Abstract
Process mining derives knowledge of the execution of processes through analyzing behavior as observed from real-life events. While benefits of process mining are widely acknowledged, finding an adequate level of detail at which a mined process model is suitable for a specific stakeholder is still an ongoing challenge. Process models can be mined at different levels of abstraction, often resulting in either highly complex or highly abstract process models. This may have an important impact on the comprehensibility of the process model, which can also differ from the perspective of a particular stakeholder. To address this problem from a stakeholder-centric perspective, we propose a methodology for determining an appropriate level of process model abstraction. To this end, we use quantitative metrics on process models as well as a qualitative evaluation by using a technology acceptance model (TAM). A logistics case study involving the fuzzy process mining discovery algorithm shows init ial evidence that the use of appropriate abstraction levels is key when considering the needs of various stakeholders.
Original language | English |
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Title of host publication | Proceedings of the 24th International Conference on Enterprise Information Systems |
Editors | Joaquim Filipe, Michal Smialek, Alexander Brodsky, Slimane Hammoudi |
Publisher | SCITEPRESS |
Pages | 137-147 |
Number of pages | 11 |
Volume | 1 |
ISBN (Print) | 978-989-758-569-2 |
DOIs | |
Publication status | Published - 2022 |
Event | 24th International Conference on Enterprise Information Systems, ICEIS 2022 - Online Duration: 25 Apr 2022 → 27 Apr 2022 Conference number: 24 https://iceis.scitevents.org/?y=2022 |
Publication series
Name | International Conference on Enterprise Information Systems, ICEIS - Proceedings |
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Volume | 1 |
ISSN (Electronic) | 2184-4992 |
Conference
Conference | 24th International Conference on Enterprise Information Systems, ICEIS 2022 |
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Abbreviated title | ICEIS 2022 |
City | Online |
Period | 25/04/22 → 27/04/22 |
Internet address |
Keywords
- process mining
- abstraction levels
- stakeholder analysis
- process models