Enhancing loyalty in luxury fashion with AI: the mediation role of customer relationships
Purpose This study aims to investigate the impact of artificial intelligence (AI) on customer loyalty in the luxury fashion market. It explores how AI-driven tools influence customer trust, satisfaction, commitment and engagement, which in turn affect loyalty. By examining these relationships, the study provides insights into the acceptance and effectiveness of AI technologies in enhancing customer loyalty within the luxury fashion sector. Design/methodology/approach This study employs structural equation modelling (SEM) to analyse data collected from 406 luxury consumers in Iran. The data was gathered using a targeted sampling procedure, leveraging DigiKala’s e-commerce platform. A comprehensive literature review informed the measurement items, and a seven-point Likert scale was used. The methodology includes confirmatory factor analysis (CFA) to assess the reliability and validity of the constructs, followed by hypothesis testing through SEM. Findings The study reveals that AI significantly enhances customer loyalty in the luxury fashion market by positively influencing trust, satisfaction, commitment and engagement. Satisfaction and engagement were found to be key mediators between AI and loyalty, while trust had no direct impact on loyalty. The results underscore the importance of AI-driven personalized experiences in fostering stronger customer relationships and loyalty. Originality/value This study is one of the first to explore the impact of AI on customer loyalty in the luxury fashion market, using a comprehensive model that includes trust, satisfaction, commitment and engagement as mediators. It extends the stimulus-organism-response (SOR) and technology acceptance model (TAM) frameworks, offering valuable insights for luxury brands on how AI can be leveraged to enhance customer relationships and loyalty.
Authors
- Hassan Kalantari Daronkola (ORCID: https://orcid.org/0000-0003-3972-0788)
- Seyed Sina Khamoushi Sahne
Institutions
- University of Science and Culture (IR)
- Swinburne University of Technology (AU)
Publication Details
- Journal
- Asia-Pacific Journal of Business Administration
- Published
- 2025-02-03
- DOI
- https://doi.org/10.1108/apjba-08-2024-0456
- Citations
- 7
- Primary Topic
- Consumer Retail Behavior Studies
- Type
- article
- Field-Weighted Citation Impact
- 14.51