Applied Game Theory has been criticised for not being able to model real decision making situations. A game's sensitive nature and the difficultly in determining the utility payoff functions make it hard for a decision maker to rely upon any game theoretic results. Therefore the models tend to be simple due to the complexity of solving them (i.e. finding the equilibrium). In recent years, due to the increases of computing power, different computer modelling techniques have been applied in Game Theory. A major example is Artificial Intelligence methods e.g. Genetic Algorithms, Neural Networks and Reinforcement Learning (RL). These techniques allow the modeller to incorporate Game Theory within their models (or simulation) without necessarily knowing the optimal solution. After a warm up period of repeated episodes is run, the model learns to play the game well (though not necessarily optimally). This is a form of simulation-optimization. The objective of the research is to investigate the practical usage of RL within a simple sequential stochastic airline seat pricing game. Different forms of RL are considered and compared to the optimal policy, which is found using standard dynamic programming techniques. The airline game and RL methods displays various interesting phenomena, which are also discussed. For completeness, convergence proofs for the RL algorithms were constructed.

This thesis considers the scheduling of aircraft landing and take-off problems on a single runway where aircraft must respect various operational constraints. The aim is to introduce generic models and solution approaches that can be implemented in practice. Existing solution methods and techniques of airport runway optimization have been reviewed. Several solution methods such as mixed integer programming, dynamic programming, iterated descent local search and simulated annealing are proposed for the scheduling of aircraft landings in the static and dynamic environment. A multi-objective formulation is used for taking into account runway throughput, earliness and lateness, and the cost of fuel arising from aircraft manoeuvres and additional flight time incurred to achieve the landing schedule. Moreover, computational results are presented using real data from Heathrow airport as well as randomly generated problem instances which are generated based on characteristics of the real data. Later, dynamic programming, descent local search and beam search algorithms are proposed for the scheduling of aircraft take-offs in the departure holding area. Scheduling aircraft take-off is formulated as a hierarchical multi-objective problem which includes maximizing departure runway throughput and minimizing total waiting time in the holding area. Performance of the algorithms have been evaluated for three common layouts of holding area. Computational results are presented on randomly generated test data.

Buses, the main form of public transport in many urban areas, are considered as an efficient and environmentally friendly transport mode because of their high passenger capacity. The concept of bus priority was originally proposed to protect buses from urban traffic congestion so that buses can be perceived as a faster mode than private cars. One such measure which is expanding in extent and sophistication is bus priority at traffic signals – or Bus Signal Priority (BSP) Strategies. The previous research on BSP has mostly focused on its effectiveness on improving bus efficiency and bus regularity/punctuality, as well as the impacts on general traffic. However the potential environmental impacts that could be caused by BSP have not been studied, particularly on emissions - despite this being an increasingly important criterion in transport assessments. For bus priority implementations this could be particularly important, if the small disbenefits to a large number of the nonpriority vehicles outweigh the benefits to buses. This lack of knowledge and potential concern has been the main motivation for this research. The thesis sets out a comprehensive review on the state-of-the-art BSP systems and evaluation approaches. It revealed that microscopic traffic simulation models are the most appropriate approach for this study with the ability to model different BSP strategies in various user-defined scenarios. The Aimsun model was selected after review and comparison. From the review on the measurement and modelling approaches for transport related emissions, instantaneous emission models were found to be able to estimate emission behaviour by relating emission rates to vehicle operation during a series of short time intervals (often one second) and for a small scale. This was required by this study as at junction areas emissions could be dominated by vehicle operational modes where the traditionally ‘average speed’ models were unable to accurately capture the emission variations. The dynamic and individual-oriented features of microsimulation models and instantaneous emission models enabled their integration at various spatial and temporal levels and at different levels of vehicle aggregation. After calibration and validation to some critical parameters in Aimsun, a signalised junction under VA control was set up, and two BSP strategies were modelled, - one including green extension and early green recall facilities and the other one including additional compensation and inhibition facilities. These strategies were applied to 18 typical scenarios, involving variables of ‘degree of saturation’, traffic flows and bus flows. The results illustrated the importance of strategy optimising in the more challenging conditions of junctions operating under high degrees of saturation and /or high bus flows. The worst-case scenario was in heavy traffic conditions with high bus flows and BSP on the minor road only, when emissions could increase by about 10%. Under a free flow condition implementing BSP on the main road is an environmentally friendly measure with emissions reductions of up to 6%.The thesis also describes a method to value emissions in monetary terms, so that operational and emissions impacts can be compared in common units. Application of this method indicated that the impact of emissions is much smaller than that for delay/journey time impacts, though some under-estimation in emissions valuation is suspected.

The World Wide Web has developed into an important platform for social interactions with the rise of social networking applications of dierent kinds. Collaborative tagging systems, as prominent examples of these applications, allow users to share their resources and to interact with each other. By assigning tags to resources on the Web in a collaborative manner, users contribute to the emergence of complex networks now commonly known as folksonomies, in which users, documents and tags are interconnected with each other. To reveal the implicit semantics of entities involved in a folksonomy, one requires an understanding of the characteristics of the collective behaviours that create these interconnections. This thesis studies how user behaviours in collaborative tagging systems can be analysed to acquire a better understanding of the collective semantics of entities in folksonomies. We approach this problem from three different but closely related perspectives. Firstly, we study how tags are used by users and how their different intended meanings can be identified. Secondly, we develop a method for assessing the expertise of users and quality of documents in folksonomies by introducing the notion of implicit endorsement. Finally, we study the relations between documents induced from collaborative tagging and compare them with existing hyperlinks between Web documents. We show that, in each of these scenarios, it is crucial to consider the collective behaviours of the users and the social contexts in order to understand the characteristics of the entities. This project can be considered as a case study of the Social Web, the research outcomes of which can be easily generalised to many other social networking applications. It also fits into the larger framework for understanding the Web set out by the emerging interdisciplinary field of Web Science, as the work involves analyses of the interactions and behaviour of Web users in order to understand how we can improve existing systems and facilitate information sharing and retrieval on the Web.

Nowadays, transforming the railway industry for better performance and making the best usage of the current capacity are the key issues in many countries. Operational research methods and in particular scheduling techniques have a substantial potential to offer algorithmic solutions to improve railway operation and control. This thesis looks at train scheduling and rescheduling problems in a microscopic level with regard to the track topology. All of the timetable components are fixed and we aim to minimize delay by considering a tardiness objective function and only allowing changes to the order and to the starting times of trains on blocks. Various operational and safety constraints should be considered. We have achieved further developments in the �eld including generalizations to the existing models in order to obtain a generic model that includes important additional constraints. We make use of the analogy between the train scheduling problem and job shop scheduling problem. The model is customized to the UK railway network and signaling system. Introduced solution methods are inspired by the successful results of the shifting bottleneck to solve the job shop scheduling problems. Several solution methods such as mathematical programming and different variants of the shifting bottleneck are investigated. The proposed methods are implemented on a real-world case study based on London Bridge area in the South East of the UK. It is a dense network of interconnected lines and complicated with regard to stations and junctions structure. Computational experiments show the effciency and limitations of the mathematical programming model and one variant of the proposed shifting bottleneck algorithms. This study also addresses train routing and rerouting problems in a mesoscopic level regarding relaxing some of the detailed constraints. The aim is to make the best usage of routing options in the network to minimize delay propagation. In addition to train routes, train entry times and orders on track segment are defined. Hence, the routing and scheduling decisions are combined in the solutions arising from this problem. Train routing and rerouting problems areformulated as modified job shop problems to include the main safety and operational constraints. Novel shifting bottleneck algorithms are provided to solve the problem. Computational results are reported on the same case study based on London Bridge area and the results show the efficiency of one variant of the developed shifting bottleneck algorithms in terms of solution quality and runtime.

With the emergence of web applications that enabled user-generated content and social interactions, the Web became a place where people can engage in a number of new activities. With the success of smart enabled devices people now actively share their location data through various applications. However, as this thesis reveals, location plays a primal role in linking and inferring new information about people, often without their knowledge or consent. Due to this inferential power of location data new privacy concerns arise, as the actual affordances of their data are far greater than people are even aware of. Regardless of the numerous controversies around privacy, people keep on sharing their data on the Web. However, privacy systems themselves (and the ways in which individuals express their preferences) have changed very little. This thesis argues that understanding the mechanisms that people employ in their privacy decisions can provide fundamental insight for the design of privacy systems. The main focus of this thesis is to understand the underlying reasons why people share their location and whether their disclosure behaviour is paradoxical when compared with their stated attitudes towards location sharing. The first part of this thesis involves a study comprising of an online survey that addresses these two issues. The findings provide supporting evidence that people's location sharing decisions are indeed paradoxical in comparison with their stated attitudes and that privacy decision-making can be seen as a process of structuration, in the sense that people's decisions are tempered by contextual factors (external structures). The second part comprises of a series of focus groups that act as a follow-up study and aim to explore in more detail the underlying reasons behind people's sharing decisions. The findings show that people's decisions are influenced by a number of different contextual factors, grouped together into three main categories; social capital, trust in the application and functionality. Based on the outcomes of the two studies, a conceptual model was developed, called the Isorropic Model, that points out the prominent role of context in privacy decision-making and stresses the need for more dynamic privacy systems.

The level of ownership and use of motorcycling has increased rapidly in Edinburgh and the UK in the last ten years. In this study, motorcycle driving cycles (rural and urban) were developed for Edinburgh (Edinburgh Motorcycle Driving cycle-EMDC). The analysis of EMDC demonstrates that motorcycles‘ driving behaviour differs between urban and rural areas. EMDC shows a typical transient nature of speed, acceleration and deceleration, which is also different from regulatory driving cycles (Economic Commission for Europe-ECE and World Motorcycle Test Cycle-WMTC) and examples from Asia (Taiwan, Bangkok and China). This research underlines the need for detailed investigations of driving cycles in any local condition. It is not generally feasible for a driving cycle developed in one area to be applicable in another area, even with some similar characteristics. Emission factors were also estimated using onboard, laboratory and micro simulation measurements along the test corridor (Air Quality Management Area-AQMA). Laboratory measurements were carried out by applying a number of standard driving cycles (ECE and WMTC) and the derived EMDCs. Results show that the emission factors (EFs) calculated in the laboratory for carbon monoxide (CO) and Hydrocarbons (HC) are higher for the urban EMDC cycle compared to the standard regulatory factors than they are for the rural (except Nitrogen Oxide-NOx). Laboratory emission factors for CO and HC for the urban EMDC were found to be higher than the micro-simulation and onboard methods. EFs obtained from micro-simulation and onboard emissions using the National Atmospheric Emission Inventory (NAEI) emission coefficients were not very different with the exception of NOx, which were relatively higher than those of EMDC. Micro simulation models were mainly developed for private cars and therefore special care should be taken when using them for modelling other conditions (e.g. motorcycles driving characteristics). This study illustrates the extent to which micro-simulation may be utilised to accurately model emissions and discusses the refinements required to model motorcycle motion (hence emission) accurately in micro simulation. The study provides a platform for a large number of potential future applications for the evaluation of emissions and for developing various policy scenarios of pollution reduction and reducing health impacts at local levels.

The shipping industry has undergone a period of rapid and fundamental change during the three decades since the end of the Second World War. While these changes have been experienced world-wide and have promoted the implementation of technological advances and the growth of the world fleet, they have occurred during a period which has also witnessed a substantial relative decline in Britain's maritime position. It is the aim of this study to analyse their effect on industrial relations in the U.K. shipping industry.

This thesis is concerned with two major areas: marketing communication via social media and small to medium size enterprise marketing for Kuwaiti SMEs. The researcher has been looking carefully at major social media sites such as Facebook, Twitter, Instagram and others by opening accounts and being involved in daily interactions in them. They have been observing and witnessing the great potential of social media and that led to five questions concerning social media marketing and its usefulness to SMEs in Kuwait. (i) Can SMEs market their products and services better through using social media rather than traditional media? (ii) Can SMEs reach their target customers through social media more easily than through traditional media? (iii) What are the benefits of marketing communication in social media? (iv) Can marketing communication be more effective by using social media rather than using traditional media? (v) Can Kuwait benefit from SMEs’ empowerment to improve its economy by reducing dependency on oil production? It was from these questions, the topic of this thesis was born, which is investigating the effectiveness of marketing communication through social media for SMEs in Kuwait. Primary data were collected through depth interviews from the owners/managers of Kuwaiti SMEs. Grounded theory as Strauss and Corbin was used. Five models are developed and recommendations made to improve the effectiveness of social media marketing communications for SMEs in Kuwait.

With the role of purchasing evolved from a paper pushing function to a strategic and value creating player in global businesses (Espich, 2004), the activities of purchasing professionals today are knowledge- and competence driven. The purpose of this study is to identify the competency needs of purchasing professionals at DFS Deutsche Flugsicherung GmbH (DFS), Europe’s largest Air Navigation Service Provider (ANSP). It also seeks to explore the role of implicit participant knowledge in the process of competency identification and model development. For these reasons, a mixed-method case study at DFS is conducted. After reviewing the literature, a purchasing competency model is developed from scratch through exploring the target population’s self-image on competency needs and by contrasting these results to the view of purchasing department’s internal customers and management. The so developed model is then verified through participant observations and the identification of the implicit knowledge of competency needs of purchasing professionals. The study contributes to business practice and the theory of competency modeling. It identifies competencies in an area where little is known about competency requirements and explores the need to consider implicit participant knowledge in the model development process. The research outcomes are valuable to solve a real-world problematic situation through developing an activity based, multi-perspective and future oriented competency model. The study provides an example of how the aspect of implicit knowledge can be integrated when studying competencies. Results from this case in Europe’s leading ANSP are likely to be transferrable to other companies in the industry.