Factors affecting the loyalty of spa service users in Bangkok

Authors

  • Anurak Treepongath Faculty of Lecturer of the Ph.D. Program College of Innovation and Management., Suan Sunadha Rajabhat University, Thailand
  • Supattra Pranee Faculty of Lecturer of the Ph.D. Program College of Innovation and Management., Suan Sunadha Rajabhat University, Thailand
  • Chaichana Wongjunya Faculty of Lecturer of the Ph.D. Program College of Innovation and Management., Suan Sunadha Rajabhat University, Thailand
  • Bundit Pungnirund Faculty of Lecturer of the Ph.D. Program College of Innovation and Management., Suan Sunadha Rajabhat University, Thailand
  • Natapong Techarattanased Faculty of Lecturer of the Ph.D. Program College of Innovation and Management., Suan Sunadha Rajabhat University, Thailand

Keywords:

Customer Loyalty, Satisfaction, Service Marketing Strategy, Perceived Quality, Image, Structural Equation Modeling, Spa Business

Abstract

The objective of this research is to develop a conceptual framework illustrating the causal relationships among key factors that influence customer loyalty in the spa service industry in Bangkok. This study adopts a documentary research methodology, analyzing a wide array of scholarly articles, research reports, and relevant publications to identify theoretical and empirical insights. The conceptual framework integrates four core constructs — Service Marketing Strategy, Image, Perceived Quality, and Satisfaction — which are posited to have direct and indirect effects on customer loyalty. The findings reveal that well-defined service marketing strategies and strong brand image positively influence customer satisfaction and loyalty, with satisfaction acting as a significant mediating variable. The framework not only contributes to the advancement of service marketing theory in wellness tourism but also offers practical implications for spa business operators aiming to foster long-term customer relationships, particularly in the post-pandemic context. The study recommends future empirical validation of the framework using Structural Equation Modeling (SEM) and encourages exploration of moderating factors such as demographic characteristics, cultural influences, and behavioral patterns.

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Published

2025-04-30