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Analysis of the Relationship Between Regulation and R & D Efficiency Using Quantile Regression
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Publication Year
2022-01-01
Journal
Proceedings - 2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
Proceedings - 2022 IEEE International Conference on Big Data and Smart Computing, BigComp 2022, pp.60-63
Keyword
data envelopment analysisquantile regressionR & D efficiencyregulation
Mesh Keyword
Efficiency levelsInput variablesNational levelOECD countriesOutput variablesQuantile regressionR & D efficiencyRegulationScience and TechnologyTriadic patents
All Science Classification Codes (ASJC)
Artificial IntelligenceComputer Science ApplicationsComputer Vision and Pattern RecognitionInformation Systems and ManagementHealth Informatics
Abstract
This study measures the R & D efficiency of 33 OECD countries using data envelopment analysis (DEA), and analyzes the effect of regulation on such R & D efficiency through quantile regression (QR). Gross expenditure on R & D and the total number of researchers are selected as the input variables in the DEA, and the total number of papers and triadic patent families corresponding to representative outputs in the field of science and technology are selected as the output variables. Three reguation indexes are used for QR analysis. Results show that regulations have a positive effect on the R & D efficiency of countries in the bottom 10%, and a negative effect on that of countries in the top 10%. Such findings suggest the need to change the government's regulatory intensity relative to each country's R & D efficiency level to increase national-level R & D efficiency.
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36786
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85127612811&origin=inward
DOI
https://doi.org/10.1109/bigcomp54360.2022.00022
Journal URL
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9736461
Type
Conference
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Joo, Yeoun.Lee이주연
Department of Industrial Engineering
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