307 resultados para systems management


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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.

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Google, Facebook, Twitter, LinkedIn, etc. are some of the prominent large-scale digital service providers that are having tremendous impact on societies, corporations and individuals. However, despite the rapid uptake and their obvious influence on the behavior of individuals and the business models and networks of organizations, we still lack a deeper, theory-guided understanding of the related phenomenon. We use Teece’s notion of complementary assets and extend it towards ‘digital complementary assets’ (DCA) in an attempt to provide such a theory-guided understanding of these digital services. Building on Teece’s theory, we make three contributions. First, we offer a new conceptualization of digital complementary assets in the form of digital public goods and digital public assets. Second, we differentiate three models for how organizations can engage with such digital complementary assets. Third, user-base is found to be a critical factor when considering appropriability.

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Enterprise architecture (EA) management has be-come an intensively discussed approach to manage enterprise transformations. While there is a strong interest in EA frameworks and EA modeling, a lack of knowledge remains about the theoretical foundation of EA benefits. In this paper, we identify EA success factors and EA benefits through a literature review, and integrate these findings with the DeLone & McLean IS success model to propose a theoretical model explaining the realization of EA benefits. In addition, we con-ducted semi-structured interviews with EA experts for a preliminary validation and further exploration of the model. We see this model as a first step to gain insights in and start a discussion on the theory of EA benefit realization. In future research, we plan to empirically validate the proposed model.

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What I want to do in this Column, is to paint a picture of the current BPM education portfolios that are offered globally by universities active in the BPM space. To do so, I will draw on work I was involved in that reviewed the BPM teaching capacities of five universities in the United States, Europe, Africa and Australia. My ambition is to complement the listings in the BPTrends Academic Program with a more comprehensive and in-depth discussion of a selected set of universities. Let us explore how BPM capability development is implemented and offered in different universities around the globe.

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Service oriented architecture (SOA) is an architectural style for building software systems based on services. Especially in those scenarios where services implement business processes, complex conversations between the services occur. Service choreographies are a means to capture all interaction obligations and constraints from a global perspective. This article introduces choreographies as an important artifact for SOA, compares them to service orchestrations and surveys existing languages for modeling them.

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Enterprise architecture (EA) management has become an intensively discussed approach to manage enterprise transformations. Despite the popularity and potential of EA, both researchers and practitioners lament a lack of knowledge about the realization of benefits from EA. To determine the benefits from EA, we explore the various dimensions of EA benefit realization and report on the development of a validated and robust measurement instrument. In this paper, we test the reliability and construct validity of the EA benefit realization model (EABRM), which we have designed based on the DeLone & McLean IS success model and findings from exploratory interviews. A confirmatory factor analysis confirms the existence of an impact of five distinct and individually important dimensions on the benefits derived from EA: EA artefact quality, EA infrastructure quality, EA service quality, EA culture, and EA use. The analysis presented in this paper shows that the EA benefit realization model is an instrument that demonstrates strong reliability and validity.

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There are many use cases in business process management that require the comparison of behavioral models. For instance, verifying equivalence is the basis for assessing whether a technical workflow correctly implements a business process, or whether a process realization conforms to a reference process. This paper proposes an equivalence relation for models that describe behaviors based on the concurrency semantics of net theory and for which an alignment relation has been defined. This equivalence, called isotactics, preserves the level of concurrency of aligned operations. Furthermore, we elaborate on the conditions under which an alignment relation can be classified as an abstraction. Finally, we show that alignment relations induced by structural refinements of behavioral models are indeed behavioral abstractions.

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The concept of Six Sigma was initiated in the 1980s by Motorola. Since then it has been implemented in several manufacturing and service organizations. Till now Six Sigma implementation is mostly limited to healthcare and financial services in private sector. Its implementation is now gradually picking up in services such as call center, education, construction and related engineering etc. in private as well as public sector. Through a literature review, a questionnaire survey, and multiple case study approach the paper develops a conceptual framework to facilitate widening the scope of Six Sigma implementation in service organizations. Using grounded theory methodology, this study develops theory for Six Sigma implementation in service organizations. The study involves a questionnaire survey and case studies to understand and build a conceptual framework. The survey was conducted in service organizations in Singapore and exploratory in nature. The case studies involved three service organizations which implemented Six Sigma. The objective is to explore and understand the issues highlighted by the survey and the literature. The findings confirm the inclusion of critical success factors, critical-to-quality characteristics, and set of tools and techniques as observed from the literature. In case of key performance indicator, there are different interpretations about it in literature and also by industry practitioners. Some literature explain key performance indicator as performance metrics whereas some feel it as key process input or output variables, which is similar to interpretations by practitioners of Six Sigma. The response of not relevant and unknown to us as reasons for not implementing Six Sigma shows the need for understanding specific requirements of service organizations. Though much theoretical description is available about Six Sigma, but there has been limited rigorous academic research on it. This gap is far more pronounced about Six Sigma implementation in service organizations, where the theory is not mature enough. Identifying this need, the study contributes by going through theory building exercise and developing a conceptual framework to understand the issues involving its implementation in service organizations.

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This paper discusses users’ query reformulation behaviour while searching information on the Web. Query reformulations have emerged as an important component of Web search behaviour and human-computer interaction (HCI) because a user’s success of information retrieval (IR) depends on how he or she formulates queries. There are various factors, such as cognitive styles, that influence users’ query reformulation behaviour. Understanding how users with different cognitive styles formulate their queries while performing Web searches can help HCI researchers and information systems (IS) developers to provide assistance to the users. This paper aims to examine the effects of users’ cognitive styles on their query reformation behaviour. To achieve the goal of the study, a user study was conducted in which a total of 3613 search terms and 872 search queries were submitted by 50 users who engaged in 150 scenario-based search tasks. Riding’s (1991) Cognitive Style Analysis (CSA) test was used to assess users’ cognitive style as wholist or analytic, and verbaliser or imager. The study findings show that users’ query reformulation behaviour is affected by their cognitive styles. The results reveal that analytic users tended to prefer Add queries while all other users preferred New queries. A significant difference was found among wholists and analytics in the manner they performed Remove query reformulations. Future HCI researchers and IS developers can utilize the study results to develop interactive and user-cantered search model, and to provide context-based query suggestions for users.

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Information technology (IT) has been playing a powerful role in creating a competitive advantage for organisations over the past decades. This role has become proportionally greater over time as expectations for IT investments to drive business opportunities keep on rising. However, this reliance on IT has also raised concerns about regulatory compliance, governance and security. IT governance (ITG) audit leverages the skills of IS/IT auditors to ensure that IT initiatives are in line with the business strategies. ITG audit emerged as part of performance audit to provide an assessment of the effective implementation of ITG. This research attempts to empirically examine the ITG audit challenges in the public sector. Based on literature and Delphi research, this paper provides insights regarding the impact of, and required effort to address these challenges. The authors also present the ten major ITG audit challenges facing Australian public sector organisations today.

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Process mining encompasses the research area which is concerned with knowledge discovery from information system event logs. Within the process mining research area, two prominent tasks can be discerned. First of all, process discovery deals with the automatic construction of a process model out of an event log. Secondly, conformance checking focuses on the assessment of the quality of a discovered or designed process model in respect to the actual behavior as captured in event logs. Hereto, multiple techniques and metrics have been developed and described in the literature. However, the process mining domain still lacks a comprehensive framework for assessing the goodness of a process model from a quantitative perspective. In this study, we describe the architecture of an extensible framework within ProM, allowing for the consistent, comparative and repeatable calculation of conformance metrics. For the development and assessment of both process discovery as well as conformance techniques, such a framework is considered greatly valuable.

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The design and construction community has shown increasing interest in adopting building information models (BIMs). The richness of information provided by BIMs has the potential to streamline the design and construction processes by enabling enhanced communication, coordination, automation and analysis. However, there are many challenges in extracting construction-specific information out of BIMs. In most cases, construction practitioners have to manually identify the required information, which is inefficient and prone to error, particularly for complex, large-scale projects. This paper describes the process and methods we have formalized to partially automate the extraction and querying of construction-specific information from a BIM. We describe methods for analyzing a BIM to query for spatial information that is relevant for construction practitioners, and that is typically represented implicitly in a BIM. Our approach integrates ifcXML data and other spatial data to develop a richer model for construction users. We employ custom 2D topological XQuery predicates to answer a variety of spatial queries. The validation results demonstrate that this approach provides a richer representation of construction-specific information compared to existing BIM tools.

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Building information modeling (BIM) is an emerging technology and process that provides rich and intelligent design information models of a facility, enabling enhanced communication, coordination, analysis, and quality control throughout all phases of a building project. Although there are many documented benefits of BIM for construction, identifying essential construction-specific information out of a BIM in an efficient and meaningful way is still a challenging task. This paper presents a framework that combines feature-based modeling and query processing to leverage BIM for construction. The feature-based modeling representation implemented enriches a BIM by representing construction-specific design features relevant to different construction management (CM) functions. The query processing implemented allows for increased flexibility to specify queries and rapidly generate the desired view from a given BIM according to the varied requirements of a specific practitioner or domain. Central to the framework is the formalization of construction domain knowledge in the form of a feature ontology and query specifications. The implementation of our framework enables the automatic extraction and querying of a wide-range of design conditions that are relevant to construction practitioners. The validation studies conducted demonstrate that our approach is significantly more effective than existing solutions. The research described in this paper has the potential to improve the efficiency and effectiveness of decision-making processes in different CM functions.

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This article proposes an approach for real-time monitoring of risks in executable business process models. The approach considers risks in all phases of the business process management lifecycle, from process design, where risks are defined on top of process models, through to process diagnosis, where risks are detected during process execution. The approach has been realized via a distributed, sensor-based architecture. At design-time, sensors are defined to specify risk conditions which when fulfilled, are a likely indicator of negative process states (faults) to eventuate. Both historical and current process execution data can be used to compose such conditions. At run-time, each sensor independently notifies a sensor manager when a risk is detected. In turn, the sensor manager interacts with the monitoring component of a business process management system to prompt the results to process administrators who may take remedial actions. The proposed architecture has been implemented on top of the YAWL system, and evaluated through performance measurements and usability tests with students. The results show that risk conditions can be computed efficiently and that the approach is perceived as useful by the participants in the tests.