In decision and risk analysis problems, modelling uncertainty probabilistically provides key insights and information for decision makers. A common challenge is that uncertainties are typically not isolated but interlinked which introduces complex (and often unexpected) effects on the model output. Therefore, dependence needs to be taken into account and modelled appropriately if simplifying assumptions, such as independence, are not sensible. Similar to the case of univariate uncertainty, relevant historical data to quantify a (dependence) model are often lacking or too costly to obtain. This may be true even when data on a model's univariate quantities, such as marginal probabilities, are available. Then, specifying dependence between the uncertain variables through expert judgement is the only sensible option. A structured and formal process to the elicitation is essential for ensuring methodological robustness. This thesis consists of three published works and two papers which are to be published (one under review and one working paper). Two of these works provide comprehensive overviews from different perspectives about the research on dependence elicitation processes. Based on these reviews, novel risk assessment and expert judgement methods are proposed - (1) allowing experts to structure and share their knowledge and beliefs about dependence relationships prior to a quantitative assessment and (2) ensuring experts' (detailed) quantitative assessments are feasible while their elicitation is intuitive. The original research presented in this thesis is applied in case-studies with experts in real risk modelling contexts for the UK Higher Education sector, terrorism risk and future risk of antibacterial multi-drug resistance.

This action research thesis was conducted at a Philippine based entity of a multinational semiconductor corporation. It was motivated by a strong interest in developing a method to increase the human component in purchasing efficacy to facilitate the integration of the purchasing function with other areas of the corporation as well as to gain strategic influence in this business-critical area. Recent research findings have reinforced the importance of uncovering the full strategic potential of the purchasing function within corporations. Literature widely acknowledges that the degree of purchasing efficacy to drive integration is seen as a major success factor in establishing cross functional alignment between the purchasing functions and their related interfaces. This in turn represents the internal dimension of purchasing strategy. Consequently, there is an ongoing practical need, as well as strong research interest, to provide a tool to assist in this integration process. Transformative learning theory argues that learning mainly occurs at the moment when meaning perspectives and meaning schemes change. It further postulates that transformation of meaning is initiated by reinterpreting past experiences and reframing them based on new experiences. Such a learning process is often activated by a "distorting dilemma" where previous meanings are suddenly no longer valid. The theory of constraints provides a framework for problem solving which includes methods to facilitate logical thinking processes and contains a tool named the current reality tree. This tool facilitates interpreting reality through a guided and rules based reasoning process which is based on methods of validity testing to prove assumptions of reality. This thesis is concerned with the increase of purchasing efficacy through a transformative learning process facilitated by the application of the logical thinking processes. Ultimately, the study presents a methodology to increase purchasing efficacy by transforming mind-sets and to increase the level of consciousness by utilizing a logical thinking process framework. However, some limitations, such as a regional and cultural focus on the Philippines, as well as the specific context in which this research was carried out, should be considered. These shortcomings are mentioned to motivate scholars to enter future research avenues in purchasing and supply management, in organizational change processes and in the application of the logical thinking process framework.

The marketing mix contains a significant proportion of elements that derive their appeal and effectiveness from visuals. This thesis proposes the application of quantitative measures from the literature on computational aesthetics to evaluate and study the formal characteristics of corporate visuals in the form of logotypes (logos). It is argued that the proposed approach has a number of advantages in terms of efficiency, consistency and accuracy over existing approaches in marketing that rely on subjective assessments. The proposed approach is grounded on a critical review of a diverse literature that encompasses Marketing, Art History and Philosophy, and, Visual Science and Psychology. The computational aesthetic measures are framed within the construct of Henderson and Cote (1998) and van der Lans et al. (2009), in order to analyse brand logo design elements along with their effect on consumers. The thesis is underpinned by three empirical studies. The first study uses an extensive set of 107 computational aesthetic measures to quantify the design elements in a sample of 215 professionally designed logotypes drawn from the World Intellectual Property Organization Global Brand Database. The study uses for the first time an array of different measures for evaluating design elements related to colour that include hue, saturation, and colourfulness. The metrics capture both global design features of logos along with features related to visual segments. The metrics are linked to logo elaborateness, naturalness and harmony, using the theoretical framework of Henderson and Cote (1998). The results show that measures have a very diverse behaviour across metrics and typically follow highly non-normal distributions. Factor analysis indicates that the categorisation of the measurements in three factors is a reasonable representation of the data with some correspondence to the dimensions of elaborateness, naturalness and harmony. The second study demonstrates that the proposed computational aesthetic measures can be used to approximate the subjective evaluation of logo designs provided by experts. Specifically, eight design elements for the sample of 215 logos, corresponding to harmony, elaborateness and naturalness, are evaluated by three experts. The results show for the first time that computational aesthetic measures related to colour along with other measures are useful in approximating subjective expert reviews. Unlike previous literature, this research combines both standard statistical methods for modelling and inference, along with more recent techniques from machine learning. Linear regression analysis suggests that the objective computational measures contain useful information for predicting proxy subjective expert reviews for logos. Model accuracy is substantially improved using neural network regression analysis based on Radial Basis Functions. The last study examines the role of consumer personality traits as moderators of the effect of perceived logo dynamism on consumer attitude towards the logo. One hundred and twenty-two participants were asked to evaluate elements of logo design (visual appearance, complexity, informativeness, familiarity, novelty, dynamism and engagement), their attitude towards the brand and their personality traits (sensation seeking, risk taking propensity, nostalgia and need for cognition). The estimates extracted were shown to vary significantly in terms of central tendency and dispersion and mostly follow non-normal distributions. Following Cian et al. (2014) the moderated mediator model by Preacher and Hayes (2008) is applied to test the suitability of personality traits as moderators of the effect of logo dynamism on attitudes towards the logo. The personality traits used as moderators are Need for Cognition and Risk-Taking Propensity, whereas Engagement was used as a Mediator. This is the first study to employ personality traits as moderators in such a study using this methodology. The results offer limited support of the role of personality traits as moderators in this relationship. Therefore, the study strengthens the case for the development of objective measures of visual characteristics. The working hypothesis in the thesis is that, with the help of computational aesthetic measures, marketing visuals such as corporate logos, can afford themselves to a consistent quantitative approach which can prove to be important for researchers and practitioners alike. By being able to group and measure the aesthetic differences, similarities and emerging patterns, access is gained to a new family of metrics, which can be applied to any type of logo across time, product, industry or culture.

This doctoral dissertation illustrates how the typically coordinated market economy of Germany fosters the creation of radical innovation. The findings of this thesis are in sharp contrast with theoretical expectations for the crucial case of Germany. The changes in the German institutional framework, including the labour market, corporate governance, financial institutions and skill creation since re-unification are illustrated. The influence of government policy on institutional change is analysed. Propositions of different approaches to the political and economic theory are discussed in the light of the findings. An enhanced theoretical framework for the support of new and emerging technologies in the coordinated institutional framework of Germany is established.

Over the past decades social problems, and poverty in particular, have been of great concern to international organisations, academics and practitioners. The multidimensional nature of poverty has made intervention programs aimed at alleviating poverty very challenging. Social partnerships have been hailed for their potential to bridge the challenges, difficulties and differences faced by individual sectors, and offer useful solutions and compromise that fulfil the mission of the partners and the overall objective of addressing the social problem set out by such partnerships. Previous studies on cross-sector partnerships have not looked at change specifically at the micro (individual) level and the role of the intended beneficiary in the partnership process. The study examines the interaction of poor women and microfinance institutions in cross-sector partnerships involving microfinance institutions and non-profit organisations in Cameroon in Sub-Saharan Africa. The thesis examines two case studies whose main objective and motive is to address poverty as a social issue prevalent in communities in the North West and South West regions of Cameroon. It focuses on the formation and implementation processes of such partnerships, with particular attention on the role of the beneficiary that is, the voice of the beneficiary in the process and outcome of the partnership. The active involvement and participation of beneficiaries has a higher potential for transformative social change. The study focuses on value creation processes at the micro (individual) level for the intended beneficiaries of the two partnership case studies. By studying the interaction process between microfinance institutions and non-profit organisations in cross-sector partnerships, it aims to identify areas within the interaction process with the potential to increase value creation through capability development, and the enhancement of functioning for the beneficiaries. It also aims to identify opportunities for the involvement and participation of the beneficiaries in partnership processes that facilitate transformative social change and impact on the partnership organisations. This thesis argues that, involving beneficiaries in the formation and implementation processes of cross-sector partnerships for poverty alleviation, is essential to maximise financial services for transformative social change.

We address the problem of locating small hydropower dams in an environmentally friendly manner. We propose the use of a multi-objective optimization model to maximize total hydropower production, while limiting negative impacts on river connectivity. Critically, we consider the so called "backwater effects" that dams have on power generation at nearby upstream sites via changes in water surface profiles. We further account for the likelihood that migratory fish and other aquatic species can successfully pass hydropower dams and other artificial/natural barriers and how this is influenced by backwater effects. Although naturally represented in nonlinear form, we manage through a series of linearization steps to formulate a mixed integer linear programing model. We illustrate the utility of our proposed framework using a case study from England and Wales. Interestingly, we show that for England and Wales, a region heavily impacted by a large number of existing river barriers, installation of small hydropower dams fitted with even moderately effective fish passes can, in fact, create a win-win situation that results in increased hydropower and improved river connectivity. We also propose a novel optimization framework to prioritize fish passage barrier mitigation decisions that incorporates both fish population and dispersal dynamics in order to maximize equilibrium population size. A case study involving a wild coho salmon (Oncorhynchus kisutch) population from the Tillamook basin, Oregon, USA is used to illustrate the benefits of our approach. We consider two extreme homing patterns, river and reach level homing, as well as straying. Under density dependent population growth, we find that the type of homing behavior has a significant effect on barrier mitigation decisions. In particular, with reach homing, our model results in virtually the same population sizes as a more traditional barrier prioritization procedure that seeks to maximize the accessible habitat. With river homing, however, there is no need to remove all barriers to maximize equilibrium population size. Indeed, a stochastic version of our model reveals that removing all barriers actually results in a marginal increase in quasi-extinction risk. We hypothesize that this is due to a population thinning effect of barriers, resulting in a surplus of recruits in areas of low spawner density. Our present study should prove useful to fish conservation managers by assessing the relative importance of incorporating spatiotemporal fish population dynamics in river connectivity restoration planning. Finally, habitat fragmentation is a leading threat to global biodiversity. Restoring habitat connectivity, especially in freshwater systems, is considered essential in improving ecosystem function and health. Various studies have looked at cost effectively prioritizing river barrier mitigation decisions. In none of these, however, has the importance of accounting for the potential presence of unknown or "hidden" barriers been considered. In this study, we propose a novel optimization based approach that accounts for hidden barrier uncertainty in river connectivity restoration planning and apply it in a case study of the US state of Maine. We find that ignoring hidden barriers leads to a dramatic reduction in anticipated accessible habitat gains. Using a conventional prioritization approach, habitat gains are on average 60% lower than expected across a range of budgets when there are just 10% additional but unknown barriers. More importantly our results show that anticipating for hidden barriers can improve potential gains in accessible habitat in excess of 110% when the budget is low and the number of hidden barriers comparatively large. Finally, we find that solutions optimized for an intermediate number of unknown barriers perform well regardless of the actual number of hidden barriers. In other words, we can build-in robustness into the barrier removal planning framework. Dealing with the hidden elephant in the room could lead to a far more realistic approach of the habitat connectivity restoration issue.

Recent financial turmoil has set in motion changes that include the switch from the Value at Risk (VaR) risk measure to the Expected Shortfall (ES). Although ES seems superior to VaR, both measures are statistical quantities estimated using historical data. This basis in historical data raises numerous concerns regarding their implementation. This thesis focuses on the estimation, evaluation and applications of the Value at Risk and Expected Shortfall risk measures. It consists of four main chapters corresponding to four research papers. The first chapter evaluates the utility of the forecast combination approach in risk forecasting. We implement a forecast combination approach aiming to improve the accuracy of the freight rate VaR forecasts. In addition, we utilize an augmented statistical evaluation approach accompanied by the relevant evaluation of the forecasts. This is done in order to acquire a thorough understanding of the performance of the forecasts. Our findings suggest that the combination approach significantly improves the accuracy of the VaR forecasts. In the second chapter we evaluate the performance of the backtesting methods and their reliability. Specifically, through a simulation exercise and a financial data application, we evaluate the size and power properties of the major VaR and ES backtesting methods. In addition, we examine the impacts of the regulatory specifications and estimation risk on the tests performance. The simulation results suggest that the size of the tests is distorted and the power of the tests is low, especially for the regulatory specifications. Finally, the empirical application results suggest that misspecified methods are not rejected. In the third chapter we focus on the relevant evaluation of the density forecasts. Specifically, we propose a new rule that aims to capture the performance of the methods at specific regions of the tail. In order to evaluate the performance of the proposed scoring rule, we conduct a simulation exercise and a financial data application. Our findings suggest that the tests of equal performance based on the newly proposed scoring rule have a robust size and power profile. In addition, the financial data application results suggest that the proposed rule provides a more clear insight into the tail performance of the forecasting methods. Finally, in the fourth chapter we utilize the VaR and ES risk measures in order to evaluate the risk-return relationship of the hedge funds and the fund of funds. In addition, we propose an optimal portfolio strategy that aims to outperform the hedge funds and their portfolio benchmarks. Our findings suggest that there are small gains from investing in fund of funds when compared to low risk hedge funds. More importantly, the optimal portfolios outperform all the fund of funds benchmarks.

Motivated by current post-crisis discussions and the corresponding shift in regulatory requirements, this thesis is dedicated to the study of model risk in financial modelling. It is well-known that the majority of finance quantities that are involved in asset pricing, trading, and risk management activities are dependent on the chosen financial models. This gives rise to model risk in all financial activities. Even when the chosen model form is appropriate, model outputs are still subject to parameter estimation uncertainty. Therefore, among different sources of model risk, we mainly focused on investigating the impact of parameter estimation risk and model selection risk in different financial models. Models investigated in this thesis are key models in option pricing, credit risk management, stochastic process of security returns and hedge fund return forecasting. We provoke a solution, which naturally stems from the Bayesian framework. Regarding parameter estimation risk, instead of focusing on point estimation value, it is possible to gauge the rich information about parameter uncertainty from the posterior distribution of parameters. Subsequent impact to model final outputs can be easily accessed by inserting the posterior distribution of parameters into the model. Depending on the related financial activities, model users may find it useful to adopt the estimated value at a certain percentile (e.g. 97.5%) of the posterior distribution as an overlay to the estimated mean value. While more than one candidate model is considered, posterior or predictive probability of a candidate model derived from the likelihood of the model output in fitting the data is applied for a model averaging exercise to account for model selection risk.

Backpacker tourism has been an increasing phenomenon since the 1960s (Cohen 1973; Hampton 2013), and many Less Developed Countries (LDCs) are now favourite destinations for backpackers. This backpacker tourism development raises questions about the effects it has on the host communities as well as on the backpackers themselves However, the impact of backpacker tourism development on the power relations between the actors of this development, i.e. the backpackers, the host communities with their businesses, and the governmental actors, have been little explored. This thesis examines the relationship between backpacker tourism development and the power relations between the backpackers, the host communities with their businesses, and the governmental actors in Colombia. Adopting a broad Political Economy (PE) approach, the thesis investigates the backpacker tourism development in two rural communities, one a long-standing backpacker tourism destination, the other one a more recent development. The study includes the three main actors of tourism development: the backpackers as tourism consumers, the businesses catering to them as tourism producers, and the governmental actors influencing backpacker tourism development. It analyses the actors' social, cultural and political embeddedness within their respective communities. The thesis explores how these three main actors of backpacker tourism development interact with each other, how they are interlinked in the two researched communities on the three types of embeddedness mentioned above, and how they affect and are affected by backpacker tourism development. The thesis key contribution is the theoretical framework. It investigates the interaction between consumption and production, as advocated by (Ateljevic 2000), while also anchoring the three actors in the social, cultural and political structures they act within. It combines two existing frameworks into a new, holistic one: The first one is a framework by Ferguson (2011), focussing on small-scale actors in rural communities, and also on the consumption patterns of consumers from LDCs, in this case on Latin American backpackers travelling within Latin America (Colombia). The second component of the framework is Mosedale's (2011) theoretical framework that examines the embeddedness of the actors of tourism development on three different types: their structural embeddedness into social structures and networks, their cultural embeddedness, and their political embeddedness on a local, regional and national level. The thesis' new framework therefore provides one answer to the call for more theorisation, both in tourism studies (see Bianchi 2009; Hannam 2002; Tribe 2006) and in PE (see Britton 1982). It further focusses on small-scale actors, in this case backpacker tourism Small and Medium-Sized Enterprises (SMEs) instead of Transnational Enterprises (TNCs) as often investigated in tourism and PE studies (e.g. Britton 1982; Freitag 1994). The research aim was addressed in an ethnographic field study, consisting of mainly interviews (n=53) with backpackers, backpacker tourism business owners, and policy makers in two different fieldwork locations in Colombia. Additional data was collected through participant observation, policy document analysis, and other supporting methods such as mapping exercises and the analysis of online and offline travel materials. The findings show that backpacker tourism development often reinforced unequal power relations that were prevalent within the communities and on a global scale. For example, on the production side, this includes issues such as the access to knowledge of the backpacker market by local business owners, resulting in foreign business owners with travel experience having more knowledge power over the locals competing in the same market. On the consumption side, many backpackers from developed countries possessed more financial power to travel for prolonged periods of time in comparison to their Latin American counterparts, who travelled for less time or had to work while travelling. Furthermore, the local government's involvement in tourism development seemed to be vital for a more successful execution of backpacker tourism within the communities, with a lack of involvement leading to a power vacuum in one community that was filled by shadow industries. The theoretical contribution of the thesis include that it brings in different voices by including different actors of tourism development from different national and social backgrounds. The inclusiveness of all actors and the structures they work within into one framework allows for a more accurate analysis of the processes of tourism development and its implicit power relations that help to shape backpacker tourism development. It also gives a better indication of why these processes happen the way they do, and how the actors work within the given social, cultural and political structures. The new framework and the analysis could then lead to a more thorough and integrated analysis, considering all actors and their influence upon tourism development and on each other. The analysis of the findings also propose some practical implications for tourism businesses and policy makers, such as an upscale shift in the backpacker tourism market, artesano backpackers bridging the gap between tourism producers and consumers, and the need for the local and regional government to invest in the education of their citizens to enable them to successfully participate in the (backpacker) tourism business.

The literature does not always make a distinction between the different types of MNE activities, such as investment and relocation, which creates a theoretical gap regarding our understanding of the motivation that underlines an MNE's behaviour. In simple terms, investment can be initial or relocation (investment). In the case of initial investment, an MNE is investing for the first time; however, in the case of relocation, an MNE has to divest an existing operation and relocate it to another region, i.e. the investment exemplifies the expansion-related activity, but relocation exemplifies the move of production facilities from one country to another (Mucchielli and Saucier 1997). Hence, in the literature, investment, as a conceptual construct, might exemplify a multiplicity of meanings without providing further clarifications. MNE is constantly changing due to the changes in the internal and the external factors, but a firm cannot grow in size endlessly "there is an optimal size beyond which the firm cannot profitably expand." (Casson 2014, p.216). Therefore, regular divestments are a part of a healthy life cycle of the firm because it helps to rationalise (i.e. increase efficiency) the allocation of existing resources. Rationalisation allows MNE to develop continuously without ever reaching the 'boundary'. The rationalisation of activities we define as footloose behaviour. Footloose behaviour -is a repeated relocation of the previously divested operations over a period of time. Footloose behaviour is a process of constant bundling (i.e. investment), unbundling (i.e. divestment) and re-bundling (i.e. relocation) of activities with the aim to balance the optimal size and growth of the MNE. In this thesis, we explore a new way of investigating FDI activity through the lens of systematic 'repeated relocations', which we approach as footloose behaviour. We aim to find the drivers of footloose behaviour. In terms of methodology, we opted for a qualitative case study method. This decision was influenced by the fact that conventional quantitative methods do not offer reliable tools for the analysis of the phenomenon that is yet to be extensively explored. We want to explore the phenomenon and find the drivers of the footloose behaviour. The analysis of the data involves the coding (Nvivo) of the textual data and linking the findings to the propositions that we develop in the conceptual framework. We found that innovation and efficiency are the main drivers of footloose behaviour. The cases studies revealed an interesting interplay between the ability of the MNE to innovate and the desire to achieve the maximum level of network efficiency. We developed a typology of footloose multinationals that highlights the relative position of the company within two dimensions: innovation and efficiency. The typology, as we developed it, describes four types of footloose multinationals: IBM, Johnson Control, Procter & Gamble and Electrolux. The purpose of developing this typology was to understand better how the combination of innovation and efficiency affect footloose behaviour within different MNE.