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https://doi.org/10.1007/s12599-016-0460-2
Comprehension of Procedural Visual Business Process Models - Business & Information Systems Engineering
Visual process models are meant to facilitate comprehension of business processes. However, in practice, process models can be difficult to understand. The
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Comprehension of Procedural Visual Business Process Models - Business & Information Systems Engineering
https://doi.org/10.1007/s12599-016-0460-2
Visual process models are meant to facilitate comprehension of business processes. However, in practice, process models can be difficult to understand. The
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Comprehension of Procedural Visual Business Process Models - Business & Information Systems Engineering
Visual process models are meant to facilitate comprehension of business processes. However, in practice, process models can be difficult to understand. The
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206- titleComprehension of Procedural Visual Business Process Models | Business & Information Systems Engineering
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- og:titleComprehension of Procedural Visual Business Process Models - Business & Information Systems Engineering
- og:descriptionVisual process models are meant to facilitate comprehension of business processes. However, in practice, process models can be difficult to understand. The main goal of this article is to clarify the sources of cognitive effort in comprehending process models. The article undertakes a comprehensive descriptive review of empirical and theoretical work in order to categorize and summarize systematically existing findings on the factors that influence comprehension of visual process models. Methodologically, the article builds on a review of forty empirical studies that measure objective comprehension of process models, seven studies that measure subjective comprehension and user preferences, and thirty-two articles that discuss the factors that influence the comprehension of process models. The article provides information systems researchers with an overview of the empirical state of the art of process model comprehension and provides recommendations for new research questions to be addressed and methods to be used in future experiments.
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