Economics at your fingertips  

Determinants of research productivity in Korean Universities: the role of research funding

Young-Hwan Lee ()
Additional contact information
Young-Hwan Lee: Won-Kwang Health Science University

The Journal of Technology Transfer, 2021, vol. 46, issue 5, No 8, 1462-1486

Abstract: Abstract University research is a vital source of innovation, and government funds are often used to support innovative research programs. As such, universities are pressured to demonstrate returns on investments through tangible research outcomes. This study analyzed how university resources affect research productivity, using data from 95 4-year universities in Korea from 2009 to 2017. Explanatory variables were remuneration, performance-based payments, and expenditures on research, experiments, machines, and books. Research productivity indices were the numbers of Korea Citation Index (KCI) and Science Citation Index (SCI) publications, authored books, patents attained, and licensing revenue. Considering that research productivity measures are related, this study used a seemingly unrelated regression (SUR) model. The SUR model analysis showed that SCI, patents, and licensing revenue were correlated and resources differentially affected research productivity. Full-time faculty remuneration, performance-based payments, and research expenditure were significant variables in determining SCI, patents, and licensing revenue. Results of quadratic form regression showed that research productivity increased when full-time faculty remuneration increased, but these gains were limited by the law of marginal diminishing returns. However, the performance-based payment variable showed opposite results, reflecting the law of marginal increasing returns. Combined results will help universities set their strategic direction, efficiently allocate their resources, and promote understanding about university functions.

Keywords: Research productivity; R&D resources; Panel data analysis; Korean universities (search for similar items in EconPapers)
JEL-codes: I22 I23 O31 O32 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link) Abstract (text/html)
Access to full text is restricted to subscribers.

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
http://www.springer. ... nt/journal/10961/PS2

DOI: 10.1007/s10961-020-09817-2

Access Statistics for this article

The Journal of Technology Transfer is currently edited by Albert N. Link, Donald S. Siegel, Barry Bozeman and Simon Mosey

More articles in The Journal of Technology Transfer from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

Page updated 2022-07-02
Handle: RePEc:kap:jtecht:v:46:y:2021:i:5:d:10.1007_s10961-020-09817-2