Development of Public Administration Research with a Bibliometric Analysis

Author:

Yu Zepeng1ORCID

Affiliation:

1. Department of Information Resources Management, School of Public Affairs, Zhejiang University, Hangzhou 310058, Zhejiang, China

Abstract

Recently, several studies adopted bibliometric methodology to estimate the development of the field of public administration (PA). However, only a small scope of journals was covered in their analyses. Few of those investigated the evolution of the entire field. To make a progress, this paper included a 19-year timespan, 53 journals, and more than 20,000 items for analysis in a bibliometric way. Both the activity and the quality indicators of research results were applied from the bibliometric perspective with 3-year and 5-year citation windows at three aggregation levels including journal, country, and institution by using publications in PA indexed in Social Sciences Citation Index (SSCI). “Resident” journal is proposed as a new concept to explore differences between traditional and emerging research forces. The results suggest that resident journals maintain a large advantage over other journals in terms of higher quality journal indicators and citation impact indicators. Moreover, international and national collaboration shows a growth tendency, especially for the international type. The majority of active institutions are from the US and the UK, which indicates their dominant position over others. This study provides more comprehensive comparisons through large-scale data and acknowledged methods to explore the development of PA field research.

Publisher

Hindawi Limited

Subject

Computer Science Applications,Software

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Bibliometric and Visual Insights Into Higher Education Informatization;International Journal of Information and Communication Technology Education;2024-03-19

2. Productive entities and citation patterns of highly cited papers in public administration domain: An informetric profile;Chinese Public Administration Review;2023-10-12

3. Research on fault diagnosis method of reciprocating compressor valve based on IVMD-CMS model;Journal of Mechanical Science and Technology;2023-08

4. Classification of multiple power quality disturbances based on continuous wavelet transform and lightweight convolutional neural network;Energy Science & Engineering;2023-07-10

5. Application of state parameter learning for fault diagnosis on the large reciprocating compressor;Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering;2023-01-09

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3