A Quantitative Review of the Research on Business Process Management in Digital Transformation: A Bibliometric Approach

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Bui Quang Truong, Anh Nguyen-Duc, Nguyen Thi Cam Van
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引用次数: 1

Abstract

In recent years, research on digital transformation (DT) and business process management (BPM) has gained significant attention in the field of business and management. This paper aims to conduct a comprehensive bibliometric analysis of global research on DT and BPM from 2007 to 2022. A total of 326 papers were selected from Web of Science and Scopus for analysis. Using bibliometric methods, we evaluated the current state and future research trends of DT and BPM. Our analysis reveals that the number of publications on DT and BPM has grown significantly over time, with the Business Process Management Journal being the most active. The countries that have contributed the most to this field are Germany (with four universities in the top 10) and the USA. The Business Process Management Journal is the most active in publishing research on digital transformation and business process management. The analysis showed that “artificial intelligence” is a technology that has been studied extensively and is increasingly asserted to influence companies’ business processes. Additionally, the study provides valuable insights from the co-citation network analysis. Based on our findings, we provide recommendations for future research directions on DT and BPM. This study contributes to a better understanding of the current state of research on DT and BPM and provides insights for future research.
数字化转型中业务流程管理研究的定量回顾:文献计量学方法
近年来,数字化转型(DT)和业务流程管理(BPM)的研究受到了商业和管理领域的广泛关注。本文旨在对2007年至2022年全球关于DT和BPM的研究进行全面的文献计量分析。从Web of Science和Scopus中选取326篇论文进行分析。采用文献计量学的方法,评价了DT和BPM的研究现状和未来的研究趋势。我们的分析显示,随着时间的推移,关于DT和BPM的出版物数量显著增长,其中业务流程管理期刊(Business Process Management Journal)最为活跃。在这一领域贡献最大的国家是德国(有4所大学进入前10名)和美国。《业务流程管理期刊》是在数字化转型和业务流程管理方面发表研究最活跃的期刊。分析显示,“人工智能”是一项被广泛研究的技术,越来越多的人认为它会影响企业的业务流程。此外,本研究还从共被引网络分析中提供了有价值的见解。在此基础上,对未来的研究方向提出了建议。本研究有助于更好地了解DT和BPM的研究现状,并为未来的研究提供见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IET Software
IET Software 工程技术-计算机:软件工程
CiteScore
4.20
自引率
0.00%
发文量
27
审稿时长
9 months
期刊介绍: IET Software publishes papers on all aspects of the software lifecycle, including design, development, implementation and maintenance. The focus of the journal is on the methods used to develop and maintain software, and their practical application. Authors are especially encouraged to submit papers on the following topics, although papers on all aspects of software engineering are welcome: Software and systems requirements engineering Formal methods, design methods, practice and experience Software architecture, aspect and object orientation, reuse and re-engineering Testing, verification and validation techniques Software dependability and measurement Human systems engineering and human-computer interaction Knowledge engineering; expert and knowledge-based systems, intelligent agents Information systems engineering Application of software engineering in industry and commerce Software engineering technology transfer Management of software development Theoretical aspects of software development Machine learning Big data and big code Cloud computing Current Special Issue. Call for papers: Knowledge Discovery for Software Development - https://digital-library.theiet.org/files/IET_SEN_CFP_KDSD.pdf Big Data Analytics for Sustainable Software Development - https://digital-library.theiet.org/files/IET_SEN_CFP_BDASSD.pdf
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