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Efficiency of Government-Sponsored R&D Projects: A Metafrontier DEA Approach

Author

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  • Jung Ho Park

    (Technology Management, Economics, and Policy Graduate Program, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 151-742, Korea)

  • Kwangsoo Shin

    (Department of Biomedical Convergence, College of Medicine, Chungbuk National University, Chungdae-ro 1, Seowon-gu, Cheongju-si, Chungbuk 28644, Korea)

Abstract

Government R&D investments are steadily increasing with the perception that R&D plays an important role in technological innovation and sustainable economic growth. In particular, because biotechnology is recognized as one of the next growth engines, the Korean government has recently increased their investment in biotechnology R&D. However, careful analysis of the efficiency of government-sponsored R&D projects is still lacking. In this paper, we measured the technical efficiency and technology gap ratio to investigate the efficiency of Korean government-sponsored R&D projects of 16 sub-biotechnologies from 2007 to 2013 using a metafrontier Data Envelopment Analysis approach. There was no improvement in overall efficiency between 2007 and 2013. Biochip development technology has been the most efficient sub-biotechnology field and the least efficient fields have been biotechnology product safety and efficacy assessment technology. Medical science and engineering is the closest to optimal production technology among sub-biotechnologies. The efficiency of universities and government-funded research institutes is high, while the efficiency of companies is relatively low. The results suggest that the government should improve the R&D planning process and establish a customized R&D investment strategy that considers the characteristics of technologies and the seven organization types of R&D conductors to increase R&D efficiency.

Suggested Citation

  • Jung Ho Park & Kwangsoo Shin, 2018. "Efficiency of Government-Sponsored R&D Projects: A Metafrontier DEA Approach," Sustainability, MDPI, vol. 10(7), pages 1-17, July.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:7:p:2316-:d:156219
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    as
    1. Diogo Cunha Ferreira & Rui Cunha Marques, 2016. "Malmquist and Hicks–Moorsteen Productivity Indexes for Clusters Performance Evaluation," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(05), pages 1015-1053, September.
    2. Chen, Ying-Hsiu & Lai, Po-Lin & Piboonrungroj, Pairach, 2017. "The relationship between airport performance and privatisation policy: A nonparametric metafrontier approach," Journal of Transport Geography, Elsevier, vol. 62(C), pages 229-235.
    3. Hagedoorn, John & Cloodt, Myriam, 2003. "Measuring innovative performance: is there an advantage in using multiple indicators?," Research Policy, Elsevier, vol. 32(8), pages 1365-1379, September.
    4. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    5. Christopher O’Donnell & D. Rao & George Battese, 2008. "Metafrontier frameworks for the study of firm-level efficiencies and technology ratios," Empirical Economics, Springer, vol. 34(2), pages 231-255, March.
    6. Chen, Yunwei & Yang, Zhiping & Shu, Fang & Hu, Zhengyin & Meyer, Martin & Bhattacharya, Sujit, 2009. "A patent based evaluation of technological innovation capability in eight economic regions in PR China," World Patent Information, Elsevier, vol. 31(2), pages 104-110, June.
    7. Bronzini, Raffaello & Piselli, Paolo, 2016. "The impact of R&D subsidies on firm innovation," Research Policy, Elsevier, vol. 45(2), pages 442-457.
    8. Lee, Chi-Chuan & Huang, Tai-Hsin, 2017. "Cost efficiency and technological gap in Western European banks: A stochastic metafrontier analysis," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 161-178.
    9. Hsu, Fang-Ming & Hsueh, Chao-Chih, 2009. "Measuring relative efficiency of government-sponsored R&D projects: A three-stage approach," Evaluation and Program Planning, Elsevier, vol. 32(2), pages 178-186, May.
    10. Lin, Boqiang & Du, Kerui, 2013. "Technology gap and China's regional energy efficiency: A parametric metafrontier approach," Energy Economics, Elsevier, vol. 40(C), pages 529-536.
    11. Baumann, Julian & Kritikos, Alexander S., 2016. "The link between R&D, innovation and productivity: Are micro firms different?," Research Policy, Elsevier, vol. 45(6), pages 1263-1274.
    12. Lee, Hakyeon & Park, Yongtae & Choi, Hoogon, 2009. "Comparative evaluation of performance of national R&D programs with heterogeneous objectives: A DEA approach," European Journal of Operational Research, Elsevier, vol. 196(3), pages 847-855, August.
    13. Holger Görg & Eric Strobl, 2007. "The Effect of R&D Subsidies on Private R&D," Economica, London School of Economics and Political Science, vol. 74(294), pages 215-234, May.
    14. Wang, Eric C. & Huang, Weichiao, 2007. "Relative efficiency of R&D activities: A cross-country study accounting for environmental factors in the DEA approach," Research Policy, Elsevier, vol. 36(2), pages 260-273, March.
    15. Abramo, Giovanni & D’Angelo, Ciriaco Andrea, 2014. "Assessing national strengths and weaknesses in research fields," Journal of Informetrics, Elsevier, vol. 8(3), pages 766-775.
    16. Guo, Di & Guo, Yan & Jiang, Kun, 2016. "Government-subsidized R&D and firm innovation: Evidence from China," Research Policy, Elsevier, vol. 45(6), pages 1129-1144.
    17. Hashimoto, Akihiro & Haneda, Shoko, 2008. "Measuring the change in R&D efficiency of the Japanese pharmaceutical industry," Research Policy, Elsevier, vol. 37(10), pages 1829-1836, December.
    18. D.S. Prasada Rao & Christopher J. O'Donnell & George E. Battese, 2003. "Metafrontier Functions for the Study of Inter-regional Productivity Differences," CEPA Working Papers Series WP012003, School of Economics, University of Queensland, Australia.
    19. Wang, Qunwei & Zhao, Zengyao & Zhou, Peng & Zhou, Dequn, 2013. "Energy efficiency and production technology heterogeneity in China: A meta-frontier DEA approach," Economic Modelling, Elsevier, vol. 35(C), pages 283-289.
    20. Hayami, Yujiro & Ruttan, Vernon W, 1970. "Agricultural Productivity Differences Among Countries," American Economic Review, American Economic Association, vol. 60(5), pages 895-911, December.
    21. Lee, Seonghee & Lee, Hakyeon, 2015. "Measuring and comparing the R&D performance of government research institutes: A bottom-up data envelopment analysis approach," Journal of Informetrics, Elsevier, vol. 9(4), pages 942-953.
    22. Hong, Jin & Feng, Bing & Wu, Yanrui & Wang, Liangbing, 2016. "Do government grants promote innovation efficiency in China's high-tech industries?," Technovation, Elsevier, vol. 57, pages 4-13.
    23. Sreejith Aravindakshan & Frederick Rossi & T. S. Amjath-Babu & Prakashan Chellattan Veettil & Timothy J. Krupnik, 2018. "Application of a bias-corrected meta-frontier approach and an endogenous switching regression to analyze the technical efficiency of conservation tillage for wheat in South Asia," Journal of Productivity Analysis, Springer, vol. 49(2), pages 153-171, June.
    24. Seema Sharma & V. J. Thomas, 2008. "Inter-country R&D efficiency analysis: An application of data envelopment analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(3), pages 483-501, September.
    25. Dong-hyun Oh & Jeong-dong Lee, 2010. "A metafrontier approach for measuring Malmquist productivity index," Empirical Economics, Springer, vol. 38(1), pages 47-64, February.
    26. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    27. George E. Battese & D. S. Prasada Rao, 2002. "Technology Gap, Efficiency, and a Stochastic Metafrontier Function," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(2), pages 87-93, August.
    28. Leoncini, R. & Maggioni, M. A. & Montresor, S., 1996. "Intersectoral innovation flows and national technological systems: network analysis for comparing Italy and Germany," Research Policy, Elsevier, vol. 25(3), pages 415-430, May.
    29. Torben Tiedemann & Tammo Francksen & Uwe Latacz-Lohmann, 2011. "Assessing the performance of German Bundesliga football players: a non-parametric metafrontier approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 19(4), pages 571-587, December.
    30. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    31. Chris Freeman & Luc Soete, 1997. "The Economics of Industrial Innovation, 3rd Edition," MIT Press Books, The MIT Press, edition 3, volume 1, number 0262061953, December.
    32. Thomas, V.J. & Sharma, Seema & Jain, Sudhir K., 2011. "Using patents and publications to assess R&D efficiency in the states of the USA," World Patent Information, Elsevier, vol. 33(1), pages 4-10, March.
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