This study explores the use of generative artificial intelligence (AI), specifically ChatGPT, in analyzing qualitative data on hotel guests’ delightful experiences. To assess the utility and trustworthiness of ChatGPT as a supplementary tool, we compared human coding, guided by Grounded Theory and Qualitative Content Analysis method, with AI-augmented coding using developed prompts in analyzing survey data. Our findings reveal that the majority of ChatGPT's themes and codes of customer delight closely match those identified by human coders, suggesting its potential to streamline data analysis. However, there are also notable differences, as human coders emphasized customer-to-customer interactions and safety and security, which were not identified by ChatGPT. The research contributes to hospitality literature by establishing a methodology for using ChatGPT in qualitative analysis, highlighting its efficiency in analyzing comments and open-ended survey data.

中文翻译：

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生成式人工智能 （AI） 的方法论探索，用于对酒店客人的愉快体验进行有效的定性分析


本研究探讨了生成式人工智能 （AI），特别是 ChatGPT 在分析酒店客人愉快体验的定性数据方面的使用。为了评估 ChatGPT 作为补充工具的实用性和可信度，我们将以扎根理论和定性内容分析方法为指导的人工编码与使用开发的提示的 AI 增强编码在分析调查数据时进行了比较。我们的研究结果表明，ChatGPT 的大多数客户满意主题和代码与人类编码人员识别的主题和代码非常匹配，这表明它有可能简化数据分析。然而，也存在显着差异，因为人类编码员强调客户对客户的互动以及安全和保障，而 ChatGPT 没有识别这些。该研究通过建立一种在定性分析中使用 ChatGPT 的方法为酒店文学做出了贡献，突出了它在分析评论和开放式调查数据方面的效率。