Corporate real estate management has become the strategic management of the company’s real estate portfolio that also includes risk management, to protect the business against developments, which could jeopardise the continuity of the organisation. However, risk management tools just represent the infrastructural and technical precondition, but it also requires an appropriate risk culture by all employees for an effective and comprehensive risk management system. Due to diverse shortcomings identified during the literature review, the researcher intends to contribute to corporate real estate management and risk management likewise, by investigating risk culture, theoretically and practically, through an in-depth case study. The case study unit is a corporate real estate organisation of a diversified retail and wholesale company based in Germany. From an academic viewpoint, the researcher has developed a general framework consisting of different key components associated with risk culture from the literature. This represents the conceptual basis for the case study that followed, to identify managerial expectations, i.e. the target risk culture, of the case study unit’s executives, through qualitative interviews (n=11). Based on this, the researcher aims to find out any differences between these expectations and employee’s perception, i.e. the existing risk culture, through a web-based survey of all their full-time employees (n=455). The described approach also represents a proven way as a theoretical concept to investigate risk culture in organisations. In terms of practical contribution for the case study unit, the survey responses (nr=199) confirms the biggest backlog demand in clarity and transparency of risk management processes, including employees’ knowledge of the respective policy, and cross departmental exchange. Management role model, sense of responsibility and entrepreneurial thinking is confirmed by the respondents which represents a fundamental basis towards their target risk culture. However, specific differences in risk culture exist by gender, age, location, job tenure and hierarchy level that is analysed and discussed, to develop more specific measures to overcome the identified deficits.

The primary objective of the research was to develop a theory of corporate branding that could be applied in a 'coopetitive' market context. The context was that of sanitary ware, heating and plumbing (SHAP) industry in Central Europe (CE). As a professional distribution channel with channel member interdependencies that [sic] and multiple brands, coopetition is created. The channel is also subject to legislation that limits the actions of its members - adding restrictions and complexities to the creation of a corporate brand.

The purpose of this thesis is to contribute to existing explanations of the organisational outcomes of Information Technology (IT). In studying this phenomenon, prior research and theory have taken different approaches. At the one end, technology is seen as a major agent of change determining the structure and behaviour of organisations and their members. In stark opposition to this perspective, the tradition of social construction of technology represents IT outcomes as the product of human interpretations, intentions, and voluntary practices. Recent debates in the field have attempted to go beyond these two extreme positions in order to admit both the role of technology, and the social context into which it is introduced. In line with this emerging literature, this research devises an original conceptual framework to allow for the incorporation of multiple entities and the consideration of the dynamic interaction amongst them. This relational approach is employed to examine IT appropriations and the ensuing organisational change in a case of implementing an IT system in three organisational units of a large airline firm. The evidence from this research reaffirms the significance of human agency in mediating IT outcomes. It also demonstrates how the exercise of agency is informed by both the internal and the external environment of the organisation, as well as by the technology's characteristics. The thesis‘s main contribution is that it provides a sociological account of an instance of IT-associated change that avoids both technological determinism and extreme social constructivism.

Modern day corporations are not only economically and politically powerful, but they also have a significant impact on society and the environment. Due to their relevance, once solely focused on government, non-governmental organisations are increasingly engaging in private politics and making corporations the targets of their campaigns. The recent economic crisis has highlighted the role of the financial market for changing corporate actions and, as a result, shareholder activism – a campaigning tactic which is comparatively new, has rapidly grown in popularity among the third sector community. The term can be defined as the use of ownership rights to actively shape corporate policy and behaviour. The research is based on three campaign case studies which provide a detailed exploration of how UK-based NGOs use various shareholder activist strategies to realise their campaign objectives: the campaign against Vedanta Resources‟ operations in India, the campaign against Shell‟s involvement in the Niger Delta, and the Tax Justice campaign targeting FTSE 100 companies. Based on the premise that companies should consider the interests of different stakeholders, the main aim is to explore the shareholder activist strategies used by NGOs, to determine their impact on the investor community and the targeted companies, and to examine what are the main challenges faced by campaigning organisations. The study adopts a multi-method qualitative approach encompassing participant observation, semi-structured interviews and document analysis. It draws on a wide range of literature to explain and build upon the findings – social science literature, but also social movement, pressure group and financial accounting literature. It has been discovered that shareholder activism can potentially be a very effective tactic and that NGOs‟ use of this strategy is on the rise – NGO share campaigns more than doubled in the period 2003-2013 compared to 1990-2002. One of the main conclusions is that NGOs are increasingly using business case arguments when engaging with companies and investors as this method enhances campaign effectiveness. Based on the case study findings, a theoretical model which attempts to explain the factors contributing to the overall impact of campaigns has been developed. The findings also have implications about the nature of corporate governance and the democratisation of business. Shareholder activism has been seen as a tool which democratises corporations through opening the door to private politics to a wider range of stakeholders such as citizens, pension savers, and voluntary organisations. In addition, the nature of a „successful‟ campaign has been reinvented and it has been suggested that the overall impact of an intervention should be regarded from a „delayed gratification‟ point of view and the symbolic outcomes of campaigns should not be discarded as irrelevant.

Motivation: Manufacturers in sectors like Information Technology (IT), Automotive and Aerospace have increasingly become focused on providing after sales services. One of the forms of after sales services is to provide service parts (or spare parts) to customers within different contracted time windows. Commonly offered by large scale IT sector companies, such services are facilitated by Service Parts Logistics (SPL) systems through a network of parts stocking facilities. The number of stocking facilities in a distribution network affects the service responsiveness and service costs related to inventory, transportation and facility set-up. Higher responsiveness can be attained through increasing the number of facilities in a distribution network, which, in turn, usually increases inventory cost. Generally, studies assume that shorter service time windows result in higher costs, but there is a lack of exploration regarding how reductions in service time limits and changes in the fractions of demand for different time-based service types impact on various service related costs. Service area partitioning (or zoning) is another related issue which is unexplored in general facility location literature when considering multiple service time (or distance) constraints and both inventory and transportation costs. This study is mainly motivated by SPL systems of IT equipment manufacturers that support the provision of service parts at customer sites under different and short service time commitments in a large geographical area. The study is of a generic nature and generates insights that can be relevant for any case where the service responses are provided within different short time windows and involve the provision (or consumption) of some stocks (e.g. emergency infrastructure repairs). Aim and methodology: The aim of this work is to investigate relationships between time-based service levels, service costs and service zones/areas under a hierarchical organization and a non-hierarchical organization of service facilities. The hierarchical organization has variable capabilities to meet different time-based requirements, while the non-hierarchical organization has a uniform capability to meet the toughest requirement for the entire customer base. The investigation is mainly done through analytical, simulation and optimization modelling with the view of producing answers that provide a general understanding and practical insights rather than producing situation specific optimization models. Empirical case studies are also conducted to complement the quantitative modelling work so that the research is not divorced from the reality. The case studies point towards the motivation for the modelling study and its relevance to some of the real-world systems, and provide a broader understanding of the issues being researched. The case studies involve two multinational ICT equipment manufacturers and service provides, and a government agency responsible for providing highway emergency services in England. Key findings: The results from the modelling experiments show that under the non-hierarchical setup, where all facilities provide the full range of service-times in their respective vicinities, inventory and transportation costs are insensitive to the fractions of demand for different time-based service types. However, with an inventory sharing mechanism under the non-hierarchical setup, the increase in the proportion of demand for the service within the longer time window can increase the service availability level while also increasing the average travelling. On the other hand, under the hierarchical setup, which provides a higher level of centralization when there is demand for the service in the longer time window, inventory and transportation costs react to the proportions of demand for different time-based service types. The hierarchical setup results in higher transportation cost compared to the non-hierarchical setup, and, interestingly, does not necessarily lower the inventory level, especially when the overall demand rate is very low. The simulation of the inventory sharing mechanism under the hierarchical setup shows that, in several cases, inventory sharing can not only increase the service availability level, but can also reduce transportation cost. The analysis based on the optimization models shows that there can be cases where it is more cost effective to serve all demand, regardless of the required service time, in a similar fashion through a non-hierarchical setup. The results also show that the demand fractions for different time-based service types, and inventory and transportation costs can significantly impact on the optimum organization of service zone. There can be distinct optimum patterns of service zones depending on whether the inventory cost or the transportation cost dominates.

This thesis investigates the experiences of women digital entrepreneurs in the United Kingdom from an intersectional cyberfeminist perspective. Informed by feminist theories of technology and critical entrepreneurship scholarship, it challenges mainstream discourse on digital entrepreneurship with the argument that, similar to traditional (offline) entrepreneurship, online or digital entrepreneurship is deeply embedded in the social world. It draws upon intersectional feminist theory that conceptualises the social world as composed of intersecting hierarchies of race, class, and gender, in which individuals and groups are positioned in dynamic yet durable ways, and by which they are affected simultaneously. This positionality is found to be tied to unequal resource distribution, and for this reason, holds important implications when mapped to extant entrepreneurship theory. The thesis also provides interdisciplinary evidence for the continued coding of Internet technology as predominantly white and male, and for the online environment itself as a stratified and unequal space, countering public discourse that portrays it as a neutral and meritocratic 'great equaliser'.

Historically, econometric models have been developed to model financial instruments and markets however the vast majority of these ‘traditional’ models have one thing in common, linearity. While this is convenient and sometimes intuitive many linear models fail to fully capture the dynamic and complex nature of financial instruments and markets. More recently, ‘sophisticated’ methodologies have been evolved to accurately capture ‘non-linear’ relationships that exist between financial time series. This rapidly advancing field in quantitative finance is known as Artifical Intelligence. The earliest forms of artificial intelligence are Neural Networks however these have since been developed using more accurate learning algoirthms. Neural networks are also of particular use because of their capability of being able to continually learn as new information is fed into the network. In this research new data is introduced using both fixed and sliding window approaches for training each of the networks. Futhermore, Genetic Programming Algorithms are also highly regarded in the financial industry and have been increasingly applied as an optimisation technique. Therefore, each of the non-linear models are supported by existing research and as a result these methodologies have become practical tools for optimising existing models and predicting future movements in financial assets. In the absence of computational algorithms to rationalise large amounts of data, investors are confronted with a difficult and seemingly impossible task of trying to comprehend large datasets of information. Nevertheless, advancements in computing technology have enabled market participants to benefit from the use of neural networks (NN) and genetic programming (GP) algorithms in order to optimise and identify patterns and trends between explanatory variables and target outputs. This is of particular importance in the agricultural market such as grains, precious metals and other commodities are informationally rich with large amounts of data being readily available to evaluate. Among the first to use neural networks for financial analysis were Rumelhart and McClelland (1986), Lippman (1987), and Medsker et al. (1993). More recently, neural networks and genetic programming algorithms have been extensively applied to the foreign exchange market (Hornik et al., 1989; Lawrenz and Westerhoff, 2003), for credit analysis (Tam and Kiang, 1992), volatility forecasting (Ormoneit and Neuneier, 1996; Donaldson and Kamstra, 1997), option pricing, (Hutchinson et al.,1994), portfolio optimisation (Chang et al., 2000; Lin et al., 2001), to both developed (Swales and Yoon, 1992) and emerging (Kimoto et al., 1990) stock markets, and for optimisation of technical trading rules (Tsai et al.,1999; Neely et al., 2003). The application of non-linear methodologies to futures contracts and inparticular, commodity spread trading, is limited. Trippi and DeSieno (1992) and Kaastra and Boyd (1995), however were among the first to explore and apply neural networks to forecast futures markets. Financial markets and assets are influenced by an array of factors including but not limited to; human behaviour, economic variables, and many other systematic and non-systematic factors . As a result, many academics and practioners have devised numerous approaches and models to explain financial time series such as fundamental analysis, technical analysis and behavioural finance. The purpose of this research however is to identify, forecast and trade daily changes in commodity spreads using a combination of novel nonlinear modeling techniques and performance enhancing trading filters. During the research process, non-linear models such as neural networks and genetic algorithms are used to identify trends in complex and expansive commodity datasets. Each of the methodologies are used to produce predictions for future time periods. In this research forecasts for t+1 horizons are examined. Progressively, each chapter presents an evolution of research in the area of non-linear forecasting to address inefficiencies associated with more traditional neural architectures. In total a collection of five non-linear methodologies are proposed and analysed to trade commodity ‘spreads’. These non-linear methodologies are benchmarked against linear models which include Naïve strategies, Moving Average Convergence Divergence (MACD) strategies, buy and hold strategies, Autoregressive Moving Average (ARMA) models, and Cointegration models. In the final chapter of the research a mixed model approach is employed to include linear outputs from benchmark models as inputs during the training of each neural network. The research includes various adaptations of existing non-linear methodologies such as neural networks and genetic programming. Through historical data input, each non-linear methodology is trained to construct ‘optimal’ trading models. Models are selected to trade commodity spreads using data from Exchange Traded Funds (ETFs) and Futures contracts. In all cases the reader is presented with results from both unfiltered and filtered trading simulations. The aim of this thesis is to benefit both hedgers and speculators who are interested in applying non-linear methodologies to the task of forecasting changes in commodity spreads. By allowing market participants to input numerous explanatory variables, non-linear methodologies such as neural networks and genetic programming algorithms can become a valuable tool for predicting changes in commodity spreads. Empirical evidence reveals that non-linear methodologies are statistically superior compared to existing linear models and they also produce higher risk adjusted returns. Moreover, by including output from linear models in the input dataset to train non-linear models, market participants are also able benefit from a ‘synergy’ of information using a ‘mixed model’ approach. In order to improve trading results the research also offers examples of numerous trading filters which can also be of use to hedgers and speculators. On the whole the research contributes a wealth of knowledge to academic studies as it offers conclusive evidence to support the widespread integration and use of non-linear modelling in the form of artificial intelligence. Empirical results are evaluated by statistical measures as well as financial performance measures which are widely used by financial institutions.

This study examines foreign market re-entry after exit, demonstrating with empirical evidence that exit is not an irreversible, win or lose process characterised by location and asset specificity. Organisations repeatedly attempt to return to once failed internationalisation projects. Drawing upon insights from organisational learning and institutional perspectives, this study examines the changes (if any) in commitment mode between exit and re-entry, the timing of re-entry, and whether developed and emerging market re-entrants differ in their re-entry choices. The highlights of this research are as follows; 1) for some re-entrants, re-entry carries with it learning inertia in that (both developed and emerging market) firms tend to re-enter via the same commitment modes in which they were operating prior to exit irrespective of prior knowledge and experience accumulated over time; 2) favourable host institutional changes, in turn, lead to commitment escalation; 3) early re-entries are motivated by the quality of host institutional environments, the choice to imitate the behaviour of other foreign (re)entrants to gain legitimacy, and the re-entrant’s strategic intent; and 4) how firms interpret exit plays a key role in their re-entry commitment and timing decisions, together with institutional pressures for legitimacy. Contrary to prior studies on de novo foreign market entry, this study proposes that it is not just the experience accumulated over time that influences the effectiveness and applicability of organisational learning. For re-entrants, prior experience does not necessarily lead to learning and more relevant tend to be institutional changes and pressures for legitimacy, how re-entrants interpret the market exit process and the re-entrant’s strategic objectives concerning the previously abandoned market. From a practitioner’s viewpoint, there may be significant consequences of not being able to transform prior knowledge and experience into learning and routines in the short term, and subsequently, leverage the lessons learned when making re-entry decisions.

The Caribbean’s creative industries have contributed significantly to the global creative economy having crafted numerous musical genres, birthed countless Nobel laureates and award winning artists, as well as creating the blueprint for the many Caribbean festivals that take place worldwide. Still, despite its successes, the region has yet to realise its full potential. This thesis argues that brand plays a critical and strategic role in cultural production, distribution and consumption, and that it can ultimately further the development of the Caribbean’s creative economy. Focusing on three of the region’s core creative industries – music, festivals and fashion – the thesis uses data gathered from qualitative interviews and document analysis in order to gain a deeper understanding of 'brand', its uses and its influence within the regional economy. The thesis explores the dominant definitions of brand, the process of brand building, the role of the 'metabrand', as well as various themes intrinsic to these, including creativity, value and authenticity. This thesis also explores the concept of Brand Caribbean, by first defining its core features and then examining its relationship with national brands and cultural identities. The thesis also examines the region’s current role within the global creative marketplace, as well as the challenges that currently impede its growth. This newfound understanding of both brand and Brand Caribbean offers a new sociocultural framework within which to evaluate the regional creative economy, and also presents new avenues for the region to negotiate a stronger position within the global market.

A vast number of new products are launched on to the market every year, 80-90% of which are destined to fail. The aim of the current study was to identify the group of people i.e. market initiators who would be the first to buy a new product. The new product in the current study was polyunsaturated fatty acid (PUFA) fed fish, a healthy food. Previous research has found attitude to determine purchase of food products (Shepherd and Farleigh 1986). Other research has found involvement and cognitive style to interact to predict the purchase of new foods (Foxall and Haskins 1986, 1987, Foxall and Bhate 1993). The current study entailed using a measure of attitude to fish, involvement in healthy eating and cognitive style to ascertain the characteristics of market initiators of PUFA fish purchasers. Attitude to fish significantly influenced PUFA fish, premium price PUFA fish, PUFA salmon, PUFA eel and PUFA sturgeon purchase. Involvement in healthy eating significantly influenced PUFA fish and premium price PUFA fish purchase. Cognitive style as expected did not influence the purchase of PUFA fish or premium price PUFA fish. Cognitive style and involvement did not interact to influence the purchase of any PUFA fish. The information obtained was used to develop a marketing plan.