Modified Technique for Type-2 Neutrosophic Number Multiple-Attribute Decision-Making and Applications to Quality Evaluation of Management Work in University Student Organizations

Abstract

The quality evaluation of management work in university student organizations is a 
process of systematically analyzing and assessing the efficiency, organizational capacity, and 
management level of student organizations. Evaluation criteria typically cover areas such as 
institutional development, event planning and execution, member development and management, 
and resource utilization. By combining quantitative and qualitative methods, the evaluation not only 
identifies strengths and weaknesses in the management process but also provides a basis for future 
improvements and optimizations, ultimately enhancing the overall management level and work 
quality of student organizations. The quality evaluation of management work in university student 
organizations is multiple-attribute decision-making (MADM). In this study, the Exponential 
TODIM (ExpTODIM) approach and TOPSIS approach are proposed for multi-attribute decision
making (MADM). To address the uncertainty and vagueness in the quality evaluation of 
management work in university student organizations, Type-2 Neutrosophic Numbers (T2NNs) are 
utilized to represent fuzzy information. The study introduces the T2NN-ExpTODIM-TOPSIS 
approach for MADM under T2NNs. Numerical example is presented to validate the effectiveness 
of the T2NN-ExpTODIM-TOPSIS in evaluating the quality of management work in university 
student organizations. The primary motivations behind this research include: (1) enhancing the 
ExpTODIM and TOPSIS approaches by incorporating Intuitionistic Fuzzy Sets (IFS); (2) using 
entropy to assign weight values based on score functions within the T2NN framework; (3) 
developing the T2NN-ExpTODIM-TOPSIS for MAGDM; and (4) conducting a numerical example 
and comparative analysis to demonstrate the validity of the proposed approach in evaluating 
management quality. Through this work, the study provides a comprehensive solution for handling 
complex decision-making scenarios where uncertainty and fuzziness are present, thereby improving 
the accuracy and reliability of quality assessments in university student organizations.

DOI: 10.5281/zenodo.14120964