A causal analytic approach to student satisfaction index modeling

Ali Turkyilmaz, Leyla Temizer, Asil Oztekin

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

The increasing number of new higher education institutions (HEIs) has resulted in a fierce competition for attracting and retaining the best students. In line with these purposes, this study is aimed at devising a student satisfaction index (SSI) model for the HEIs. The SSI model is developed to measure the satisfaction of students in terms of different aspects such as image of the university, expectations, perceived quality, perceived value, and loyalty. The SSI model was developed using the Bayesian neural networks-based Universal Structure Modeling method. The results provide strategically valuable information for HEIs decision makers with regard to influential factors of student satisfaction and loyalty.

Original languageEnglish
Pages (from-to)1-21
Number of pages21
JournalAnnals of Operations Research
DOIs
Publication statusAccepted/In press - Jun 18 2016
Externally publishedYes

Fingerprint

Student satisfaction
Modeling
Index model
Higher education institutions
Loyalty
Neural networks
Modeling method
Perceived quality
Decision maker
Influential factors
Perceived value

Keywords

  • Bayesian neural networks
  • Causal analytics
  • Data mining
  • Higher education
  • Student satisfaction index
  • Universal Structure Modeling

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Decision Sciences(all)

Cite this

A causal analytic approach to student satisfaction index modeling. / Turkyilmaz, Ali; Temizer, Leyla; Oztekin, Asil.

In: Annals of Operations Research, 18.06.2016, p. 1-21.

Research output: Contribution to journalArticle

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