1000 resultados para Decision traps
Resumo:
A wide range of decision-making models have been offered to assist in making ethical decisions in the workplace. Those that are based on normative moral frameworks typically include elements of traditional moral philosophy such as consequentialist and/or deontological␣ethics. This paper suggests an alternative model drawing on Jean-Paul Sartre’s existentialism. Accordingly, the model focuses on making decisions in full awareness of one’s freedom and responsibility. The steps of the model are intended to encourage reflection of one’s projects and one’s situation and the possibility of refusing the expectations of others. A case study involving affirmative action in South Africa is used to demonstrate the workings of the model and a number of strengths and weaknesses are identified. Despite several weaknesses that can be raised regarding existential ethics, the model’s success lies in the way that it reframes ethical dilemmas in terms of individual freedom and responsibility, and in its acceptance and analysis of subjective experiences and personal situations
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This chapter examines the challenges and opportunities associated with planning for competitive, smart and healthy cities. The chapter is based on the assumptions that a healthy city is an important prerequisite for a competitive city and a fundamental outcome of smart cities. Thus, it is preeminent to understand the planning decision support system based on local determinants of health, economic and social factors. One of the major decision support systems is e-health and this chapter will focus on the role of e-health planning, by utilising web-based geographic decision support systems. The proposed novel decision support system would provide a powerful and effective platform for stakeholders to access online information for a better decision-making while empowering community participation. The chapter also highlights the need for a comprehensive conceptual framework to guide the decision process of planning for healthy cities in association with opportunities and limitations. In summary, this chapter provides the critical insights of using information science-based framework and suggest online decision support methods, as part of a broader e-health approach for creating a healthy, competitive and smart city.
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The aim of this thesis is to examine how risk tolerance and risk perception, two important but often misunderstood constructs, jointly influence client investment decisions in a financial advice context. By distinguishing the roles of these two risk constructs in client decision-making, in this thesis a new direction in studying financial/investment risks is provided while practice and regulation in the financial services industry is potentially informed. Based on the literature relating to risks and individual decision-making, a theoretical framework is developed and relevant hypotheses are tested in two studies with financial adviser clients in Australia. Results reveal that financial risk tolerance influences asset allocation both directly and indirectly through risk perception. The intervening role of risk perception suggests that risk tolerance affects how clients perceive the riskiness of an investment product which influences client decision-making.
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This paper details the design and performance assessment of a unique collision avoidance decision and control strategy for autonomous vision-based See and Avoid systems. The general approach revolves around re-positioning a collision object in the image using image-based visual servoing, without estimating range or time to collision. The decision strategy thus involves determining where to move the collision object, to induce a safe avoidance manuever, and when to cease the avoidance behaviour. These tasks are accomplished by exploiting human navigation models, spiral motion properties, expected image feature uncertainty and the rules of the air. The result is a simple threshold based system that can be tuned and statistically evaluated by extending performance assessment techniques derived for alerting systems. Our results demonstrate how autonomous vision-only See and Avoid systems may be designed under realistic problem constraints, and then evaluated in a manner consistent to aviation expectations.
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Objectives Demonstrate the application of decision trees – classification and regression trees (CARTs), and their cousins, boosted regression trees (BRTs) – to understand structure in missing data. Setting Data taken from employees at three different industry sites in Australia. Participants 7915 observations were included. Materials and Methods The approach was evaluated using an occupational health dataset comprising results of questionnaires, medical tests, and environmental monitoring. Statistical methods included standard statistical tests and the ‘rpart’ and ‘gbm’ packages for CART and BRT analyses, respectively, from the statistical software ‘R’. A simulation study was conducted to explore the capability of decision tree models in describing data with missingness artificially introduced. Results CART and BRT models were effective in highlighting a missingness structure in the data, related to the Type of data (medical or environmental), the site in which it was collected, the number of visits and the presence of extreme values. The simulation study revealed that CART models were able to identify variables and values responsible for inducing missingness. There was greater variation in variable importance for unstructured compared to structured missingness. Discussion Both CART and BRT models were effective in describing structural missingness in data. CART models may be preferred over BRT models for exploratory analysis of missing data, and selecting variables important for predicting missingness. BRT models can show how values of other variables influence missingness, which may prove useful for researchers. Conclusion Researchers are encouraged to use CART and BRT models to explore and understand missing data.
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This is an ongoing research investigating the use of health information technologies (HIT) to improve clinical decision-making processes. Effective and timely clinical decision-making can lead to positive improvements in patient’s health outcome...
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The cognitive benefits of biophilia have been studied quite extensively, dating as far back as the 1980s, while studies into economic benefits are still in their infancy. Recent research has attempted to quantify a number of economic returns on biophilic elements; however knowledge in this field is still ad hoc and highly variable. Many studies acknowledge difficulties in discerning information such as certain social and aesthetic benefits. While conceptual understanding of the physiological and psychological effects of exposure to nature is widely recognised and understood, this has not yet been systematically translated into monetary terms. It is clear from the literature that further research is needed to both obtain data on the economics of biophilic urbanism, and to create the business case for biophilic urbanism. With this in mind, this paper will briefly highlight biophilic urbanism referencing previous work in the field. It will then explore a number of emergent gaps in the measurable economic understanding of these elements and suggest opportunities for engaging decision makers in the business case for biophilic urbanism. The paper concludes with recommendations for moving forward through targeted research and economic analysis.
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This chapter explains how customers make purchase decisions and how these decisions are influenced not only by the service marketer but also by the customers own emotions. While decision-making is described from the perspective of purchasing services rather than purchasing goods, we challenge the traditional notion that customers make informed, rational and well-thought-out decisions. Rather customers are often driven by subjective feelings such as emotions. We present evidence of how these emotions influence the behavior of customers, their attitudes and evaluation of the service, as well as final decision-making processes.
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Scenario planning is a method widely used by strategic planners to address uncertainty about the future. However, current methods either fail to address the future behaviour and impact of stakeholders or they treat the role of stakeholders informally. We present a practical decision-analysis-based methodology for analysing stakeholder objectives and likely behaviour within contested unfolding futures. We address issues of power, interest, and commitment to achieve desired outcomes across a broad stakeholder constituency. Drawing on frameworks for corporate social responsibility (CSR), we provide an illustrative example of our approach to analyse a complex contested issue that crosses geographic, organisational and cultural boundaries. Whilst strategies can be developed by individual organisations that consider the interests of others – for example in consideration of an organisation's CSR agenda – we show that our augmentation of scenario method provides a further, nuanced, analysis of the power and objectives of all concerned stakeholders across a variety of unfolding futures. The resulting modelling framework is intended to yield insights and hence more informed decision making by individual stakeholders or regulators.
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When a household welcomes a new infant a transformation occurs whereby household routines, values and decisions change. This research explores how decision-making is influenced by fluctuating identity subjectivities. We explore longitudinally, using a family identity framework, how the transitioning between self, couple and family self-identities influences the decisions made regarding social issues, in this case infant feeding. Results indicate that decision-making during a period of transformation is not straightforward, relying on a multiplicity of identities that are constantly renegotiated and dependent on other influences. Decisions made conform to the identity-construct-of-the-moment, but are fluid and subject to change, such that pinpointing causal pathways is inappropriate. Implications for influencing the consumption of social behaviors for consumer researchers are one size does not fit all and require an in-depth understanding of the fluidity of decision-making. Consequently, social marketing strategies need to be tailored to constructed identities and flexible across time to remain influential.
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The High Court of Australia’s ruling on the plain packaging of tobacco products is one of the great constitutional cases of our age. The ruling will resonate throughout the world - as other countries will undoubtedly seek to emulate Australia’s plain packaging regime.
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Engineers and asset managers must often make decisions on how to best allocate limited resources amongst different interrelated activities, including repair, renewal, inspection, and procurement of new assets. The presence of project interdependencies and the lack of sufficient information on the true value of an activity often produce complex problems and leave the decision maker guessing about the quality and robustness of their decision. In this paper, a decision support framework for uncertain interrelated activities is presented. The framework employs a methodology for multi-criteria ranking in the presence of uncertainty, detailing the effect that uncertain valuations may have on the priority of a particular activity. The framework employs employing semi-quantitative risk measures that can be tailored to an organisation and enable a transparent and simple-to-use uncertainty specification by the decision maker. The framework is then demonstrated on a real world project set from a major Australian utility provider.
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The need for better and more accurate assessments of testamentary and decision-making capacity grows as Australian society ages and incidences of mentally disabling conditions increase. Capacity is a legal determination, but one on which medical opinion is increasingly being sought. The difficulties inherent within capacity assessments are exacerbated by the ad hoc approaches adopted by legal and medical professionals based on individual knowledge and skill, as well as the numerous assessment paradigms that exist. This can negatively affect the quality of assessments, and results in confusion as to the best way to assess capacity. This article begins by assessing the nature of capacity. The most common general assessment models used in Australia are then discussed, as are the practical challenges associated with capacity assessment. The article concludes by suggesting a way forward to satisfactorily assess legal capacity given the significant ramifications of getting it wrong.
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In recent years accounting education has seen numerous changes to the way financial accounting is taught. These changes reflect the demands of an ever-changing business world, opportunities created by new technology and instructional technologies, and an increased understanding of how students learn. The foundation of Financial Accounting is based on a number of unique principles and innovations in accounting education. The objective of Financial Accounting is to provide students with an understanding of those concepts that are fundamental to the preparation and use of accounting information. Most students will forget procedural details within a short period of time. On the other hand, concepts, if well taught, should be remembered for a lifetime. Concepts are especially important in a world where the details are constantly changing. Students learn best when they are actively engaged. The overriding pedagogical objective of Financial Accounting is to provide students with continual opportunities for active learning. One of the best tools for active learning is strategically placed questions. Discussions are framed by questions, often beginning with rhetorical questions and ending with review questions, and our analytical devices, called decision-making toolkits, use key questions to demonstrate the purpose of each.
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We consider the problem of controlling a Markov decision process (MDP) with a large state space, so as to minimize average cost. Since it is intractable to compete with the optimal policy for large scale problems, we pursue the more modest goal of competing with a low-dimensional family of policies. We use the dual linear programming formulation of the MDP average cost problem, in which the variable is a stationary distribution over state-action pairs, and we consider a neighborhood of a low-dimensional subset of the set of stationary distributions (defined in terms of state-action features) as the comparison class. We propose a technique based on stochastic convex optimization and give bounds that show that the performance of our algorithm approaches the best achievable by any policy in the comparison class. Most importantly, this result depends on the size of the comparison class, but not on the size of the state space. Preliminary experiments show the effectiveness of the proposed algorithm in a queuing application.