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Predicting Airline Customer Loyalty by Integrating Structural Equation Modeling and Bayesian Networks

Author

Listed:
  • Kattreeya Chanpariyavatevong

    (School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand)

  • Warit Wipulanusat

    (Logistics and Business Analytics Center of Excellence and School of Engineering and Technology, Walailak University, Nakhonsithammarat 80161, Thailand)

  • Thanapong Champahom

    (Department of Management, Faculty of Business Administration, Rajamangala University of Technology Isan, Nakhon Ratchasima 30000, Thailand)

  • Sajjakaj Jomnonkwao

    (School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand)

  • Dissakoon Chonsalasin

    (School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand)

  • Vatanavongs Ratanavaraha

    (School of Transportation Engineering, Institute of Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, Thailand)

Abstract

The aviation industry has grown rapidly worldwide and is struggling against intense competition. Especially in Thailand, the compound annual growth rate of passengers traveling by air has increased continuously over the past decade. Unfortunately, during the past two years, the ongoing COVID-19 pandemic has caused severe economic crises for nearly all businesses and industries, including the aviation industry and especially for passenger airlines whose number of customers has decreased astoundingly due to travel restriction. To maintain business stability, therefore, airlines must build customer loyalty to survive in times of crisis. This study thus examines critical factors’ impact on airline loyalty by using a Bayesian network (BN) derived from a structural equation modeling (SEM). The study integrates the SEM and BN to refine causal relationships between critical factors, identified as critical pathways. Findings reveal that customer satisfaction and customer trust, followed by perceived value, dramatically influence customer loyalty and so are considered priorities for building airlines’ customer loyalty. This study also recommends practical strategies and policies to improve customer loyalty amid the competitive airline business during and after the COVID-19 era.

Suggested Citation

  • Kattreeya Chanpariyavatevong & Warit Wipulanusat & Thanapong Champahom & Sajjakaj Jomnonkwao & Dissakoon Chonsalasin & Vatanavongs Ratanavaraha, 2021. "Predicting Airline Customer Loyalty by Integrating Structural Equation Modeling and Bayesian Networks," Sustainability, MDPI, vol. 13(13), pages 1-21, June.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:13:p:7046-:d:580417
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