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Towards measuring and quantifying the comprehensibility of process models: the process model comprehension framework

Author

Listed:
  • Michael Winter

    (Ulm University)

  • Rudiger Pryss

    (University of Würzburg)

  • Matthias Fink

    (Ventum Consulting GmbH & Co. KG)

  • Manfred Reichert

    (Ulm University)

Abstract

Process models constitute crucial artifacts in modern information systems, and their proper comprehension is of utmost importance in utilizing such systems. Generally, process models are considered from two different perspectives: process modelers and readers. Both perspectives share similarities and differences in the comprehension of process models (e.g., diverse experiences when working with process models). The literature proposed many rules and guidelines to ensure proper comprehension of process models for both perspectives. As a novel contribution in this context, this paper introduces the process model comprehension framework (PMCF), constituting a first approach towards the measurement and quantification of the perspectives of process modelers and readers, as well as the interaction of both regarding the comprehension of process models. Therefore, the PMCF describes an Evaluation theory tree based on the communication theory and the conceptual modeling quality framework and considers a total of 96 quality metrics to quantify process model comprehension. Furthermore, the PMCF was evaluated in a survey with 131 participants and has been implemented and applied successfully in a practical case study including 33 participants. To conclude, the PMCF allows for the identification of pitfalls and provides related information about how to assist process modelers and readers in fostering and enabling a proper comprehension of process models.

Suggested Citation

  • Michael Winter & Rudiger Pryss & Matthias Fink & Manfred Reichert, 2023. "Towards measuring and quantifying the comprehensibility of process models: the process model comprehension framework," Information Systems and e-Business Management, Springer, vol. 21(3), pages 723-751, September.
    • Handle: RePEc:spr:infsem:v:21:y:2023:i:3:d:10.1007_s10257-023-00642-2
    DOI: 10.1007/s10257-023-00642-2
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    References listed on IDEAS

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    1. John Krogstie & Guttorm Sindre & Håvard Jørgensen, 2006. "Process models representing knowledge for action: a revised quality framework," European Journal of Information Systems, Taylor & Francis Journals, vol. 15(1), pages 91-102, February.
    2. Jan Mendling & Jan Recker & Hajo A. Reijers & Henrik Leopold, 2019. "An Empirical Review of the Connection Between Model Viewer Characteristics and the Comprehension of Conceptual Process Models," Information Systems Frontiers, Springer, vol. 21(5), pages 1111-1135, October.
    3. Rahimi, Fatemeh & Møller, Charles & Hvam, Lars, 2016. "Business process management and IT management: The missing integration," International Journal of Information Management, Elsevier, vol. 36(1), pages 142-154.
    4. Gustavo Teodoro Gabriel & Afonso Teberga Campos & Fabiano Leal & José Arnaldo Barra Montevechi, 2022. "Good practices and deficiencies in conceptual modelling: A systematic literature review," Journal of Simulation, Taylor & Francis Journals, vol. 16(1), pages 84-100, January.
    5. Kathrin Figl, 2017. "Comprehension of Procedural Visual Business Process Models," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 59(1), pages 41-67, February.
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