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The Use of Process Mining in Business Process Simulation Model Construction

Author

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  • Niels Martin
  • Benoît Depaire
  • An Caris

Abstract

The paper focuses on the use of process mining (PM) to support the construction of business process simulation (BPS) models. Given the useful BPS insights that are available in event logs, further research on this topic is required. To provide a solid basis for future work, this paper presents a structured overview of BPS modeling tasks and how PM can support them. As directly related research efforts are scarce, a multitude of research challenges are identified. In an effort to provide suggestions on how these challenges can be tackled, an analysis of PM literature shows that few PM algorithms are directly applicable in a BPS context. Consequently, the results presented in this paper can encourage and guide future research to fundamentally bridge the gap between PM and BPS. Copyright Springer Fachmedien Wiesbaden 2016

Suggested Citation

  • Niels Martin & Benoît Depaire & An Caris, 2016. "The Use of Process Mining in Business Process Simulation Model Construction," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 58(1), pages 73-87, February.
    • Handle: RePEc:spr:binfse:v:58:y:2016:i:1:p:73-87
    DOI: 10.1007/s12599-015-0410-4
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    References listed on IDEAS

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    1. Wil M. P. Aalst & Joyce Nakatumba & Anne Rozinat & Nick Russell, 2010. "Business Process Simulation," International Handbooks on Information Systems, in: Jan vom Brocke & Michael Rosemann (ed.), Handbook on Business Process Management 1, pages 313-338, Springer.
    2. Wil M. P. Aalst, 2015. "Extracting Event Data from Databases to Unleash Process Mining," Management for Professionals, in: Jan vom Brocke & Theresa Schmiedel (ed.), BPM - Driving Innovation in a Digital World, edition 127, pages 105-128, Springer.
    3. N Melão & M Pidd, 2003. "Use of business process simulation: A survey of practitioners," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(1), pages 2-10, January.
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    Cited by:

    1. Rong Liu & Akhil Kumar & Juhnyoung Lee, 2022. "Multi-level Team Assignment in Social Business Processes: An Algorithm and Simulation Study," Information Systems Frontiers, Springer, vol. 24(6), pages 1949-1969, December.
    2. Kristina Rosenthal & Benjamin Ternes & Stefan Strecker, 2021. "Business Process Simulation on Procedural Graphical Process Models," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(5), pages 569-602, October.
    3. Volodymyr Leno & Artem Polyvyanyy & Marlon Dumas & Marcello La Rosa & Fabrizio Maria Maggi, 2021. "Robotic Process Mining: Vision and Challenges," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(3), pages 301-314, June.
    4. Niels Martin & Dominik A. Fischer & Georgi D. Kerpedzhiev & Kanika Goel & Sander J. J. Leemans & Maximilian Röglinger & Wil M. P. van der Aalst & Marlon Dumas & Marcello La Rosa & Moe T. Wynn, 2021. "Opportunities and Challenges for Process Mining in Organizations: Results of a Delphi Study," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(5), pages 511-527, October.

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