Bibliometric analysis for process capability research

Ahmad, S, Alatefi, M, Alkahtani, M, Anwar, S, Sharaf, M and ABDOLLAHIAN, M 2018, 'Bibliometric analysis for process capability research', Quality Technology & Quantitative Management, vol. 16, no. 4, pp. 459-477.


Document type: Journal Article
Collection: Journal Articles

Title Bibliometric analysis for process capability research
Author(s) Ahmad, S
Alatefi, M
Alkahtani, M
Anwar, S
Sharaf, M
ABDOLLAHIAN, M
Year 2018
Journal name Quality Technology & Quantitative Management
Volume number 16
Issue number 4
Start page 459
End page 477
Total pages 19
Publisher Taylor and Francis
Abstract Bibliometric research focuses on the analysis of the bibliographic indicators quantitatively. It is a useful way for classifying information according to different variables, including journals, institutions and countries. This paper presents a general overview of research conducted in the field of process capability using bibliometric indicators. The main advantage of the current study is that the bibliometric indicators provide a broad picture and identify some of the most influential research conducted in the area of process capability. The analysis is divided into key sections focused on relevant journals, research papers, authors, institutions and countries. Web of Science (WOS) databases is the source of data for carrying out this bibliometric analysis. The study reveals that W.L. Pearn and C.W. Wu. are the two most influential authors in process capability research. On the other hand, Journal of Quality Technology, and Quality and Reliability Engineering International are the two most influential journals for publishing process capability researches. Furthermore, Taiwan is found to be the most influential country, followed by the U.S.A. in the process capability research.
Subject Applied Statistics
Keyword(s) Process capability (PC) research
Process capability indices (PCIs)
Bibliometric indicators
Influential authors
Influential research organizations
Influential countries
DOI - identifier 10.1080/16843703.2018.1464426
Copyright notice © 2018 International Chinese Association of Quantitative Management
ISSN 1684-3703
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