This thesis aims to develop a new way for port authorities to predict, analyse and make decisions in Port State Control (PSC) inspections. Under the New Inspection Regime (NIR), it is necessary to not only figure out the influence of new regime to the PSC system, but also provide some technical tools capable of predicting the inspection results and supporting the decision-making of port authorities when regulating the inspection policy. The study consists of analysis from multiple perspectives, both qualitative and quantitative. The risk factors influencing the inspection results and the decision-making of port authorities under NIR are identified through the practical inspection records and related literature. The Paris Memorandum of Understanding (MoU) offers the historical inspection records within the region of Europe and the North Atlantic basin, reflecting different conditions in different periods. Given the different inspection system since 2011, port authorities require a brand new perception of the new inspection regime to estimate the inspection results, and further make decisions when making their own inspection policy. To achieve the objective, an incorporation of two types of models that have proved popular and superior is applied in this study. One is the risk assessment model of Bayesian network (BN), the other is the decision-making model of game theory. The BN models in this research utilize a data-driven approach called Tree Augmented Naïve (TAN) learning to derive the structure of the models. Based on the inspection reports collected from Paris MoU, two BNs that represent the situations of Paris MoU inspection system in different periods are constructed. Company performance, the new indicator, is viewed as one of the important factors influencing the inspection results for the first time and considered in the models. The BN model after the implementation of NIR can serve as the prediction tool for estimating inspection results under dynamic situations. Additionally, a comparative analysis between two models is conducted to clarify the influence on PSC inspection system brought by NIR. When constructing the non-cooperative strategic game model between port authorities and ship owners under NIR, the BN model outcomes play a crucial role in this process, highlighting the novelty of this model. Through the analysis and calculation on the payoff matrix, a Nash equilibrium solution representing the theoretical optimal inspection rate for port authorities is obtained. To validate the feasibility and practical significance of the game model, an empirical study is conducted. The statistics are quantitative and collected from different sources, i.e. Basic vessel information from the World Shipping Encyclopaedia (WSE), casualty information from IMO and Lloyd's Register of Shipping, PSC Inspection records from Paris MoU online inspection database, and the estimated value of different cost types from Drewry Shipping Consultants Ltd. The empirical study illustrates the insights of the optimal inspection policy for port authorities (i.e. with the increase of punishment severity, the optimal inspection rates experience a decreasing trend whatever the vessel condition), as well as providing suggestions for them when formulating the optimal inspection policy under various situations. Based on the BN model and the strategic game model after the implementation of NIR, the thesis eventually proposes a decision-making framework for port authorities to prioritise and select the strategies under different situations. The six-step framework incorporates a risk assessment approach and decision-making approach to provide a novel way to rank the candidate options of port authorities in terms of their resources, which enables decision-makers to find optimal strategies to improve the performance of the PSC inspection system under dynamic business environments. In general, this thesis provides important insights for port authorities to ensure that optimal inspection actions are taken to improve safety at sea in a cost effective manner. The two technical tools (i.e. the dynamic prediction tool for inspection results & the optimal inspection strategy), and the decision-making framework proposed in this project are helpful for port authorities within the Paris MoU region when regulating their inspection policy under NIR. Meanwhile, the comparative analysis in this study further clarifies the influence of NIR on new inspection system from different angles for the first time, demonstrating the introduction and implementation of NIR is a wise and positive decision.

Healthcare is recognised as a complex high risk industry that demands effective management of the risks presented. A total of 260 NHS Trusts were surveyed to identify the risk management arrangements in place. The results were analysed alongside three different sources of nationally published data (CQC, Monitor and NHSLA) to determine if certain organisational or system characteristics existed that would either predetermine risk performance or predispose the Trust to a higher or lower level of performance. The results successfully dispelled a number of preconceptions relating to the size and status of the Trust in determining the performance achieved. However what was evident was the influence that the Trust’s culture and commitment to risk has on the safety and quality of services delivered. A second finding was the significant influence of central policy in the arrangements that organisations had in place from the presentation and content of risk strategy documents, criteria considered and executive leadership. The constraints of a national policy applied locally potentially limits the effectiveness of the processes in managing risk. It was concluded that whilst central policy may help in standardising how risk is managed current arrangements focus arrangements to narrowly. As a result the role of central policy makers should be to set principles that draw on and translate best practice from other high risk industries and encourage local health leaders to flex the approach to reflect local needs and priorities. This local flex should aim to integrate with other corporate programmes to ensure that risk is embedded in all decision making and the risk of the safety and quality of patients is considered alongside risks that may be perceived to be a higher priority such as operational targets and financial balance.

Petroleum Transportation Systems (PTSs) have a significant impact on the flow of crude oil within a Petroleum Supply Chain (PSC), due to the great demand on this natural product. Such systems are used for safe movement of crude and/or refined products from starting points (i.e. production sites or storage tanks), to their final destinations, via land or sea transportation. PTSs are vulnerable to several risks because they often operate in a dynamic environment. Due to this environment, many potential risks and uncertainties are involved. Not only having a direct effect on the product flow within PSC, PTSs accidents could also have severe consequences for the humans, businesses, and the environment. Therefore, safe operations of the key systems such as port, ship and pipeline, are vital for the success of PTSs. This research introduces an advanced approach to ensure safety of PTSs. This research proposes multiple network analysis, risk assessment, uncertainties treatment and decision making techniques for dealing with potential hazards and operational issues that are happening within the marine ports, ships, or pipeline transportation segments within one complete system. The main phases of the developed framework are formulated in six steps. In the first phase of the research, the hazards in PTSs operations that can lead to a crude oil spill are identified through conducting an extensive review of literature and experts’ knowledge. In the second phase, a Fuzzy Rule-Based Bayesian Reasoning (FRBBR) and Hugin software are applied in the new context of PTSs to assess and prioritise the local PTSs failures as one complete system. The third phase uses Analytic Hierarchy Process (AHP) in order to determine the weight of PTSs local factors. In the fourth phase, network analysis approach is used to measure the importance of petroleum ports, ships and pipelines systems globally within Petroleum Transportation Networks (PTNs). This approach can help decision makers to measure and detect the critical nodes (ports and transportation routes) within PTNs. The fifth phase uses an Evidential Reasoning (ER) approach and Intelligence Decision System (IDS) software, to assess hazards influencing on PTSs as one complete system. This research developed an advance risk-based framework applied ER approach due to its ability to combine the local/internal and global/external risk analysis results of the PTSs. To complete the cycle of this study, the best mitigating strategies are introduced and evaluated by incorporating VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and AHP to rank the risk control options. The novelty of this framework provides decision makers with realistic and flexible results to ensure efficient and safe operations for PTSs.

This research proposes a risk management framework and develops generic risk-based decision-making, and risk-assessment models for dealing with potential Hazard Events (HEs) and risks associated with uncertainty for Operational Safety Performance (OSP) in container terminals and maritime ports. Three main sections are formulated in this study: Section 1: Risk Assessment, in the first phase, all HEs are identified through a literature review and human knowledge base and expertise. In the second phase, a Fuzzy Rule Base (FRB) is developed using the proportion method to assess the most significant HEs identified. The FRB leads to the development of a generic risk-based model incorporating the FRB and a Bayesian Network (BN) into a Fuzzy Rule Base Bayesian Network (FRBN) method using Hugin software to evaluate each HE individually and prioritise their specific risk estimations locally. The third phase demonstrated the FRBN method with a case study. The fourth phase concludes this section with a developed generic risk-based model incorporating FRBN and Evidential Reasoning to form an FRBER method using the Intelligence Decision System (IDS) software to evaluate all HEs aggregated collectively for their Risk Influence (RI) globally with a case study demonstration. In addition, a new sensitivity analysis method is developed to rank the HEs based on their True Risk Influence (TRI) considering their specific risk estimations locally and their RI globally. Section 2: Risk Models Simulations, the first phase explains the construction of the simulation model Bayesian Network Artificial Neural Networks (BNANNs), which is formed by applying Artificial Neural Networks (ANNs). In the second phase, the simulation model Evidential Reasoning Artificial Neural Networks (ERANNs) is constructed. The final phase in this section integrates the BNANNs and ERANNs that can predict the risk magnitude for HEs and provide a panoramic view on the risk inference in both perspectives, locally and globally. Section 3: Risk Control Options is the last link that finalises the risk management based methodology cycle in this study. The Analytical Hierarchal Process (AHP) method was used for determining the relative weights of all criteria identified in the first phase. The last phase develops a risk control options method by incorporating Fuzzy Logic (FL) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to form an FTOPSIS method. The novelty of this research provides an effective risk management framework for OSP in container terminals and maritime ports. In addition, it provides an efficient safety prediction tool that can ease all the processes in the methods and techniques used with the risk management framework by applying the ANN concept to simulate the risk models.

Maritime container supply chains (MCSCs) is exposed to various risks arising from both internal operations and the external environment, and the increasing complexity of the modern global logistics system makes the situation even worse, thus causing a significant challenge to the effective risk management of MCSCs. However, systematic studies on this topic are relatively few. In view of this, this study aims to explore and analyse various MCSC risks, develop suitable risk assessment methods, and evaluate the overall performance of MCSCs from a systematic perspective, so as to ensure the safety, reliability, and resilience of MCSCs. This research starts with the identification and classification of all possible risk factors that may be involved in an MCSC based on a comprehensive literature review, and the research results are further validated through a Delphi expert survey. The identified risk factors are then analysed, screened, and assessed in detail. The novelty of this study lies not only on the risk assessment of MCSCs under an uncertain environment from a supply chain level but also on the consideration of the impact of risk condition of each individual MCSC on the overall performance of the entire container supply network. The research results will provide useful insights and valuable information for both researchers and practitioners on the risk analysis and assessment of MCSCs, which is beneficial to different types of stakeholders involved in the maritime shipping industry. The work is also able to provide a theoretical foundation for risk-based decision making and shipping route optimisation in further work. Although the risk assessment methods are presented on the basis of the specific context in MCSCs, it is believed that, with domain-specific knowledge and data, they can also be tailored for a wide range of applications to evaluate the reliability and performance of other supply chain systems, especially where a high level of uncertainty is involved.

The research presents the findings on developers' views of the major risk factors, risks pricing and risks management on redevelopment. Developers bear and manage a lot of risks. Up to date, academic research has focused primarily on the normative or 'should be' aspect of developers' decisions. This study attempts to fill in the gap unravelling the behavioural aspects of their decisions that truly reflect developers' actions in the current market conditions in practice. This research makes use of research instruments such as questionnaires, interviews and focus groups, prior to the development of conjoint analysis to delve deeper into developers' trade-offs of risk factors. Findings of the research with particular reference to the context of Hong Kong, a high density built environment, suggest profits and the uncertainty of obtaining the profits are the main factors. Planning procedures is also an important risk noting the recent amendments to the Town Planning Ordinance in Hong Kong allowing wider public participation which in turn increase developers’ risks. State action through the quango, the Urban Renewal Authority (URA), is not a concern to developers as they prefer and can redevelop on their own without being tied up by the bureaucracy associated with partnering with URA. Other factors such as the macroeconomic and market conditions, lease aspect, land assembly, public engagement and relation with stakeholders are not significant. The findings of the present research add to the current knowledge and understanding of how best developers should manage risks in redevelopment. As a result of such awareness and insight, it is hoped that developers would be better able to design and implement more financially viable and better redevelopment schemes. This will in the long term facilitate the pace of redevelopment in Hong Kong; and provide insights into redevelopment elsewhere, especially in high density built environments worldwide, such as New York. The Thesis is dedicated to my dear mother and father, my Saviour Jesus Christ, those who love me and those who suffer.

This study analyses the phenomenon of political risk in the German energy industry. Political risk can be understood as “the probability that factors caused or influenced by the (in) action or reactions of stakeholders within a political system to events outside or within the country” (Brink 2004). This study asks for determinants and characteristics of political risk, its origination, its occurrence, and its impact. The focus of this study lies in the German energy industry, where politically initiated drastic changes are the predominant challenge for utilities (Roland Berger, 2013). The industry levels investigated include strategic and risk company’s issues and are focused on the senior management and senior politicians’ insights. It looks for the identification and analysis of the linkage of political risk and their effect on utility companies in Germany of different sizes and active within different sectors. While political risk is not limited to Germany or the energy industry, there have been enormous changes in this field recently: the German government recently decided to shut down all nuclear-fuelled power plants as part of a programme called energy turnaround (Energiewende). The content of this programme will change the industry structure radically. Renewable energy is now heavily favoured with a consequent decline in nuclear energy usage. This study analyses political risk combining two approaches: an outside-in and an inside-out analysis. Two important perspectives are captured, evaluated and compared with each other. The first group of interviews focuses on senior political experts, who are strongly connected with the energy industry. This “inside” information comes from experts including members of the state and federal parliament, as well as European parliament and one former federal minister of economics. The second group of interviews therefore seeks “outside” information from industry experts, senior managers of the German energy industries, who are daily confronted with the impact of political risk. It is enriching to combine these two sides, to develop an understanding of the phenomenon of political risk in the German energy industry. The approach of having two interview series with conflicting expert opinion generates a new view of this topic. The findings illustrate these ideas, thoughts, and opinions together, which helps to explain the different sides of political risk in the German energy industry and generates approaches for the utility companies to take to mitigate political risk. The analyses of the experts’ insights generated the following results (1) identification and description of the definitional tensions of understanding political risk in the German energy industry (2) analysis of the political risks the industry is facing (3) evaluation of the potential impact of these risks on the industry and its companies (4) development of a conceptual approach for political risk management in the German energy industry. In detail, it has been derived from the analysis that there are huge differentiations in the understanding of political risk between politicians and managers. There is also no common understanding within the group of politicians. The different perception of political risk was also evident for the types of political risk that were discussed in this study. Despite the observed influence of political decisions on single enterprises in Germany in recent history, there are also differentiations in the evaluation of the impact of political risk within practice. Managers perceive it as a given fact and accept is as an element of their environment that they must interact with, while some political experts argue towards a legislative character of political decisions. The generated insights of the experts were used to develop a conceptual approach for the evaluation of political risk in the German energy industry. It uses three groups of criteria (inside view, outside view, and level of political communication) to evaluate the level of political risk. Three levels of political risk are described and linked with level-related sets of recommendation as a main contribution to theory and practice. The model enables the individual company to take individual actions by anticipating their individual political risk exposure.

It is essential that all countries operate a form of blood banking service, where blood is collected at donation sessions, stored and then distributed to local healthcare providers. It is imperative that these services are efficiently managed to ensure a safe supply of blood and that costs and wastages are kept minimal. Previous works in the area of blood management have focussed primarily on the perishable inventory problem and on routing blood deliveries to hospitals; there has been relatively little work focusing on scheduling blood donation sessions. The primary aim of this research is to provide a tool that allows the National Blood Service (the English and Welsh blood service) to schedule donation sessions so that collection targets are met in such a way that costs are minimised (the Blood Scheduling Problem). As secondary aims, the research identifies the key types of data that blood services should be collecting for this type of problem. Finally, various what-if scenarios are considered, specifically improv- ing donor attendance through paying donors and the proposed changes to the inter-donation times for male and female donors. The Blood Scheduling Problem is formulated as a Mixed Integer Linear Programming (MILP) problem and solved using a variable bound heuristic. Data from the South East of England is used to create a collection schedule, with all further analysis also being carried out on this data set. It was possible to make improvements to the number of units under collected in the current schedule, moreover the number of venues and panels operated could be reduced. Further- more, it was found that paying donors to donate was uneconomical. Finally, changing the inter-donation times could lead to a reduction in the number of shortfalls, even when demand was increased by as much as 20%. Though the model is specific to England and Wales, it can easily be adapted to other countries’ blood services. It is hoped that this model will provide blood services with a model to help them better schedule donation sessions and allow them to identify the data necessary to better understand their performance.

While technical failures remain the most common triggers for overruns in metro projects, the causes have not typically been deficiencies in the underlying engineering principles but in project management. This work involves the complementary use of requirements and risk management processes and real options theory. The Crossrail project provides a case study with a scheme design for an underground station at Farringdon being considered in detail. The requirements process documented in this research is capable of providing an interactive format for managing project requirements and importantly, any changes that are made to them. This is achieved using commercial software (Telelogic DOORS®) and it is shown that this process is effective when working on multidisciplinary metro projects. This process is then expanded to consider the interaction between risks on a project. This is identified as being crucial given the impacts that technical, project and external risks can have on each other. The developed risk process therefore allows the interactions between all risks to be recorded and provides a holistic view of all risks for management purposes. The requirements and risk processes are complemented by a fuzzy logic methodology to evaluate global and elemental risks (such as political or client risks). Over 50 external risk factors which are known to have caused overruns on previous projects are identified and the performance of Crossrail is evaluated against each risk factor by way of a questionnaire circulated to industry professionals. An approach to avoiding cost overruns is demonstrated by the application of real options theory where the chosen design for Farringdon station is developed alongside an alternative design. Real options theory is used to value the cost of implementing the design alternative should it be needed during the project construction cycle due to cost increases and the potential occurrence of major risks. This implementation cost is presented as a fixed cost agreed prior to construction rather than being an added cost to the agreed budget once construction has started. It is proposed that using real options in this context can avoid significant cost overruns by predetermining the value of payments to be made for changing from one design to another. This thesis will show how additions and adjustments to existing processes and the inclusion of real options valuation in the procurement of metro projects can help practitioners avoid cost overruns in a metro rail project.

Container supply chains are vulnerable to many risks. Vulnerability can be defined as an exposure to serious disturbances arising from the risks within the supply chain as well as the risks external to the supply chain. Vulnerability can also be defined as exposure to serious disturbances arising from a hazard or a threat. Containers are one of the major sources of security concerns and have been used, for example, to smuggle illegal immigrants, weapons, and drugs. The consequences of the use of a weapon of mass destruction or discovery of such a device in a container are serious. Estimates suggest that a weapon of mass destruction explosion and the resulting port closure could cost billions of dollars. The annual cost of container losses as consequences of serious disturbances arising from hazards is estimated as $500 million per year. The literature review, historical failure data, and statistical analysis in the context of containerships' accidents from a safety point of view clearly indicate that the container cargo damage, machinery failure, collision, grounding, fire/explosion, and contact are the most significant accident categories with high percentages of occurrences. Another important finding from the literature review is that the most significant basic event contributing to the supply chains' vulnerability is human error. Therefore, firstly, this research makes full use of the Evidential Reasoning (ER) advantages and further develops and extends the Fuzzy Evidential Reasoning (FER) by exploiting a conceptual and sound methodology for the assessment of a seafarer's reliability. Accordingly, control options to enhance seafarers' reliability are suggested. The proposed methodology enables and facilitates the decision makers to measure the reliability of a seafarer before his/her designation to any activities and during his/her seafaring period. Secondly, this research makes full use of the Bayesian Networks (BNs) advantages and further develops and extends the Fuzzy Bayesian Networks (FBNs) and a "symmetric method" by exploiting a conceptual and sound methodology for the assessment of human reliability. Furthermore a FBN model (i. e. dependency network), which is capable of illustrating the dependency among the variables, is constructed. By exploiting the proposed FBN model, a general equation for the reduction of human reliability attributable to a person's continuous hours of wakefulness, acute sleep loss and cumulative sleep debt is formulated and tested. A container supply chain includes dozens of stakeholders who can physically come into contact with containers and their contents and are potentially related with the container trade and transportation. Security-based disruptions can occur at various points along the supply chain. Experience has shown that a limited percentage of inspection, coupled with a targeted approach based on risk analysis, can provide an acceptable security level. Thus, in order not to hamper the logistics process in an intolerable manner, the number of physical checks should be chosen cautiously. Thirdly, a conceptual and sound methodology (i. e. FBN model) for evaluating a container's security score, based on the importer security filling, shipping documents, ocean or sea carriers' reliability, and the security scores of various commercial operators and premises, is developed. Accordingly, control options to avoid unnecessary delays and security scanning are suggested. Finally, a decision making model for assessing the security level of a port associated with ship/port interface and based on the security score of the ship's cargo containers, is developed. It is further suggested that regardless of scanning all import cargo containers, one realistic way to secure the supply chain, due to lack of information and number of variables, is to enhance the ocean or sea carriers' reliability through enhancing their ship staff's reliability. Accordingly a decision making model to analyse the cost and benefit (i.e. CBA) is developed.