Robotic process automation: bibliometric reflection and future opportunities

Dahlia Fernandez, Omkar Dastane, Hafizah Omar Zaki and Aini Aman

European Journal of Innovation Management, 2023, vol. 27, issue 2, 692-712

Abstract: Purpose - Robotic Process Automation (RPA) is a digital transformation tool that demonstrated tremendous growth in research output as well as its application in the past decade. This study attempts to identify essential research gaps and proposes future research agendas in the field by analyzing publishing trends, major stakeholders (authors, countries, affiliations, journals), key clusters and evolving themes by mapping the most recent research (2016–2022) in the field. Design/methodology/approach - Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) was used to retrieve a total of 244 publications from the Web of Science (WOS) database for this analysis. The study then uses the open-source R program bibliometrix to conduct bibliometric analysis. A variety of tools and methods including collaboration network, word dynamics, co-occurrence network, thematic map and strategy map were utilized. Findings - The analysis reveals the most influential stakeholders (country: the USA, author: Arai K, affiliation: Christ Deemed University), main clusters of intellectual structure (process mining, digital transformation, blockchain, information systems) and the evolution of themes (model innovation, artificial intelligence, big-data, design science and user acceptance) in the subject. Originality/value - This study uses bibliometric analysis to provide a comprehensive overview of RPA literature which unravels the conceptual structure of the stream and proposes a research agenda for the future. Based on the growth of themes and the strategy map, this study may assist entrepreneurs and practitioners in determining field priorities for strategizing process innovation.

Keywords: Robotic process automation; Process management; Digital transformation; Process innovation; Digital technology; Bibliometric analysis (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eme:ejimpp:ejim-10-2022-0570

DOI: 10.1108/EJIM-10-2022-0570

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