Typescript. / Bibliography: leaves 112-124. / viii, 175 l tables

Typescript. / Bibliography: leaves [176]-181. / x, 181 l tables

Most decision making processes involve risk associated with the uncertainty of a range of outcomes that may, or may not, occur at some time in the future. In recent years, many of the recent advances in risk theory have come from the field of financial mathematics. While the latter subject is now well developed we claim that there are still some important aspects of decision-making involving risk that are not covered by the existing theory. In particular, we believe that the following three questions require further investigations. 1. In the financial portfolio management context, if decisions need to be taken at multiple stages, is it possible to devise a time consistent risk minimization policy? 2. If the value of an asset of interest is strongly influenced by a climatic variable (such as temperature or rainfall) that is best modelled by techniques that are not normally used in financial modelling, how should financial derivatives on such an asset be priced? 3. If the undesirable risky phenomenon depends on both the upper and lower tails of a, possibly asymmetric, probability distribution (e.g., that of amount of rainfall), what is a suitable measure of risk in this context? This thesis supplies, at least partial, answers to each of these challenging questions. We hope that these results will motivate others to develop even better solutions. / First, for the purpose of defining a dynamic measure of risk, we introduce the time consistency concept that is inspired by the so-called principle of optimality of dynamic programming and demonstrate - via an example - that the conditional value-at-risk (CVaR) need not be time consistent in a multi-stage case. Then, we give the formulation of the target-percentile risk measure which is time consistent and hence more suitable in the multi-stage investment context. / Second, in order to hedge the risk related to the uncertainty of weather we study pricing of derivatives where the underlying asset is sensitive to the weather and the price is a function of a weather variable, for instance, temperature or rain-fall. We use time series to model the temperature and assume that the price of the underlying asset is a deterministic function of the temperature. We discuss both the continuous and discrete time models using the replicating portfolio approach. We obtain a partial differential equation that is similar to the Black-Scholes PDE in the continuous time case. We also provide a binomial approximation for the continuous time model and the corresponding PDE, and report on some numerical experiments. / Next, we analyze the risk encountered in many environmental problems that appear to exhibit special "two-sided" characteristics. For instance, in a given area and in a given period, farmers do not want to see too much or too little rainfall. We formulate and solve this problem with the help of a "two-sided loss function" that depends on the above ranges. Even in financial portfolio optimization a loss and a gain are "two sides of a coin", so it is desirable to deal with them in a manner that reflects an investor's relative concern. Consequently, we define Type I risk: "the loss is too big" and Type II risk: "the gain is too small". Ideally, we would want to minimize the two risks simultaneously. However, this may be impossible and hence we try to balance these two types of risk. / Thesis (PhDMathematics)--University of South Australia, 2006.

This research is possibly the first study investigating the impact of cognitive biases on information searching and decision making. Set in the context of making health-related decisions, this research tests the hypotheses that (i) people experience cognitive biases during information searching; (ii) cognitive biases can be corrected during information searching; and (iii) correcting for biases during information searching improves decision making. Using a retrospective data analysis, a Bayesian model and a series of prospective empirical experiments, the cognitive biases investigated are anchoring effect, order effects, exposure effect and reinforcement effect. People may experience anchoring effect, exposure effect and order effects while searching for information. A person???s prior belief (anchoring effect) has a significant impact on decision outcome (P &lt 0.001). Documents accessed at different positions in a search journey (order effects) and documents processed for different lengths of time (exposure effect) have different degrees of influence on decision making (order: P = 0.026; exposure: P = 0.0081). To remedy the impact of cognitive biases, a series of interventions were designed and trialled to test for their ability to modify the impact of biases during search. A search engine interface was modified to allow for a document-level intervention, which attempts to debias order effects, exposure effect and reinforcement effect; a decision-focussed intervention for debiasing the anchoring effect; and an education-based intervention to inform users about the biases investigated in this research. Evaluation of these alterations to the search interface showed that some of the interventions can reduce or exacerbate cognitive biases during search. Order effects are no longer apparent amongst subjects using a keep document tool (i.e. order debiasing intervention) (P = 0.34); however, it is not associated with any significant improvement in decision accuracy (P = 0.23). Although the anchoring effect remains robust amongst subjects using a for/against document tool (i.e. anchor debiasing intervention) (P &lt 0.001), the intervention is marginally associated with a 10.3% increased proportion of subjects who answered incorrectly pre-search to answer correctly post-search (P = 0.10). Overall, this research concludes with evidence that using a debiasing intervention can alter search behaviour and influence the accuracy and confidence in decision making.

Pattern mining is a knowledge discovery task which is useful for finding interesting data characteristics. Existing mining techniques sometimes suffer from limited performance in challenging situations, such as when finding patterns in high-dimensional datasets. Binary Decision Diagrams and their variants are a compact and efficient graph data structure for representing and manipulating boolean functions and they are potentially attractive for solving many problems in pattern mining. This thesis explores techniques for the use of binary decision diagrams for mining both simple and complex types of patterns. / Firstly, we investigate the use of Binary Decision Diagrams for mining the fundamental types of patterns. These include frequent patterns, also known as frequent itemsets. We introduce a structure called the Weighted Zero-suppressed Binary Decision Diagram and evaluate its use on high dimensional data. This type of Decision Diagram is extremely useful for re-using intermediate patterns during computation. / Secondly, we study the problem of mining patterns in sequential databases. Here, we introduce a new structure called the Sequence Binary Decision Diagram, which can be used for mining frequent subsequences. We show that our technique is competitive with the state of the art and identify situations where it is superior. / Thirdly, we show how Weighted Zero-suppressed Binary Decision Diagrams can be used for discovering new and complex types of patterns. We introduce new types of highly expressive patterns for capturing contrasts, which express disjunctions of attribute values. Moreover, to investigate the usefulness of disjunctive patterns for knowledge discovery, we employ a statistical methodology for testing their significance, and study their use for solving classification problems. Our findings show that classifiers based on significant disjunctive patterns can be more robust than those which are only based on simple patterns. / Finally, we introduce patterns for capturing second-order differences between two groups of classes, which can provide useful insights for human experts. Again, we show how binary decision diagrams can be deployed for efficiently discovering this type of knowledge. / In summary, we demonstrate that Binary Decision Diagrams, are a powerful and scalable tool in pattern mining. We believe their use is very promising for a range of current and future tasks in the data mining context.

One explanation for the increased use of interactive groups in organisations is that benefits are obtained from pooling individuals?? differing knowledge and abilities. However, prior experimental research has established that groups often do not discuss and use information effectively, exhibiting a bias toward information that is commonly known by all group members, rather than information that is unique to individual group members (common information bias). This dissertation investigated whether the provision of quantitative information resulted in improved group performance in two respects. First, it investigated whether quantitative information was discussed and used more than qualitative information. Second, it examined whether the quantification of information reduced the common information bias. This is important because a basic purpose of managerial accounting is to provide information that improves employees?? abilities to make optimal decisions. This dissertation utilised an experimental task known as a ??hidden profile?? to achieve the research objectives. In a hidden profile experiment, each group member receives some information that is common to everyone in the group, and some information that is unique to them. The group must discuss and use members?? unique information in order to uncover the optimal task solution. This dissertation examined the effect of information availability (common or unique) and information type (quantitative or qualitative) on information discussion and use. There were two stages to the experiment. First, individual group members had to make a capital investment decision, and write down their reasons for that decision. Second, groups had to discuss the information, come to a group decision, and write down their reasons for that decision. The results confirmed a common information bias at the group decision level, with groups significantly favouring common information over unique information, for all measures of discussion and information use. In contrast, while a preference for quantitative information was found at the individual decision level, at a group decision level there were no significant differences in the discussion or use of quantitative and qualitative information, with only one exception: significantly more statements were made about quantitative information.

Clinical decision-making (CDM) research has focused on diagnostic reasoning, CDM models, factors influencing CDM and the development of expertise. The research approaches used, including phenomenology, have not addressed the question of how CDM is perceived and approached by nurses. This study describes perceptions of CDM in relation to patients in pain using a phenomenographic methodology. At semi-structured interviews, participants were asked to recall their responses to a situation involving a patient in pain. The responses fell into four categories: (1) the effect of the clinical environment; (2) the role of other health professionals; (3) the place of the patient; and (4) the role of experience. Examples of differences in perceptions that were likely to impact on the nurses� approach to CDM include: the ongoing effects of time and workload demands on CDM; nurses are initially dependent but were eventually able to make decisions autonomously; the patient who may be peripheral or central to CDM; and the nurses� move from the use of theoretical principles to experiential knowledge as reflection-on-practice is employed. Perceptions in all categories are strongly implicated in the nurses� sense of confidence and independence. Implications for nursing practice and nursing education suggested by the findings relate to the number of areas in which graduates work in the first year of practice, the size of new graduate workloads, graduate transition programs, the place of reflection-on-practice and undergraduate (UG) program clinical experience patterns. Among issues for further research arising from the study are: replication of the study; detailed examination of the development of CDM in the first year of nursing practice and during UG nursing education programs; the role of other health professionals in the development of CDM behaviour; the links between CDM and clinical knowledge development; and the type of clinical environments that foster confidence and independence. A conclusion of the study is that the way CDM is approached is influenced by the amount, quality, relevancy and recency of clinical experience. In this study, phenomenography was shown to be an appropriate approach to the description of nurses� perceptions of CDM in relation to patients in pain. In addition, nurses� changing perceptions over two years and the subsequent effect on CDM behaviour were described.

Doctor of Philosophy / Multiple sclerosis (MS) is the most common neurological disease affecting young adults. MS affects approximately 1 in 1000 people and, like other autoimmune diseases, women are more likely to be affected than men. The illness typically onsets between the ages of 20 and 40, and hence usually affects women of child-bearing age. The course of the MS is often unclear for years after diagnosis and since most women are diagnosed in their child-bearing years, they often have to make reproductive choices before their prognosis is clear and while the future remains uncertain. For women with MS, starting a family is an individual choice that needs to balance the importance of motherhood for the woman and her partner against the risks that she will be unable to care for the infant or child as a result of increasing disability. In other areas of medicine where finely balanced decisions are required, there has been a recent proliferation of decision aids that aim to inform people of the benefits and risks of opposing courses of action. In addition, decision aids help patients to weigh their values against the risks and benefits to make an informed decision. Despite the existence of over 200 decision aids to help patients consider decisions related to their medical conditions, not one exists that deals with the decision of whether or not to have a family for women with a chronic disability, such as MS. This thesis developed and evaluated a decision aid for women with MS to help them decide whether to start, forego or enlarge their families. The study utilised the criteria set out for the development of decision aids, according to the Cochrane Systematic Review of Patient Decision Aids (O'Connor et al., 2003). The first aim was to determine the proportion of women who are undecided about the motherhood choice and for whom a decision aid may be relevant. Results found that the motherhood choice was relevant to 46% of the women who responded to an initial mail-out. The second study aimed to establish women’s current concerns and thoughts regarding pregnancy and motherhood, and their response to the pilot decision aid. Twenty women participated in qualitative interviews and results supported previous findings that the mother’s health concerns, coping with parenting and societal attitudes are significant concerns when considering this decision. This study further identified concerns from different groups that had a direct impact on the decision to have children, including the experience of parenting, the child’s well-being and the timing and pressure of the decision. The main study was a randomised controlled trial of the decision aid aiming to determine whether the decision aid facilitated decision-making in women with MS. The study confirmed that the decision aid presented a balanced view to women, increased knowledge, reduced decisional conflict, increased decisional self-efficacy and certainty of the decision, and was free from adverse effects on psychopathology. The final component of the study was a 12 month follow-up which aimed to explore the long-term effectiveness of the decision aid and what aspects were valued by the women who received it. It was found that over time, women in the intervention group did maintain their certainty, but women in the control group also became more certain of their choice. At follow-up, the difference in certainty was no longer significant between the two groups. However, women did report that the intervention was useful in (a) providing access to information previously unavailable or difficult to obtain, (b) facilitating communication between women, their partners and health care professionals, (c) aiding them in considering and utilising their networks of support, and (d) preparing them for potential difficulties. In summary, this thesis developed and evaluated a decision aid for women with MS who are considering motherhood. The results showed that many women were undecided and, in the absence of good information on the topic, many women had concerns about pregnancy and parenthood. The decision aid was shown to be effective across a range of measures and free from adverse psychological effects. Hence, this is evidence-based resource can now be recommended for those women with MS who are currently contemplating motherhood.

Research Doctorate - Doctor of Philosophy / Information and communication technology (ICT) advances relating to the architectural, engineering and construction (AEC) sector have been rapid, offering efficiency gains and improved business effectiveness. However economic considerations, industry-specific conditions, legal, and business issues have limited their adoption by multi-firm project teams. ICT adoption rates are the manifestation of boundedly rational business decisions, formed by personal attitudes to innovation. Although attitudes are personal constructs they are phenomena that are experienced, can be personally reported, and observed from a distance. This research maps attitudinal influences wherein the attitudinal profiles of decision-makers can be located. Adopting etic and emic perspectives it reveals independent indication of the extent and features of the phenomenon, and the personal construction of meaning and rules for decision-making. These perspectives are obtained using an asynchronous, online Delphi study of 13 international experts, combined with investigation of the phenomenological experiences of 39 experienced practitioners through in-depth interviews. Thematic analysis, supported by appropriate correlation analysis reveals patterns and structure in each study, which are modeled. These are then synthesised into a unified, multi-dimensional model. This model reveals that individual attitude is composed of a number of components: exogenous issues include human, technological and business processes; an endogenous component relating to personal considerations; technological push, cultural pull, and a temporal dimension. It posits intra-firm and inter-organisational dimensions, observing variance along a continuum related to the context within which they are being considered. The significance of this research is twofold: it maps the domain within which ICT decision-makers in the AEC sector make their decisions; it provides a reliable basis upon which to base further investigations.

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.