Service Innovation in Resort Management: The Case of a Tourism Firm in Indonesia - Ghina, Astri; Hatammimi, Jurry (Unit Research and Knowledge, School of Business and Management, Institut Teknologi Bandung, 2025)
Abstract. Purpose: This study adopted a design thinking approach to create an artificial intelligence (AI)-integrated chatbot that enhances service responsiveness while simultaneously leading to operational efficiency and enabling personalization. Methodology: Through qualitative research techniques comprising a literature review and interviews with nine people, this study identifies critical service-specific pain points. It delves into the transformative role of AI within the realm of resort management performance. Here, the Gioia Methodology was used to analyse the qualitative data, thereby enabling systematic coding and concept development, as well as the development of robust theoretical propositions for future research. Findings: The results provide relevant information on AI-driven knowledge co-creation, operational transformation through AI chatbots, and customer-centric innovation. This analysis yielded three theoretical implications: (1) AI chatbots enable knowledge co-creation that benefits interdepartmental communication and real-time information sharing; (2) AI chatbots transform service operations by addressing knowledge gaps and allowing automation in coordination; and (3) AI-driven personalization fosters customer experiences, which subsequently fosters service innovation in the context of resort management. Implications for Theory and Practice: The study theoretically extends service-dominant logic (SDL) and the technology acceptance model (TAM) by showcasing how AI facilitates co-creation and personalized service. Practically, it offers resort managers actionable insights on leveraging AI to improve operational workflows, service quality, and customer satisfaction. Originality/Value: This study offers a novel contribution by applying the Gioia Methodology within a resort management context. It produces grounded theoretical propositions that can guide future research on AI-driven service innovation. The originality of this work lies not only in the context of SME-based resorts but also in the methodological rigor and development of transferable insights for theory and practice. Keywords: Service innovation, resort management, customer experience, customer-centric innovation, AI chatbot, and design thinking.