Economics at your fingertips  

Does gender structure influence R&D efficiency? A regional perspective

Mingting Kou, Yi Zhang, Yu Zhang (), Kaihua Chen, Jiancheng Guan and Senmao Xia
Additional contact information
Mingting Kou: University of Sciences and Technology Beijing
Yi Zhang: Guangdong Ocean University
Yu Zhang: Chinese Academy of Sciences
Kaihua Chen: Chinese Academy of Sciences
Jiancheng Guan: University of Chinese Academy of Sciences
Senmao Xia: Coventry University

Scientometrics, 2020, vol. 122, issue 1, No 22, 477-501

Abstract: Abstract The gender structure in research and development (R&D) activities has received more and more attention in terms of its increasing importance in R&D management, but it is still not clear what the R&D efficiency discrepancy between female and male personnel is in the science and technology (S&T) field and whether the gender structure affects the R&D efficiency. Based on the region-level panel dataset of China’s research institutes, this study uses four types of R&D outputs (papers, books, patents and standards) together and individually to measure R&D efficiency score to reveal this topic. When four types of R&D outputs are jointly considered, this paper applies the multi-output stochastic frontier analysis and finds that in general the higher proportion of male R&D personnel produces the higher R&D efficiency. Nevertheless, in terms of S&T papers or S&T books as a single R&D output, we find that the higher proportion of female R&D personnel leads to the higher R&D efficiency. On the contrary, the R&D efficiency is lower with the higher proportion of female R&D personnel when the single R&D output is measured by invention patent applications or national/industrial standards, respectively. Our findings suggest that the female R&D personnel are more effective in conducting scientific research activities, while their counterparts are more effective in doing technology development activities.

Keywords: R&D efficiency; Gender structure; Gender gap; China’s research institutes; Region-level analysis (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from

DOI: 10.1007/s11192-019-03282-x

Access Statistics for this article

Scientometrics is currently edited by Wolfgang Glänzel

More articles in Scientometrics from Springer, Akadémiai Kiadó
Bibliographic data for series maintained by Sonal Shukla ().

Page updated 2020-04-23
Handle: RePEc:spr:scient:v:122:y:2020:i:1:d:10.1007_s11192-019-03282-x