IDEAS home Printed from https://ideas.repec.org/a/eee/soceps/v87y2023ipbs0038012123000794.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0038012123000794
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.seps.2023.101579?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kara, Karahan & Yalçın, Galip Cihan & Simic, Vladimir & Baysal, Zeynep & Pamucar, Dragan, 2024. "The alternative ranking using two-step logarithmic normalization method for benchmarking the supply chain performance of countries," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gao, Kang & Yuan, Yijun, 2022. "Government intervention, spillover effect and urban innovation performance: Empirical evidence from national innovative city pilot policy in China," Technology in Society, Elsevier, vol. 70(C).
    2. Huseyin Emre Sayici & Mehmet Fatih Ulu, 2023. "Economic Effects of R&D Supports," Koç University-TUSIAD Economic Research Forum Working Papers 2308, Koc University-TUSIAD Economic Research Forum.
    3. Thomas H. W. Ziesemer, 2021. "The Effects of R&D Subsidies and Publicly Performed R&D on Business R&D: A Survey," Hacienda Pública Española / Review of Public Economics, IEF, vol. 236(1), pages 171-205, March.
    4. Amir Homayoun Sarfaraz & Amir Karbassi Yazdi & Thomas Hanne & Peter Fernandes Wanke & Raheleh Sadat Hosseini, 2023. "Assessing repair and maintenance efficiency for water suppliers: a novel hybrid USBM-FIS framework," Operations Management Research, Springer, vol. 16(3), pages 1321-1342, September.
    5. Hyensup Shim & Kiyoon Shin, 2021. "Empirical Analysis of Evidence-Based Policymaking in R&D Programmes," Sustainability, MDPI, vol. 14(1), pages 1-15, December.
    6. Sergio Afcha & Jose García-Quevedo, 2016. "The impact of R&D subsidies on R&D employment composition," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 25(6), pages 955-975.
    7. Yunyao Li & Yanji Ma, 2022. "Research on Industrial Innovation Efficiency and the Influencing Factors of the Old Industrial Base Based on the Lock-In Effect, a Case Study of Jilin Province, China," Sustainability, MDPI, vol. 14(19), pages 1-23, October.
    8. Caloffi, Annalisa & Freo, Marzia & Ghinoi, Stefano & Mariani, Marco & Rossi, Federica, 2022. "Assessing the effects of a deliberate policy mix: The case of technology and innovation advisory services and innovation vouchers," Research Policy, Elsevier, vol. 51(6).
    9. Montmartin, Benjamin & Herrera, Marcos & Massard, Nadine, 2018. "The impact of the French policy mix on business R&D: How geography matters," Research Policy, Elsevier, vol. 47(10), pages 2010-2027.
    10. Dimos, Christos & Pugh, Geoff & Hisarciklilar, Mehtap & Talam, Ema & Jackson, Ian, 2022. "The relative effectiveness of R&D tax credits and R&D subsidies: A comparative meta-regression analysis," Technovation, Elsevier, vol. 115(C).
    11. Haddoud, Mohamed Yacine & Kock, Ned & Onjewu, Adah-Kole Emmanuel & Jafari-Sadeghi, Vahid & Jones, Paul, 2023. "Technology, innovation and SMEs' export intensity: Evidence from Morocco," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    12. Le Roy, Frédéric & Robert, Frank & Hamouti, Rizlane, 2022. "Vertical vs horizontal coopetition and the market performance of product innovation: An empirical study of the video game industry," Technovation, Elsevier, vol. 112(C).
    13. Emmanuel Chavez, 2020. "The Effects of Public R&D Subsidies on Private R&D Activities in Mexico," Working Papers halshs-02355106, HAL.
    14. Natália L. Figueiredo & João J. M. Ferreira, 2022. "More than meets the partner: a systematic review and agenda for University–Industry cooperation," Management Review Quarterly, Springer, vol. 72(1), pages 231-273, February.
    15. Nilsen, Øivind A. & Raknerud, Arvid, 2024. "Dynamics of first-time patenting firms," Research Policy, Elsevier, vol. 53(8).
    16. Seul-gi Lee & Bashir Adelodun & Mirza Junaid Ahmad & Kyung Sook Choi, 2022. "Multi-Level Prioritization Analysis of Water Governance Components to Improve Agricultural Water-Saving Policy: A Case Study from Korea," Sustainability, MDPI, vol. 14(6), pages 1-18, March.
    17. Boeing, Philipp, 2016. "The allocation and effectiveness of China’s R&D subsidies - Evidence from listed firms," Research Policy, Elsevier, vol. 45(9), pages 1774-1789.
    18. Tong Zhao & Zhijie Song & Tianjiao Li, 2018. "Effect of innovation capacity, production capacity and vertical specialization on innovation performance in China's electronic manufacturing: Analysis from the supply and demand sides," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-23, July.
    19. Zhang, Hongyan & Zhang, Lin, 2023. "Public support and energy innovation: Why do firms react differently?," Energy Economics, Elsevier, vol. 119(C).
    20. Zhong, Qi & Sun, Yaowu, 2020. "The more the better? Relational governance in platforms and the role of appropriability mechanisms," Journal of Business Research, Elsevier, vol. 108(C), pages 62-73.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:soceps:v:87:y:2023:i:pb:s0038012123000794. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/seps .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.