18 resultados para Model Making
em University of Queensland eSpace - Australia
Intuitive and analytical decision-making in a high risk industry: Development and testing of a model
Resumo:
The interplay between two perspectives that have recently been applied in the attitude area-the social identity approach to attitude-behaviour relations (Terry & Hogg, 1996) and the MODE model (Fazio, 1990a)-was examined in the present research. Two experimental studies were conducted to examine the role of group norms, group identification, attitude accessibility, and mode of behavioural decision-making in the attitude-behaviour relationship. In Study I (N = 211), the effects of norms and identification on attitude-behaviour consistency as a function of attitude accessibility and mood were investigated. Study 2 (N = 354) replicated and extended the first experiment by using time pressure to manipulate mode of behavioural decision-making. As expected, the effects of norm congruency varied as a function of identification and mode of behavioural decision-making. Under conditions assumed to promote deliberative processing (neutral mood/low time pressure), high identifiers behaved in a manner consistent with the norm. No effects emerged under positive mood and high time pressure conditions. In Study 2, there was evidence that exposure to an attitude-incongruent norm resulted in attitude change only under low accessibility conditions. The results of these studies highlight the powerful role of group norms in directing individual behaviour and suggest limited support for the MODE model in this context. Copyright (C) 2003 John Wiley Sons, Ltd.
Resumo:
Identifying inequities in access to health care requires critical scrutiny of the patterns and processes of care decisions. This paper describes a conceptual model. derived from social problems theory. which is proposed as a useful framework for explaining patterns of post-acute care referral and in particular, individual variations in referral to rehabilitation after traumatic brain injury (TBI). The model is based on three main components: (1) characteristics of the individual with TBI, (2) activities of health care professionals and the processes of referral. and (3) the contexts of care. The central argument is that access to rehabilitation following TBI is a dynamic phenomenon concerning the interpretations and negotiations of health care professionals. which in turn are shaped by the organisational and broader health care contexts. The model developed in this paper provides opportunity to develop a complex analysis of post-acute care referral based on patient factors, contextual factors and decision-making processes. It is anticipated that this framework will have utility in other areas examining and understanding patterns of access to health care. (C) 2002 Elsevier Science Ltd. All rights reserved.
Resumo:
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.
Resumo:
The study aimed to examine the factors influencing referral to rehabilitation following traumatic brain injury (TBI) by using social problems theory as a conceptual model to focus on practitioners and the process of decision-making in two Australian hospitals. The research design involved semi-structured interviews with 18 practitioners and observations of 10 team meetings, and was part of a larger study on factors influencing referral to rehabilitation in the same settings. Analysis revealed that referral decisions were influenced primarily by practitioners' selection and their interpretation of clinical and non-clinical patient factors. Further, practitioners generally considered patient factors concurrently during an ongoing process of decision-making, with the combinations and interactions of these factors forming the basis for interpretations of problems and referral justifications. Key patient factors considered in referral decisions included functional and tracheostomy status, time since injury, age, family, place of residence and Indigenous status. However, rate and extent of progress, recovery potential, safety and burden of care, potential for independence and capacity to cope were five interpretative themes, which emerged as the justifications for referral decisions. The subsequent negotiation of referral based on patient factors was in turn shaped by the involvement of practitioners. While multi-disciplinary processes of decision-making were the norm, allied health professionals occupied a central role in referral to rehabilitation, and involvement of medical, nursing and allied health practitioners varied. Finally, the organizational pressures and resource constraints, combined with practitioners' assimilation of the broader efficiency agenda were central factors shaping referral. (C) 2004 Elsevier Ltd. All rights reserved.
Resumo:
This study explored the nature of two construals of meaning, benefit finding and sense making, in parents of a child with Asperger syndrome, and examined relations between both meaning constructs and the Double ABCX family stress model variables (initial stressor and pile-up of demands, appraisal, social support, coping strategies and adjustment) [H.I. McCubbin, J.M. Patterson, Social Stress and the Family: Advances and Developments in Family Stress Theory and Research, Haworth, New York, 1983, pp. 7-37]. A total of 59 parents completed questionnaires. Content analyses of parents' responses to questions inquiring about gains and sense making explanations revealed 8 benefit and 12 sense making themes. Results of correlations indicated that one or more of the meaning variables were related to each of the Double ABCX model predictors of parental adjustment. The meaning variables were positively related to adaptive coping processes: social support, self-efficacy, and problem-focused and emotional approach coping strategies. (C) 2004 Elsevier Ltd. All rights reserved.
Resumo:
We tested a social-cognitive intervention to influence contraceptive practices among men living in rural communes in Vietnam. It was predicted that participants who received a stage-targeted program based on the Transtheoretical Model (TTM) would report positive movement in their stage of motivational readiness for their wife to use an intrauterine device (IUD) compared to those in a control condition. A quasi-experimental design was used, where the primary unit for allocation was villages. Villages were allocated randomly to a control condition or to two rounds of intervention with stage-targeted letters and interpersonal counseling. There were 651 eligible married men in the 12 villages chosen. A significant positive movement in men's stage of readiness for IUD use by their wife occurred in the intervention group, with a decrease in the proportions in the precontemplation stage from 28.6 to 20.2% and an increase in action/maintenance from 59.8 to 74.4% (P < 0.05). There were no significant changes in the control group. Compared to the control group, the intervention group showed higher pros, lower cons and higher self-efficacy for IUD use by their wife as a contraceptive method (P < 0.05). Interventions based on social-cognitive theory can increase men's involvement in IUD use in rural Vietnam and should assist in reducing future rates of unwanted pregnancy.
Resumo:
A calibration methodology based on an efficient and stable mathematical regularization scheme is described. This scheme is a variant of so-called Tikhonov regularization in which the parameter estimation process is formulated as a constrained minimization problem. Use of the methodology eliminates the need for a modeler to formulate a parsimonious inverse problem in which a handful of parameters are designated for estimation prior to initiating the calibration process. Instead, the level of parameter parsimony required to achieve a stable solution to the inverse problem is determined by the inversion algorithm itself. Where parameters, or combinations of parameters, cannot be uniquely estimated, they are provided with values, or assigned relationships with other parameters, that are decreed to be realistic by the modeler. Conversely, where the information content of a calibration dataset is sufficient to allow estimates to be made of the values of many parameters, the making of such estimates is not precluded by preemptive parsimonizing ahead of the calibration process. White Tikhonov schemes are very attractive and hence widely used, problems with numerical stability can sometimes arise because the strength with which regularization constraints are applied throughout the regularized inversion process cannot be guaranteed to exactly complement inadequacies in the information content of a given calibration dataset. A new technique overcomes this problem by allowing relative regularization weights to be estimated as parameters through the calibration process itself. The technique is applied to the simultaneous calibration of five subwatershed models, and it is demonstrated that the new scheme results in a more efficient inversion, and better enforcement of regularization constraints than traditional Tikhonov regularization methodologies. Moreover, it is argued that a joint calibration exercise of this type results in a more meaningful set of parameters than can be achieved by individual subwatershed model calibration. (c) 2005 Elsevier B.V. All rights reserved.
Resumo:
Calibration of a groundwater model requires that hydraulic properties be estimated throughout a model domain. This generally constitutes an underdetermined inverse problem, for which a Solution can only be found when some kind of regularization device is included in the inversion process. Inclusion of regularization in the calibration process can be implicit, for example through the use of zones of constant parameter value, or explicit, for example through solution of a constrained minimization problem in which parameters are made to respect preferred values, or preferred relationships, to the degree necessary for a unique solution to be obtained. The cost of uniqueness is this: no matter which regularization methodology is employed, the inevitable consequence of its use is a loss of detail in the calibrated field. This, ill turn, can lead to erroneous predictions made by a model that is ostensibly well calibrated. Information made available as a by-product of the regularized inversion process allows the reasons for this loss of detail to be better understood. In particular, it is easily demonstrated that the estimated value for an hydraulic property at any point within a model domain is, in fact, a weighted average of the true hydraulic property over a much larger area. This averaging process causes loss of resolution in the estimated field. Where hydraulic conductivity is the hydraulic property being estimated, high averaging weights exist in areas that are strategically disposed with respect to measurement wells, while other areas may contribute very little to the estimated hydraulic conductivity at any point within the model domain, this possibly making the detection of hydraulic conductivity anomalies in these latter areas almost impossible. A study of the post-calibration parameter field covariance matrix allows further insights into the loss of system detail incurred through the calibration process to be gained. A comparison of pre- and post-calibration parameter covariance matrices shows that the latter often possess a much smaller spectral bandwidth than the former. It is also demonstrated that, as all inevitable consequence of the fact that a calibrated model cannot replicate every detail of the true system, model-to-measurement residuals can show a high degree of spatial correlation, a fact which must be taken into account when assessing these residuals either qualitatively, or quantitatively in the exploration of model predictive uncertainty. These principles are demonstrated using a synthetic case in which spatial parameter definition is based oil pilot points, and calibration is Implemented using both zones of piecewise constancy and constrained minimization regularization. (C) 2005 Elsevier Ltd. All rights reserved.
Resumo:
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.
Resumo:
The Operator Choice Model (OCM) was developed to model the behaviour of operators attending to complex tasks involving interdependent concurrent activities, such as in Air Traffic Control (ATC). The purpose of the OCM is to provide a flexible framework for modelling and simulation that can be used for quantitative analyses in human reliability assessment, comparison between human computer interaction (HCI) designs, and analysis of operator workload. The OCM virtual operator is essentially a cycle of four processes: Scan Classify Decide Action Perform Action. Once a cycle is complete, the operator will return to the Scan process. It is also possible to truncate a cycle and return to Scan after each of the processes. These processes are described using Continuous Time Probabilistic Automata (CTPA). The details of the probability and timing models are specific to the domain of application, and need to be specified using domain experts. We are building an application of the OCM for use in ATC. In order to develop a realistic model we are calibrating the probability and timing models that comprise each process using experimental data from a series of experiments conducted with student subjects. These experiments have identified the factors that influence perception and decision making in simplified conflict detection and resolution tasks. This paper presents an application of the OCM approach to a simple ATC conflict detection experiment. The aim is to calibrate the OCM so that its behaviour resembles that of the experimental subjects when it is challenged with the same task. Its behaviour should also interpolate when challenged with scenarios similar to those used to calibrate it. The approach illustrated here uses logistic regression to model the classifications made by the subjects. This model is fitted to the calibration data, and provides an extrapolation to classifications in scenarios outside of the calibration data. A simple strategy is used to calibrate the timing component of the model, and the results for reaction times are compared between the OCM and the student subjects. While this approach to timing does not capture the full complexity of the reaction time distribution seen in the data from the student subjects, the mean and the tail of the distributions are similar.