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Control and Monitoring of Software Robots: What Can Academia and Industry Learn from Each Other?

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Research Challenges in Information Science (RCIS 2024)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 514))

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Abstract

Robotic Process Automation (RPA) has witnessed significant growth, becoming widely adopted in practice. This surge in the use of RPA technology has given rise to new challenges, particularly concerning the effective control and monitoring of software robots. Ideally, academia and industry would work together on develo** new RPA capabilities, but both domains operate rather separately. In this paper, we employ an explorative approach to examine how academic theories can improve industrial RPA practices and vice versa. By analyzing both academic literature and leading RPA platforms, we present four recommendations for academia, four for industry, and a general recommendation aiming to advance the collaboration between them.

This research was supported by the EQUAVEL project PID2022-137646OB-C31 funded by MICIU/AEI/10.13039/501100011033 and by FEDER, UE; the grant FPU20/05984 funded by MICIU/AEI/10.13039/501100011033 and by FSE+, and its mobility grant EST23/00732.

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Notes

  1. 1.

    Gartner Magic Quadrant RPA: www.uipath.com/es/resources/automation-analyst-reports/gartner-magic-quadrant-robotic-process-automation.

  2. 2.

    Forrester Wave RPA: https://www.uipath.com/resources/automation-analyst-reports/forrester-wave-rpa.

  3. 3.

    Full academic analysis described in: https://doi.org/10.5281/zenodo.10818625.

  4. 4.

    Full industrial analysis described in: https://doi.org/10.5281/zenodo.10818625.

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Authors and Affiliations

  1. Department of Information and Computing Sciences, Utrecht University, Utrecht, The Netherlands

    Kelly Kurowski & Hajo A. Reijers

  2. Department of Computer Languages and Systems, University of Seville, Seville, Spain

    Antonio Martínez-Rojas

Authors
  1. Kelly Kurowski
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  2. Antonio Martínez-Rojas
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  3. Hajo A. Reijers
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Corresponding author

Correspondence to Antonio Martínez-Rojas .

Editor information

Editors and Affiliations

  1. NOVA University Lisbon, Caparica, Portugal

    João Araújo

  2. University of Castilla La Mancha, Albacete, Albacete, Spain

    Jose Luis de la Vara

  3. University of Minho, Guimarães, Portugal

    Maribel Yasmina Santos

  4. Institut Mines-Télécom Business School, Evry, France

    Saïd Assar

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Kurowski, K., Martínez-Rojas, A., Reijers, H.A. (2024). Control and Monitoring of Software Robots: What Can Academia and Industry Learn from Each Other?. In: Araújo, J., de la Vara, J.L., Santos, M.Y., Assar, S. (eds) Research Challenges in Information Science. RCIS 2024. Lecture Notes in Business Information Processing, vol 514. Springer, Cham. https://doi.org/10.1007/978-3-031-59468-7_7

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  • DOI: https://doi.org/10.1007/978-3-031-59468-7_7

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