Tripolar Sentiment Toward Generative AI in Hospitality Marketing: Legitimacy, Herd Dynamics, and Managerial Implications

İngilizce (OpenAlex)

This exploratory study employs sentiment analysis and topic modeling to investigate the perceptions of hospitality stakeholders regarding Generative Artificial Intelligence (GenAI) by analyzing 1,520 hospitality-oriented texts. By utilizing the theory of Herd Mentality and building upon the theory of organizational legitimacy, we identify three distinct sentiment types within a tripolar sentiment structure: positive (52.96%), negative (8.36%), and neutral (38.68%). Positive sentiment includes personalization, operational efficiency, and dynamic pricing. Neutral sentiment includes tactical hesitation and cognitive indecision. Negative sentiment includes ethical concerns, data privacy, and job loss. The results of topic modeling reveal five topics: 1) customer-centric innovation, 2) restaurant app, 3) global standardization, 4) tech transformation, and 5) machine learning operation. Overall, based on Natural Language Processing (NLP) and expert judgment, the results of this study contribute to the base of research on planned adoption dynamics and the role of the neutral segment in ethical and responsible GenAI use in hospitality.