3 resultados para Problems and potentials

em CORA - Cork Open Research Archive - University College Cork - Ireland


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The organisational decision making environment is complex, and decision makers must deal with uncertainty and ambiguity on a continuous basis. Managing and handling decision problems and implementing a solution, requires an understanding of the complexity of the decision domain to the point where the problem and its complexity, as well as the requirements for supporting decision makers, can be described. Research in the Decision Support Systems domain has been extensive over the last thirty years with an emphasis on the development of further technology and better applications on the one hand, and on the other hand, a social approach focusing on understanding what decision making is about and how developers and users should interact. This research project considers a combined approach that endeavours to understand the thinking behind managers’ decision making, as well as their informational and decisional guidance and decision support requirements. This research utilises a cognitive framework, developed in 1985 by Humphreys and Berkeley that juxtaposes the mental processes and ideas of decision problem definition and problem solution that are developed in tandem through cognitive refinement of the problem, based on the analysis and judgement of the decision maker. The framework facilitates the separation of what is essentially a continuous process, into five distinct levels of abstraction of manager’s thinking, and suggests a structure for the underlying cognitive activities. Alter (2004) argues that decision support provides a richer basis than decision support systems, in both practice and research. The constituent literature on decision support, especially in regard to modern high profile systems, including Business Intelligence and Business analytics, can give the impression that all ‘smart’ organisations utilise decision support and data analytics capabilities for all of their key decision making activities. However this empirical investigation indicates a very different reality.

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The administration of psychotropic and psychoactive medication for persons with learning disability and accompanying mental illness and/or challenging behaviour has undergone much critical review over the past two decades. Assessment and diagnosis of mental illness in this population continues to be psychopharmacological treatment include polypharmacy, irrational prescription procedures and frequent over-prescription. It is clear that all forms of treatment including non-pharmacological interventions need to be driven by accurate and appropriate diagnoses. Where a psychiatric diagnosis has been identified, it greatly aides the selection of appropriate medication, although a specific medication for each diagnosis, as was once hoped, is simply no longer a reality in practice. Part one of the present thesis seeks to address many of the current issues in mental health problems and pharmacological treatment to date. The author undertook a drug prevalence study within both residential and community facilities for persons with learning disability within the Mid-West region of Ireland in order to ascertain the current level of prescribing of psychotropic and psychoactive medications for this population. While many attempts have been made to account for the variation in prescribing, little systematic and empirical research has been undertaken to investigate the factors thought to influence such prescribing. While studies investigating the prescribing behaviours of General Practitioners (GP's) have illustrated the complex nature of the decision making process in the context of general practice, no similar efforts have yet been directed at examining the prescribing behaviours of Consultant Psychiatrists. Using The Critical Incident Technique, the author interviewed Consultant Psychiatrists in the Republic of Ireland to gather information relating not only to their patterns of prescribing for learning disabled populations, but also to examine reasons influencing their prescribing in addition to several related factors. Part two of this thesis presents the findings from this study and a number of issues are raised, not only in relation to attempting to account for the findings from part one of the thesis, but also with respect to implications for improved management and clinical practice.

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In decision making problems where we need to choose a particular decision or alternative from a set of possible choices, we often have some preferences which determine if we prefer one decision over another. When these preferences give us an ordering on the decisions that is complete, then it is easy to choose the best or one of the best decisions. However it often occurs that the preferences relation is partially ordered, and we have no best decision. In this thesis, we look at what happens when we have such a partial order over a set of decisions, in particular when we have multiple orderings on a set of decisions, and we present a framework for qualitative decision making. We look at the different natural notions of optimal decision that occur in this framework, which gives us different optimality classes, and we examine the relationships between these classes. We then look in particular at a qualitative preference relation called Sorted-Pareto Dominance, which is an extension of Pareto Dominance, and we give a semantics for this relation as one that is compatible with any order-preserving mapping of an ordinal preference scale to a numerical one. We apply Sorted-Pareto dominance to a Soft Constraints setting, where we solve problems in which the soft constraints associate qualitative preferences to decisions in a decision problem. We also examine the Sorted-Pareto dominance relation in the context of our qualitative decision making framework, looking at the relevant optimality classes for the Sorted-Pareto case, which gives us classes of decisions that are necessarily optimal, and optimal for some choice of mapping of an ordinal scale to a quantitative one. We provide some empirical analysis of Sorted-Pareto constraints problems and examine the optimality classes that result.