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Computers in Industry
Article . 2020
License: taverne
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Computers in Industry
Article . 2020 . Peer-reviewed
License: Elsevier TDM
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Article . 2021
Data sources: DBLP
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Robotic Process Automation: Contemporary themes and challenges

Contemporary themes and challenges
Authors: Rehan Syed; Suriadi Suriadi; Michael Adams 0001; Wasana Bandara; Sander J. J. Leemans; Chun Ouyang 0001; Arthur H. M. ter Hofstede; +3 Authors

Robotic Process Automation: Contemporary themes and challenges

Abstract

Through the application of Robotic Process Automation (RPA) organisations aim to increase their operational efficiency. In RPA, robots, or ‘bots’ for short, represent software agents capable of interacting with software systems by mimicking user actions, thus alleviating the workload of the human workforce. RPA has already seen significant uptake in practice; solution technologies are offered by multiple vendors. Contrasting with this early practical adoption is the hitherto relative lack of attention to RPA in the academic literature. As a consequence, RPA lacks the sound theoretical foundations that allow for objective reasoning around its application and development. This, in turn, hinders initiatives for achieving meaningful advances in the field. This paper presents a structured literature review that identifies a number of contemporary, RPA-related themes and challenges for future research.

Countries
Netherlands, Australia
Keywords

Robotic Process Automation, Process automation, General Computer Science, Software bots, Taverne, Systematic literature review, General Engineering, Research agenda, Service automation

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    364
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 0.1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 0.1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
364
Top 0.1%
Top 1%
Top 0.1%
Green
hybrid