804 resultados para Defense Systems Management College


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Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to manage large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business process model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective and less error-prone than developing them from scratch. Since process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. To make our approach more applicable, we consider the semantic similarity between labels. Experiments are conducted to demonstrate that our approach is efficient.

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Business process models are becoming available in large numbers due to their popular use in many industrial applications such as enterprise and quality engineering projects. On the one hand, this raises a challenge as to their proper management: How can it be ensured that the proper process model is always available to the interested stakeholder? On the other hand, the richness of a large set of process models also offers opportunities, for example with respect to the re-use of existing model parts for new models. This paper describes the functionalities and architecture of an advanced process model repository, named APROMORE. This tool brings together a rich set of features for the analysis, management and usage of large sets of process models, drawing from state-of-the art research in the field of process modeling. A prototype of the platform is presented in this paper, demonstrating its feasibility, as well as an outlook on the further development of APROMORE.

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Though enterprise resource planning (ERP) has gained some prominence in the information systems (IS) literature over the past few years and is a significant phenomenon in practice, through (a) a historical analysis, (b) meta-analysis of representative IS literature, and (c) a survey of academic experts, we reveal dissenting views on the phenomenon. Given this diversity of perspectives, it is unlikely that at this stage a broadly agreed definition of ERP can be achieved. We thus seek to increase awareness of the issues and stimulate further discussion, with the ultimate aim being to: (a) aid communication amongst researchers and between researchers and practitioners; (2) inform development of teaching materials on ERP and related concepts in university curricula and in commercial education and training; and (3) aid communication amongst clients, consultants and vendors. Increase transparence of the ERP concept within IS may also benefit other aligned fields of knowledge.

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In a resource constrained business world, strategic choices must be made on process improvement and service delivery. There are calls for more agile forms of enterprises and much effort is being directed at moving organizations from a complex landscape of disparate application systems to that of an integrated and flexible enterprise accessing complex systems landscapes through service oriented architecture (SOA). This paper describes the analysis of strategies to detect supporting business services. These services can then be delivered in a variety of ways: web-services, new application services or outsourced services. The focus of this paper is on strategy analysis to identify those strategies that are common to lines of business and thus can be supported through shared services. A case study of a state government is used to show the analytical method and the detection of shared strategies.

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While Business Process Management (BPM) is an established discipline, the increased adoption of BPM technology in recent years has introduced new challenges. One challenge concerns dealing with the ever-growing complexity of business process models. Mechanisms for dealing with this complexity can be classified into two categories: 1) those that are solely concerned with the visual representation of the model and 2) those that change its inner structure. While significant attention is paid to the latter category in the BPM literature, this paper focuses on the former category. It presents a collection of patterns that generalize and conceptualize various existing mechanisms to change the visual representation of a process model. Next, it provides a detailed analysis of the degree of support for these patterns in a number of state-of-the-art languages and tools. This paper concludes with the results of a usability evaluation of the patterns conducted with BPM practitioners.

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With over 100,000 alcohol-related hospitalisations every year, risky drinking within Australia is a major health issue (Pascal, Chikritzhs, & Jones, 2009). Typically health advocates focus on parental and peer influence as a source of excessive drinking; leaving out the often overlooked role of siblings. Using consumer socialisation theory (Ward, 1974), the adoption of alcohol related behaviours between siblings was examined. Using a sample of 257 young adults alcohol behaviours were examined between sibship groups. The results revealed that alcohol type similarity was significant for siblings of who were of the same gender, but not significant for siblings of opposite genders. The results suggest that in order for an older sibling to influence a younger brother or sister they must be of the same gender and that there must be a relatively large age gap between them. This suggests that power in sibling relationships could play an important factor in alcohol behaviours.

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We all live in a yellow submarine… When I go to work in the morning, in the office building that hosts our BPM research group, on the way up to our level I come by this big breakout room that hosts a number of computer scientists, working away at the next generation software algorithms and iPad applications (I assume). I have never actually been in that room, but every now and then the door is left ajar for a while and I can spot couches, lots (I mean, lots!) of monitors, the odd scientist, a number of Lara Croft posters, and the usual room equipment you’d probably expect from computer scientists (and, no, it’s not like that evil Dennis guy from the Jurassic Park movie, buried in chips, coke, and flickering code screens… It’s also not like the command room from the Nebuchadnezzar, Neo’s hovercraft in the Matrix movies, although I still strongly believe these green lines of code make a good screensaver).

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The study proposes to test the ‘IS-Impact’ index as Analytic Theory (AT). To (a) methodically evaluate the ‘relevance’ qualities of IS-Impact; namely, Utility & Intuitiveness. In so doing, to (b) document an exemplar of ‘a rigorous approach to relevance’, while (c) treating the overarching study as a higher-order case study having AT as the unit-of-analysis, and assessing adequacy of the 6 AT qualities, both for IS-Impact and for similar taxonomies. Also to (d) look beyond IS-Impact to other forms of Design Science, considering the generality of the AT qualities; and (e) further validating IS-Impact in new system organisation contexts taking account of contemporary understandings of construct theorisation, operationalization and validation.

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With the emergence of Web 2.0, Web users can classify Web items of their interest by using tags. Tags reflect users’ understanding to the items collected in each tag. Exploring user tagging behavior provides a promising way to understand users’ information needs. However, free and relatively uncontrolled vocabulary has its drawback in terms of lack of standardization and semantic ambiguity. Moreover, the relationships among tags have not been explored even there exist rich relationships among tags which could provide valuable information for us to better understand users. In this paper, we propose a novel approach to construct tag ontology based on the widely used general ontology WordNet to capture the semantics and the structural relationships of tags. Ambiguity of tags is a challenging problem to deal with in order to construct high quality tag ontology. We propose strategies to find the semantic meanings of tags and a strategy to disambiguate the semantics of tags based on the opinion of WordNet lexicographers. In order to evaluate the usefulness of the constructed tag ontology, in this paper we apply the extracted tag ontology in a tag recommendation experiment. We believe this is the first application of tag ontology for recommendation making. The initial result shows that by using the tag ontology to re-rank the recommended tags, the accuracy of the tag recommendation can be improved.

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Formalised service innovation is a central tenet of enterprise systems lifecycle phases. Event driven process models extended with knowledge objects are found to be not useful in early lifecycle phases. When an upgrade is required, a map of the knowledge infrastructure is needed to better design further service innovation because functional maps no longer adequately describe the context adequately. By looking at formal changes to business processes as service innovations, and recognising the knowledge infrastructure inherent in services generally, changes driven through technology such as ES can be better understood with the application of frameworks such as B-KIDE.

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In a world of intense competition, Six Sigma is considered to be an important management philosophy, supporting organisations in their efforts to obtain satisfied customers. As financial service organisations have been slow to adopt Six Sigma, issues concerning its implementation are of major importance. For its implementation a large number of tools and techniques have been suggested by academics and practitioners. Intriguingly, despite the extensive effort that has been invested and benefits that can be obtained, the systematic implementation of Six Sigma in financial service organisations is limited. This paper presents a conceptual framework derived from literature and empirical results with a focus on financial services. Using this framework a financial service company should be able to cope with the relevant critical success factors. Thus, the framework allows identifying relevant aspects for a sustainable and successful implementation of a Six Sigma initiative.

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As business process management technology matures, organisations acquire more and more business process models. The resulting collections can consist of hundreds, even thousands of models and their management poses real challenges. One of these challenges concerns model retrieval where support should be provided for the formulation and efficient execution of business process model queries. As queries based on only structural information cannot deal with all querying requirements in practice, there should be support for queries that require knowledge of process model semantics. In this paper we formally define a process model query language that is based on semantic relationships between tasks. This query language is independent of the particular process modelling notation used, but we will demonstrate how it can be used in the context of Petri nets by showing how the semantic relationships can be determined for these nets in such a way that state space explosion is avoided as much as possible. An experiment with three large process model repositories shows that queries expressed in our language can be evaluated efficiently.

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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.