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Regional R&D Efficiency in Korea from Static and Dynamic Perspectives

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  • Ungkyu Han
  • Mette Asmild
  • Martin Kunc

Abstract

Han U., Asmild M. and Kunc M. Regional R&D efficiency in Korea from static and dynamic perspectives, Regional Studies. Research and development (R&D) efficiency has gained great attention in regional innovation research. This study examines the R&D efficiency patterns of 15 Korean regions for 2005–09. It employs data envelopment analysis to identify the regions' R&D performances relative to the best practices from the static perspective, and the Malmquist productivity index to evaluate their changes in performance within a given timeframe, providing a dynamic perspective. The results classify the Korean regions into deteriorating, lagging and improving groups, and indicate that most regions suffer from declining R&D productivity over time because of their inability to catch up with the best practices.

Suggested Citation

  • Ungkyu Han & Mette Asmild & Martin Kunc, 2016. "Regional R&D Efficiency in Korea from Static and Dynamic Perspectives," Regional Studies, Taylor & Francis Journals, vol. 50(7), pages 1170-1184, July.
  • Handle: RePEc:taf:regstd:v:50:y:2016:i:7:p:1170-1184
    DOI: 10.1080/00343404.2014.984670
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    Cited by:

    1. Benita, Francisco & Urzúa, Carlos M., 2018. "Efficient creativity in Mexican metropolitan areas," Economic Modelling, Elsevier, vol. 71(C), pages 25-33.
    2. Manevska-Tasevska, Gordana & Hansson, Helena & Asmild, Mette & Surry, Yves, 2018. "Assessing the regional efficiency of Swedish agriculture under the CAP ‒ a multidirectional efficiency approach," 162nd Seminar, April 26-27, 2018, Budapest, Hungary 271971, European Association of Agricultural Economists.
    3. Tziogkidis, Panagiotis & Philippas, Dionisis & Leontitsis, Alexandros & Sickles, Robin C., 2020. "A data envelopment analysis and local partial least squares approach for identifying the optimal innovation policy direction," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1011-1024.
    4. Leontitsis, Alexandros & Philippas, Dionisis & Sickles, Robin C. & Tziogkidis, Panagiotis, 2018. "Evaluating countries’ innovation potential: an international perspective," Working Papers 18-011, Rice University, Department of Economics.
    5. Xiong, Xi & Yang, Guo-liang & Guan, Zhong-cheng, 2020. "Estimating the multi-period efficiency of high-tech research institutes of the Chinese Academy of Sciences: A dynamic slacks-based measure," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    6. Chen, Kaihua & Kou, Mingting & Fu, Xiaolan, 2018. "Evaluation of multi-period regional R&D efficiency: An application of dynamic DEA to China's regional R&D systems," Omega, Elsevier, vol. 74(C), pages 103-114.
    7. Kangjuan Lv & Yu Cheng & Yousen Wang, 2021. "Does regional innovation system efficiency facilitate energy-related carbon dioxide intensity reduction in China?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(1), pages 789-813, January.
    8. Xi Xiong & Guo-liang Yang & Kai-di Liu & De-qun Zhou, 2022. "A proposed fixed-sum carryovers reallocation DEA approach for social scientific resources of Chinese public universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 4097-4121, July.
    9. Vladimír Holý & Karel Šafr, 2018. "Are economically advanced countries more efficient in basic and applied research?," 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. 26(4), pages 933-950, December.
    10. Xianzhong Cao & Bo Chen & Yuefang Si & Senlin Hu & Gang Zeng, 2021. "Spatio-temporal evolution and mechanism of regional innovation efficiency: Evidence from Yangtze River Delta Urban Agglomeration of China," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-13, July.
    11. Kairui Zuo & Jiancheng Guan, 2017. "Measuring the R&D efficiency of regions by a parallel DEA game model," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(1), pages 175-194, July.
    12. Shuai Liu & Xiao-Yu Xu & Kai Zhao & Li-Ming Xiao & Qi Li, 2021. "Understanding the Complexity of Regional Innovation Capacity Dynamics in China: From the Perspective of Hidden Markov Model," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
    13. Fenfen Wei & Nanping Feng & Kevin H. Zhang, 2017. "Innovation Capability and Innovation Talents: Evidence from China Based on a Quantile Regression Approach," Sustainability, MDPI, vol. 9(7), pages 1-15, July.
    14. Wang, Qian & Ren, Shuming, 2022. "Evaluation of green technology innovation efficiency in a regional context: A dynamic network slacks-based measuring approach," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    15. Pu, Xiaohong & Zeng, Ming & Zhang, Weike, 2023. "Corporate sustainable development driven by high-quality innovation: Does fiscal decentralization really matter?," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 273-289.
    16. Puertas, Rosa & Marti, Luisa & Guaita-Martinez, José M., 2020. "Innovation, lifestyle, policy and socioeconomic factors: An analysis of European quality of life," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    17. Manevska-Tasevska, Gordana & Hansson, Helena & Asmild, Mette & Surry, Yves, 2021. "Exploring the regional efficiency of the Swedish agricultural sector during the CAP reforms ‒ multi-directional efficiency analysis approach," Land Use Policy, Elsevier, vol. 100(C).
    18. Xiong, Xi & Yang, Guo-liang & Guan, Zhong-cheng, 2020. "A parallel DEA-based method for evaluating parallel independent subunits with heterogeneous outputs," Journal of Informetrics, Elsevier, vol. 14(3).
    19. Yu Zhu & Feng Yang & Bengang Gong & Wei Zeng, 2023. "RETRACTED ARTICLE: Assessing the efficiency of innovation entities in China: evidence from a nonhomogeneous data envelopment analysis and Tobit," Electronic Commerce Research, Springer, vol. 23(1), pages 175-205, March.
    20. Stepan Zemtsov & Maxim Kotsemir, 2019. "An assessment of regional innovation system efficiency in Russia: the application of the DEA approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 375-404, August.
    21. Min, Sujin & Kim, Juseong & Sawng, Yeong-Wha, 2020. "The effect of innovation network size and public R&D investment on regional innovation efficiency," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    22. Baocheng He & Jiawei Wang & Jiaoyang Wang & Kun Wang, 2018. "The Impact of Government Competition on Regional R&D Efficiency: Does Legal Environment Matter in China’s Innovation System?," Sustainability, MDPI, vol. 10(12), pages 1-18, November.

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