Many enterprises are currently exploring the possibility of migrating some or all of their IT functionalities to public clouds with the objective of reducing their overall IT service costs or to open new business frontiers. Unfortunately, making such a decision is not a straightforward task; it requires a vigorous evaluation of the various benefits, risks and costs associated with the migration of their diverse business processes that comprise of their current IT services. Yet, this problem has received very little attention in the literature, mainly due to its interdisciplinary nature. This thesis aims at filling this gap by aiding the enterprises during the phase of making their cloud migration decision. The contributions of this work are twofold. First, a novel cloud-migration framework is introduced to guide the enterprises through a sequence of well-defined recommended analysis steps. These steps culminate with the formulation of the migration decision problem as a mathematical optimization one. The second contribution is a decision engine that efficiently solves this optimization problem. More precisely, the proposed framework gradually guides the enterprise to first identify the various business processes that are related to their IT services and then to determine the relationship and the communication needed among those processes. The identified inter-process communication represents an indicator of how tightly coupled these business processes are to each other. When outsourcing business processes, tightly coupled processes add a high communication cost and may introduce service latency if they are not co-located. As such, inter-process communication becomes an important input parameter that affects the migration decision. Enterprises can then determine to partially or completely migrate IT services to clouds. Furthermore, multiple vendors can be used for different services. However, when different vendors are involved, the communication cost between different processes increases. The objective is to maximize profit for an organization which includes lowering IT expenses in the long term without compromising data integrity or security. An optimization formula is finally constructed to help the enterprise determine which services to migrate given input parameters of the cost of doing business in-house, cost of outsourcing, and communication costs. Finally, a case study is utilized to demonstrate the performance of the proposed work by analyzing the process of migrating the services to clouds for an IPTV service provider. More specifically, the case study focuses on the content delivery network (CDN) within the IPTV provider’s infrastructure which is responsible for delivering contents to viewers. The CDN network can use the proposed profit-optimization formula to determine whether to utilize a cloud service or to use its internal resource to deliver the content. A performance evaluation from a simulation is presented to demonstrate the proposed profit-optimization formula can return a set of optimal mix of both internal and external services to maximize profits.

Yes / The prevalence of big data is starting to spread across the public and private sectors however, an impediment to its widespread adoption orientates around a lack of appropriate big data analytics (BDA) and resulting skills to exploit the full potential of big data availability. In this paper, we propose a novel BDA to contribute towards this void, using a fuzzy cognitive map (FCM) approach that will enhance decision-making thus prioritising IT service procurement in the public sector. This is achieved through the development of decision models that capture the strengths of both data analytics and the established intuitive qualitative approach. By taking advantages of both data analytics and FCM, the proposed approach captures the strength of data-driven decision-making and intuitive model-driven decision modelling. This approach is then validated through a decision-making case regarding IT service procurement in public sector, which is the fundamental step of IT infrastructure supply for publics in a regional government in the Russia federation. The analysis result for the given decision-making problem is then evaluated by decision makers and e-government expertise to confirm the applicability of the proposed BDA. In doing so, demonstrating the value of this approach in contributing towards robust public decision-making regarding IT service procurement. / EU FP7 project Policy Compass (Project No. 612133)

The complexity of the strategic decision making environments, in which busi- nesses and governments live in, makes such decisions more and more difficult to make. People and organizations with access to the best known decision support modelling and analysis tools and methods cannot seem to benefit from such re- sources. We argue that the reason behind the failure of most current decision and game theoretic methods is that these methods are made to deal with operational and tactical decisions, not strategic decisions. While operational and tactical decisions are clear and concise with limited scope and short-term implications, allowing them to be easily formalized and reasoned about, strategic decisions tend to be more gen- eral, ill-structured, complex, with broader scope and long-term implications. This research work starts with a review of the current dominant modelling and analysis approaches, their strengths and shortcomings, and a look at how pioneers in the field criticize these approaches as restrictive and unpractical. Then, the work goes on to propose a new paradigm shift in how strategic decisions and conflicts should be modelled and analyzed. Constrained Rationality is a formal qualitative framework, with a robust method- ological approach, to model and analyze ill-structured strategic single and multi- agent decision making situations and conflicts. The framework brings back the strategic decision making problem to its roots, from being an optimization/efficiency problem about evaluating predetermined alternatives to satisfy predetermined pref- erences or utility functions, as most current decision and game theoretic approaches treats it, to being an effectiveness problem of: 1) identifying and modelling explic- itly the strategic and conflicting goals of the involved agents (also called players and decision makers in our work), and the decision making context (the external and internal constraints including the agents priorities, emotions and attitudes); 2) finding, uncovering and/or creating the right set of alternatives to consider; and then 3) reasoning about the ability of each of these alternatives to satisfy the stated strategic goals the agents have, given their constraints. Instead of assuming that the agents’ alternatives and preferences are well-known, as most current decision and game theoretic approaches do, the Constrained Rationality framework start by capturing and modelling clearly the context of the strategic decision making situation, and then use this contextual knowledge to guide the process of finding the agents’ alternatives, analyzing them, and choosing the most effective one. The Constrained Rationality framework, at its heart, provides a novel set of modelling facilities to capture the contextual knowledge of the decision making sit- uations. These modelling facilities are based on the Viewpoint-based Value-Driven - Enterprise Knowledge Management (ViVD-EKM) conceptual modelling frame- work proposed by Al-Shawa (2006b), and include facilities: to capture and model the goals and constraints of the different involved agents, in the decision making situation, in complex graphs within viewpoint models; and to model the complex cause-effect interrelationships among theses goals and constraints. The framework provides a set of robust, extensible and formal Goal-to-Goal and Constraint-to Goal relationships, through which qualitative linguistic value labels about the goals’ op- erationalization, achievement and prevention propagate these relationships until they are finalized to reflect the state of the goals’ achievement at any single point of time during the situation. The framework provides also sufficient, but extensible, representation facilities to model the agents’ priorities, emotional valences and attitudes as value properties with qualitative linguistic value labels. All of these goals and constraints, and the value labels of their respective value properties (operationalization, achievement, prevention, importance, emotional valence, etc.) are used to evaluate the different alternatives (options, plans, products, product/design features, etc.) agents have, and generate cardinal and ordinal preferences for the agents over their respective alternatives. For analysts, and decision makers alike, these preferences can easily be verified, validates and traced back to how much each of these alternatives con- tribute to each agent’s strategic goals, given his constraints, priorities, emotions and attitudes. The Constrained Rationality framework offers a detailed process to model and analyze decision making situations, with special paths and steps to satisfy the spe- cific needs of: 1) single-agent decision making situations, or multi-agent situations in which agents act in an individualistic manner with no regard to others’ current or future options and decisions; 2) collaborative multi-agent decision making situ- ations, where agents disclose their goals and constraints, and choose from a set of shared alternatives one that best satisfy the collective goals of the group; and 3) adversarial competitive multi-agent decision making situations (called Games, in gamete theory literature, or Conflicts, in the broader management science litera- ture). The framework’s modelling and analysis process covers also three types of con- flicts/games: a) non-cooperative games, where agents can take unilateral moves among the game’s states; b) cooperative games, with no coalitions allowed, where agents still act individually (not as groups/coalitions) taking both unilateral moves and cooperative single-step moves when it benefit them; and c) cooperative games, with coalitions allowed, where the games include, in addition to individual agents, agents who are grouped in formal alliances/coalitions, giving themselves the ability to take multi-step group moves to advance their collective position in the game. ....

The complexity of the strategic decision making environments, in which busi- nesses and governments live in, makes such decisions more and more difficult to make. People and organizations with access to the best known decision support modelling and analysis tools and methods cannot seem to benefit from such re- sources. We argue that the reason behind the failure of most current decision and game theoretic methods is that these methods are made to deal with operational and tactical decisions, not strategic decisions. While operational and tactical decisions are clear and concise with limited scope and short-term implications, allowing them to be easily formalized and reasoned about, strategic decisions tend to be more gen- eral, ill-structured, complex, with broader scope and long-term implications. This research work starts with a review of the current dominant modelling and analysis approaches, their strengths and shortcomings, and a look at how pioneers in the field criticize these approaches as restrictive and unpractical. Then, the work goes on to propose a new paradigm shift in how strategic decisions and conflicts should be modelled and analyzed. Constrained Rationality is a formal qualitative framework, with a robust method- ological approach, to model and analyze ill-structured strategic single and multi- agent decision making situations and conflicts. The framework brings back the strategic decision making problem to its roots, from being an optimization/efficiency problem about evaluating predetermined alternatives to satisfy predetermined pref- erences or utility functions, as most current decision and game theoretic approaches treats it, to being an effectiveness problem of: 1) identifying and modelling explic- itly the strategic and conflicting goals of the involved agents (also called players and decision makers in our work), and the decision making context (the external and internal constraints including the agents priorities, emotions and attitudes); 2) finding, uncovering and/or creating the right set of alternatives to consider; and then 3) reasoning about the ability of each of these alternatives to satisfy the stated strategic goals the agents have, given their constraints. Instead of assuming that the agents’ alternatives and preferences are well-known, as most current decision and game theoretic approaches do, the Constrained Rationality framework start by capturing and modelling clearly the context of the strategic decision making situation, and then use this contextual knowledge to guide the process of finding the agents’ alternatives, analyzing them, and choosing the most effective one. The Constrained Rationality framework, at its heart, provides a novel set of modelling facilities to capture the contextual knowledge of the decision making sit- uations. These modelling facilities are based on the Viewpoint-based Value-Driven - Enterprise Knowledge Management (ViVD-EKM) conceptual modelling frame- work proposed by Al-Shawa (2006b), and include facilities: to capture and model the goals and constraints of the different involved agents, in the decision making situation, in complex graphs within viewpoint models; and to model the complex cause-effect interrelationships among theses goals and constraints. The framework provides a set of robust, extensible and formal Goal-to-Goal and Constraint-to Goal relationships, through which qualitative linguistic value labels about the goals’ op- erationalization, achievement and prevention propagate these relationships until they are finalized to reflect the state of the goals’ achievement at any single point of time during the situation. The framework provides also sufficient, but extensible, representation facilities to model the agents’ priorities, emotional valences and attitudes as value properties with qualitative linguistic value labels. All of these goals and constraints, and the value labels of their respective value properties (operationalization, achievement, prevention, importance, emotional valence, etc.) are used to evaluate the different alternatives (options, plans, products, product/design features, etc.) agents have, and generate cardinal and ordinal preferences for the agents over their respective alternatives. For analysts, and decision makers alike, these preferences can easily be verified, validates and traced back to how much each of these alternatives con- tribute to each agent’s strategic goals, given his constraints, priorities, emotions and attitudes. The Constrained Rationality framework offers a detailed process to model and analyze decision making situations, with special paths and steps to satisfy the spe- cific needs of: 1) single-agent decision making situations, or multi-agent situations in which agents act in an individualistic manner with no regard to others’ current or future options and decisions; 2) collaborative multi-agent decision making situ- ations, where agents disclose their goals and constraints, and choose from a set of shared alternatives one that best satisfy the collective goals of the group; and 3) adversarial competitive multi-agent decision making situations (called Games, in gamete theory literature, or Conflicts, in the broader management science litera- ture). The framework’s modelling and analysis process covers also three types of con- flicts/games: a) non-cooperative games, where agents can take unilateral moves among the game’s states; b) cooperative games, with no coalitions allowed, where agents still act individually (not as groups/coalitions) taking both unilateral moves and cooperative single-step moves when it benefit them; and c) cooperative games, with coalitions allowed, where the games include, in addition to individual agents, agents who are grouped in formal alliances/coalitions, giving themselves the ability to take multi-step group moves to advance their collective position in the game. ....

Pharmakodiagnostische Tests eröffnen die Möglichkeit, Krebstherapien individueller auf den Patienten zugeschnitten zu verschreiben. Die vorliegende Dissertation widmet sich deshalb der Frage, wie diese Gruppen in Deutschland sowie den USA in Bezug auf diese Tests Entscheidungen treffen. Alle im Rahmen dieser Arbeit durchgeführten Studien waren unterteilt in eine Vorstudie und eine Hauptsstudie. Die Ergebnisse der Vorstudie wurden im Rahmen der Hauptstudie zur Entwicklung eines Fall-Vignetten Fragebogens benutzt,um die Verwendung von kompensatorischen und nicht-kompensatorischen Entscheidungsstrategien zu untersuchen. Mit Studie I wurde gezeigt, dass sowohl deutsche als auch amerikanische Onkologen eine hohe Bereitschaft haben, solche Tests anzuwenden. Die entsprechenden Entscheidungen wurden am besten durch ein kompensatorisches Modell (Franklin’s Rule)vorhergesagt. Eine Leitlinien-Empfehlung führte nahezu immer zu einer Test-Entscheidung. Verschiedene Bedingungen machten eine Entscheidung für nicht-empfohlene Tests jedoch wahrscheinlicher. Studie II zeigte, dass Pathologen nur zu einem beschränkten Ausmaß bereit waren, von dem etablierten Test-Standard für neuartige Test-Prozeduren abzuweichen. Die Entscheidungsstrategie beider Gruppen wurde gleich gut durch die jeweiligen kompensatorischen Modelle (Franklin’s und Dawes’ Rule) sowie durch das nicht-kompensatorische Modell (Take The Best) vorhergesagt. Für die mit Studie III untersuchten Krebspatienten zeigte sich, dass ein nicht-kompensatorisches Modell (Matching Heuristic) die besten Entscheidungs-Vorhersagen machte.Während die Entscheidungen der US Patienten jedoch maßgeblich von einer Arzt-Empfehlung geleitet waren, fand sich dies nicht für die deutschen Patienten. Die sich aus den Befunden ergebenden Implikationen für die hier untersuchten Gruppen, für die mit der Leitlinien-Entwicklung beauftragten Autoritäten als auch für das Gesundheitssystem im Allgemeinen wurden abschließend diskutiert. / Upcoming pharmacodiagnostic tests offer the opportunity to better tailor cancer treatment decisions to individual patient needs. However, they put oncologists, pathologists, and cancer patients in the position of having to deal with a new technology, which often comes with its own specific risks. Little is known about how these different groups will handle this situation. This thesis is a first effort to examine, within Germany and the USA, how the respective groups would deal with a decision on applying such a test to a cancer treatment decision. All accomplished studies were divided into an explorative pilot study and a main study. Results of the pilot study were used for the main study to develop a case vignette questionnaire in order to investigate compensatory and noncompensatory decision-making strategies.In Study I, it was found that both, German and US oncologists’ decision-making policies were best described by a compensatory model (Franklin’s rule). A recommendation of a test by guidelines triggered nearly always a choice for having the test, although under different conditions also choices for nonrecommended tests were likely. Study II found that pathologists were, to a rather small extent, prepared to opt for more sophisticated test alternatives, compared to standard procedures. For both samples, decision making was equally well-predicted by two compensatory models (Franklin’s rule and Dawes’ rule), as it was by a noncompensatory model (Take The Best.Study III focused on cancer patients. The German as well as the US patients’ decisions were best predicted by a noncompensatory model (Matching Heuristic), while for the US patients, the most impacting cue was the recommendation by an oncologist, what could not be found for the German sample.Several implications of these findings for the respective groups, for authorities in charge of developing guidelines, as well as for the health systems in general, are discussed.

In the search to reduce the various divides between the developed and the developing world, Information and Communication Technology (ICT) is seen as an enabler in resource-constrained environments. However, the impact of ICT for Development (ICT4D) implementations is contested, and the ability to facilitate sustained change remains elusive. Sustainability emerged as a key lesson from the failure of early ICT4D projects, and has served as a focal point in facilitating ICT4D success. However, interpretation of the concepts of sustainability and sustainable development seems to be multiple and disconnected from practice, and is rarely translated into a useful construct for guiding project-level actions. The focus of international development is gradually shifting from donated aid towards capability and choice, empowerment, and per-poor initiatives. However, the reality remains that multiple organisations with varying levels of power, resources, and influence determine the outcomes and the sustainability of benefits from a development intervention. This research investigates mechanisms to sustain benefit by exploring the interface between various role players through the lens of decision-making. It builds on the view that the value created by the virtual ‘organisation’ of stakeholders in an ICT4D implementation results from the sum of its decisions, and develops a framework for decision-making with a view on sustaining benefits. The work follows a Design Science Research methodology, comprising an iterative process for the development, testing, and improvement of the framework based on three literature reviews, two case studies, and an expert review. The research answers the primary research question, namely: What are the elements of a framework that support strategic decision-making for the design and implementation of ICT4D interventions in resource-constrained environments, in support of sustained benefit? The knowledge contribution is primarily at the concept and methodological level. In addition to framework development, the decision problem in ICT4D is defined, andthe concept of sustained benefit is proposed as a means of operationalizing sustainability. This research illustrates the role of decision concepts in structuring the complexity of ICT4D problems. It introduces an alternative perspective into the debate on sustainability in ICT4D, and provides a basis for the future development of theory. / Information Systems / D. Litt. et Phil. (Information Systems)

The Ph.D. project has evolved from focusing on the technical problem of the integration and interoperability of an assemblage of complex systems and SoS within a flight training system to development of a workflow process using frameworks to aid the decision making process for the selection of optimal flight training blending mixes. The focus of the research involved developing a methodology to satisfy research project proposal requirements agreed upon with the industrial sponsor. This thesis investigates the complexity of a modern flight training systems and the need for understanding that it is supported by a complex Family of Systems (FoS) including Virtual Reality Training Environments such as flight simulators, to live training aircraft with various configurations of avionic controls. One of the key technical problems today is how best to develop and assemble a family of flight training system into an integrated Live/Synthetic mix for aircrew training to optimise organisation and training objectives. With the increased use of emulation/synthetic data on aircraft for live training, the synthetic boundary is becoming increasingly blurred. Systematic consideration of the most appropriate blend is needed. The methodology used in the research is model driven and the architecture produced is described at a level of abstraction to enable communication to all stakeholders for the means of understanding the structure involved in the system design process. Relational Oriented Systems Engineering and Technology Trade-Off Analysis (ROSETTA) frameworks are described using Model Based Systems Engineering (MBSE) techniques for supporting capability based trade-off decisions for selection of optimal flight training FoS mixes dependent on capability. The research proposes a methodology and associated methods including a high-level systematic closed loop information management structure for blended device/tool aircrew training and a modelling and analysis approach for the FoS aviation training problem to enhance the existing training programmes to provide a more efficient and agile training environment. The mathematical formalisms used provide a method of quantifying subjective opinions and judgements for trade studies to be accomplished on the suitability of technology for each student pilot in relation to training and organisational objectives. The methodology presented is by no means a final solution, but a path for further research to enable a greater understanding of the suitability of training tools/technology used to train individual pilots at various stages throughout the training pipeline lifecycle(s).