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Bibliometric Analysis of Robotic Process Automation Domain: Key Topics, Challenges and Solutions

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Computational Science and Its Applications – ICCSA 2023 (ICCSA 2023)

Abstract

In the era of Industry Revolution 4.0, organizations around the world are continuously looking for new technological breakthroughs that can enhance business process efficiency and reduce the cost of operations. Robotic Process Automation (RPA) has effectively addressed these issues in many different business sectors. RPA is a software application that automates Graphical User Interface (GUI) tasks that were previously performed by human users. However, the current literature in this research is lacking comprehensive bibliometric literature review which can be used to identify the future trend and the latest issues in the RPA research domain. To address these gaps, the objective of this study is to identify the current issues and future trends in the RPA domain. Firstly, a performance analysis of the dataset is performed to understand the future trend of the research domain. Then, the science mapping co-word examination bibliometric data analysis is performed on the selected dataset to identify current issues in this research domain. This work also addresses these issues with a practical evaluation framework for business organizations to effectively exploit the advantages provided by the RPA implementation.

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Acknowledgement

This work was supported in part by Sunway University and Sunway Business School under Kick Start Grant Scheme (KSGS) NO: GRTIN-KSGS-DBA[S]-02–2022. This work is also part of the Sustainable Business Research Cluster and Research Centre for Human-Machine Collaboration (HUMAC) at Sunway University. We also wish to thank those who have supported this research.

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Tang, T.Y., Hwang, H.J. (2023). Bibliometric Analysis of Robotic Process Automation Domain: Key Topics, Challenges and Solutions. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2023. ICCSA 2023. Lecture Notes in Computer Science, vol 13956 . Springer, Cham. https://doi.org/10.1007/978-3-031-36805-9_32

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  • DOI: https://doi.org/10.1007/978-3-031-36805-9_32

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