Bibliometric analysis of global scientific research on Public Administration: 1923-2020

Mahdi Abdolhamid, Mohammadreza Abdolhoseinzadeh, Mohammadreza Esmaeili Givi,Mohammad Karim Saberi,Seyedeh Zahra Mirezati,Mohammad Reza Amiri

International Journal of Information Science and Management(2023)

引用 0|浏览0
暂无评分
摘要
This study aims to perform a bibliometric analysis of documents published in the field of Public Administration during the years 1923-2020. In this bibliometric study, all Web of Science (WOS) databases were used to retrieve the publications in this field. Using a proper search strategy, 93093 records were retrieved in the WOS database from 1923 to 2020. Excel and VOSviewer software were used for bibliometric analysis and visualization of documents. The findings show that 64.31% of documents (59860 documents) were articles; most documents were published in the Public Administration Review-Journal (n= 9011). The United States (with 31930 documents), ENGLAND (with 14636 documents), and Canada (with 7104 documents) published the most documents in this field, respectively. The University of Birmingham was the most productive institution (n=1,441, 1.54 %). Meier, K. J. S was the most productive author (n= 119, 0.12%). Keywords with the highest frequency were "management", "governance", "government", "policy", "performance", "politics", "state", and "organizations". The most co-occurrence keywords existed within three clusters, the first including keywords related to policy issues, the second including author keywords about management and performance, and the third including keywords related to state and local management. The global trend of publications in the field of Public Administration has been upward, from 54 documents in 1923 to 4561 documents in 2020. This study not only presents a full view of global Public Administration research but also can contribute to future research in this field and bibliometric studies.
更多
查看译文
关键词
bibliometric analysis,visualization,public administration,keywords co-occurrence map
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要