Generative AI vs. humans in online hotel review management: A Task-Technology Fit perspective

Abstract

Despite Generative AI's ability to produce human-like content, its effectiveness as references for human responses, particularly in online review management, remains unclear. To address this question, this study explores if human responses resembling AI patterns are associated with enhanced customer perceptions. To provide deeper insights, we examined how this relationship shifts under varying technological and task conditions, guided by the Task-Technology Fit theory. In the empirical analysis, we automated responses to 32,129 online reviews using GPT, calculated the similarity between existing managerial responses and AI-generated content, and tested the relationship between human-AI similarity and the perceived helpfulness of review-response pairs. The findings reveal benefits of resembling AI with high model temperatures, particularly for positive reviews, while identifying negative outcomes under lower temperatures. This study enriches our understanding of an emerging technology that could have a huge impact on the industry and provides insights for practitioners to refine AI adoption strategies.