812 resultados para Model of Decision Making


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Bayesian decision theory is increasingly applied to support decision-making processes under environmental variability and uncertainty. Researchers from application areas like psychology and biomedicine have applied these techniques successfully. However, in the area of software engineering and speci?cally in the area of self-adaptive systems (SASs), little progress has been made in the application of Bayesian decision theory. We believe that techniques based on Bayesian Networks (BNs) are useful for systems that dynamically adapt themselves at runtime to a changing environment, which is usually uncertain. In this paper, we discuss the case for the use of BNs, speci?cally Dynamic Decision Networks (DDNs), to support the decision-making of self-adaptive systems. We present how such a probabilistic model can be used to support the decision making in SASs and justify its applicability. We have applied our DDN-based approach to the case of an adaptive remote data mirroring system. We discuss results, implications and potential bene?ts of the DDN to enhance the development and operation of self-adaptive systems, by providing mechanisms to cope with uncertainty and automatically make the best decision.

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Extending the growing interest in affect in work groups, we propose that groups with distributed information make higher quality decisions when they are in a negative rather than a positive mood, but that these effects are moderated by group members' trait negative affect. In support of this hypothesis, an experiment (N = 175 groups) showed that positive mood led to lower quality decisions than did negative or neutral moods when group members were low in trait negative affect, whereas such mood effects were not observed in groups higher in trait negative affect. Mediational analysis based on behavioral observations of group process confirmed that group information elaboration mediated this effect. These results provide an important caveat on the benefits of positive moods in work groups, and suggest that the study of trait × state affect interactions is an important avenue for future research.

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Purpose: The purpose of this paper is to review the literature which focuses on four major higher education decision problems. These are: resource allocation; performance measurement; budgeting; and scheduling. Design/methodology/approach: Related articles appearing in the international journals from 1996 to 2005 are gathered and analyzed so that the following three questions can be answered: "What kind of decision problems were paid most attention to?"; "Were the multiple criteria decision-making techniques prevalently adopted?"; and "What are the inadequacies of these approaches?" Findings: Based on the inadequacies, some improvements and possible future work are recommended, and a comprehensive resource allocation model is developed taking account of these factors. Finally, a new knowledge-based goal programming technique which integrates some operations of analytic hierarchy process is proposed to tackle the model intelligently. Originality/value: Higher education has faced the problem of budget cuts or constrained budgets for the past 30 years. Managing the process of the higher education system is, therefore, a crucial and urgent task for the decision makers of universities in order to improve their performance or competitiveness. © Emerald Group Publishing Limited.

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This paper critically reviews the strategic decision-making process literature, with a specific focus on the effects of context. Context refers to the top management team, strategic decision-specific characteristics, the external environment and firm characteristics. This literature review also develops an illustrative framework that incorporates these four different categories of contextual variables that influence the strategic decision-making process. As a result of the variety and pervasiveness of contextual variables featured within the literature, a comprehensive and up-to-date review is essential for organizing and synthesizing the extant literature to explicate an agenda for future research. The purpose of this literature review is threefold: first, to critically review the strategic decision-making process literature to highlight the underlying themes, issues, tensions and debates in the field; second, to identify the opportunities for future theory development; and third, to state the methodological implications arising from this review. © 2013 British Academy of Management and John Wiley & Sons Ltd.

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Intuition can produce effective strategic decisions because of its speed and ability to solve less-structured problems. Despite this, there are only a very small number of empirical studies that have examined intuition in the strategic decision-making process. We examine the relationship between the use of intuition in the strategic decision-making process, and strategic decision effectiveness. We propose that the expertise of the decision-maker, environmental dynamism and the characteristics of the strategic decision itself moderate the relationship between the use of intuition in the strategic decision making process, and strategic decision effectiveness. We make a significant theoretical contribution by integrating the management and social-psychology literatures in order to identify the variables that affect the relationship between the use of intuition in the strategic decision-making process, and strategic decision effectiveness. This article builds upon existing empirical research that has examined intuition in the strategic decision-making process, and reconciles some of the confounding results that have emerged. The paper presents a conceptual model and research propositions, which if empirically examined, would make a significant contribution to knowledge in the strategic decision-making domain of literature.

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Bioenergy schemes are multi-faceted and complex by nature, with many available raw material supplies and technical options and a diverse set of stakeholders holding a raft of conflicting opinions. To develop and operate a successful scheme there are many requirements that should be considered and satisfied. This paper provides a review of those academic works attempting to deal with problems arising within the bioenergy sector using multi-criteria decision-making (MCDM) methods. These methods are particularly suitable to bioenergy given its multi-faceted nature but could be equally relevant to other energy conversion technologies. Related articles appearing in the international journals from 2000 to 2010 are gathered and analysed so that the following two questions can be answered. (i) Which methods are the most popular? (ii) Which problems attract the most attention? The review finds that optimisation methods are most popular with methods choosing between few alternatives being used in 44% of reviewed papers and methods choosing between many alternatives being used in 28%. The most popular application area was to technology selection with 27% of reviewed papers followed by policy decisions with 18%. © 2012 Elsevier Ltd.

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This paper examines UK and US primary care doctors' decision-making about older (aged 75 years) and midlife (aged 55 years) patients presenting with coronary heart disease (CHD). Using an analytic approach based on conceptualising clinical decision-making as a classification process, it explores the ways in which doctors' cognitive processes contribute to ageism in health-care at three key decision points during consultations. In each country, 56 randomly selected doctors were shown videotaped vignettes of actors portraying patients with CHD. The patients' ages (55 or 75 years), gender, ethnicity and social class were varied systematically. During the interviews, doctors gave free-recall accounts of their decision-making. The results do not establish that there was substantial ageism in the doctors' decisions, but rather suggest that diagnostic processes pay insufficient attention to the significance of older patients' age and its association with the likelihood of co-morbidity and atypical disease presentations. The doctors also demonstrated more limited use of 'knowledge structures' when diagnosing older than midlife patients. With respect to interventions, differences in the national health-care systems rather than patients' age accounted for the differences in doctors' decisions. US doctors were significantly more concerned about the potential for adverse outcomes if important diagnoses were untreated, while UK general practitioners cited greater difficulty in accessing diagnostic tests.

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This research describes a computerized model of human classification which has been constructed to represent the process by which assessments are made for psychodynamic psychotherapy. The model assigns membership grades (MGs) to clients so that the most suitable ones have high values in the therapy category. Categories consist of a hierarchy of components, one of which, ego strength, is analysed in detail to demonstrate the way it has captured the psychotherapist's knowledge. The bottom of the hierarchy represents the measurable factors being assessed during an interview. A questionnaire was created to gather the identified information and was completed by the psychotherapist after each assessment. The results were fed into the computerized model, demonstrating a high correlation between the model MGs and the suitability ratings of the psychotherapist (r = .825 for 24 clients). The model has successfully identified the relevant data involved in assessment and simulated the decision-making process of the expert. Its cognitive validity enables decisions to be explained, which means that it has potential for therapist training and also for enhancing the referral process, with benefits in cost effectiveness as well as in the reduction of trauma to clients. An adapted version measuring client improvement would give quantitative evidence for the benefit of therapy, thereby supporting auditing and accountability. © 1997 The British Psychological Society.

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the article views examine the problems concerning with the sources of origin of unconscious the inner personal conflicts and the way the presence of this factor is reflected on the decision-making process by a person.

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Synergetic methods of data complexation are proposed that make it possible to obtain a maximal amount of available information using a limited number of channels. Along with freedom degrees reducers, a mechanism of freedom degrees discriminators is proposed that enables all the channels to take part in the development of a cooperative decision in accordance with their informativeness in a current situation.

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Active monitoring and problem of non-stable of sound signal parameters in the regime of piling up response signal of environment is under consideration. Math model of testing object by set of weak stationary dynamic actions is offered. The response of structures to the set of signals is under processing for getting important information about object condition in high frequency band. Making decision procedure by using researcher’s heuristic and aprioristic knowledge is discussed as well. As an example the result of numerical solution is given.

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Shared decision-making (SDM), a component of patient-centered care, is the process in which the clinician and patient both participate in decision-making about treatment; information is shared between the parties and both agree with the decision. Shared decision-making is appropriate for health care conditions in which there is more than one evidence-based treatment or management option that have different benefits and risks. The patient's involvement ensures that the decisions regarding treatment are sensitive to the patient's values and preferences. Audiologic rehabilitation requires substantial behavior changes on the part of patients and includes benefits to their communication as well as compromises and potential risks. This article identifies the importance of shared decision-making in audiologic rehabilitation and the changes required to implement it effectively.

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There is growing interest in exploring the potential links between human biology and management and organization studies, which is bringing greater attention to bear on the place of mental processes in explaining human behaviour and effectiveness. The authors define this new field as organizational cognitive neuroscience (OCN), which is in the exploratory phase of its emergence and diffusion. It is clear that there are methodological debates and issues associated with OCN research, and the aim of this paper is to illuminate these concerns, and provide a roadmap for rigorous and relevant future work in the area. To this end, the current reach of OCN is investigated by the systematic review methodology, revealing three clusters of activity, covering the fields of economics, marketing and organizational behaviour. Among these clusters, organizational behaviour seems to be an outlier, owing to its far greater variety of empirical work, which the authors argue is largely a result of the plurality of research methods that have taken root within this field. Nevertheless, all three clusters contribute to a greater understanding of the biological mechanisms that mediate choice and decision-making. The paper concludes that OCN research has already provided important insights regarding the boundaries surrounding human freedom to act in various domains and, in turn, self-determination to influence the workplace. However, there is much to be done, and emerging research of significant interest is highlighted.

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Decision-making in product quality is an indispensable stage in product development, in order to reduce product development risk. Based on the identification of the deficiencies of quality function deployment (QFD) and failure modes and effects analysis (FMEA), a novel decision-making method is presented that draws upon a knowledge network of failure scenarios. An ontological expression of failure scenarios is presented together with a framework of failure knowledge network (FKN). According to the roles of quality characteristics (QCs) in failure processing, QCs are set into three categories namely perceptible QCs, restrictive QCs, and controllable QCs, which present the monitor targets, control targets and improvement targets respectively for quality management. A mathematical model and algorithms based on the analytic network process (ANP) is introduced for calculating the priority of QCs with respect to different development scenarios. A case study is provided according to the proposed decision-making procedure based on FKN. This methodology is applied in the propeller design process to solve the problem of prioritising QCs. This paper provides a practical approach for decision-making in product quality. Copyright © 2011 Inderscience Enterprises Ltd.