672 resultados para Prediction theory
Resumo:
Enterprise social networks provide benefits especially for knowledge-intensive work as they enable communication, collaboration and knowledge exchange. These platforms should therefore lead to increased adoption and use by knowledge-intensive workers such as consultants or indeed researchers. Our interest is in ascertaining whether scientific researchers use enterprise social networks as part of their work practices. This focus is motivated by an apparent schism between a need for researchers to exchange knowledge and profile themselves, and the aversion to sharing breakthrough ideas and joining in an ever-increasing publishing and marketing game. We draw on research on academic work practices and impression management to develop a model of academics’ ESN usage for impression management tactics. We describe important constructs of our model, offer strategies for their operationalization and give an outlook to our ongoing empirical study of the use of an ESN platform by 20 schools across six faculties at an Australian university.
Resumo:
I develop a model of individuals’ intentions to discontinue information system use. Understanding these intentions is important because they give insights into users’ willingness to carry out system tasks, and provide a basis for maintenance decisions as well as possible replacement decisions. I offer a first conceptualization of factors determining users’ discontinuance intentions on basis of existing literature on technology use, status quo bias and dual factor concepts. The model is grounded in rational choice theory to distinguish determinants of a conscious decision between continuing or discontinuing IS use. I provide details on the empirical test of the model through a field study of IS users in a retail organization. The work will have implications for theory on information systems continuance and dual-factor logic in information system use. The empirical findings will provide suggestions for managers dealing with cessation of information systems and work routine changes in organizations.
Resumo:
There is a general perception that public confidence in the insolvency profession is low as the result of the recent unethical practices of a few high profile liquidators. As a result, the effectiveness of the current regulatory mechanisms has been questioned, leading to a review of the performance of insolvency practitioners and subsequent regulation proposals. The challenge for the insolvency profession is balancing the expectations of the general public whilst ensuring that the obligations and duties imposed upon them are performed to acceptable and realistic standards. It is difficult (if not impossible) for the profession to meet this challenge in the absence of a cohesive framework which identifies those issues that require further regulation as opposed to those that relate to general education on the insolvency process. This paper will examine the audit expectations gap theory in the context of insolvency practitioners and suggests that a model based on this theory provides an effective framework for evaluating the regulation of the insolvency industry.
Resumo:
This thesis examines the question why the automotive mode and the large technological system it creates, continues to dominate urban transport systems despite the availability of more cost-efficient alternatives. A number of theoretical insights are developed into the way these losses evolve from path dependent growth, and lead to market failure and lock-in. The important role of asymmetries of influence is highlighted. A survey of commuters in Jakarta Indonesia is used to provide a measure of transport modal lock-in (TML) in a developing country conurbation. A discrete choice experiment is used to provide evidence for the thesis central hypothesis that in such conurbations there is a high level of commuter awareness of the negative externalities generated by TML which can produce a strong level of support for its reversal. Why TML nevertheless remains a strong and durable feature of the transport system is examined with reference to the role of asymmetries of influence.
Resumo:
This article responds to the invitation extended by Carney to engage in a dialogue on the topic of graduate legal research units. In his paper, Carney stated the approach of the Sydney course as being to teach theory rather than skills, to "pursue academic goals over skill competencies... ". The Faculty of Law at Queensland University of Technology introduced a postgraduate legal research unit in 1993 with different perspectives and purposes to the Sydney course, and given this experience, the opportunity for a discussion on aspects of such units including the theoretical versus practical approach to teaching cannot be ignored.
Resumo:
Objectives Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Design Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Methods Eleven children aged 3–6 years (mean age = 4.8 ± 0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Results Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Conclusions Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children.
Resumo:
The functions of the volunteer functions inventory were combined with the constructs of the theory of planned behaviour (i.e., attitudes, subjective norms, and perceived behavioural control) to establish whether a stronger, single explanatory model prevailed. Undertaken in the context of episodic, skilled volunteering by individuals who were retired or approaching retirement (N = 186), the research advances on prior studies which either examined the predictive capacity of each model independently or compared their explanatory value. Using hierarchical regression analysis, the functions of the volunteer functions inventory (when controlling for demographic variables) explained an additional 7.0% of variability in individuals’ willingness to volunteer over and above that accounted for by the theory of planned behaviour. Significant predictors in the final model included attitudes, subjective norms and perceived behavioural control from the theory of planned behaviour and the understanding function from the volunteer functions inventory. It is proposed that the items comprising the understanding function may represent a deeper psychological construct (e.g., self-actualisation) not accounted for by the theory of planned behaviour. The findings highlight the potential benefit of combining these two prominent models in terms of improving understanding of volunteerism and providing a single parsimonious model for raising rates of this important behaviour.
Resumo:
This paper uses transaction cost theory to study cloud computing adoption. A model is developed and tested with data from an Australian survey. According to the results, perceived vendor opportunism and perceived legislative uncertainty around cloud computing were significantly associated with perceived cloud computing security risk. There was also a significant negative relationship between perceived cloud computing security risk and the intention to adopt cloud services. This study also reports on adoption rates of cloud computing in terms of applications, as well as the types of services used.
Resumo:
The wave of democratisation across Europe, Africa, Asia and Latin America in the early 1990s triggered an increase in donor funding to media assistance initiatives, primarily within good governance policy frameworks. However, few media assistance projects have managed to effectively evaluate the impacts of their work. This thesis explores how the impacts of Australian media assistance on social change and governance can be most effectively evaluated and understood. The findings of this research suggest the importance of early investment in participatory planning of evaluation designs, which are then periodically revisited. These evaluation designs should be based on a theoretically sound link between models of change, evaluative questions and methods.
Resumo:
The phenomenon which dialogism addresses is human interaction. It enables us to conceptualise human interaction as intersubjective, symbolic, cultural, transformative and conflictual, in short, as complex. The complexity of human interaction is evident in all domains of human life, for example, in therapy, education, health intervention, communication, and coordination at all levels. A dialogical approach starts by acknowledging that the social world is perspectival, that people and groups inhabit different social realities. This book stands apart from the proliferation of recent books on dialogism, because rather than applying dialogism to this or that domain, the present volume focuses on dialogicality itself to interrogate the concepts and methods which are taken for granted in the burgeoning literature.
Resumo:
Introduction: Ten years after the publication of Elaborated Intrusion (EI) Theory, there is now substantial research into its key predictions. The distinction between intrusive thoughts, which are driven by automatic processes, and their elaboration, involving controlled processing, is well established. Desires for both addictive substances and other desired targets are typically marked by imagery, especially when they are intense. Attention training strategies such as body scanning reduce intrusive thoughts, while concurrent tasks that introduce competing sensory information interfere with elaboration, especially if they compete for the same limited-capacity working memory resources. Conclusion: EI Theory has spawned new assessment instruments that are performing strongly and offer the ability to more clearly delineate craving from correlated processes. It has also inspired new approaches to treatment. In particular, training people to use vivid sensory imagery for functional goals holds promise as an intervention for substance misuse, since it is likely to both sustain motivation and moderate craving.
Resumo:
Background and Aims Research into craving is hampered by lack of theoretical specification and a plethora of substance-specific measures. This study aimed to develop a generic measure of craving based on elaborated intrusion (EI) theory. Confirmatory factor analysis (CFA) examined whether a generic measure replicated the three-factor structure of the Alcohol Craving Experience (ACE) scale over different consummatory targets and time-frames. Design Twelve studies were pooled for CFA. Targets included alcohol, cigarettes, chocolate and food. Focal periods varied from the present moment to the previous week. Separate analyses were conducted for strength and frequency forms. Setting Nine studies included university students, with single studies drawn from an internet survey, a community sample of smokers and alcohol-dependent out-patients. Participants A heterogeneous sample of 1230 participants. Measurements Adaptations of the ACE questionnaire. Findings Both craving strength [comparative fit indices (CFI = 0.974; root mean square error of approximation (RMSEA) = 0.039, 95% confidence interval (CI) = 0.035–0.044] and frequency (CFI = 0.971, RMSEA = 0.049, 95% CI = 0.044–0.055) gave an acceptable three-factor solution across desired targets that mapped onto the structure of the original ACE (intensity, imagery, intrusiveness), after removing an item, re-allocating another and taking intercorrelated error terms into account. Similar structures were obtained across time-frames and targets. Preliminary validity data on the resulting 10-item Craving Experience Questionnaire (CEQ) for cigarettes and alcohol were strong. Conclusions The Craving Experience Questionnaire (CEQ) is a brief, conceptually grounded and psychometrically sound measure of desires. It demonstrates a consistent factor structure across a range of consummatory targets in both laboratory and clinical contexts.
Resumo:
We compare three alternative methods for eliciting retrospective confidence in the context of a simple perceptual task: the Simple Confidence Rating (a direct report on a numerical scale), the Quadratic Scoring Rule (a post-wagering procedure), and the Matching Probability (MP; a generalization of the no-loss gambling method). We systematically compare the results obtained with these three rules to the theoretical confidence levels that can be inferred from performance in the perceptual task using Signal Detection Theory (SDT). We find that the MP provides better results in that respect. We conclude that MP is particularly well suited for studies of confidence that use SDT as a theoretical framework.
Resumo:
We propose expected attainable discrimination (EAD) as a measure to select discrete valued features for reliable discrimination between two classes of data. EAD is an average of the area under the ROC curves obtained when a simple histogram probability density model is trained and tested on many random partitions of a data set. EAD can be incorporated into various stepwise search methods to determine promising subsets of features, particularly when misclassification costs are difficult or impossible to specify. Experimental application to the problem of risk prediction in pregnancy is described.
Resumo:
We propose and mathematically examine a theory of calcium profile formation in unwounded mammalian epidermis based on: changes in keratinocyte proliferation, fluid and calcium exchange with the extracellular fluid during these cells' passage through the epidermal sublayers, and the barrier functions of both the stratum corneum and tight junctions localised in the stratum granulosum. Using this theory, we develop a mathematical model that predicts epidermal sublayer transit times, partitioning of the epidermal calcium gradient between intracellular and extracellular domains, and the permeability of the tight junction barrier to calcium ions. Comparison of our model's predictions of epidermal transit times with experimental data indicates that keratinocytes lose at least 87% of their volume during their disintegration to become corneocytes. Intracellular calcium is suggested as the main contributor to the epidermal calcium gradient, with its distribution actively regulated by a phenotypic switch in calcium exchange between keratinocytes and extracellular fluid present at the boundary between the stratum spinosum and the stratum granulosum. Formation of the extracellular calcium distribution, which rises in concentration through the stratum granulosum towards the skin surface, is attributed to a tight junction barrier in this sublayer possessing permeability to calcium ions that is less than 15 nm/s in human epidermis and less than 37 nm/s in murine epidermis. Future experimental work may refine the presented theory and reduce the mathematical uncertainty present in the model predictions.