Research on Analyzing the Efficiency of R&D Projects for Climate Change Response Using DEA–Malmquist

In responding to climate change, the world is focusing on technology development. Korea also continues to invest in R&D to reduce greenhouse gas emissions and adapt to climate change. However, compared to the government’s continuous investment in R&D, there is a lack of systematic analysis o...

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Bibliographic Details
Published in:Sustainability 2023-05, Vol.15 (10), p.8433
Main Authors: Han, Suhyeon, Park, Shinyoung, An, Sejin, Choi, Wonjun, Lee, Mina
Format: Article
Language:English
Subjects:
Air pollution
Climate change
Comparative analysis
Data envelopment analysis
Developing countries
Development projects
Efficiency
Emissions
Emissions control
Fossil fuels
Global temperature changes
Greenhouse effect
Greenhouse gases
LDCs
Linear programming
Nuclear energy
Paris Agreement
Productivity
R&D
Research & development
Scale efficiency
Sustainability
Technology
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Summary:In responding to climate change, the world is focusing on technology development. Korea also continues to invest in R&D to reduce greenhouse gas emissions and adapt to climate change. However, compared to the government’s continuous investment in R&D, there is a lack of systematic analysis of R&D investment performance. Rather than simply reducing and increasing the investment in R&D to respond to climate change in terms of high and low efficiency, we aim to improve the efficiency of national R&D projects by analyzing the causes of low efficiency and deriving improvement directions. In this study, data envelopment analysis (DEA) was used to analyze the efficiency of climate change response technology development projects conducted by the Ministry of Science and ICT in Korea. The efficiency of 1500 projects conducted during the 2014–2020 period was analyzed from a static and dynamic perspective, focusing on project information. Through static efficiency analysis, total efficiency (TE), pure technical efficiency (PTE), and scale efficiency (SE) were measured, and the causes of inefficiency were identified. In addition, the results of the dynamic efficiency analysis using the Malmquist analysis were presented, and alternatives for each field were suggested by presenting the static and dynamic results as an integrated model.
ISSN:2071-1050
2071-1050
DOI:10.3390/su15108433