Magister Commercii - MCom / The humble Pong arcade game at the corner store ignited a fundamental culture shift in the 1970s and it is increasingly gaining momentum. A generation of gamers is already permeating organisations. The socio-cultural phenomenon of digital gaming has become pervasive. The intersection point of the three trends, Ubiquitous Computing, Ubiquitous Gaming and Social Networking, is the focus point of this study. It is at this intersection point that both social online gaming and cutting-edge leadership competencies co-exist and have the potential to flourish when implemented with caution and circumspection. Leadership is frequently touted as an almost mystical holy grail in modern business. Leadership :pevelopment is therefore often recognised as a critical pivot for business success. If business leaders can successfully utilise game-based learning to maximise their return on investment in Leadership Development initiatives, this may not only increase business metrics, but also enable business leaders to leave a lasting legacy by sculpting new generations of leaders who are ready and able to face the future. Social Online Simulation Gaming (SOSG) as a learning design and learning technology can prove particularly valuable as a leadership and skills development tool within the "digimodem" world. Current literature, however, does not provide a clearly focused framework for the implementation of ICT supported game-based Leadership Development technologies within the information economy. Current literature fails to integrate and take into account aspects critical to the successful utilisation of SOSG, such as the principles of "Flow Design", the often "Puppet Master" role and the interrelatedness, even interdependence, of the required utilisation competencies There is currently not a clear and specific framework for evaluating the Information and Communication Technology (ICT) competencies, knowledge, skills and attitudes required to successfully use Socia1 ·bnline Simulation Games software within the context of Organisational Leaden;hip Development. This study aimed to create and refine a framework for evaluating the ICT competencies required to successfully implement SOSG as Leadership Development tool.

The Macroscopic Fundamental Diagram (MFD) describes the relation of average network flow, density and speed in urban networks. It can be estimated based on empirical or simulation data, or approximated analytically. Two main analytical approximation methods to derive the MFD for arterial roads and urban networks exist at the moment. These are the method of cuts (MoC) and related approaches, as well as the stochastic approximation (SA). This paper systematically evaluates these methods including their most recent advancements for the case of an urban arterial MFD. Both approaches are evaluated based on a traffic data set for a segment of an arterial in the city of Munich, Germany. This data set includes loop detector and signal data for a typical working day. It is found that the deterministic MoC finds a more accurate upper bound for the MFD for the studied case. The estimation error of the stochastic method is about three times higher than the one of the deterministic method. However, the SA outperforms the MoC in approximating the free-flow branch of the MFD. The analysis of the discrepancies between the empirical and the analytical MFDs includes an investigation of the measurement bias and an in-depth sensitivity study of signal control and public transport operation related input parameters. This study is conducted as a Monte-Carlo-Simulation based on a Latin Hypercube sampling. Interestingly, it is found that applying the MoC for a high number of feasible green-to-cycle ratios predicts the empirical MFD well. Overall, it is concluded that the availability of signal data can improve the analytical approximation of the MFD even for a highly inhomogeneous arterial.

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To stay competitive in today's market, organizations focus on efficiency to reduce costs. Since there are still processes that are manually handled, there is a risk of affecting workers health during streamlining. Volvo CE Braås are currently working with a takt time of 35 minutes throughout their facility. They are looking to implement a takt flow system on their Pallet breakdown disassembly line to unify the systems within the company. The current situation of the pallet breakdown consists of variation, ergonomic issues, inconsistencies, disturbances and lay-out problems. Main problems have remained unidentified. The goal of the thesis has been to determine how optimization as well as, takt time implementation affects the workers. The aim of the thesis has been to analyze their current situation, present relevant changes to be made and to improve the ergonomics of the employees. Methods such as flow mapping, surveys, gemba walks and interviews have contributed to a basis of understanding. The methods have, together with selected theory, contributed to important knowledge and understanding of the disassembly system, that has led to conclusions and recommendations regarding the impact of optimization and takt time implementation on ergonomics. By using ergonomic guidelines together with discrete event simulation, an identification of human factors when optimizing has been detected. For Volvo CE to successfully implement takt time, several optimizations are needed together with relevant investments to ensure that the ergonomic values are kept on an appropriate level when the frequency of tasks increases. As a conclusion, to optimize a system which has a direct impact on the employees, there is a need to investigate the ergonomic values of today together with values after optimization. Optimization can not occur without investing in tools.

Most of the existing bicycle flow traffic research is limited to characterizing the longitudinal motion of bicyclists based on the assumption that there is no significant differences between the dynamics of a single-file bicycle traffic and the longitudinal motion behavior of cars. This research reparametrizes an existing car-following model to describe bicycle-following and motion behavior. Furthermore, the lack of naturalistic data has limited the validation of this model. This research aims at developing a descriptive model that is capable of capturing the inherent non-lane-based traffic behavior characteristics of bicycle traffic and provides a methodology for extracting naturalistic cycling data from video feeds for use in safety and mobility applications. In this study, The Fadhloun-Rakha (FR) bicycle-following longitudinal motion model was extended through complementing it with a lateral motion strategy; thus allowing for overtaking maneuvers and lateral bicycle movements. For the most part, the following strategy of the FR model remains valid for modeling the longitudinal motion of bicycles except for the activation conditions of the collision avoidance strategy which are modified in order to allow for overtaking when possible. The proposed methodology is innovative in that it makes use of the intersection of certain pre-defined regions around the bicycles to decide on the feasibility of angular motion along with its direction and magnitude. The resulting model is the first point-mass dynamics-based model for the description of the longitudinal and lateral behavior of bicycles in both constrained and unconstrained conditions, and it is the only existing model that is sensitive to the bicyclist physical characteristics and the bicycle and roadway surface conditions given that the used longitudinal logic was previously validated against experimental cycling data. In relation to the development of the naturalistic cycling dataset, the used videos come from a dataset collected in a previous Virginia Tech Transportation Institute study in collaboration with SPIN in which continuous video data at a non-signalized intersection on the Virginia Tech campus was recorded. The research applied computer vision and machine learning techniques to develop a comprehensive framework for the extraction of naturalistic cycling trajectories. In total, this study resulted in the collection and classification of 619 bicycle trajectories based on their type of interactions with other road users. The results confirm the success of the proposed methodology in relation to extracting the locations, speeds, and accelerations of the bicycles with a high precision level. Furthermore, preliminary insights into the acceleration and speed behavior of bicyclists around motorists are determined. / Master of Science / The behavior of bicycle traffic differs from the that of cars. Bicycle traffic flow dynamics is unconstrained in lateral motion and overtaking when compared to car traffic flow. Based on this inherent behavior, existing car-following can only model the longitudinal motion of the bicycle flow traffic and it does not describe the non-lane base traffic that characterizes bicycle traffic dynamics. Furthermore, the existing experimental controlled dataset used for validating bicycle traffic flow models does not capture the naturalistic behavior of cyclists. Therefore, this research aims to develop a descriptive model that is capable of capturing the inherent non-lane-based traffic behavior characteristics of bicycle traffic and provides a methodology for extracting a naturalistic cycling data from a video dataset for use in safety and mobility applications. In this study, the Fadhloun-Rakha (FR) bicycle-following longitudinal motion model was extended through complementing it with a lateral motion strategy; thus allowing for overtaking maneuvers and lateral bicycle movements. For the most part, the following strategy of the FR model remains valid for modeling the longitudinal motion of bicycles except for the activation conditions of the collision avoidance strategy which are modified in order to allow for overtaking when possible. The proposed methodology is innovative in that it makes use of the intersection of certain pre-defined regions around the bicycles to decide on the feasibility of angular motion along with its direction and magnitude. The resulting model is the first point-mass dynamics-based model for the description of the longitudinal and lateral behavior of bicycles in both constrained and unconstrained conditions, and it is the only existing model that is sensitive to the bicyclist physical characteristics and the bicycle and roadway surface conditions given that the used longitudinal logic was previously validated against experimental cycling data. In relation to the development of the naturalistic cycling dataset, the used videos come from a dataset collected in a previous Virginia Tech Transportation Institute study in collaboration with SPIN in which continuous video data at a non-signalized intersection on the Virginia Tech campus was recorded. The research applied computer vision and machine learning techniques to develop a comprehensive framework for the extraction of naturalistic cycling trajectories. In total, this study resulted in the collection and classification of 619 bicycle trajectories based on their type of interactions with other road users. The results confirm the success of the proposed methodology in relation to extracting the locations, speeds, and accelerations of the bicycles with a high precision level. Furthermore, preliminary insights into the acceleration and speed behavior of bicyclists around motorists are determined.

The level of learner engagement, performance, self-efficacy, and enjoyment on a knot-tying task by college students who received positive verbal and non-verbal learning-oriented feedback by trained facilitators was examined. Secondary learner outcomes were learner perception of engagement and learner perception of facilitator support. Facilitator variables were attitude and competency. Changes in facilitators" attitudes toward (1) flow theory (Csikszentmihalyi, 1997), (2) systematic feedback (Ilgen, Fisher, & Taylor, 1979; Liden & Mitchell, 1985; Locke & Latham, 1985), and (3) hands-on learning (Joplin, 1995; Kolb, 1984; Pfieffer & Jones, 1985; Williamson, 1995) were examined. Facilitators" competence in (1) delivering learning-oriented feedback, (2) using verbal learning-oriented feedback to increase learner engagement, and (3) using nonverbal learning-oriented feedback to increase learner engagement was measured. One hundred twenty-six college students from an introductory human development class were randomly selected and randomly assigned to one of three treatment groups as facilitators, learners, or timekeepers for a knot-tying task. Twelve psychology majors, members of an independent study group in the same class, were trained as observers and randomly assigned to one of the three treatment groups. The treatment was the administration of learning-oriented feedback by trained facilitators during a knot-tying task. The primary findings were that learning-oriented feedback provided by trained facilitators increased learner engagement, learner self-efficacy, learner task enjoyment, learner perception of facilitator support, and learner perception of personal engagement in the task. Learner performance was not affected by the administration of learning oriented feedback. Facilitators showed significant change in their attitude toward flow theory, systematic feedback, and hands-on learning. It can be concluded that facilitators who received training in learning-oriented feedback had a greater effect on the affective side of learning (engagement, self-efficacy, enjoyment) than those who did not receive training. However, the training of facilitators in the use of learning-oriented feedback had no effect on learner performance. Further, teaching a task using facilitated verbal and nonverbal cues positively affects how facilitators feel about flow theory, hands-on learning, and feedback. Further research to verify effects of learning-oriented feedback on learner engagement using other tasks is suggested. Additional research to examine the attitudes of facilitators is suggested. / Ph. D.

Ocean wave energy is a promising renewable source to contribute to supplying the world’s energy demand. The Division of Electricity at Uppsala University is developing a technology to capture energy from ocean waves with a wave energy converter (WEC) consisting of a linear permanent magnet generator and a point absorber. The linear generator is placed on sea bed and is driven directly by the floating absorber. Since March 2006, multiple wave energy converters have been deployed on the Swedish west coast outside the town of Lysekil. The technology is verified by long-term operation during at sea and satisfactory reliability of the electricity generation. This thesis focuses on developing advanced control strategies for fully coupled wave energy converters subject to constraints. A nonlinear control strategy is studied in detail for a single WEC subject to constraints under regular and irregular waves. Besides, two coordinated control strategies are developed to investigate the performance of a wave energy farm subject to constraints. The performance of the WECs using these control strategies are investigated in case studies, and optimal PTO damping coefficients are found to maximize the output power. The results show that these control strategies can significantly improve the performance of the WECs, in terms of mean power, compared to a conventional control. Besides these control strategies, a wave-to-wire simulation platform is built to study the power generation control of the WEC subject to constraints.  The wave-to-wire simulation platform allows both nonlinear and linear control force. The results show that there is a good agreement between the desired value and the actual value after advanced control.

Les ordinateurs peuvent-ils enseigner ? Pour répondre à cette question, la recherche dans les Systèmes Tuteurs Intelligents est en pleine expansion parmi la communauté travaillant sur les Technologies de l'Information et de la Communication pour l'Enseignement (TICE). C'est un domaine qui rassemble différentes problématiques et réunit des chercheurs venant de domaines variés, tels que la psychologie, la didactique, les neurosciences et, plus particulièrement, le machine learning. Les technologies numériques deviennent de plus en plus présentes dans la vie quotidienne avec le développement des tablettes et des smartphones. Il semble naturel d'utiliser ces technologies dans un but éducatif. Cela amène de nombreuses problématiques, telles que comment faire des interfaces accessibles à tous, comment rendre des contenus pédagogiques motivants ou encore comment personnaliser les activités afin d'adapter le contenu à chacun. Au cours de cette thèse, nous avons développé des méthodes, regroupées dans un framework nommé HMABITS, afin d'adapter des séquences d'activités pédagogiques en fonction des performances et des préférences des apprenants, dans le but de maximiser leur vitesse d'apprentissage et leur motivation. Ces méthodes utilisent des modèles computationnels de motivation intrinsèque pour identifier les activités offrant les plus grands progrès d'apprentissage, et utilisent des algorithmes de Bandits Multi-Bras pour gérer le compromis exploration/exploitation à l'intérieur de l'espace d'activité. Les activités présentant un intérêt optimal sont ainsi privilégiées afin de maintenir l'apprenant dans un état de Flow ou dans sa Zone de Développement Proximal. De plus, certaines de nos méthodes permettent à l'apprenant de faire des choix sur des caractéristiques contextuelles ou le contenu pédagogique de l'application, ce qui est un vecteur d'autodétermination et de motivation. Afin d'évaluer l'efficacité et la pertinence de nos algorithmes, nous avons mené plusieurs types d'expérimentation. Nos méthodes ont d'abord été testées en simulation afin d'évaluer leur fonctionnement avant de les utiliser dans d'actuelles applications d'apprentissage. Pour ce faire, nous avons développé différents modèles d'apprenants, afin de pouvoir éprouver nos méthodes selon différentes approches, un modèle d'apprenant virtuel ne reflétant jamais le comportement d'un apprenant réel. Les résultats des simulations montrent que le framework HMABITS permet d'obtenir des résultats d'apprentissage comparables et, dans certains cas, meilleurs qu'une solution optimale ou qu'une séquence experte. Nous avons ensuite développé notre propre scénario pédagogique et notre propre serious game afin de tester nos algorithmes en situation réelle avec de vrais élèves. Nous avons donc développé un jeu sur la thématique de la décomposition des nombres, au travers de la manipulation de la monnaie, pour les enfants de 6 à 8 ans. Nous avons ensuite travaillé avec le rectorat et différentes écoles de l'académie de bordeaux. Sur l'ensemble des expérimentations, environ 1000 élèves ont travaillé sur l'application sur tablette. Les résultats des études en situation réelle montrent que le framework HMABITS permet aux élèves d'accéder à des activités plus diverses et plus difficiles, d'avoir un meilleure apprentissage et d'être plus motivés qu'avec une séquence experte. Les résultats montrent même que ces effets sont encore plus marqués lorsque les élèves ont la possibilité de faire des choix. / Can computers teach people? To answer this question, Intelligent Tutoring Systems are a rapidly expanding field of research among the Information and Communication Technologies for the Education community. This subject brings together different issues and researchers from various fields, such as psychology, didactics, neurosciences and, particularly, machine learning. Digital technologies are becoming more and more a part of everyday life with the development of tablets and smartphones. It seems natural to consider using these technologies for educational purposes. This raises several questions, such as how to make user interfaces accessible to everyone, how to make educational content motivating and how to customize it to individual learners. In this PhD, we developed methods, grouped in the aptly-named HMABITS framework, to adapt pedagogical activity sequences based on learners' performances and preferences to maximize their learning speed and motivation. These methods use computational models of intrinsic motivation and curiosity-driven learning to identify the activities providing the highest learning progress and use Multi-Armed Bandit algorithms to manage the exploration/exploitation trade-off inside the activity space. Activities of optimal interest are thus privileged with the target to keep the learner in a state of Flow or in his or her Zone of Proximal Development. Moreover, some of our methods allow the student to make choices about contextual features or pedagogical content, which is a vector of self-determination and motivation. To evaluate the effectiveness and relevance of our algorithms, we carried out several types of experiments. We first evaluated these methods with numerical simulations before applying them to real teaching conditions. To do this, we developed multiple models of learners, since a single model never exactly replicates the behavior of a real learner. The simulation results show the HMABITS framework achieves comparable, and in some cases better, learning results than an optimal solution or an expert sequence. We then developed our own pedagogical scenario and serious game to test our algorithms in classrooms with real students. We developed a game on the theme of number decomposition, through the manipulation of money, for children aged 6 to 8. We then worked with the educational institutions and several schools in the Bordeaux school district. Overall, about 1000 students participated in trial lessons using the tablet application. The results of the real-world studies show that the HMABITS framework allows the students to do more diverse and difficult activities, to achieve better learning and to be more motivated than with an Expert Sequence. The results show that this effect is even greater when the students have the possibility to make choices.

This thesis investigates the determinants of UK corporate cash holdings between 1980 and 2012. The global and long term phenomenon of corporate cash pilling has drawn significant attention from researchers. Similarly, this study aims at shedding light on the empirical relationship between cash holding and specific firm characteristics. Our preliminary research incorporates a comprehensive literature review. Towards this end, the relevant financial theory is presented and the previous empirical studies are highlighted. Afterwards, the expected results of our research are synthesized into a set of distinct hypotheses and tested with regression analysis. The empirical findings suggest that cash holdings are positively related to investment opportunity, as R&D and market to book ratio. Cash ratio is also positively related to industry cash flow volatility and negatively affected by cash flow, net working capital, capital expenditures, leverage, tax expenses, age and size. Regarding the development of the determinants of cash holdings, the study indicates that three major variables influenced cash holdings over the years of analysis. In particular, leverage, tax regime and capital expenditures significantly affect the corporate liquidity in UK market. Furthermore, the results suggest that cash holdings are mostly defined by trade off theory. Indeed, our findings offer stimulating insights on the factors that determine the firms’ cash holdings during the past three decades. These findings may be beneficial for financial managers, investors and consultants. / Στην παρούσα διατριβή εξετάζονται οι προσδιοριστικοί παράγοντες του δείκτη μετρητών σε επιχειρήσεις του Ηνωμένου Βασιλείου μεταξύ των ετών 1980 και 2012. Η διακράτηση μετρητών αποτελεί παγκόσμιο φαινόμενο και λαμβάνει της ανάλογης προσοχής από πληθώρα ερευνητών. Σε αυτή τη βάση, η μελέτη αυτή έχει ως στόχο να ρίξει φως σχετικά με την εμπειρική σχέση μεταξύ του δείκτη μετρητών και τα συγκεκριμένα χαρακτηριστικά που επηρεάζουν την ρευστότητα στις επιχειρήσεις διαχρονικά. Αρχικά η έρευνα ενσωματώνει μια βιβλιογραφική ανασκόπηση. Προς το σκοπό αυτό, οι σχετικές οικονομικές θεωρίες και οι προηγούμενες εμπειρικές μελέτες παρουσιάζονται. Στη συνέχεια, τα αναμενόμενα αποτελέσματα της έρευνας συντίθενται σε ένα σύνολο διακριτών υποθέσεων και δοκιμάζονται με ανάλυση παλινδρόμησης. Τα εμπειρικά ευρήματα υποδηλώνουν ότι ο δείκτης μετρητών σχετίζεται θετικά με τις επενδυτικές ευκαιρίες, τις δαπάνες Ε&Α και τον λόγο της αγοραίας προς τη λογιστική αξία των βιβλίων της επιχείρησης. Ο δείκτης μετρητών επίσης, σχετίζεται θετικά με την μεταβλητότητα των ταμειακών ροών του κλάδου και επηρεάζεται αρνητικά από τις ταμειακές ροές, το καθαρό κεφάλαιο κίνησης, τις κεφαλαιακές δαπάνες, την μόχλευση, τα φορολογικά έξοδα, την ηλικία και το μέγεθος των επιχειρήσεων. Όσον αφορά την εξέλιξη των προσδιοριστικών παραγόντων των ταμειακών ρευστών διαθεσίμων, η μελέτη δείχνει ότι τρεις είναι οι κύριες μεταβλητές που επηρεάζουν τη διακράτηση μετρητών κατά τη διάρκεια των χρόνων της ανάλυσης. Ειδικότερα, η μόχλευση, το φορολογικό καθεστώς και τις κεφαλαιακές δαπάνες επηρεάΖουν σημαντικά την απόφαση για εταιρική ρευστότητα στην αγορά του Ηνωμένου Βασιλείου. Επιπλέον, τα αποτελέσματα δείχνουν ότι η διακράτηση μετρητών ακολουθεί κυρίως την trade off θεωρία. Πράγματι, τα ευρήματά προσφέρουν χρήσιμες γνώσεις σχετικά με τους παράγοντες που καθορίζουν τη διακράτηση μετρητών των επιχειρήσεων κατά τη διάρκεια των τριών τελευταίων δεκαετιών. Τα ευρήματα αυτά μπορεί να είναι επωφελή για οικονομολόγους, επενδυτές και συμβούλους.

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No. of bitstreams: 1 arquivototal.pdf: 1608246 bytes, checksum: d413321e8f56ef27fe1d4c30fb99ae01 (MD5) Previous issue date: 2015-08-25 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Work teams are seen as flexible structures for collective work organization, with superior ability to improve organizational performance when compared to traditional hierarchical structures. Work teams in information technology (IT) can be perceived as high-performance drives, dynamic and productive, especially important in times of organizational change or leading complex and critics organizational (re)designs. Specifically in the software development field (an IT specialization) these teams performance is a measure of quality, functionality/applicability and reliability of IT artifacts, as their main outcomes. It is also expected that software development teams could be self-managed, so that the main concerns relating to the composition, internal processes, tasks, and performance are of intrinsic nature. This document reports the course of actions for building issues for the thesis demonstration, one that establishes that teams working with intrinsic motivations have better performance than teams that rely solely on extrinsic motivations or controls. Drawing on flow theory (Csikszentmihalyi, 1990) as a theoretical guidance for explanation of intrinsic motivation, antecedents and consequents of flow on work teams were identified and an instrument was developed for flow measurement in work teams, specifically on IT teams, with also a model proposition for the measurement of flow influence on IT teams performance. Discussions on the findings suggest (1) theoretical implications, especially compilation of empirical evidence linking flow, antecedents and consequences, as a complement and update for classic studies of the same nature, and instrument offering focused on collective perceptions and developed specifically for flow measurement on IT work teams; and (2) practical implications, highlighting the perception of interest in the matter by the practitioners (managers and developers) and rationale offered to subsidize maintaining positive vibe in teams as a way for turnover reduction and widening the appeal to new members, for instance. / Equipes de trabalho podem ser definidas como estruturas flexíveis de organização do trabalho coletivo, com capacidade superior de contribuição para o desempenho organizacional quando comparadas a estruturas hierárquicas tradicionais. Equipes de trabalho em tecnologia da informação (TI) podem ser percebidas como unidades de elevado desempenho, dinâmicas e produtivas, especialmente importantes em tempos de mudança organizacional ou em liderança de projetos organizacionais complexos e críticos. Especificamente em desenvolvimento de software (uma especialidade dos estudos em TI), o desempenho dessas equipes é medido por meio de parâmetros relacionados à qualidade, funcionalidade/aplicabilidade e confiabilidade dos artefatos gerados. Espera-se, ainda, que equipes de desenvolvimento de software sejam autogerenciadas, de modo que as principais preocupações relativas à composição, processos, tarefas e desempenho sejam de natureza intrínseca. O presente documento reporta o percurso de elaboração e provimento de recursos de demonstração da tese de doutoramento que estabelece que equipes que trabalham com motivações intrínsecas apresentam melhor desempenho que equipes que dependem exclusivamente de motivações ou controles extrínsecos. Adotando-se flow (Csikszentmihalyi, 1990) como orientação teórica para explicação de motivação intrínseca, identificaram-se antecedentes que levam ao estado de flow em equipe, e consequentes desse estado, especificamente em equipes de trabalho; e elaborou-se instrumento de mensuração do estado de flow em equipes de trabalho, especificamente em equipes de TI, com proposição de modelo de mensuração da influência de flow sobre o desempenho de equipes de TI. Discussões sobre os resultados sugerem (1) implicações teóricas, especialmente compilação de evidências empíricas relacionando flow, antecedentes e consequentes, e oferta de instrumento focado em percepções coletivas e desenvolvido especificamente para mensuração de flow em equipes de trabalho em TI; e (2) implicações práticas, com destaque para a oferta de base conceitual que subsidie a manutenção de vibração positiva nas equipes como forma de redução de rotatividade (turnover) e ampliação da atração a novos profissionais.