Designing a generative artificial intelligence-based hotel review management assistant: a design science approach

초록

The increasing reliance on online platforms has substantially reshaped consumer-business interactions, particularly in the travel and tourism sector. Online consumer reviews now serve as key decision-making tools for travelers and vital channels for firms to manage digital customer relationships. However, responding to large volumes of reviews, especially negative ones, poses significant operational and emotional challenges, particularly for resource-constrained tourism businesses. To address these issues, this study develops HormAS, a human-supervised GAI-based review response support artifact, using a design science research methodology. The artifact analyzes customer sentiment, emotion, and intention to generate contextually appropriate and empathetic responses. By shifting the focus from review analysis to response generation, this study contributes both theoretically and practically to the fields of digital marketing, tourism management, and information systems. Under controlled evaluation conditions, the proposed artifact provides preliminary evidence of improved response efficiency and reduced self-reported stress, thereby offering a foundation for future research on scalable, human-supervised systems for managing online review responses in tourism.

키워드