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Evaluation of scientific research projects on the basis of evidential reasoning approach under the perspective of expert reliability

Author

Listed:
  • Weidong Zhu

    (Hefei University of Technology)

  • Shaorong Li

    (Hefei University of Technology)

  • Hongtao Zhang

    (Zhejiang A&F University)

  • Tianjiao Zhang

    (Hefei University of Technology)

  • Zhimin Li

    (Hefei University of Technology)

Abstract

The evaluation of scientific research projects is a multi-expert decision-making problem under incomplete information environment. Whether evaluation results are reasonable or not depends on the expression of experts’ opinions, the reliability of experts and the aggregation method of experts’ opinions. From the perspective of expert reliability, this paper proposes a data-driven evidential reasoning method based on two-dimensional frames of discernment. In the proposed method, project evaluation information and experts’ characteristics information are used as two-dimensional evidence to represent decision information and decision quality information respectively, and belief distribution is used to express these two kinds of information. Experts’ characteristics information is used to measure the reliability of experts to modify project evaluation information given by experts. The discounted project evaluation information is aggregated by using evidential reasoning analysis algorithm to complete the evaluation of scientific research projects. In addition, a learning optimisation model is constructed to determine the relevant parameter values of the proposed method in a data-driven manner using historical evaluation data of projects. The empirical analysis of the National Nature Science Foundation of China verifies the validity and applicability of the proposed method.

Suggested Citation

  • Weidong Zhu & Shaorong Li & Hongtao Zhang & Tianjiao Zhang & Zhimin Li, 2022. "Evaluation of scientific research projects on the basis of evidential reasoning approach under the perspective of expert reliability," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 275-298, January.
    • Handle: RePEc:spr:scient:v:127:y:2022:i:1:d:10.1007_s11192-021-04201-9
    DOI: 10.1007/s11192-021-04201-9
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    References listed on IDEAS

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    1. Sen Liu & Wei Yu & Ling Liu & Yanan Hu, 2019. "Variable weights theory and its application to multi-attribute group decision making with intuitionistic fuzzy numbers on determining decision maker’s weights," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-21, March.
    2. Yang, Jian-Bo, 2001. "Rule and utility based evidential reasoning approach for multiattribute decision analysis under uncertainties," European Journal of Operational Research, Elsevier, vol. 131(1), pages 31-61, May.
    3. Wen-Tao Guo & Van-Nam Huynh & Songsak Sriboonchitta, 2017. "A proportional linguistic distribution based model for multiple attribute decision making under linguistic uncertainty," Annals of Operations Research, Springer, vol. 256(2), pages 305-328, September.
    4. Wang, Ying-Ming & Yang, Jian-Bo & Xu, Dong-Ling, 2006. "Environmental impact assessment using the evidential reasoning approach," European Journal of Operational Research, Elsevier, vol. 174(3), pages 1885-1913, November.
    5. Carole J. Lee & Cassidy R. Sugimoto & Guo Zhang & Blaise Cronin, 2013. "Bias in peer review," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(1), pages 2-17, January.
    6. Simon, C. & Weber, P. & Evsukoff, A., 2008. "Bayesian networks inference algorithm to implement Dempster Shafer theory in reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 950-963.
    7. Carole J. Lee & Cassidy R. Sugimoto & Guo Zhang & Blaise Cronin, 2013. "Bias in peer review," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(1), pages 2-17, January.
    8. Jun Xu & Jiu-Ying Dong & Shu-Ping Wan & De-Yan Yang & Yi-Feng Zeng, 2019. "A Heterogeneous Multiattribute Group Decision-Making Method Based on Intuitionistic Triangular Fuzzy Information," Complexity, Hindawi, vol. 2019, pages 1-18, August.
    9. Minghua Shi & Yuewen Xiao & Qing Wan, 2019. "Extended Heronian Mean Based on Hesitant Fuzzy Linguistic Information for Multiple Attribute Group Decision-Making," Complexity, Hindawi, vol. 2019, pages 1-19, August.
    10. Wei-dong Zhu & Fang Liu & Yu-wang Chen & Jian-bo Yang & Dong-ling Xu & Dong-peng Wang, 2015. "Research project evaluation and selection: an evidential reasoning rule-based method for aggregating peer review information with reliabilities," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1469-1490, December.
    11. Fang Liu & Wei-dong Zhu & Yu-wang Chen & Dong-ling Xu & Jian-bo Yang, 2017. "Evaluation, ranking and selection of R&D projects by multiple experts: an evidential reasoning rule based approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1501-1519, June.
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