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Institutional basis for research boom: From catch-up development to advanced economy

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  • Ahn, Sang-Jin

Abstract

Historical best practice emphasizes that the decision for large-scale R&D investment is important to catch-up growth. It is desirable in most developing countries to establish coherence between technological forecasting and science, technology, and innovation policies. This study demonstrates that national foresight has disadvantages in implementing such policies because of insufficient monetized information with discriminant power for investment. To compensate for such disadvantages, a logic model is indispensable, and can be achieved by subsequent foresight at the time of each decision rather than by one-time national foresight. The example of the Korean government emphasizes that decision-making involving consecutive value-based technological forecasting can act as an institutional framework to progress from catch-up development to being an advanced economy. Despite a tradition against aggressive R&D investment in Korea, quantitative ex-ante evaluations with a feasible value chain have given the financial authorities' confidence. This is what has made Korea's research boom possible. If developing or transition countries plan to achieve catch-up growth by expanding R&D investment, the institutional cases in this study will be an important reference.

Suggested Citation

  • Ahn, Sang-Jin, 2017. "Institutional basis for research boom: From catch-up development to advanced economy," Technological Forecasting and Social Change, Elsevier, vol. 119(C), pages 237-245.
  • Handle: RePEc:eee:tefoso:v:119:y:2017:i:c:p:237-245
    DOI: 10.1016/j.techfore.2016.05.022
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    Citations

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    Cited by:

    1. Ahn, Sang-Jin & Yi, Seung-Kyu, 2021. "Methodological framework for analyzing peace engineering: Focusing on Kaesong Industrial Complex and North Korean innovators in South Korea," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    2. Ahn, Sang-Jin & Yoon, Ho Young & Lee, Young-Joo, 2021. "Text mining as a tool for real-time technology assessment: Application to the cross-national comparative study on artificial organ technology," Technology in Society, Elsevier, vol. 66(C).
    3. Keishiro Hara & Iori Miura & Masanori Suzuki & Toshihiro Tanaka, 2023. "Designing research strategy and technology innovation for sustainability by adopting “imaginary future generations”—A case study using metallurgy," Futures & Foresight Science, John Wiley & Sons, vol. 5(3-4), September.
    4. Hara, Keishiro & Miura, Iori & Suzuki, Masanori & Tanaka, Toshihiro, 2024. "Assessing future potentiality of technologies from the perspective of “imaginary future generations” – A case study of hydrothermal technology," Technological Forecasting and Social Change, Elsevier, vol. 202(C).
    5. Dimitris KALLIORAS & Nickolaos TZEREMES & Panayiotis TZEREMES & Maria ADAMAKOU, 2021. "Technological Change, Technological Catch-Up And Market Potential: Evidence From The Eu Regions," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(1), pages 135-151, June.
    6. Ahn, Sang-Jin, 2020. "Three characteristics of technology competition by IoT-driven digitization," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    7. Hyun-Kyu Kang, 2017. "Policy Analysis in Ex-ante Evaluation of Government R&D Programs," Proceedings of International Academic Conferences 5007765, International Institute of Social and Economic Sciences.
    8. Kim, Hyunuk & Ahn, Sang-Jin & Jung, Woo-Sung, 2019. "Horizon scanning in policy research database with a probabilistic topic model," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 588-594.

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