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A vague set based decision support approach for evaluating research funding programs

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  • Wang, Jue
  • Xu, Wei
  • Ma, Jian
  • Wang, Shouyang

Abstract

Scientific Research Assessment (SRA) is receiving increasing attention in both academic and industry. More and more organizations are recognizing the importance of SRA for the optimal use of scarce resources. In this paper, a vague set theory based decision support approach is proposed for SRA. Specifically, a family of parameterized S-OWA operator is developed for the aggregation of vague assessments. The proposed approach is introduced to evaluate the research funding programs of the National Natural Science Foundation of China (NSFC). It provides a soft and expansive way to help the decision maker in NSFC to make his decisions. The proposed approach can also be used for some other agencies to make similar assessment.

Suggested Citation

  • Wang, Jue & Xu, Wei & Ma, Jian & Wang, Shouyang, 2013. "A vague set based decision support approach for evaluating research funding programs," European Journal of Operational Research, Elsevier, vol. 230(3), pages 656-665.
    • Handle: RePEc:eee:ejores:v:230:y:2013:i:3:p:656-665
    DOI: 10.1016/j.ejor.2013.04.045
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    2. Çağlar, Musa & Gürel, Sinan, 2019. "Impact assessment based sectoral balancing in public R&D project portfolio selection," Socio-Economic Planning Sciences, Elsevier, vol. 66(C), pages 68-81.
    3. Xiaomin Xu & Qiong Wang & Dongxiao Niu & Lihui Zhang, 2018. "Synergistic Effect Evaluation of Main and Auxiliary Industry of Power Grid Based on the Information Fusion Technology from the Perspective of Sustainable Development of Enterprises," Sustainability, MDPI, vol. 10(2), pages 1-18, February.
    4. Jessop, Alan, 2014. "IMP: A decision aid for multiattribute evaluation using imprecise weight estimates," Omega, Elsevier, vol. 49(C), pages 18-29.
    5. Mavrotas, George & Makryvelios, Evangelos, 2021. "Combining multiple criteria analysis, mathematical programming and Monte Carlo simulation to tackle uncertainty in Research and Development project portfolio selection: A case study from Greece," European Journal of Operational Research, Elsevier, vol. 291(2), pages 794-806.
    6. Schäfer, Luca E. & Dietz, Tobias & Barbati, Maria & Figueira, José Rui & Greco, Salvatore & Ruzika, Stefan, 2021. "The binary knapsack problem with qualitative levels," European Journal of Operational Research, Elsevier, vol. 289(2), pages 508-514.
    7. Aorui Bi & Shuya Huang & Xinguo Sun, 2023. "Risk Assessment of Oil and Gas Pipeline Based on Vague Set-Weighted Set Pair Analysis Method," Mathematics, MDPI, vol. 11(2), pages 1-21, January.

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