Remarks on the analytic hierarchy process
Management Science
Reply to “remarks on the analytic hierarchy process” by J. S. Dyer
Management Science
A clarification of “remarks on the analytic hierarchy process”
Management Science
Group decision support with the analytic hierarchy process
Decision Support Systems
Using AHP and TOPSIS approaches in customer-driven product design process
Computers in Industry
A fuzzy model of customer satisfaction index in e-commerce
Mathematics and Computers in Simulation
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Weapon selection using the AHP and TOPSIS methods under fuzzy environment
Expert Systems with Applications: An International Journal
Information systems outsourcing decisions using a group decision-making approach
Engineering Applications of Artificial Intelligence
Expert Systems with Applications: An International Journal
A Delphi-AHP-TOPSIS based benchmarking framework for performance improvement of a cold chain
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
An extension of TOPSIS for group decision making
Mathematical and Computer Modelling: An International Journal
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This paper aims to develop a framework that evaluates the student satisfaction. It has divided the whole framework into three stages. The first stage is to build index system to the student satisfaction. The second stage is Analytic Hierarchy Process AHP to calculate weights. The third stage is Technique for Order Preference by Similarity to Ideal Solution TOPSIS. The proposed framework can assist principals to comprehend their students' overall situation. They can identify good practices from others and can benchmark them for improving weaknesses. This framework also facilitates the decision-makers to better understand the complex relationships of student satisfaction factors in decision-making.