Control and Monitoring of Software Robots: What Can Academia and Industry Learn from Each Other?
Lecture Notes in Business Information Processing, ISSN: 1865-1356, Vol: 514 LNBIP, Page: 56-64
2024
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Conference Paper Description
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 developing 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.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85193631047&origin=inward; http://dx.doi.org/10.1007/978-3-031-59468-7_7; https://link.springer.com/10.1007/978-3-031-59468-7_7; https://dx.doi.org/10.1007/978-3-031-59468-7_7; https://link.springer.com/chapter/10.1007/978-3-031-59468-7_7
Springer Science and Business Media LLC
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