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Stratified network mapping decision making technique based decision support framework for R&D budget allocation in South Korea

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  • Geetha, Selvaraj
  • Jeon, JeongHwan

Abstract

In this research work, we proposed and developed a stratified network mapping (SNM) decision making method and used it to improve the industry–university specialization in R&D in each region selected in this study. The proposed method considers the influence of criteria on and their priority in alternatives performance evaluation process. By analyzing the influence of these criteria on decision-making, we can easily improve the performance of alternatives. The SNM gives a clear understanding of each alternatives performance efficiency level. It explores possible and inefficient states and high-level influence states in inefficient states. Narrowly using multi-criteria decision-making methods to rank alternatives does not improve the performance of alternatives. The proposed method helps rank alternatives and improve the performance level of alternatives in each state. We analyzed the R&D investment of central and local governments of South Korea. It is an attempt to invigorate and facilitate R&D collaboration using a decision support model. We analyzed industry–academia research networks and enhanced the efficiency of the research.

Suggested Citation

  • Geetha, Selvaraj & Jeon, JeongHwan, 2023. "Stratified network mapping decision making technique based decision support framework for R&D budget allocation in South Korea," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    • Handle: RePEc:eee:soceps:v:87:y:2023:i:pb:s0038012123000794
    DOI: 10.1016/j.seps.2023.101579
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    1. Crespi, Gustavo & Figal Garone, Lucas & Maffioli, Alessandro & Stein, Ernesto, 2020. "Public support to R&D, productivity, and spillover effects: Firm-level evidence from Chile," World Development, Elsevier, vol. 130(C).
    2. Batur Sir, G. Didem & Çalışkan, Emre, 2019. "Assessment of development regions for financial support allocation with fuzzy decision making: A case of Turkey," Socio-Economic Planning Sciences, Elsevier, vol. 66(C), pages 161-169.
    3. Ching-Te Lin & Jen-Jen Yang & Wen-Jen Chiang & Jen-Jung Yang & Chin-Cheng Yang & Zeljko Stevic, 2022. "Analysis of Mutual Influence Relationships of Purchase Intention Factors of Electric Bicycles: Application of DEMATEL Taking into Account Information Uncertainty and Expert Confidence," Complexity, Hindawi, vol. 2022, pages 1-13, September.
    4. Khoshnevis, Pegah & Teirlinck, Peter, 2018. "Performance evaluation of R&D active firms," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 16-28.
    5. Jun, Seung-Pyo & Yoo, Hyoung Sun & Hwang, Jeena, 2021. "A hybrid recommendation model for successful R&D collaboration: Mixing machine learning and discriminant analysis," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    6. Parvin Golfam & Parisa-Sadat Ashofteh & Taher Rajaee & Xuefeng Chu, 2019. "Prioritization of Water Allocation for Adaptation to Climate Change Using Multi-Criteria Decision Making (MCDM)," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(10), pages 3401-3416, August.
    7. Tse, Caleb H. & Yim, Chi Kin Bennett & Yin, Eden & Wan, Feng & Jiao, Hao, 2021. "R&D activities and innovation performance of MNE subsidiaries: The moderating effects of government support and entry mode," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    8. 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).
    9. Huergo, Elena & Moreno, Lourdes, 2017. "Subsidies or loans? Evaluating the impact of R&D support programmes," Research Policy, Elsevier, vol. 46(7), pages 1198-1214.
    10. Seo, Hangyeol & Chung, Yanghon & Yoon, Hyungseok (David), 2017. "R&D cooperation and unintended innovation performance: Role of appropriability regimes and sectoral characteristics," Technovation, Elsevier, vol. 66, pages 28-42.
    11. Suh, Yongyoon & Woo, Chulwan & Koh, Jinhwan & Jeon, Jeonghwan, 2019. "Analysing the satisfaction of university–industry cooperation efforts based on the Kano model: A Korean case," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    12. Abbas Roozbahani & Ebrahim Ebrahimi & Mohammad Ebrahim Banihabib, 2018. "A Framework for Ground Water Management Based on Bayesian Network and MCDM Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(15), pages 4985-5005, December.
    13. Nilsen, Øivind A. & Raknerud, Arvid & Iancu, Diana-Cristina, 2020. "Public R&D support and firm performance: A multivariate dose-response analysis," Research Policy, Elsevier, vol. 49(7).
    14. Özçelik, Emre & Taymaz, Erol, 2008. "R&D support programs in developing countries: The Turkish experience," Research Policy, Elsevier, vol. 37(2), pages 258-275, March.
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