919 resultados para Voice of Process


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Research into complaints handling in the health care system has predominately focused on examining the processes that underpin the organisational systems. An understanding of the cognitive decisions made by patients that influence whether they are satisfied or dissatisfied with the care they are receiving has had limited attention thus far. This study explored the lived experiences of Queensland acute care patients who complained about some aspect of their inpatient stay. A purposive sample of sixteen participants was recruited and interviewed about their experience of making a complaint. The qualitative data gathered through the interview process was subjected to an Interpretative Phenomenological Analysis (IPA) approach, guided by the philosophical influences of Heidegger (1889-1976). As part of the interpretive endeavour of this study, Lazarus’ cognitive emotive model with situational challenge was drawn on to provide a contextual understanding of the emotions experienced by the study participants. Analysis of the research data, aided by Leximancer™ software, revealed a series of relational themes that supported the interpretative data analysis process undertaken. The superordinate thematic statements that emerged from the narratives via the hermeneutic process were ineffective communication, standards of care were not consistent, being treated with disrespect, information on how to complain was not clear, and perceptions of negligence. This study’s goal was to provide health services with information about complaints handling that can help them develop service improvements. The study patients articulated the need for health care system reform; they want to be listened to, to be acknowledged, to be believed, for people to take ownership if they had made a mistake, for mistakes not to occur again, and to receive an apology. For these initiatives to be fully realised, the paradigm shift must go beyond regurgitating complaints data metrics in percentages per patient contact, towards a concerted effort to evaluate what the qualitative complaints data is really saying. An opportunity to identify a more positive and proactive approach in encouraging our patients to complain when they are dissatisfied has the potential to influence improvements.

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In the reform by the liberal-conservative government of Swedish upper secondary education in 2011, history was recognized as an important part of citizenship education and was introduced into the curriculum for vocational education and training (VET) tracks. Through the concepts of classification and framing, this article explores the process of constructing the history syllabus for VET. The data consist of archived material from the working group responsible for the history curriculum under the Swedish National Agency for Education. The analysis shows that there are competing discourses concerning the relative emphasis on competencies and skills and concerning the emphasis on contemporary and modern history. Although historians, history teachers and other agents are invited to respond to the content of the curriculum, the respondents have no influence on the knowledge structure of the curriculum, which is controlled by agents of the dominant educational ideology. From a critical perspective, this article suggests that the curriculum reflects the instrumental and neoconservative message of the reform through strong classification and framing and through the emphasis on general abilities and a contemporary history that has a more direct explanatory value to contemporary society.

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This dissertation examines the role that music has played in the expression of identity and revitalization of culture of the Alevis in Turkey, since the start of their sociocultural revival movement in the late 1980s. Music is central to Alevi claims of ethnic and religious difference—singing and playing the bağlama (Turkish folk lute) constitutes an expressive practice in worship and everyday life. Based on research conducted from 2012 to 2014, I investigate and present Alevi music through the lens of discourses on the construction of identity as a social and musical process. Alevi musicians perform a revived repertoire of the ritual music and folk songs of Anatolian bards and dervish-lodge poets that developed over several centuries. Contemporary media and performance contexts have blurred former distinctions between sacred and secular, yet have provided new avenues to build community in an urban setting. I compare music performances in the worship services of urban and small-town areas, and other community events such as devotional meetings, concerts, clubs, and broadcast and social media to illustrate the ways that participation—both performing and listening—reinforces identity and solidarity. I also examine the influence of these different contexts on performers’ musical choices, and the power of music to evoke a range of responses and emotional feelings in the participants. Through my investigation I argue that the Alevi music repertoire is not only a cultural practice but also a symbol of power and collective action in their struggle for human rights and self-determination. As Alevis have faced a redefined Turkish nationalism that incorporates Sunni Muslim piety, this music has gained even greater potency in their resistance to misrecognition as a folkloric, rather than a living, tradition.

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Process modeling can be regarded as the currently most popular form of conceptual modeling. Research evidence illustrates how process modeling is applied across the different information system life cycle phases for a range of different applications, such as configuration of Enterprise Systems, workflow management, or software development. However, a detailed discussion of critical factors of the quality of process models is still missing. This paper proposes a framework consisting of six quality factors, which is derived from a comprehensive literature review. It then presents in a case study, a utility provider, who had designed various business process models for the selection of an Enterprise System. The paper summarizes potential means of conducting a successful process modeling initiative and evaluates the described modeling approach within the Guidelines of Modeling (GoM) framework. An outlook shows the potential lessons learnt, and concludes with insights to the next phases of this study.

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The integrated and process oriented nature of Enterprise Systems (ES) has led organizations to use process modeling as an aid in managing these systems. Enterprise Systems success factor studies explicitly and implicitly state the importance of process modeling and its contribution to overall Enterprise System success. However, no empirical evidence exists on how to conduct process modeling successfully and possibly differentially in the main phases of the ES life-cycle. This paper reports on an empirical investigation of the factors that influence process modeling success. An a-priori model with 8 candidate success factors has been developed to this stage. This paper introduces the research context and objectives, describes the research design and the derived model, and concludes by looking ahead to the next phases of the research design.

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Selecting an appropriate business process modelling technique forms an important task within the methodological challenges of a business process management project. While a plethora of available techniques has been developed over the last decades, there is an obvious shortage of well-accepted reference frameworks that can be used to evaluate and compare the capabilities of the different techniques. Academic progress has been made at least in the area of representational analyses that use ontology as a benchmark for such evaluations. This paper reflects on the comprehensive experiences with the application of a model based on the Bunge ontology in this context. A brief overview of the underlying research model characterizes the different steps in such a research project. A comparative summary of previous representational analyses of process modelling techniques over time gives insights into the relative maturity of selected process modelling techniques. Based on these experiences suggestions are made as to where ontology-based representational analyses could be further developed and what limitations are inherent to such analyses.

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Process modeling grammars are used by analysts to describe information systems domains in terms of the business operations an organization is conducting. While prior research has examined the factors that lead to continued usage behavior, little knowledge has been established as to what extent characteristics of the users of process modeling grammars inform usage behavior. In this study, a theoretical model is advanced that incorporates determinants of continued usage behavior as well as key antecedent individual difference factors of the grammar users, such as modeling experience, modeling background and perceived grammar familiarity. Findings from a global survey of 529 grammar users support the hypothesized relationships of the model. The study offers three central contributions. First, it provides a validated theoretical model of post-adoptive modeling grammar usage intentions. Second, it discusses the effects of individual difference factors of grammar users in the context of modeling grammar usage. Third, it provides implications for research and practice.

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Our objective was to determine the factors that lead users to continue working with process modeling grammars after their initial adoption. We examined the explanatory power of three theoretical models of IT usage by applying them to two popular process modeling grammars. We found that a hybrid model of technology acceptance and expectation-confirmation best explained user intentions to continue using the grammars. We examined differences in the model results, and used them to provide three contributions. First, the study confirmed the applicability of IT usage models to the domain of process modeling. Second, we discovered that differences in continued usage intentions depended on the grammar type instead of the user characteristics. Third, we suggest implications and practice.

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Business process modeling is widely regarded as one of the most popular forms of conceptual modeling. However, little is known about the capabilities and deficiencies of process modeling grammars and how existing deficiencies impact actual process modeling practice. This paper is a first contribution towards a theory-driven, exploratory empirical investigation of the ontological deficiencies of process modeling with the industry standard Business Process Modeling Notation (BPMN). We perform an analysis of BPMN using a theory of ontological expressiveness. Through a series of semi-structured interviews with BPMN adopters we explore empirically the actual use of this grammar. Nine ontological deficiencies related to the practice of modeling with BPMN are identified, for example, the capture of business rules and the specification of process decompositions. We also uncover five contextual factors that impact on the use of process modeling grammars, such as tool support and modeling conventions. We discuss implications for research and practice, highlighting the need for consideration of representational issues and contextual factors in decisions relating to BPMN adoption in organizations.

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Business processes have emerged as a well-respected variable in the design of successful corporations. However, unlike other key managerial variables, such as products and services, customers and employees, physical or digital assets, the conceptualization and management of business processes are in many respects in their infancy. In this book, Jan Recker investigates the notion of quality of business process modeling grammars. His evaluation is based on an ontological-, qualitative-, and quantitative analysis, applied to BPMN, a widely-used business process modeling grammar. His results reveal the ontological shortcomings of BPMN and how these manifest themselves in actual process modeling practice, as well as how they influence the usage behavior of modeling practitioners. More generally, his book constitutes a landmark for empirical technology assessment, analyzing the way in which design flaws in technology influence usage behavior.

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Process models are used by information professionals to convey semantics about the business operations in a real world domain intended to be supported by an information system. The understandability of these models is vital to them being used for information systems development. In this paper, we examine two factors that we predict will influence the understanding of a business process that novice developers obtain from a corresponding process model: the content presentation form chosen to articulate the business domain, and the user characteristics of the novice developers working with the model. Our experimental study provides evidence that novice developers obtain similar levels of understanding when confronted with an unfamiliar or a familiar process model. However, previous modeling experience, the use of English as a second language, and previous work experience in BPM are important influencing factors of model understanding. Our findings suggest that education and research in process modeling should increase the focus on human factors and how they relate to content and content presentation formats for different modeling tasks. We discuss implications for practice and research.

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Process models in organizational collections are typically modeled by the same team and using the same conventions. As such, these models share many characteristic features like size range, type and frequency of errors. In most cases merely small samples of these collections are available due to e.g. the sensitive information they contain. Because of their sizes, these samples may not provide an accurate representation of the characteristics of the originating collection. This paper deals with the problem of constructing collections of process models, in the form of Petri nets, from small samples of a collection for accurate estimations of the characteristics of this collection. Given a small sample of process models drawn from a real-life collection, we mine a set of generation parameters that we use to generate arbitrary-large collections that feature the same characteristics of the original collection. In this way we can estimate the characteristics of the original collection on the generated collections.We extensively evaluate the quality of our technique on various sample datasets drawn from both research and industry.