Journal
SUSTAINABILITY
Volume 12, Issue 1, Pages -Publisher
MDPI
DOI: 10.3390/su12010202
Keywords
big data; decision tree; government; national R&D project; small and medium-sized enterprises; commercialization performance
Funding
- Korea Institute of Science and Technology Information
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To expand the field of governmental applications of Big Data analytics, this study presents a case of data-driven decision-making using information on research and development (R&D) projects in Korea. The Korean government has continuously expanded the proportion of its R&D investment in small and medium-size enterprises to improve the commercialization performance of national R&D projects. However, the government has struggled with the so-called Korea R&D Paradox, which refers to how performance has lagged despite the high level of investment in R&D. Using data from 48,309 national R&D projects carried out by enterprises from 2013 to 2017, we perform a cluster analysis and decision tree analysis to derive the determinants of their commercialization performance. This study provides government entities with insights into how they might adjust their approach to Big Data analytics to improve the efficiency of R&D investment in small- and medium-sized enterprises.
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