Structural equation modelling – artificial neural network based hybrid approach for assessing quality of university cafeteria services
ISSN: 1754-2731
Article publication date: 23 May 2022
Issue publication date: 4 May 2023
Abstract
Purpose
This study aims to show the effectiveness and applicability of artificial intelligence applications in the measurement and evaluation of university services. Universities can gain competitive advantage through providing their students with quality services in various aspects, such as bookstores, dormitories, recreation centers as well as cafeterias. Among these facilities, university cafeterias are places where students spend a significant amount of time. Therefore, this study aims to integrate artificial intelligence application in the evaluation of university cafeteria services based on students' perceptions with two-stage structural equation modeling (SEM) and artificial neural network (ANN) approach.
Design/methodology/approach
An artificial intelligence based SEM-ANN hybrid approach was used to determine the factors that have significant influence on student satisfaction, sufficiency-of-services and likelihood-of-recommendation. Data were collected from 373 students through a face-to-face questionnaire. Initially, four service quality dimensions were attained through factor analysis. Then, hypotheses, which were determined via literature review, were tested through SEM-ANN hybrid approach.
Findings
Incorporating the results of SEM analysis into the ANN technique resulted in superior models with good prediction performance. Based on four ANN models created and ANN sensitivity analyses conducted, significant predictors of satisfaction, sufficiency, reliability and recommendation are determined and ranked.
Originality/value
Prior studies have assessed service quality using traditional techniques, whereas, this study integrates artificial intelligence in the assessment of higher-educational institutions' services quality. Also, as a distinction from previous studies, this study ranked importance levels of predictor variables through ANN sensitivity analysis.
Keywords
Citation
Uluskan, M. (2023), "Structural equation modelling – artificial neural network based hybrid approach for assessing quality of university cafeteria services", The TQM Journal, Vol. 35 No. 4, pp. 1048-1071. https://doi.org/10.1108/TQM-01-2022-0001
Publisher
:Emerald Publishing Limited
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