disaster relief operations. Therefore, this will inform the need for the improvement of practices in critical aspects of the emergency supply chain through the selection of logistics and supply chain strategies that can ensure the robustness and resilience of the system. Originality/value This research uses empirical data to identify, categorize and validate risk factors in emergency supply chains. This study contributes to the theory of supply chain risk management. The study also adopts the fuzzy-AHP technique to evaluate and prioritize these risk factors to inform practitioners and policymakers of the most significant risk factors. Furthermore, this study serves as the first phase of managing risk in emergency supply chains since it motivates future studies to empirically identify, evaluate and select effective strategies that can eliminate or minimize the effects of these risk factors.

-The task of producing a generic model of the modal choice decision making process is a challenging one. Modal choice is strongly influenced by the infrastructure limitations and geographical constraints of the area in which the decision is being made. With this in mind, addressing modal choice on an individual basis for each region may be the optimal solution. This is the approach adopted in this paper. The creation of a modal choice model is a multistage process of which this paper addresses the first stage, the production a framework of the decision making process. Firstly, a number of criteria that are commonly used in modal choice models are identified. Then a number of gaps in the criteria utilized in previous papers are established. Subsequently, the method used to produce a framework of the decision making process within North West England's Atlantic Gateway is outlined. Through consultation with transport industry experts in North West England, an initial list of sixty eight papers was reduced to thirty six that were considered to be of specific relevance to modern day freight transportation within their region. The criteria used in each of these papers were then, along with further industry input, used to create the foundation on which a modal choice framework specific to the Atlantic Gateway could be built. A greater understanding of what influences modal choice within this region will allow informed decisions to be made by policy makers on how to more efficiently utilize the available modes of freight transport. Having established this, future work can then go on to build upon these findings. This paper recommends that future work is performed to establish the weights of each criteria and sub-criteria within the framework. This should then be followed by establishing industry's perceptions of the best and worst alternatives for moving freight within the Atlantic Gateway.