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An Analysis of Influence on the Selection of R&D Project by Evaluation Index for National Land Transport R&D Project - Focusing on the Technology Commercialization Support Project -

국토교통연구개발사업 평가지표별 연구개발과제 선정에 대한 영향력 분석 - 국토교통기술사업화지원 사업을 중심으로 -

  • 심형욱 (국토교통과학기술진흥원)
  • Received : 2022.01.07
  • Accepted : 2022.02.20
  • Published : 2022.02.28

Abstract

As the need for improvement of transparency and fairness in the selection of national R&D projects has been continuously raised, we analyzed the impact on the evaluation selection results by evaluation indexes for The land transportation technology commercialization support project and searched for ways to improve indexes using the analysis results. As for the research data, it were applied as selection results of new R&D projects and evaluation indexes in two fields(SME innovation and start-up) in 2021. Logistic regression analysis is used for the influence of each evaluation indexes on the evaluation result, and for the regression model, evaluation indexes with low influence are removed in advance through artificial neural network multiple perceptron analysis to improve the reliability of the analysis results. As a result of the analysis, in the field of SME innovation, the influence of the evaluation index on the workforce planning was the lowest and the influence of the appropriateness of commercialization promotion plan was the highest. In the start-up field, the influence of the evaluation indexes for technology development suitability, marketability, and suitability for carrying out the project were estimated to be similar to each other, and the influence of the technology evaluation index was found to be the lowest. The analysis results of this thesis suggest the need for continuous improvement of selection and evaluation indexes, and by using the analysis results to select a fair R&D institution according to the selection of appropriate indexes, it will be possible to contribute to deriving excellent research results and fostering excellent companies in the field of land transportation.

국가연구개발사업 연구개발과제 선정에 대한 투명성과 공정성에 대한 개선 필요성이 지속적으로 제기됨에 따라, 국토교통기술사업화지원 사업을 대상으로 선정평가 지표별 평가 결과에 미치는 영향력을 분석하고 분석결과를 활용한 지표 개선 방안을 모색하였다. 연구자료는 2021년도 국토교통기술사업화지원 사업 중소기업 혁신, 스타트업 2개 분야의 신규 연구개발과제의 선정평가 결과 자료와 평가지표를 적용하였으며, 로지스틱 회귀분석을 이용하여 평가지표별 영향력을 분석하였다. 회귀모형은 분석결과의 신뢰성 제고를 위해 인공신경망 다중 퍼셉트론 분석을 수행하여 영향력이 낮은 평가지표를 사전에 제거하였다. 분석결과, 중소기업 혁신 분야는 인력운영계획에 대한 평가지표의 영향력이 가장 낮고 사업화 추진계획의 적절성 지표의 영향력이 가장 높게 나타났다. 스타트업 분야는 기술개발 적합성, 시장성, 사업수행 적합성 평가지표의 영향력이 상호 유사하게 추정되었으며, 기술성 평가지표의 영향력이 가장 낮게 나타났다. 본 논문의 분석결과는 지속적인 선정평가 지표의 개선 필요성을 시사하며, 분석결과를 활용한 타당한 평가지표 선정 및 공정한 연구개발기관 선정을 통해 국토교통 분야 우수 연구성과 도출 및 우수 기업 육성에 기여할 수 있을 것으로 사료된다.

Keywords

References

  1. KAIA. (2021). 2021 Land Transport Science and Technology R&D Project Implementation Plan. Anyang.
  2. NABO. (2020). System analysis of task planning, selection and evaluation of national R&D projects. Seoul.
  3. Y. S. Ryu. (2019). Proposal for innovation of national R&D evaluation system. Seoul : KISTEP.
  4. P. S. Jang, S. H. Oh & J. Y. Lee. (2019). Study on Application of Data-based Selection Model of Firm R&D Support: Focusing on A.I. Methodologies. Sejong : STEPI.
  5. S. M. Yoon, Y. H. Lee & Y. J. Kim. (2021). A Study on the Accuracy of Research Proposal Appraisals: Measuring Expertise and Acquaintanceship of Evaluators. Journal of Korea technology innovation society, 24(5), 891-918. DOI: 10.35978/jktis.2021.10.24.5.891
  6. S. H. Park, J. T. Oh & S. Y. Yong. (2020). An AHP-based Assessment Criteria Decision System for National Research and Development Tasks. Journal of Digital Convergence, 18(5), 405-410. DOI: 10.14400/JDC.2020.18.5.405
  7. H. N. Oh, S. H. Oh, Y. S. Park & S. B. Han. (2019). A Study on the Appropriateness of the New Drug Development Evaluation Indicators. The Journal of Policy Development, 19(2), 41-73. DOI: 10.35224/kapd.2019.19.2.002
  8. J. M. Won. (2015). Urban traffic theory. Seoul : Parkyoungsa.
  9. J. M. Choi & D. M. Lee. (2017). A Study on National R&D Project Proposal Evaluation Indicator for Small-Medium Business. Ocean Policy Research, 32(2), 169-189. DOI: 10.35372/kmiopr.2017.32.2.007
  10. T. I. Kim & J. Y. Song. (2016). Development of Technology and Enterprise Assessment Model for Commercialization of Public Technology. Journal of the Korea Academia-Industrial cooperation Society, 17(5), 153-163. DOI: 10.5762/KAIS.2016.17.5.153
  11. T. E. Sung, H. H. Lee, H. E. Kim & H. W. Park. (2017). Improving the efficiency of the R&D evaluation management system to which technology valuation is applied. Journal of Korea Technology Innovation Society, 2017(11), 747-754.
  12. KAIA. (2021). Land Transport R&D Announcement. https://www.kaia.re.kr/
  13. J. M. Won. (2015). Urban traffic theory. Seoul : Parkyoungsa.
  14. S. H. Kwon, J. W. Lee & G. H. Jung. (2017). Snow Damages Estimation using Artificial Neural Network and Multiple Regression Analysis. Journal of The Korean Society of Hazard Mitigation, 17(2), 315-325. DOI: 10.9798/KOSHAM.2017.17.2.315