289 research outputs found

    Investigating expressiveness and understandability of hierarchy in declarative business process models

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    Hierarchy has widely been recognized as a viable approach to deal with the complexity of conceptual models. For instance, in declarative business process models, hierarchy is realized by sub-processes. While technical implementations of declarative sub-processes exist, their application, semantics, and the resulting impact on understandability are less understood yet—this research gap is addressed in this work. More specifically, we discuss the semantics and the application of hierarchy and show how subprocesses enhance the expressiveness of declarative modeling languages. Then, we turn to the influence of hierarchy on the understandability of declarative process models. In particular, we present a cognitive-psychology-based framework that allows to assess the impact of hierarchy on the understandability of a declarative process model. To empirically test the proposed framework, a combination of quantitative and qualitative research methods is followed. While statistical tests provide numerical evidence, think-aloud protocols give insights into the reasoning processes taking place when reading declarative process models

    Investigating Inconsistency Understanding to Support Interactive Inconsistency Resolution in Declarative Process Models

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    Handling inconsistencies in business rules is an important part of corporate compliance management. This includes the resolution of inconsistencies, which currently is a fully automated process that might not always be plausible in a real-world scenario. To include human experts and develop interactive resolution approaches, an understanding of inconsistencies is crucial. Thus, we focus on investigating inconsistency understanding in declarative process models by testing the applicability of insights from declarative process model understanding to different inconsistency characteristics. In the future, this will provide the basis for a series of cognitive experiments evaluating the effects of inconsistency characteristics and representation on inconsistency understanding in declarative process models

    Making Sense of Declarative Process Models: Common Strategies and Typical Pitfalls

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    Declarative approaches to process modeling are regarded as well suited for highly volatile environments as they provide a high degree of flexibility. However, problems in understanding and maintaining declarative business process models impede often their usage. In particular, how declarative models are understood has not been investigated yet. This paper takes a first step toward addressing this question and reports on an exploratory study investigating how analysts make sense of declarative process models. We have handed out real-world declarative process models to subjects and asked them to describe the illustrated process. Our qualitative analysis shows that subjects tried to describe the processes in a sequential way although the models represent circumstantial information, namely, conditions that produce an outcome, rather than a sequence of activities. Finally, we observed difficulties with single building blocks and combinations of relations between activities

    Understanding Declare Models: Strategies, Pitfalls, Empirical Results

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    Declarative approaches to business process modeling are regarded as well suited for highly volatile environments, as they enable a high degree of flexibility. However, problems in understanding and maintaining declarative process models often impede their adoption. Likewise, little research has been conducted into the understanding of declarative process models. This paper takes a first step toward addressing this fundamental question and reports on an empirical investigation consisting of an exploratory study and a follow-up study focusing on the system analysts' sense-making of declarative process models that are specified in Declare. For this purpose, we distributed real-world Declare models to the participating subjects and asked them to describe the illustrated process and to perform a series of sense-making tasks. The results of our studies indicate that two main strategies for reading Declare models exist: either considering the execution order of the activities in the process model, or orienting by the layout of the process model. In addition, the results indicate that single constraints can be handled well by most subjects, while combinations of constraints pose significant challenges. Moreover, the study revealed that aspects that are similar in both imperative and declarative process modeling languages at a graphical level, while having different semantics, cause considerable troubles. This research not only helps guiding the future development of tools for supporting system analysts,but also gives advice on the design of declarative process modeling notations and points out typical pitfalls to teachers and educators of future systems analysts

    ON THE THEORETICAL FOUNDATIONS OF RESEARCH INTO THE UNDERSTANDABILITY OF BUSINESS PROCESS MODELS

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    Against the background of the growing significance of Business Process Management (BPM) for Information Systems (IS) research and practice, especially the field of Business Process Modeling gains more and more importance. Business process models support communication about as well as the coordination of processes and have become a widely adopted tool in practice. As the understandability of business process models plays a crucial role in communication processes, more and more studies on process model understandability have been conducted in IS research. This article aims at investigating underlying theories of research into business process model understandability by means of an in-depth analysis of 126 systematically retrieved research articles on the topic. It shows in how far process model understandability research is multi-theoretically founded. Identified theories differ regarding addressed subject matters, their coverage, their focus as well as the underlying notion of model understanding, which is exemplarily demonstrated and discussed in this article. Moreover, implications of the findings are discussed and an outlook on future business process model understandability research and on the integration potential of theories in this field is given

    Hybrid process technologies in the financial sector

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    Abstract. Danish mortgage credit institutes deal with highly variable and knowledge-intensive processes. At the same time these processes are required to be strictly conformant to current regulations and laws. In addition different divisions of the business are interested in different views on the same process: whereas the IT department implementing the processes would like a complete view that shows the underlying business rules and supports all variants, the end users are only in-terested in a local view that (1) shows only the aspects of the process that they are responsible for and (2) only shows the variants of the process that are rel-evant to them. This paper reports on a project we undertook with such a credit institute where we investigated and addressed these issues by providing a hybrid solution, allowing processes to be modelled using our constraint-based modelling tools, but also supporting flow-based views of both the entire process and specific variants
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