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The Empirical Analysis of the Comprehensibility of Process Models created by Process Mining

Bühler, Jana (2021) The Empirical Analysis of the Comprehensibility of Process Models created by Process Mining. Masters thesis, Ulm University.

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Abstract

Companies use process models to specify their operational processes. With the help of process models, the business processes in a company are analysed by process mining techniques to optimise them. The subdiscipline of process discovery identifies the actual state of business processes and enables them to be examined. Various tools and algorithms can be used, which lead to different process visualisations. The type of process visualisation has a major influence on the comprehensibility of process models. The objective of this thesis is to investigate the comprehensibility of process models generated by process mining. For this purpose, an exploratory eye-tracking study is conducted with fifteen participants. The study examines process models from two scenarios - a vaccination process and an insurance process. The corresponding process models are created manually, and event logs are generated from them using self-created applications. These event logs are loaded into the process mining tools Celonis Snap, Disco, ProM, Apromore and PM4Py and process models are generated from them. A selection of the resulting process models is then tested for comprehensibility in the user study. The analysis of variance (ANOVA) shows no significant differences between the different generated process models. Finally, with the Pearson correlation’s help, the participants’ subjective ranking is highly significantly related to the level of acceptability and cognitive load. The correlation between the time spent looking at the process models and the number of correctly answered comprehension questions is interesting. From this correlation, it can be concluded that understanding process models requires a certain amount of time. An astonishing result of the study is that the quality between manually created models and models generated by process mining is similarly high. Despite interesting results, further studies are needed, as the study is confronted with some limitations (particularly the number of participants). The results can be used as a basis for future studies to further explore this field of research.

Item Type:Thesis (Masters)
Subjects:DBIS Research > Master and Phd-Thesis
ID Code:2047
Deposited By: Herr Michael Winter
BibTex Export:BibTeX
Deposited On:06 Oct 2021 16:45
Last Modified:06 Oct 2021 16:45

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