44 resultados para data-driven decision making
em CentAUR: Central Archive University of Reading - UK
Resumo:
Many different individuals, who have their own expertise and criteria for decision making, are involved in making decisions on construction projects. Decision-making processes are thus significantly affected by communication, in which a dynamic performance of human intentions leads to unpredictable outcomes. In order to theorise the decision making processes including communication, it is argued here that the decision making processes resemble evolutionary dynamics in terms of both selection and mutation, which can be expressed by the replicator-mutator equation. To support this argument, a mathematical model of decision making has been made from an analogy with evolutionary dynamics, in which there are three variables: initial support rate, business hierarchy, and power of persuasion. On the other hand, a survey of patterns in decision making in construction projects has also been performed through self-administered mail questionnaire to construction practitioners. Consequently, comparison between the numerical analysis of mathematical model and the statistical analysis of empirical data has shown a significant potential of the replicator-mutator equation as a tool to study dynamic properties of intentions in communication.
Resumo:
Modern buildings are designed to enhance the match between environment, spaces and the people carrying out work, so that the well-being and the performance of the occupants are all in harmony. Building services are systems that facilitate a healthy working environment within which workers productivity can be optimised in the buildings. However, the maintenance of these services is fraught with problems that may contribute to up to 50% of the total life cycle cost of the building. Maintenance support is one area which is not usually designed into the system as this is not common practice in the services industry. The other areas of shortfall for future designs are; client requirements, commissioning, facilities management data and post occupancy evaluation feedback which needs to be adequately planned to capture and document this information for use in future designs. At the University of Reading an integrated approach has been developed to assemble the multitude of aspects inherent in this field. The means records required and measured achievements for the benefit of both building owners and practitioners. This integrated approach can be represented in a Through Life Business Model (TLBM) format using the concept of Integrated Logistic Support (ILS). The prototype TLBM developed utilises the tailored tools and techniques of ILS for building services. This TLBM approach will facilitate the successful development of a databank that would be invaluable in capturing essential data (e.g. reliability of components) for enhancing future building services designs, life cycle costing and decision making by practitioners, in particular facilities managers.
Resumo:
Studies of ignorance-driven decision making have been employed to analyse when ignorance should prove advantageous on theoretical grounds or else they have been employed to examine whether human behaviour is consistent with an ignorance-driven inference strategy (e. g., the recognition heuristic). In the current study we examine whether-under conditions where such inferences might be expected-the advantages that theoretical analyses predict are evident in human performance data. A single experiment shows that, when asked to make relative wealth judgements, participants reliably use recognition as a basis for their judgements. Their wealth judgements under these conditions are reliably more accurate when some of the target names are unknown than when participants recognize all of the names (a "less-is-more effect"). These results are consistent across a number of variations: the number of options given to participants and the nature of the wealth judgement. A basic model of recognition-based inference predicts these effects.
Resumo:
Pro-poor decision making depends on an understanding of the complexities and interrelationships between household livelihood, demographic, and economic factors. This article describes the design and implementation of the Poverty Assessor, a software programme to assist practitioners, policy makers, and researchers in visualising the direct impacts on poverty of specific livelihood factors and events among populations living in poverty. The software enables users to upload their own data and profile households in relation to the national poverty line, by selecting from a range of demographic and livelihood indicators. The authors present findings from the programme, using a dataset from Bolivia.
Resumo:
Conventional economic theory, applied to information released by listed companies, equates ‘useful’ with ‘price-sensitive’. Stock exchange rules accordingly prohibit the selec- tive, private communication of price-sensitive information. Yet, even in the absence of such communication, UK equity fund managers routinely meet privately with the senior execu- tives of the companies in which they invest. Moreover, they consider these brief, formal and formulaic meetings to be their most important sources of investment information. In this paper we ask how that can be. Drawing on interview and observation data with fund managers and CFOs, we find evidence for three, non-mutually exclusive explanations: that the characterisation of information in conventional economic theory is too restricted, that fund managers fail to act with the rationality that conventional economic theory assumes, and/or that the primary value of the meetings for fund managers is not related to their investment decision making but to the claims of superior knowledge made to clients in marketing their active fund management expertise. Our findings suggest a disconnect between economic theory and economic policy based on that theory, as well as a corre- sponding limitation in research studies that test information-usefulness by assuming it to be synonymous with price-sensitivity. We draw implications for further research into the role of tacit knowledge in equity investment decision-making, and also into the effects of the principal–agent relationship between fund managers and their clients.
Resumo:
We examined the maturation of decision-making from early adolescence to mid-adulthood using fMRI of a variant of the Iowa gambling task. We have previously shown that performance in this task relies on sensitivity to accumulating negative outcomes in ventromedial PFC and dorsolateral PFC. Here, we further formalize outcome evaluation (as driven by prediction errors [PE], using a reinforcement learning model) and examine its development. Task performance improved significantly during adolescence, stabilizing in adulthood. Performance relied on greater impact of negative compared with positive PEs, the relative impact of which matured from adolescence into adulthood. Adolescents also showed increased exploratory behavior, expressed as a propensity to shift responding between options independently of outcome quality, whereas adults showed no systematic shifting patterns. The correlation between PE representation and improved performance strengthened with age for activation in ventral and dorsal PFC, ventral striatum, and temporal and parietal cortices. There was a medial-lateral distinction in the prefrontal substrates of effective PE utilization between adults and adolescents: Increased utilization of negative PEs, a hallmark of successful performance in the task, was associated with increased activation in ventromedial PFC in adults, but decreased activation in ventrolateral PFC and striatum in adolescents. These results suggest that adults and adolescents engage qualitatively distinct neural and psychological processes during decision-making, the development of which is not exclusively dependent on reward-processing maturation.
Resumo:
Seamless phase II/III clinical trials are conducted in two stages with treatment selection at the first stage. In the first stage, patients are randomized to a control or one of k > 1 experimental treatments. At the end of this stage, interim data are analysed, and a decision is made concerning which experimental treatment should continue to the second stage. If the primary endpoint is observable only after some period of follow-up, at the interim analysis data may be available on some early outcome on a larger number of patients than those for whom the primary endpoint is available. These early endpoint data can thus be used for treatment selection. For two previously proposed approaches, the power has been shown to be greater for one or other method depending on the true treatment effects and correlations. We propose a new approach that builds on the previously proposed approaches and uses data available at the interim analysis to estimate these parameters and then, on the basis of these estimates, chooses the treatment selection method with the highest probability of correctly selecting the most effective treatment. This method is shown to perform well compared with the two previously described methods for a wide range of true parameter values. In most cases, the performance of the new method is either similar to or, in some cases, better than either of the two previously proposed methods.
Resumo:
The games-against-nature approach to the analysis of uncertainty in decision-making relies on the assumption that the behaviour of a decision-maker can be explained by concepts such as maximin, minimax regret, or a similarly defined criterion. In reality, however, these criteria represent a spectrum and, the actual behaviour of a decision-maker is most likely to embody a mixture of such idealisations. This paper proposes that in game-theoretic approach to decision-making under uncertainty, a more realistic representation of a decision-maker's behaviour can be achieved by synthesising games-against-nature with goal programming into a single framework. The proposed formulation is illustrated by using a well-known example from the literature on mathematical programming models for agricultural-decision-making. (c) 2005 Elsevier Inc. All rights reserved.
Resumo:
The aim of a phase H clinical trial is to decide whether or not to develop an experimental therapy further through phase III clinical evaluation. In this paper, we present a Bayesian approach to the phase H trial, although we assume that subsequent phase III clinical trials will hat,e standard frequentist analyses. The decision whether to conduct the phase III trial is based on the posterior predictive probability of a significant result being obtained. This fusion of Bayesian and frequentist techniques accepts the current paradigm for expressing objective evidence of therapeutic value, while optimizing the form of the phase II investigation that leads to it. By using prior information, we can assess whether a phase II study is needed at all, and how much or what sort of evidence is required. The proposed approach is illustrated by the design of a phase II clinical trial of a multi-drug resistance modulator used in combination with standard chemotherapy in the treatment of metastatic breast cancer. Copyright (c) 2005 John Wiley & Sons, Ltd.