31 resultados para Brunet, Marta

em Queensland University of Technology - ePrints Archive


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Business process modeling has undoubtedly emerged as a popular and relevant practice in Information Systems. Despite being an actively researched field, anecdotal evidence and experiences suggest that the focus of the research community is not always well aligned with the needs of industry. The main aim of this paper is, accordingly, to explore the current issues and the future challenges in business process modeling, as perceived by three key stakeholder groups (academics, practitioners, and tool vendors). We present the results of a global Delphi study with these three groups of stakeholders, and discuss the findings and their implications for research and practice. Our findings suggest that the critical areas of concern are standardization of modeling approaches, identification of the value proposition of business process modeling, and model-driven process execution. These areas are also expected to persist as business process modeling roadblocks in the future.

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The process-centered design of organizations and information systems is globally seen as an appropriate response to the increased economic pressure on organizations. At the methodological core of process-centered management is process modeling. However, business process modeling in large initiatives can be a time-consuming and costly exercise, making it potentially difficult to convince executive management of its benefits. To date, and despite substantial interest and research in the area of process modeling, the understanding of the actual benefits of process modeling in academia and practice is limited. To address this gap, this paper explores the perception of benefits derived from process modeling initiatives, as reported through a global Delphi study. The study incorporates the views of three groups of stakeholders – academics, practitioners and vendors. Our findings lead to the first identification and ranking of 19 unique benefits associated with process modeling. The study in particular found that process modeling benefits vary significantly between practitioners and academics. We argue that these variations may point to a dangerous disconnect between research projects and practical demands.

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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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Spatial representations, metaphors and imaginaries (cyberspace, web pages) have been the mainstay of internet research for a long time. Instead of repeating these themes, this paper seeks to answer the question of how we might understand the concept of time in relation to internet research. After a brief excursus on the general history of the concept, this paper proposes three different approaches to the conceptualisation of internet time. The common thread underlying all the approaches is the notion of time as an assemblage of elements such as technical artefacts, social relations and metaphors. By drawing out time in this way, the paper addresses the challenge of thinking of internet time as coexistence, a clash of fluxes, metaphors, lived experiences and assemblages. In other words, this paper proposes a way to articulate internet time as a multiplicity.

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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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Network has emerged from a contempory worldwide phenomenon, culturally manifested as a consequence of globalization and the knowledge economy. It is in this context that the internet revolution has prompted a radical re-ordering of social and institutional relations and the associated structures, processes and places which support them. Within the duality of virtual space and the augmentation of traditional notions of physical place, the organizational structures pose new challenges for the design professions. Technological developments increasingly permit communication anytime and anywhere, and provide the opportunity for both synchronous and asynchronous collaboration. The resultant ecology formed through the network enterprise has resulted in an often convolted and complex world wherein designers are forced to consider the relevance and meaning of this new context. The role of technology and that of space are thus interwined in the relation between the network and the individual workplace. This paper explores a way to inform the interior desgn process for contemporary workplace environments. It reports on both theoretical and practical outcomes through an Australia-wide case study of three collaborating, yet independent business entities. It further suggests the link between workplace design and successful business innovation being realized between partnering organizations in Great Britain. Evidence presented indicates that, for architects and interior designers, the scope of the problem has widened, the depth of knowledge required to provide solutions has increased, and the rules of engagement are required to change. The ontological and epistemological positions adopted in the study enabled the spatial dimensions to be examined from both within and beyond the confines of a traditional design only viewpoint. Importantly it highlights the significance of a trans-disiplinary collaboration in dealing with the multiple layers and complexity of the contemporary social and business world, from both a research and practice perspective.

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Conceptual modeling grammars are a fundamental means for specifying information systems requirements. However, the actual usage of these grammars is only poorly understood. In particular, little is known about how properties of these grammars inform usage beliefs such as usefulness and ease of use. In this paper we use an ontological theory to describe conceptual modeling grammars in terms of their ontological deficiencies, and formulate two propositions in regard to how these ontological deficiencies influence primary usage beliefs. Using BPMN as an example modeling grammar, we surveyed 528 modeling practitioners to test the theorized relationships. Our results show that users of conceptual modeling grammars perceive ontological deficiencies to exist, and that these deficiency perceptions are negatively associated with usefulness and ease of use of these grammars. With our research we provide empirical evidence in support of the predictions of the ontological theory of modeling grammar expressiveness, and we identify previously unexplored links between conceptual modeling grammars and grammar usage beliefs. This work implies for practice a much closer coupling of the act of (re ) designing modeling grammars with usage-related success metrics.

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Conceptual modeling continues to be an important means for graphically capturing the requirements of an information system. Observations of modeling practice suggest that modelers often use multiple modeling grammars in combination to articulate various aspects of real-world domains. We extend an ontological theory of representation to suggest why and how users employ multiple conceptual modeling grammars in combination. We provide an empirical test of the extended theory using survey data and structured interviews about the use of traditional and structured analysis grammars within an automated tool environment. We find that users of the analyzed tool combine grammars to overcome the ontological incompleteness that exists in each grammar. Users further selected their starting grammar from a predicted subset of grammars only. The qualitative data provides insights as to why some of the predicted deficiencies manifest in practice differently than predicted.

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Unstructured text data, such as emails, blogs, contracts, academic publications, organizational documents, transcribed interviews, and even tweets, are important sources of data in Information Systems research. Various forms of qualitative analysis of the content of these data exist and have revealed important insights. Yet, to date, these analyses have been hampered by limitations of human coding of large data sets, and by bias due to human interpretation. In this paper, we compare and combine two quantitative analysis techniques to demonstrate the capabilities of computational analysis for content analysis of unstructured text. Specifically, we seek to demonstrate how two quantitative analytic methods, viz., Latent Semantic Analysis and data mining, can aid researchers in revealing core content topic areas in large (or small) data sets, and in visualizing how these concepts evolve, migrate, converge or diverge over time. We exemplify the complementary application of these techniques through an examination of a 25-year sample of abstracts from selected journals in Information Systems, Management, and Accounting disciplines. Through this work, we explore the capabilities of two computational techniques, and show how these techniques can be used to gather insights from a large corpus of unstructured text.