A meta-evaluation model on science and technology project review experts using IVIF-BWM and MULTIMOORA. (15th April 2021)
- Record Type:
- Journal Article
- Title:
- A meta-evaluation model on science and technology project review experts using IVIF-BWM and MULTIMOORA. (15th April 2021)
- Main Title:
- A meta-evaluation model on science and technology project review experts using IVIF-BWM and MULTIMOORA
- Authors:
- Wang, Jian
Ma, Qianqian
Liu, Hu-Chen - Abstract:
- Abstract: Meta evaluation theory and methods were used to evaluate the review experts of science and technology projects. Dozens of meta evaluation criteria can be found within two categories: the objective data of the experts' review results, i.e. the coefficient of deviation, the Spearman rank correlation coefficient, the reliability coefficient of binary value; the subjective data of the experts, i.e., the degree of experts' participation, the degree of review punctuality, the qualification of experts, and the degree of review seriousness. How these criteria impact each other has few been examined, and how to integrate the objective and subjective criteria need a comprehensive model with considering the fuzzy characteristics of the subjective criteria. This study targeted these two questions. An empirical study was adopted with hundreds of experts taking part in reviewing hundreds of Sci-Tech projects. The impacting relationships among the criteria were analyzed based on the empirical study. In order to deal with the intuitionistic fuzzy data on the subjective criteria and improve the estimation efficiency, an IVIF-BWM (best worst method under interval-valued intuitionistic fuzzy environment) was proposed by combining IVIF and the classical BWM to generate the importance weight for each criterion. The MULTIMOORA (multi-objective optimization by ratio analysis plus the full multiplicative form) was used to determine how to combine these criteria. At last, the proposedAbstract: Meta evaluation theory and methods were used to evaluate the review experts of science and technology projects. Dozens of meta evaluation criteria can be found within two categories: the objective data of the experts' review results, i.e. the coefficient of deviation, the Spearman rank correlation coefficient, the reliability coefficient of binary value; the subjective data of the experts, i.e., the degree of experts' participation, the degree of review punctuality, the qualification of experts, and the degree of review seriousness. How these criteria impact each other has few been examined, and how to integrate the objective and subjective criteria need a comprehensive model with considering the fuzzy characteristics of the subjective criteria. This study targeted these two questions. An empirical study was adopted with hundreds of experts taking part in reviewing hundreds of Sci-Tech projects. The impacting relationships among the criteria were analyzed based on the empirical study. In order to deal with the intuitionistic fuzzy data on the subjective criteria and improve the estimation efficiency, an IVIF-BWM (best worst method under interval-valued intuitionistic fuzzy environment) was proposed by combining IVIF and the classical BWM to generate the importance weight for each criterion. The MULTIMOORA (multi-objective optimization by ratio analysis plus the full multiplicative form) was used to determine how to combine these criteria. At last, the proposed meta-evaluation model based on IVIF-BWM and MULTIMOORA was applied in a real case. The case study results supported the accuracy and reliability of the proposed model. Highlights: A meta-evaluation model was established to evaluate the technology project review experts. Based on the empirical results, seven meta-evaluation criteria were selected and modified for the model. BWM was improved in interval valued intuitionistic fuzzy environment, and a method called as IVIF-BWM was proposed. A comprehensive meta-evaluation model was founded based on IVIF-BWM and MULTIMOORA. … (more)
- Is Part Of:
- Expert systems with applications. Volume 168(2021)
- Journal:
- Expert systems with applications
- Issue:
- Volume 168(2021)
- Issue Display:
- Volume 168, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 168
- Issue:
- 2021
- Issue Sort Value:
- 2021-0168-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-04-15
- Subjects:
- Science and technology project review -- Meta-evaluation model -- Interval-valued Intuitionistic Fuzzy (IVIF) -- Best Worst Method (BWM) -- MULTIMOORA method
Expert systems (Computer science) -- Periodicals
Systèmes experts (Informatique) -- Périodiques
Electronic journals
006.33 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09574174 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.eswa.2020.114236 ↗
- Languages:
- English
- ISSNs:
- 0957-4174
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3842.004220
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23110.xml