Using the BHPS data, we have carried out three empirical studies to investigate household risky asset choice in the UK. In the first study we follow appropriate econometric procedures to identify household specific factors that can be observed to influence a household’s asset choice through parameters of their objective function, such as risk aversion and habit. In the second and third study, we use techniques to explain the specific influence of various factors rather than finding what lies behind the interactions observed. Specifically, the second study is about examining the effect of retirement on household risky asset choice and investigating whether this effect would be different when house ownership is taken into account. In fact, we do find that retirement has a positive effect on risky asset shares for house owners while it has no effect on non-house owners. In the third study, we carry out an empirical study on the impact of taxation on household risky asset choice, and we find in the short run paying income tax has negative impact on individual’s risky asset shares and in the long run paying capital gain tax has positive effect on individual’s risky asset shares. Hence a possible policy implication is to increase the income tax allowance in order to provide incentives for people on low incomes to save, and to save in a balanced portfolio of low and high risk assets.

The frequency and intensity of flooding has increased over the last few decades. The UK is not an exception, despite large amounts of money invested every year in flood risk management, flooding is a prevalent issue in the country causing millions of losses every year. In this thesis we contribute to debate on the economic valuation of flood risk in the UK from a household perspective using a non-market valuation approach from the housing market. In the first chapter we investigate the capitalisation of flood risk in property prices by means of a meta-analysis. In the second and third chapters we use a repeatsales specification of a hedonic model to investigate the capitalisation of flood defences and the effect of flooding in the price of properties in England. The results suggest that the current benefit estimates used by the UK Government to determine the allocation of resources to flood relief projects results in a misallocation of resources. We highlight the importance of rethinking the strategy for flood risk management in the UK. Our results provide a sound economic basis to guide the allocation of resources for flood alleviation strategies in a socially efficient way.

The search to find new ways of improving performance in the construction industry led to the introduction of collaborative working and, after fifteen years the question is has this approach delivered the expected improvements. The management of collaborative relationships is often underpinned by trust as a governance mechanism. However, owing to the practical problems of operating in the public sector combined, with the natural disposition of human behavior, the risk of opportunism and exploitation remains, requiring additional governance mechanisms to be put in place. However these mechanisms can only be realised if there is a position of strong buyer power. Therefore, the purpose of this thesis is to consider what impact buyer / supplier power has on collaboration and the consequent benefits delivered. Research has been carried out on a case study involving four projects from the Birmingham Construction Partnership using interviews and a questionnaire. It was found that levels of collaboration were not affected by marginal differences in power, but rather by agency factors and trust. However, the conclusion drawn is that the buyer must retain a strong position of power in order to ensure the buyer obtains a good apportionment of value generated by collaboration.

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.