Are Principal Component Analysis and Factor Analysis Suitable for Technology Evaluation? — Taking Academic Journal Evaluation as an Example

Journal of Measurement and Evaluation

JME, Vol. 1, No. 1, 2026, pp.36-54.

Print ISSN: 3106-0463; Online ISSN: 3106-0471

Journal homepage: https://www.jmeacta.com 

DOI：Https://doi.org/10.64058/JME.26.1.03

Are Principal Component Analysis and Factor Analysis Suitable for Technology Evaluation? — Taking Academic Journal Evaluation as an Example

Yu Liping, Liu Jun, Liu Zihang(translator)

Abstract: Principal component analysis (PCA) and factor analysis are widely used in scientific and technological evaluation, but there is a lack of testing on the selection of evaluation methods. This paper establishes a testing framework and system for the applicability of PCA and factor analysis evaluation methods, conducting tests from three perspectives: pre-evaluation tests, mid-evaluation tests, and post-evaluation tests. Pre-evaluation tests include the KMO test, Bartlett's test, and normality test; mid-evaluation tests mainly involve testing information loss of evaluation indicators; post-evaluation tests mainly include tests of the explanatory power of principal components or common factors, representativeness, monotonicity of indicators, and rationality of weights. An empirical analysis was conducted using the 2015 JCR economics journals as an example. The study suggests that the applicability of methods must be tested when using PCA and factor analysis for evaluation; factor analysis is not suitable for scientific and technological evaluation when information loss is significant; and PCA is not suitable when the number of evaluation objects is large.

Keywords: Principal Component Analysis, Factor Analysis, Method Testing, Science and Technology Evaluation

Author Biographies: Yu Liping, Ph.D., Professor and Ph.D. Supervisor at the School of Statistics and Mathematics, Zhejiang Gongshang University. His research interests include technology economics and science and technology evaluation. E-mail: yvliping@126.com. Liu Jun, Ph.D., an Associate Professor. His research focuses primarily on technology economics and science and technology evaluation. E-mail: 479095320@qq.com. Liu Zihang (translator), corresponding author, Master's student at the School of Statistics and Data Science, Zhejiang Gongshang University.

Received: 18 Nov 2025 / Revised: 04 Dec 2025 / Accepted: 20 Dec 2025 / Published online: 30 Apr 2026 / Print published: 30 May 2026.

This article is an English translation of the following Chinese article: Yu, L., & Liu, J. (2018). Are principal component analysis and factor analysis suitable for technology evaluation?—Taking academic journal evaluation as an example. Journal of Modern Information, 38(6), 73-79, 137. https://doi.org/10.3969/j.issn.1008-0821.2018.06.011