TOPSIS-Based Multi-Criteria Decision-Making Using 2-Tuple Linguistic Neutrosophic Numbers: A Comprehensive Evaluation of Industry-Education Integration in Applied Undergraduate Universities

Abstract

 The quality evaluation of university-industry integration aims to assess the effectiveness 
of collaboration between universities and industries by evaluating the quality of talent cultivation, 
curriculum design, and practical teaching. This evaluation ensures a close alignment between 
education and industry needs. It not only focuses on enhancing students' professional skills but also 
assesses the sustainability and innovation of collaborative projects, promoting educational reform 
in universities, improving students' employability, and supplying highly qualified talent to society 
and industry. The quality evaluation of industry-education integration in applied undergraduate 
universities is a multiple-attribute group decision-making (MAGDM) approach. The TOPSIS and 
average approach are put forward by MAGDM. 2-tuple linguistic neutrosophic numbers (2TLNNs) 
could excavate the uncertainty more effectively and deeply for quality evaluation of industry
education integration in applied undergraduate universities. In this study, the Opinion Weight 
Criteria Method (OWCM) is put forward weight numbers along with 2TLNNs and 2TLNN 
combined TOPSIS (2TLNN-CTOPSIS) approach based on 2TLNN Hamming distance (2TLNNHD) 
and 2TLNN Euclidean distance (2TLNNED) is put forward MAGDM. At last, numerical examples 
for quality evaluation of industry-education integration in applied undergraduate universities were 
put forward and some comparisons are put forward to illustrate the 2TLNN-CTOPSIS approach.

DOI: 10.5281/zenodo.14194778