TOPSIS, VIKOR and aggregation operators based on q-rung orthopair fuzzy soft sets and their applications

In this article, we study some concepts related to q-rung orthopair fuzzy soft sets (q-ROFSSs) together with their algebraic structure. We present operations on q-ROFSSs and their specific properties and elaborate them with real-life examples and tabular representations to develop an influx of linguistic variables based on q-rung orthopair fuzzy soft (q-ROFS) information. We present an application of q-ROFSSs to multi-criteria group decision-making (MCGDM) process related to the university choice, accompanied by algorithm and flowchart. We develop q-ROFS TOPSIS method and q-ROFS VIKOR method as extensions of TOPSIS (a technique for ordering preference through the ideal solution) and VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje), respectively. Finally, we tackle a problem of construction utilizing q-ROFS TOPSIS and q-ROFS VIKOR methods.

INFLUENCES ON STUDENT CHOICE OF UNIVERSITY: EVIDENCE FROM VIETNAM

The purpose of this study was to identify the factors that influenced university choice in Vietnam. Survey data was collected from 167 students studying in Industrial University of HCM City, Vietnam. The research model was proposed from the study of university choice in the context of education in Vietnam. The reliability and validity of the scale were tested by Cronbach's Alpha, Average Variance Extracted (Pvc) and Composite Reliability (Pc). The analysis results of structural equation model (SEM) showed that the tested relationship between university choice and the four components of the University Choice included University Advertising, Student Expectation, Reference (Family and Friend) and University Reputation. Student Ability, University Characteristics and Enroll to university were not influenced University Choice of Student.

Predicting the Variables That Determine University (Re-)Entrance as a Career Development Using Support Vector Machines with Recursive Feature Elimination: The Case of South Korea

The current study seeks to identify variables that affect the career decision-making of high school graduates with respect to the choice of university (re-)entrance in South Korea where education has great importance as a tool for self-cultivation and social prestige. For pattern recognition, we adopted a support vector machine with recursive feature elimination (SVM-RFE) with a big-data of survey of Korean college candidates. Based on the SVM-RFE analysis results, new enrollers were mostly affected by the mesosystems of interactions with parents, while re-enrollers were affected by the macrosystems of social awareness as well as individual estimates of talent and aptitude of individual systems. By predicting the variables that affect the high school graduates’ preparation for university re-entrance, some survey questions provide information on why they make the university choice based on interactions with their parents or acquaintances. Along with these empirical results, implications for future research are also presented.