108 resultados para data-driven decision making

em University of Queensland eSpace - Australia


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This study investigates the direct and indirect effects of financial participation (FP) and participation in decision-making (PDM) on employee job attitudes. The central premise is that both financial participation and participation in decision-making have effects on job attitudes, such as integration, involvement and commitment, perceived pay equity, performance-reward contingencies, satisfaction and motivation. After reviewing the theoretical and empirical literature and testing two theoretical frameworks, developed by Long (1978a) and Florkowski ( 1989), a new model was constructed to consider a combined effects of both FP and PDM, herein referred to as employee participation (EP). The underpinning of the model is based on the assumption that both ( a) the combination of financial participation and participation in decision-making ('employee participation'), and (b) participation in decision-making produce favourable effects on employee job attitudes. The test of the new model showed that employee participation does not produce more favourable effects on employee job attitudes, than does participation in decision-making on its own. The data were gathered from a questionnaire study administered in a large British retail organization that operates two types of ownership schemes - profit-sharing and SAYE schemes.

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Fundamental principles of precaution are legal maxims that ask for preventive actions, perhaps as contingent interim measures while relevant information about causality and harm remains unavailable, to minimize the societal impact of potentially severe or irreversible outcomes. Such principles do not explain how to make choices or how to identify what is protective when incomplete and inconsistent scientific evidence of causation characterizes the potential hazards. Rather, they entrust lower jurisdictions, such as agencies or authorities, to make current decisions while recognizing that future information can contradict the scientific basis that supported the initial decision. After reviewing and synthesizing national and international legal aspects of precautionary principles, this paper addresses the key question: How can society manage potentially severe, irreversible or serious environmental outcomes when variability, uncertainty, and limited causal knowledge characterize their decision-making? A decision-analytic solution is outlined that focuses on risky decisions and accounts for prior states of information and scientific beliefs that can be updated as subsequent information becomes available. As a practical and established approach to causal reasoning and decision-making under risk, inherent to precautionary decision-making, these (Bayesian) methods help decision-makers and stakeholders because they formally account for probabilistic outcomes, new information, and are consistent and replicable. Rational choice of an action from among various alternatives-defined as a choice that makes preferred consequences more likely-requires accounting for costs, benefits and the change in risks associated with each candidate action. Decisions under any form of the precautionary principle reviewed must account for the contingent nature of scientific information, creating a link to the decision-analytic principle of expected value of information (VOI), to show the relevance of new information, relative to the initial ( and smaller) set of data on which the decision was based. We exemplify this seemingly simple situation using risk management of BSE. As an integral aspect of causal analysis under risk, the methods developed in this paper permit the addition of non-linear, hormetic dose-response models to the current set of regulatory defaults such as the linear, non-threshold models. This increase in the number of defaults is an important improvement because most of the variants of the precautionary principle require cost-benefit balancing. Specifically, increasing the set of causal defaults accounts for beneficial effects at very low doses. We also show and conclude that quantitative risk assessment dominates qualitative risk assessment, supporting the extension of the set of default causal models.

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Two studies in the context of English-French relations in Québec suggest that individuals who strongly identify with a group derive the individual-level costs and benefits that drive expectancy-value processes (rational decision-making) from group-level costs and benefits. In Study 1, high identifiers linked group- and individual-level outcomes of conflict choices whereas low identifiers did not. Group-level expectancy-value processes, in Study 2, mediated the relationship between social identity and perceptions that collective action benefits the individual actor and between social identity and intentions to act. These findings suggest the rational underpinnings of identity-driven political behavior, a relationship sometimes obscured in intergroup theory that focuses on cognitive processes of self-stereotyping. But the results also challenge the view that individuals' cost-benefit analyses are independent of identity processes. The findings suggest the importance of modeling the relationship of group and individual levels of expectancy-value processes as both hierarchical and contingent on social identity processes

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The purpose of this study was to identify, through in-depth interview, factors that influenced 27 Hong Kong Chinese patients' decision-making in seeking early treatment for acute myocardial infarction (AMI). The median delay time from the onset of symptoms to arrival at the hospital was 15.6 hours for men and 53.7 hours for women. Three major categories emerged from the data: (a) becoming aware of the threat, (b) maintaining a sense of normality, and (c) struggling to mobilize resources. A variety of decisions were made by patients from the onset of chest Pain to seeking help. These decisions were heavily influenced by healthcare factors (access to emergency medical service (EMS) and treatment), personal factors (cognitive interpretations of symptoms), sociocultural factors (family situation, cultural beliefs, and practices), and coping strategies. (c) 2006 Wiley Periodicals, Inc.

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There have been many models developed by scientists to assist decision-makers in making socio-economic and environmental decisions. It is now recognised that there is a shift in the dominant paradigm to making decisions with stakeholders, rather than making decisions for stakeholders. Our paper investigates two case studies where group model building has been undertaken for maintaining biodiversity in Australia. The first case study focuses on preservation and management of green spaces and biodiversity in metropolitan Melbourne under the umbrella of the Melbourne 2030 planning strategy. A geographical information system is used to collate a number of spatial datasets encompassing a range of cultural and natural assets data layers including: existing open spaces, waterways, threatened fauna and flora, ecological vegetation covers, registered cultural heritage sites, and existing land parcel zoning. Group model building is incorporated into the study through eliciting weightings and ratings of importance for each datasets from urban planners to formulate different urban green system scenarios. The second case study focuses on modelling ecoregions from spatial datasets for the state of Queensland. The modelling combines collaborative expert knowledge and a vast amount of environmental data to build biogeographical classifications of regions. An information elicitation process is used to capture expert knowledge of ecoregions as geographical descriptions, and to transform this into prior probability distributions that characterise regions in terms of environmental variables. This prior information is combined with measured data on the environmental variables within a Bayesian modelling technique to produce the final classified regions. We describe how linked views between descriptive information, mapping and statistical plots are used to decide upon representative regions that satisfy a number of criteria for biodiversity and conservation. This paper discusses the advantages and problems encountered when undertaking group model building. Future research will extend the group model building approach to include interested individuals and community groups.

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This paper reports on a current research project in which virtual reality simulators are being investigated as a means of simulating hazardous Rail work conditions in order to allow train drivers to practice decision-making under stress. When working under high stress conditions train drivers need to move beyond procedural responses into a response activated through their own problem-solving and decision-making skills. This study focuses on the use of stress inoculation training which aims to build driver’s confidence in the use of new decision-making skills by being repeatedly required to respond to hazardous driving conditions. In particular, the study makes use of a train cab driving simulator to reproduce potentially stress inducing real-world scenarios. Initial pilot research has been undertaken in which drivers have experienced the training simulation and subsequently completed surveys on the level of immersion experienced. Concurrently drivers have also participated in a velocity perception experiment designed to objectively measure the fidelity of the virtual training environment. Baseline data, against which decision-making skills post training will be measured, is being gathered via cognitive task analysis designed to identify primary decision requirements for specific rail events. While considerable efforts have been invested in improving Virtual Reality technology, little is known about how to best use this technology for training personnel to respond to workplace conditions in the Rail Industry. To enable the best use of simulators for training in the Rail context the project aims to identify those factors within virtual reality that support required learning outcomes and use this information to design training simulations that reliably and safely train staff in required workplace accident response skills.

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Faced with today’s ill-structured business environment of fast-paced change and rising uncertainty, organizations have been searching for management tools that will perform satisfactorily under such ambiguous conditions. In the arena of managerial decision making, one of the approaches being assessed is the use of intuition. Based on our definition of intuition as a non-sequential information-processing mode, which comprises both cognitive and affective elements and results in direct knowing without any use of conscious reasoning, we develop a testable model of integrated analytical and intuitive decision making and propose ways to measure the use of intuition.

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This study was designed to test the utility of a revised theory of planned behavior in the prediction of intentions to volunteer among older people. Such a perspective allowed for the consideration of a broader range of social and contextual factors than has been examined in previous research on volunteer decision making among older people. The article reports the findings from a study that investigated volunteer intentions and behavior in a random sample of older people aged 65 to 74 years living in an Australian capital city. Results showed that, as predicted by the revised theory of planned behavior, intention to volunteer predicted subsequent reported volunteer behavior. Intention was, in turn, predicted by social norms (both subjective and behavioral), perceived behavioral control, and moral obligation, with the effect of attitude being mediated through moral obligation.

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A chance constrained programming model is developed to assist Queensland barley growers make varietal and agronomic decisions in the face of changing product demands and volatile production conditions. Unsuitable or overlooked in many risk programming applications, the chance constrained programming approach nonetheless aptly captures the single-stage decision problem faced by barley growers of whether to plant lower-yielding but potentially higher-priced malting varieties, given a particular expectation of meeting malting grade standards. Different expectations greatly affect the optimal mix of malting and feed barley activities. The analysis highlights the suitability of chance constrained programming to this specific class of farm decision problem.

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Research investigating the role of stereotypes in jury decision-making has typically considered stereotypes as acting as peripheral cues in determin ing the credibility of experts or likelihood of guilt of defendants — with counter-stereotypic courtroom participants faring less well. The present study investigated the possibility that the extent to which courtroom participants are stereotypic can alter the mode of information processing. Students (N = 78) read a transcript of a case in which either a male or female allegedly committed an armed robbery. As predicted, the female counter-stereotypic defendant was distracting and effortful processing only occurred when the defendant was male. The male was seen as more guilty and the prosecution's case was more convincing when the prosecution had a strong, but not weak, case. There were no effects of case strength for the female defendant. Results are discussed in terms of the role of stereotypes in the jury decision-making.

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