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 IET Software Pub Date : 2023-09-01 DOI:10.3390/software2030018
Bui Quang Truong, Anh Nguyen-Duc, Nguyen Thi Cam Van
{"title":"A Quantitative Review of the Research on Business Process Management in Digital Transformation: A Bibliometric Approach","authors":"Bui Quang Truong, Anh Nguyen-Duc, Nguyen Thi Cam Van","doi":"10.3390/software2030018","DOIUrl":null,"url":null,"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.","PeriodicalId":50378,"journal":{"name":"IET Software","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Software","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.3390/software2030018","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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。
求助全文
约1分钟内获得全文 去求助
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
期刊最新文献
Breaking the Blockchain Trilemma: A Comprehensive Consensus Mechanism for Ensuring Security, Scalability, and Decentralization IC-GraF: An Improved Clustering with Graph-Embedding-Based Features for Software Defect Prediction IAPCP: An Effective Cross-Project Defect Prediction Model via Intra-Domain Alignment and Programming-Based Distribution Adaptation Understanding Work Rhythms in Software Development and Their Effects on Technical Performance Research and Application of Firewall Log and Intrusion Detection Log Data Visualization System
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1