A Three-Stage Hybrid SEM-BN-ANN Approach for Analyzing Airport Service Quality

Thitinan Pholsook, Warit Wipulanusat (), Poomporn Thamsatitdej, Sarawut Ramjan, Jirapon Sunkpho and Vatanavongs Ratanavaraha
Additional contact information
Thitinan Pholsook: School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand
Warit Wipulanusat: Thammasat University Research Unit in Data Science and Digital Transformation, Department of Civil Engineering, Faculty of Engineering, Thammasat School of Engineering, Thammasat University, Pathumthani 12120, Thailand
Poomporn Thamsatitdej: Thammasat University Research Unit in Data Science and Digital Transformation, College of Innovation, Thammasat University, Bangkok 10200, Thailand
Sarawut Ramjan: Thammasat University Research Unit in Data Science and Digital Transformation, College of Innovation, Thammasat University, Bangkok 10200, Thailand
Jirapon Sunkpho: Thammasat University Research Unit in Data Science and Digital Transformation, College of Innovation, Thammasat University, Bangkok 10200, Thailand
Vatanavongs Ratanavaraha: School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand

Sustainability, 2023, vol. 15, issue 11, 1-20

Abstract: The novel coronavirus (COVID-19) outbreak has impacted the aviation industry worldwide. Several restrictions and regulations have been implemented to prevent the virus’s spread and maintain airport operations. To recover the trustworthiness of air travelers in the new normality, improving airport service quality (ASQ) is necessary, ultimately increasing passenger satisfaction in airports. This research focuses on the relationship between passenger satisfaction and the ASQ dimensions of airports in Thailand. A three-stage analysis model was conducted by integrating structural equation modeling, Bayesian networks, and artificial neural networks to identify critical ASQ dimensions that highly impact overall satisfaction. The findings reveal that airport facilities, wayfinding, and security are three dominant dimensions influencing overall passenger satisfaction. This insight could help airport managers and operators recover passenger satisfaction, increase trustworthiness, and maintain the efficiency of the airports in not only this severe crisis but also in the new normality.

Keywords: airport service quality; passenger satisfaction; structural equation modeling; Bayesian network; artificial neural network (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/11/8885/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/11/8885/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:11:p:8885-:d:1160890

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().