Rethinking HR through AI: a sectoral analysis of customer complaints and training programs in tourism
SERVICE INDUSTRIES JOURNAL, 2026 (SSCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Basım Tarihi: 2026
- Doi Numarası: 10.1080/02642069.2026.2737149
- Dergi Adı: SERVICE INDUSTRIES JOURNAL
- Derginin Tarandığı İndeksler: Social Sciences Citation Index (SSCI), Scopus, IBZ Online, Periodicals Index Online, ABI/INFORM, Geobase, Hospitality & Tourism Complete, Hospitality & Tourism Index, Business Source Ultimate (EBSCO), Sociology Source Ultimate (EBSCO)
- Çanakkale Onsekiz Mart Üniversitesi Adresli: Evet
Özet
Ensuring high-quality service in hospitality depends on effective human resource management (HRM), where employee performance and relational interactions shape the guest experience. While generative artificial intelligence (AI) offers transformative potential for HR practices, the comparative value of AI versus human expertise in training design remains unexplored. This study investigates how training recommendations generated by HR managers compare with those produced by ChatGPT, examining their similarities and differences and their implications for service quality in hospitality. Customer complaints from TripAdvisor were analyzed using MAXQDA within the HOLSERV framework, categorizing failures into employee, reliability, and tangible dimensions. HR experts provided training recommendations based on these insights, and ChatGPT generated parallel recommendations. Both sets of recommendations were systematically compared to identify converging and diverging patterns. Human generated recommendations emphasize relational, context sensitive, and experience-based aspects of service delivery, whereas AI-generated recommendations focus on structured and operationally oriented solutions. Drawing on Human Capital Theory and Contact Theory, this study suggests that human expertise is crucial for addressing interactional failures, whereas AI enhances efficiency and pattern recognition. This study advocates a hybrid HRM approach in which AI complements rather than replaces human judgment.