An improved MULTIMOORA method with combined weights and its application in assessing the innovative ability of universities. Issue 2 (21st January 2019)

• Record Type: Journal Article
• Authors: Dong, Liang; Gu, Xin; Wu, Xingli; Liao, Huchang
• Is Part Of: Expert systems. Volume 36:Issue 2(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-01-21
• Subjects: combined attribute weights -- innovative ability assessment -- multi‐attributes decision making -- MULTIMOORA; Expert systems (Computer science); 006.33
• DOI: 10.1111/exsy.12362
• Languages: English
• ISSNs: 0266-4720

Abstract

Abstract: Innovative ability plays a critical role in the sustainable development of universities. Although the assessment of universities' innovative ability is a significant undertaking, it is difficult work. This challenge can be addressed as a typical multiple attribute decision making (MADM) problem, in which multiple attributes should be considered with different levels of importance. This paper aims to propose an integrated MADM method to solve this issue. To do so, we first introduce the least square method with the hesitant fuzzy linguistic term set to determine the subjective attribute weights. Considering that the selected attributes are not always in conflict with each other due to the complexity of objective things, we further present a correlation coefficient‐based method to calculate another kind of attribute weight. The final weights are the combined form of these two types of attribute weights. In addition, we enhance the robust ranking method, MULTIMOORA, with the Borda rule to calculate the utility values of universities and derive their rankings. Finally, after establishing an index system, the assessment of the innovative ability of 26 world‐class construction universities in China is conducted by using the proposed method. The advantages and disadvantages of the assessed universities are analysed.