230 resultados para Hofstede


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In keeping with the proliferation of free software development initiatives and the increased interest in the business process management domain, many open source workflow and business process management systems have appeared during the last few years and are now under active development. This upsurge gives rise to two important questions: What are the capabilities of these systems? and How do they compare to each other and to their closed source counterparts? In other words: What is the state-of-the-art in the area?. To gain an insight into these questions, we have conducted an in-depth analysis of three of the major open source workflow management systems – jBPM, OpenWFE, and Enhydra Shark, the results of which are reported here. This analysis is based on the workflow patterns framework and provides a continuation of the series of evaluations performed using the same framework on closed source systems, business process modelling languages, and web-service composition standards. The results from evaluations of the three open source systems are compared with each other and also with the results from evaluations of three representative closed source systems: Staffware, WebSphere MQ, and Oracle BPEL PM. The overall conclusion is that open source systems are targeted more toward developers rather than business analysts. They generally provide less support for the patterns than closed source systems, particularly with respect to the resource perspective, i.e. the various ways in which work is distributed amongst business users and managed through to completion.

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Evidence exists that repositories of business process models used in industrial practice contain significant amounts of duplication. This duplication may stem from the fact that the repository describes variants of the same pro- cesses and/or because of copy/pasting activity throughout the lifetime of the repository. Previous work has put forward techniques for identifying duplicate fragments (clones) that can be refactored into shared subprocesses. However, these techniques are limited to finding exact clones. This paper analyzes the prob- lem of approximate clone detection and puts forward two techniques for detecting clusters of approximate clones. Experiments show that the proposed techniques are able to accurately retrieve clusters of approximate clones that originate from copy/pasting followed by independent modifications to the copied fragments.

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This paper investigates the role of cultural factors as possible partial explanation of the disparity in terms of project management deployment observed between various studied countries. The topic of culture has received increasing attention in the management literature in general during the last decades and in the project management literature in particular during the last few years. The globalization of businesses and worldwide Governmental/International organizations collaborations drives this interest in the national culture to increase more and more. Based on Hofstede national culture framework, the study hypothesizes and tests the impact of the culture and development of the country on the PM deployment. Seventy-four countries are selected to conduct a correlation and regression analysis between Hofstede’s national culture dimensions and the used PM deployment indicator. The results show the relations between various national culture dimensions and development indicator (GDP/Capita) on the project management deployment levels of the considered countries.

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With the large diffusion of Business Process Managemen (BPM) automation suites, the possibility of managing process-related risks arises. This paper introduces an innovative framework for process-related risk management and describes a working implementation realized by extending the YAWL system. The framework covers three aspects of risk management: risk monitoring, risk prevention, and risk mitigation. Risk monitoring functionality is provided using a sensor-based architecture, where sensors are defined at design time and used at run-time for monitoring purposes. Risk prevention functionality is provided in the form of suggestions about what should be executed, by who, and how, through the use of decision trees. Finally, risk mitigation functionality is provided as a sequence of remedial actions (e.g. reallocating, skipping, rolling back of a work item) that should be executed to restore the process to a normal situation.

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This paper investigates the role of cultural factors as possible partial explanation of the disparity in terms of Project Management Deployment observed between various studied countries. The topic of culture has received increasing attention in the management literature in general during the last decades and in the Project Management literature in particular during the last few years. The globalization of businesses and worldwide Governmental / International organizations collaborations drives this interest in the national culture to increase more and more. Based on Hofstede national culture framework, the study hypothesizes and tests the impact of the culture and development of the country on the PM Deployment. 74 countries are selected to conduct a correlation and regression analysis between Hofstede’s national culture dimensions and the used PM Deployment indicator. The results show the relations between various national culture dimensions and development indicator (GDP/Capita) on the Project Management Deployment levels of the considered countries.

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The management of risks in business processes has been a subject of active research in the past few years. Many benefits can potentially be obtained by integrating the two traditionally-separated fields of risk management and business process management, including the ability to minimize risks in business processes (by design) and to mitigate risks at run time. In the past few years, an increasing amount of research aimed at delivering such an integrated system has been proposed. However, these research efforts vary in terms of their scope, goals, and functionality. Through systematic collection and evaluation of relevant literature, this paper compares and classifies current approaches in the area of risk-aware business process management in order to identify and explain relevant research gaps. The process through which relevant literature is collected, filtered, and evaluated is also detailed.

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In the field of process mining, the use of event logs for the purpose of root cause analysis is increasingly studied. In such an analysis, the availability of attributes/features that may explain the root cause of some phenomena is crucial. Currently, the process of obtaining these attributes from raw event logs is performed more or less on a case-by-case basis: there is still a lack of generalized systematic approach that captures this process. This paper proposes a systematic approach to enrich and transform event logs in order to obtain the required attributes for root cause analysis using classical data mining techniques, the classification techniques. This approach is formalized and its applicability has been validated using both self-generated and publicly-available logs.

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Process-aware information systems, ranging from generic workflow systems to dedicated enterprise information systems, use work-lists to offer so-called work items to users. In real scenarios, users can be confronted with a very large number of work items that stem from multiple cases of different processes. In this jungle of work items, users may find it hard to choose the right item to work on next. The system cannot autonomously decide which is the right work item, since the decision is also dependent on conditions that are somehow outside the system. For instance, what is “best” for an organisation should be mediated with what is “best” for its employees. Current work-list handlers show work items as a simple sorted list and therefore do not provide much decision support for choosing the right work item. Since the work-list handler is the dominant interface between the system and its users, it is worthwhile to provide an intuitive graphical interface that uses contextual information about work items and users to provide suggestions about prioritisation of work items. This paper uses the so-called map metaphor to visualise work items and resources (e.g., users) in a sophisticated manner. Moreover, based on distance notions, the work-list handler can suggest the next work item by considering different perspectives. For example, urgent work items of a type that suits the user may be highlighted. The underlying map and distance notions may be of a geographical nature (e.g., a map of a city or office building), but may also be based on process designs, organisational structures, social networks, due dates, calendars, etc. The framework proposed in this paper is generic and can be applied to any process-aware information system. Moreover, in order to show its practical feasibility, the paper discusses a full-fledged implementation developed in the context of the open-source workflow environment YAWL, together with two real examples stemming from two very different scenarios. The results of an initial usability evaluation of the implementation are also presented, which provide a first indication of the validity of the approach.

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Nowadays, Workflow Management Systems (WfMSs) and, more generally, Process Management Systems (PMPs) are process-aware Information Systems (PAISs), are widely used to support many human organizational activities, ranging from well-understood, relatively stable and structures processes (supply chain management, postal delivery tracking, etc.) to processes that are more complicated, less structured and may exhibit a high degree of variation (health-care, emergency management, etc.). Every aspect of a business process involves a certain amount of knowledge which may be complex depending on the domain of interest. The adequate representation of this knowledge is determined by the modeling language used. Some processes behave in a way that is well understood, predictable and repeatable: the tasks are clearly delineated and the control flow is straightforward. Recent discussions, however, illustrate the increasing demand for solutions for knowledge-intensive processes, where these characteristics are less applicable. The actors involved in the conduct of a knowledge-intensive process have to deal with a high degree of uncertainty. Tasks may be hard to perform and the order in which they need to be performed may be highly variable. Modeling knowledge-intensive processes can be complex as it may be hard to capture at design-time what knowledge is available at run-time. In realistic environments, for example, actors lack important knowledge at execution time or this knowledge can become obsolete as the process progresses. Even if each actor (at some point) has perfect knowledge of the world, it may not be certain of its beliefs at later points in time, since tasks by other actors may change the world without those changes being perceived. Typically, a knowledge-intensive process cannot be adequately modeled by classical, state of the art process/workflow modeling approaches. In some respect there is a lack of maturity when it comes to capturing the semantic aspects involved, both in terms of reasoning about them. The main focus of the 1st International Workshop on Knowledge-intensive Business processes (KiBP 2012) was investigating how techniques from different fields, such as Artificial Intelligence (AI), Knowledge Representation (KR), Business Process Management (BPM), Service Oriented Computing (SOC), etc., can be combined with the aim of improving the modeling and the enactment phases of a knowledge-intensive process. The 1st International Workshop on Knowledge-intensive Business process (KiBP 2012) was held as part of the program of the 2012 Knowledge Representation & Reasoning International Conference (KR 2012) in Rome, Italy, in June 2012. The workshop was hosted by the Dipartimento di Ingegneria Informatica, Automatica e Gestionale Antonio Ruberti of Sapienza Universita di Roma, with financial support of the University, through grant 2010-C26A107CN9 TESTMED, and the EU Commission through the projects FP7-25888 Greener Buildings and FP7-257899 Smart Vortex. This volume contains the 5 papers accepted and presented at the workshop. Each paper was reviewed by three members of the internationally renowned Program Committee. In addition, a further paper was invted for inclusion in the workshop proceedings and for presentation at the workshop. There were two keynote talks, one by Marlon Dumas (Institute of Computer Science, University of Tartu, Estonia) on "Integrated Data and Process Management: Finally?" and the other by Yves Lesperance (Department of Computer Science and Engineering, York University, Canada) on "A Logic-Based Approach to Business Processes Customization" completed the scientific program. We would like to thank all the Program Committee members for the valuable work in selecting the papers, Andrea Marrella for his valuable work as publication and publicity chair of the workshop, and Carola Aiello and the consulting agency Consulta Umbria for the organization of this successful event.

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In his paper “Approaches to Modeling Business Processes. A Critical Analysis of BPMN, Workflow Patterns and YAWL”, Egon Börger criticizes the work of the Workflow Patterns Initiative in a rather provocative manner. Although the workflow patterns and YAWL are well established and frequently used, Börger seems to misunderstand the goals and contributions of the Workflow Patterns Initiative. Therefore, we put the workflow patterns and YAWL in their historic context. Moreover, we address some of the criticism of Börger by pointing out the real purpose of the workflow patterns and their relationship to formal languages (Petri nets) and real-life WFM/BPM systems.

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Effective risk management is crucial for any organisation. One of its key steps is risk identification, but few tools exist to support this process. Here we present a method for the automatic discovery of a particular type of process-related risk, the danger of deadline transgressions or overruns, based on the analysis of event logs. We define a set of time-related process risk indicators, i.e., patterns observable in event logs that highlight the likelihood of an overrun, and then show how instances of these patterns can be identified automatically using statistical principles. To demonstrate its feasibility, the approach has been implemented as a plug-in module to the process mining framework ProM and tested using an event log from a Dutch financial institution.