230 resultados para Hofstede


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Approximate clone detection is the process of identifying similar process fragments in business process model collections. The tool presented in this paper can efficiently cluster approximate clones in large process model repositories. Once a repository is clustered, users can filter and browse the clusters using different filtering parameters. Our tool can also visualize clusters in the 2D space, allowing a better understanding of clusters and their member fragments. This demonstration will be useful for researchers and practitioners working on large process model repositories, where process standardization is a critical task for increasing the consistency and reducing the complexity of the repository.

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Having a reliable understanding about the behaviours, problems, and performance of existing processes is important in enabling a targeted process improvement initiative. Recently, there has been an increase in the application of innovative process mining techniques to facilitate evidence-based understanding about organizations' business processes. Nevertheless, the application of these techniques in the domain of finance in Australia is, at best, scarce. This paper details a 6-month case study on the application of process mining in one of the largest insurance companies in Australia. In particular, the challenges encountered, the lessons learned, and the results obtained from this case study are detailed. Through this case study, we not only validated existing `lessons learned' from other similar case studies, but also added new insights that can be beneficial to other practitioners in applying process mining in their respective fields.

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Substantial research efforts have been expended to deal with the complexity of concurrent systems that is inherent to their analysis, e.g., works that tackle the well-known state space explosion problem. Approaches differ in the classes of properties that they are able to suitably check and this is largely a result of the way they balance the trade-off between analysis time and space employed to describe a concurrent system. One interesting class of properties is concerned with behavioral characteristics. These properties are conveniently expressed in terms of computations, or runs, in concurrent systems. This article introduces the theory of untanglings that exploits a particular representation of a collection of runs in a concurrent system. It is shown that a representative untangling of a bounded concurrent system can be constructed that captures all and only the behavior of the system. Representative untanglings strike a unique balance between time and space, yet provide a single model for the convenient extraction of various behavioral properties. Performance measurements in terms of construction time and size of representative untanglings with respect to the original specifications of concurrent systems, conducted on a collection of models from practice, confirm the scalability of the approach. Finally, this article demonstrates practical benefits of using representative untanglings when checking various behavioral properties of concurrent systems.

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As business process management technology matures, organisations acquire more and more business process models. The management of the resulting collections of process models 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 in process models and is independent of any particular process modelling notation.

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This paper proposes a concrete approach for the automatic mitigation of risks that are detected during process enactment. Given a process model exposed to risks, e.g. a financial process exposed to the risk of approval fraud, we enact this process and as soon as the likelihood of the associated risk(s) is no longer tolerable, we generate a set of possible mitigation actions to reduce the risks' likelihood, ideally annulling the risks altogether. A mitigation action is a sequence of controlled changes applied to the running process instance, taking into account a snapshot of the process resources and data, and the current status of the system in which the process is executed. These actions are proposed as recommendations to help process administrators mitigate process-related risks as soon as they arise. The approach has been implemented in the YAWL environment and its performance evaluated. The results show that it is possible to mitigate process-related risks within a few minutes.

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Information security policies play an important role in achieving information security. Confidentiality, Integrity, and Availability are classic information security goals attained by enforcing appropriate security policies. Workflow Management Systems (WfMSs) also benefit from inclusion of these policies to maintain the security of business-critical data. However, in typical WfMSs these policies are designed to enforce the organisation’s security requirements but do not consider those of other stakeholders. Privacy is an important security requirement that concerns the subject of data held by an organisation. WfMSs often process sensitive data about individuals and institutions who demand that their data is properly protected, but WfMSs fail to recognise and enforce privacy policies. In this paper, we illustrate existing WfMS privacy weaknesses and introduce WfMS extensions required to enforce data privacy. We have implemented these extensions in the YAWL system and present a case scenario to demonstrate how it can enforce a subject’s privacy policy.

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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.

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Despite advances in the field of workflow flexibility, there is still insufficient support for dealing with unforeseen exceptions. In particular, it is challenging to find a solution which preserves the intent of the process as much as possible when such exceptions are encountered. This challenge can be alleviated by making the connection between a process and its objectives more explicit. This paper presents a demo illustrating the blended workflow approach where two specifications are fused together, a "classic" process model and a goal model. End users are guided by the process model but may deviate from this model whenever unexpected situations are encountered. The two models involved provide views on the process and the demo shows how one can switch between these views and how they are kept consistent by the blended workflow engine. A simple example involving the making of a doctor's appointment illustrates the potential advantages of the proposed approach to both researchers and developers.

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Principal Topic Counties in Northern Europe, such as Sweden, Finland and Denmark, have comparatively low per capita rates of entrepreneurship as measured by independent new venture start-up rates – as for example measured by the Global Entrepreneurship Monitor (GEM) Total entrepreneurial activity (TEA) rate. However, the latest 2011 GEM data reveals that these same countries have comparatively very high Employee Entrepreneurship Activity (EEA) rates – that is a high rate per capita of employees involved in new product development or new enterprise activities. This observation has prompted us to investigate the role of national culture in driving independent versus employee entrepreneurial activities. Prior research has established that national (and regional) culture plays an important role in forming an “entrepreneurial culture” that encourages (or discourages) independent business start-ups and TEA (e.g. Davidsson, 1995; Beugelsdijk, 2007). However, the relationship of culture and EEA has not received research attention. Moreover, empirical relationships between elements of national culture and independent entrepreneurship have revealed some surprising results. For example, Wildeman et al. (1999) report an unexpected higher share of individual business ownership in countries that have higher uncertainty avoidance, higher power distance and lower individualism according to Hofstede’s dimensions of culture. They speculate that dissatisfaction can be a source of entrepreneurship: in countries with a high power distance, a high uncertainty avoidance and low individualism, there may be relatively more business owners since enterprising individuals cannot satisfy their needs within existing organizations. Yet it remains a rather open question whether entrepreneurial behaviour in existing organisations provides a satisfactory explanation for these empirical findings. Methods We will conduct a cross sectional study of the influence of national culture according to the five / six dimensions of Hofstede (1980; 2001) on both TEA and EEA for the 54 countries that participated in GEM 2011. Since it is well established that the opportunities for entrepreneurship vary substantially with a country’s level of economic development, we intend to conduct separate analyses for the three categories of development – innovation driven economies, efficient driven economies and factor driven economies. We also intend to restrict our assessment of TEA to opportunity driven entrepreneurship, as necessity driven entrepreneurship has a different relationship to the “entrepreneurial culture” that is the focus of our study. We will control for a range of factors such as GDP growth, ease of doing business index and unemployment. Results and Implications Descriptive analyses of the GEM TEA and EEA data reveal clusters of countries that appear to be have similar national culture. We are yet to conduct regression analyses.

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This article describes the architecture of a monitoring component for the YAWL system. The architecture proposed is based on sensors and it is realized as a YAWL service to have perfect integration with the YAWL systems. The architecture proposed is generic and applicable in different contexts of business process monitoring. Finally, it was tested and evaluated in the context of risk monitoring for business processes.

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Risk identification is one of the most challenging stages in the risk management process. Conventional risk management approaches provide little guidance and companies often rely on the knowledge of experts for risk identification. In this paper we demonstrate how risk indicators can be used to predict process delays via a method for configuring so-called Process Risk Indicators(PRIs). The method learns suitable configurations from past process behaviour recorded in event logs. To validate the approach we have implemented it as a plug-in of the ProM process mining framework and have conducted experiments using various data sets from a major insurance company.

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The ability to steer business operations in alignment with the true origins of costs, and to be informed about this on a real-time basis, allows businesses to increase profitability. In most organisations however, high-level cost-based managerial decisions are still being made separately from process-related operational decisions. In this paper, we describe how process-related decisions at the operational level can be guided by cost considerations and how these cost-informed decision rules can be supported by a workflow management system. The paper presents the conceptual framework together with data requirements and technical challenges that need to be addressed to realise cost-informed workflow execution. The feasibility of our approach is demonstrated using a prototype implementation in the YAWL workflow environment.

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While there are many similarities between the languages of the various workflow management systems, there are also significant differences. One particular area of differences is caused by the fact that different systems impose different syntactic restrictions. In such cases, business analysts have to choose between either conforming to the language in their specifications or transforming these specifications afterwards. The latter option is preferable as this allows for a separation of concerns. In this paper we investigate to what extent such transformations are possible in the context of various syntactical restrictions (the most restrictive of which will be referred to as structured workflows). We also provide a deep insight into the consequences, particularly in terms of expressive power, of imposing such restrictions.

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The Yet Another Workflow Language (YAWL) language and environment has been used to prototype, verify, execute and analyse business processes in a wide variety of industrial domains, such as telephony, construction, supply chain, insurance services, medical environments, personnel management and the creative arts. These engagements offer the YAWL researcher community a great opportunity to validate our research findings within an industry setting, as well as discovery of possible enhancements from the end user perspective. This paper describes three such industry projects, discusses why YAWL was chosen and how it was used in each, and reacts on the insights gained along the way.

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The YAWL Worklet Service is an effective approach to facilitating dynamic flexibility and exception handling in workflow processes. Recent additions to the Service extend its capabilities through a programming interface that provides easier access to rules storage and evaluation, and an event server that notifies listening servers and applications when exceptions are detected, which together serve enhance the functionality and accessibility of the Service's features and expand its usability to new potential domains.