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Decision-Making in Robotic Process Automation Programming and its Influence on Robotic Process Mining

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Business Process Management: Blockchain, Robotic Process Automation, Central and Eastern European, Educators and Industry Forum (BPM 2024)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 527))

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Abstract

Robotic Process Automation (RPA) technology leverages software bots to automate repetitive tasks within digital environments. While RPA offers significant efficiency gains, current bot programming processes remain heavily manual, requiring extensive effort from developers and domain experts. A current research gap exists in the factors influencing developer decisions during the low-code programming of RPA bots, specifically the choices they make when implementing a selected process. This limited knowledge hinders efforts to automate the bot programming process itself utilizing Robotic Process Mining (RPM) methods. This research study aims to address this knowledge gap by investigating the decision-making of RPA developers. A semi-structured interview study with RPA professionals was conducted to explore the factors influencing developers’ decisions when selecting and translating manual actions into automated processes. The findings from the interview have been the basis to show their implications on RPM tools and to give guidance for the improvement of RPM tools.

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Authors and Affiliations

  1. KU Eichstätt-Ingolstadt, Ostenstr. 28a, 85072, Eichstätt, Germany

    Tom Hohenadl

  2. Technische Hochschule Ingolstadt, Esplanade 10, 85049, Ingolstadt, Germany

    Tom Hohenadl, Bernhard Axmann & Christian Stummeyer

Authors
  1. Tom Hohenadl
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  2. Bernhard Axmann
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  3. Christian Stummeyer
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Corresponding author

Correspondence to Tom Hohenadl .

Editor information

Editors and Affiliations

  1. Utrecht University, Utrecht, The Netherlands

    Claudio Di Ciccio

  2. University of Vienna, Vienna, Austria

    Walid Fdhila

  3. Sapienza University of Rome, Rome, Italy

    Simone Agostinelli

  4. University of Ottawa, Ottawa, ON, Canada

    Daniel Amyot

  5. Kühne Logistics University, Hamburg, Germany

    Henrik Leopold

  6. Masaryk University, Brno, Czech Republic

    Michal Krčál

  7. TU Wien, Vienna, Austria

    Monika Malinova Mandelburger

  8. University of Maribor, Maribor, Slovenia

    Gregor Polančič

  9. University of Zagreb, Varaždin, Croatia

    Katarina Tomičić-Pupek

  10. AGH University of Krakow, Kraków, Poland

    Katarzyna Gdowska

  11. University of St. Gallen, St. Gallen, Switzerland

    Thomas Grisold

  12. University of Gdańsk, Gdańsk, Poland

    Piotr Sliż

  13. Utrecht University, Utrecht, The Netherlands

    Iris Beerepoot

  14. University of Warsaw, Warsaw, Poland

    Renata Gabryelczyk

  15. University of Duisburg-Essen, Essen, Germany

    Ralf Plattfaut

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Hohenadl, T., Axmann, B., Stummeyer, C. (2024). Decision-Making in Robotic Process Automation Programming and its Influence on Robotic Process Mining. In: Di Ciccio, C., et al. Business Process Management: Blockchain, Robotic Process Automation, Central and Eastern European, Educators and Industry Forum. BPM 2024. Lecture Notes in Business Information Processing, vol 527. Springer, Cham. https://doi.org/10.1007/978-3-031-70445-1_11

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  • DOI: https://doi.org/10.1007/978-3-031-70445-1_11

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  • Online ISBN: 978-3-031-70445-1

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