Despite that formal and informal quality aspects are of significant importance to business process modeling, there is only little empirical work reported on process model quality and its impact factors. In this paper we investigate understandability as a proxy for quality of process models and focus on its relations with personal and model characteristics. We used a questionnaire in classes at three European universities and generated several novel hypotheses from an exploratory data analysis. Furthermore, we interviewed practitioners to validate our findings. The results reveal that participants tend to exaggerate the differences in model understandability, that self-assessment of modeling competence appears to be invalid, and that the number of arcs in models has an important influence on understandability. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Mendling, J., Reijers, H. A., & Cardoso, J. (2007). What makes process models understandable? In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4714 LNCS, pp. 48–63). Springer Verlag. https://doi.org/10.1007/978-3-540-75183-0_4
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