994 resultados para Process Elicitation


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Business process models have traditionally been an effective way of examining business practices to identify areas for improvement. While common information gathering approaches are generally efficacious, they can be quite time consuming and have the risk of developing inaccuracies when information is forgotten or incorrectly interpreted by analysts. In this study, the potential of a role-playing approach for process elicitation and specification has been examined. This method allows stakeholders to enter a virtual world and role-play actions as they would in reality. As actions are completed, a model is automatically developed, removing the need for stakeholders to learn and understand a modelling grammar. Empirical data obtained in this study suggests that this approach may not only improve both the number of individual process task steps remembered and the correctness of task ordering, but also provide a reduction in the time required for stakeholders to model a process view.

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Business process models have become an effective way of examining business practices to identify areas for improvement. While common information gathering approaches are generally efficacious, they can be quite time consuming and have the risk of developing inaccuracies when information is forgotten or incorrectly interpreted by analysts. In this study, the potential of a role-playing approach to process elicitation and specification has been examined. This method allows stakeholders to enter a virtual world and role-play actions similarly to how they would in reality. As actions are completed, a model is automatically developed, removing the need for stakeholders to learn and understand a modelling grammar. An empirical investigation comparing both the modelling outputs and participant behaviour of this virtual world role-play elicitor with an S-BPM process modelling tool found that while the modelling approaches of the two groups varied greatly, the virtual world elicitor may not only improve both the number of individual process task steps remembered and the correctness of task ordering, but also provide a reduction in the time required for stakeholders to model a process view.

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Accurate process model elicitation continues to be a time consuming task, requiring skill on the part of the interviewer to extract explicit and tacit process information from the interviewee. Many errors occur in this elicitation stage that would be avoided by better activity recall, more consistent specification methods and greater engagement in the elicitation process by interviewees. Theories of situated cognition indicate that interactive 3D representations of real work environments engage and prime the cognitive state of the viewer. In this paper, our major contribution is to augment a previous process elicitation methodology with virtual world context metadata, drawn from a 3D simulation of the workplace. We present a conceptual and formal approach for representing this contextual metadata, integrated into a process similarity measure that provides hints for the business analyst to use in later modelling steps. Finally, we conclude with examples from two use cases to illustrate the potential abilities of this approach.

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Accurate process model elicitation continues to be a time consuming task, requiring skill on the part of the interviewer to extract explicit and tacit process information from the interviewee. Many errors occur in this elicitation stage that would be avoided by better activity recall, more consistent specification methods and greater engagement in the elicitation process by interviewees. Metasonic GmbH has developed a process elicitation tool for their process suite. As part of a research engagement with Metasonic, staff from QUT, Australia have developed a 3D virtual world approach to the same problem, viz. eliciting process models from stakeholders in an intuitive manner. This book chapter tells the story of how QUT staff developed a 3D Virtual World tool for process elicitation, took the outcomes of their research project to Metasonic for evaluation, and finally, Metasonic’s response to the initial proof of concept.

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We have developed a virtual world environment for eliciting expert information from stakeholders. The intention is that the virtual world prompts the user to remember more about their work processes. Our example shows a sparse visualisation of the University of Vienna Department of Computer Science, our collaborators in this project.

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This research investigated expertise in hazardous substance risk assessment (HSRA). Competent pro-active risk assessment is needed to prevent occupational ill-health caused by hazardous substance exposure occurring in the future. In recent years there has been a strong demand for HSRA expertise and a shortage of expert practitioners. The discipline of Occupational Hygiene was identified as the key repository of knowledge and skills for HSRA and one objective of this research was to develop a method to elicit this expertise from experienced occupational hygienists. In the study of generic expertise, many methods of knowledge elicitation (KE) have been investigated, since this has been relevant to the development of 'expert systems' (thinking computers). Here, knowledge needed to be elicited from human experts, and this stage was often a bottleneck in system development, since experts could not explain the basis of their expertise. At an intermediate stage, information collected was used to structure a basic model of hazardous substance risk assessment activity (HSRA Model B) and this formed the basis of tape transcript analysis in the main study with derivation of a 'classification' and a 'performance matrix'. The study aimed to elicit the expertise of occupational hygienists and compare their performance with other health and safety professionals (occupational health physicians, occupational health nurses, health and safety practitioners and trainee health and safety inspectors), as evaluated using the matrix. As a group, the hygienists performed best in the exercise, and this group were particularly good at process elicitation and at recommending specific control measures, although the other groups also performed well in selected aspects of the matrix and the work provided useful findings and insights. From the research, two models of HSRA have been derived, an HSRA aid, together with a novel videotape KE technique and interesting research findings. The implications of this are discussed with respect to future training of HS professionals and wider application of the videotape KE method.

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As an understanding of users' tacit knowledge and latent needs embedded in user experience has played a critical role in product development, users’ direct involvement in design has become a necessary part of the design process. Various ways of accessing users' tacit knowledge and latent needs have been explored in the field of user-centred design, participatory design, and design for experiencing. User-designer collaboration has been used unconsciously by traditional designers to facilitate the transfer of users' tacit knowledge and to elicit new knowledge. However, what makes user-designer collaboration an effective strategy has rarely been reported on or explored. Therefore, interaction patterns between the users and the designers in three industry-supported user involvement cases were studied. In order to develop a coding system, collaboration was defined as a set of coordinated and joint problem solving activities, measured by the elicitation of new knowledge from collaboration. The analysis of interaction patterns in the user involvement cases revealed that allowing users to challenge or modify their contextual experiences facilitates the transfer of knowledge and new knowledge generation. It was concluded that users can be more effectively integrated into the product development process by employing collaboration strategies to intensify the depth of user involvement.

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Expert elicitation is the process of retrieving and quantifying expert knowledge in a particular domain. Such information is of particular value when the empirical data is expensive, limited, or unreliable. This paper describes a new software tool, called Elicitator, which assists in quantifying expert knowledge in a form suitable for use as a prior model in Bayesian regression. Potential environmental domains for applying this elicitation tool include habitat modeling, assessing detectability or eradication, ecological condition assessments, risk analysis, and quantifying inputs to complex models of ecological processes. The tool has been developed to be user-friendly, extensible, and facilitate consistent and repeatable elicitation of expert knowledge across these various domains. We demonstrate its application to elicitation for logistic regression in a geographically based ecological context. The underlying statistical methodology is also novel, utilizing an indirect elicitation approach to target expert knowledge on a case-by-case basis. For several elicitation sites (or cases), experts are asked simply to quantify their estimated ecological response (e.g. probability of presence), and its range of plausible values, after inspecting (habitat) covariates via GIS.

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Expert knowledge is valuable in many modelling endeavours, particularly where data is not extensive or sufficiently robust. In Bayesian statistics, expert opinion may be formulated as informative priors, to provide an honest reflection of the current state of knowledge, before updating this with new information. Technology is increasingly being exploited to help support the process of eliciting such information. This paper reviews the benefits that have been gained from utilizing technology in this way. These benefits can be structured within a six-step elicitation design framework proposed recently (Low Choy et al., 2009). We assume that the purpose of elicitation is to formulate a Bayesian statistical prior, either to provide a standalone expert-defined model, or for updating new data within a Bayesian analysis. We also assume that the model has been pre-specified before selecting the software. In this case, technology has the most to offer to: targeting what experts know (E2), eliciting and encoding expert opinions (E4), whilst enhancing accuracy (E5), and providing an effective and efficient protocol (E6). Benefits include: -providing an environment with familiar nuances (to make the expert comfortable) where experts can explore their knowledge from various perspectives (E2); -automating tedious or repetitive tasks, thereby minimizing calculation errors, as well as encouraging interaction between elicitors and experts (E5); -cognitive gains by educating users, enabling instant feedback (E2, E4-E5), and providing alternative methods of communicating assessments and feedback information, since experts think and learn differently; and -ensuring a repeatable and transparent protocol is used (E6).

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Expert elicitation is the process of determining what expert knowledge is relevant to support a quantitative analysis and then eliciting this information in a form that supports analysis or decision-making. The credibility of the overall analysis, therefore, relies on the credibility of the elicited knowledge. This, in turn, is determined by the rigor of the design and execution of the elicitation methodology, as well as by its clear communication to ensure transparency and repeatability. It is difficult to establish rigor when the elicitation methods are not documented, as often occurs in ecological research. In this chapter, we describe software that can be combined with a well-structured elicitation process to improve the rigor of expert elicitation and documentation of the results

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Existing work in Computer Science and Electronic Engineering demonstrates that Digital Signal Processing techniques can effectively identify the presence of stress in the speech signal. These techniques use datasets containing real or actual stress samples i.e. real-life stress such as 911 calls and so on. Studies that use simulated or laboratory-induced stress have been less successful and inconsistent. Pervasive, ubiquitous computing is increasingly moving towards voice-activated and voice-controlled systems and devices. Speech recognition and speaker identification algorithms will have to improve and take emotional speech into account. Modelling the influence of stress on speech and voice is of interest to researchers from many different disciplines including security, telecommunications, psychology, speech science, forensics and Human Computer Interaction (HCI). The aim of this work is to assess the impact of moderate stress on the speech signal. In order to do this, a dataset of laboratory-induced stress is required. While attempting to build this dataset it became apparent that reliably inducing measurable stress in a controlled environment, when speech is a requirement, is a challenging task. This work focuses on the use of a variety of stressors to elicit a stress response during tasks that involve speech content. Biosignal analysis (commercial Brain Computer Interfaces, eye tracking and skin resistance) is used to verify and quantify the stress response, if any. This thesis explains the basis of the author’s hypotheses on the elicitation of affectively-toned speech and presents the results of several studies carried out throughout the PhD research period. These results show that the elicitation of stress, particularly the induction of affectively-toned speech, is not a simple matter and that many modulating factors influence the stress response process. A model is proposed to reflect the author’s hypothesis on the emotional response pathways relating to the elicitation of stress with a required speech content. Finally the author provides guidelines and recommendations for future research on speech under stress. Further research paths are identified and a roadmap for future research in this area is defined.

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Although the theory of planned behaviour (TPB) has been applied successfully in the area of food choice, it has been criticized for its pure utilitarian approach to the factors determining behaviour. Despite the increase in predictive power of the model with added components such as affective attitude and moral and ethical concerns, in most studies the elicitation process still only addresses people's utilitarian beliefs about the behaviour with little attention paid to other aspects. This study compares the traditional method of elicitation of advantages and disadvantages with two other methods (word association and open-ended) in the elicitations of beliefs, attitudes and moral concerns in relation to the consumption of organic foods. Results show the traditional method to be best for eliciting cognitive beliefs, open-ended emotion task for eliciting emotional beliefs and open-ended beliefs task best for moral concerns. The advantages and disadvantages of each method are discussed.

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Online help-seeking is an emerging trend within the 21st century. Yet despite some movement towards developing online services, little is known about how young people locate, access and receive support online. This study aims to conceptualise the process of online help-seeking among adolescent males. Modified photo-elicitation techniques were employed within eight semi-structured focus group sessions with adolescent males aged 14 – 15 years (n= 56) across seven schools in Northern Ireland. Thematic analyses was conducted within an ontological framework of critical realism and an epistemological framework of contextualism. Informal online help-seeking pathways increased opportunity for social support and reduced stigma but also included loss of control and reduced anonymity. Formal pathways offered increased anonymity but concerns were raised regarding participants’ ability to locate and appraise the quality of information online. A conceptual model of online help-seeking has been developed to highlight the key help seeking pathways taken by adolescent males.

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Management control in public university hospitals is a challenging task because of continuous changes due to external pressures (e.g. economic pressures, stakeholder focuses and scientific progress) and internal complexities (top management turnover, shared leadership, technological evolution, and researcher oriented mission). Interactive budgeting contributed to improving vertical and horizontal communication between hospital and stakeholders and between different organizational levels. This paper describes an application of Analytic Hierarchy Process (AHP) to enhance interactive budgeting in one of the biggest public university hospital in Italy. AHP improved budget allocation facilitating elicitation and formalization of units' needs. Furthermore, AHP facilitated vertical communication among manager and stakeholders, as it allowed multilevel hierarchical representation of hospital needs, and horizontal communication among staff of the same hospital, as it allowed units' need prioritization and standardization, with a scientific multi-criteria approach, without using complex mathematics. Finally, AHP allowed traceability of a complex decision making processes (as budget allocation), this aspect being of paramount importance in public sectors, where managers are called to respond to many different stakeholders about their choices.