{"title":"生成式人工智能(AI)用于酒店客人愉悦体验高效定性分析的方法论探索","authors":"Hala Sun , MiRan Kim , Soyeon Kim , Laee Choi","doi":"10.1016/j.ijhm.2024.103974","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48444,"journal":{"name":"International Journal of Hospitality Management","volume":"124 ","pages":"Article 103974"},"PeriodicalIF":9.9000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A methodological exploration of generative artificial intelligence (AI) for efficient qualitative analysis on hotel guests’ delightful experiences\",\"authors\":\"Hala Sun , MiRan Kim , Soyeon Kim , Laee Choi\",\"doi\":\"10.1016/j.ijhm.2024.103974\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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.</div></div>\",\"PeriodicalId\":48444,\"journal\":{\"name\":\"International Journal of Hospitality Management\",\"volume\":\"124 \",\"pages\":\"Article 103974\"},\"PeriodicalIF\":9.9000,\"publicationDate\":\"2024-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Hospitality Management\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S027843192400286X\",\"RegionNum\":1,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HOSPITALITY, LEISURE, SPORT & TOURISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Hospitality Management","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S027843192400286X","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HOSPITALITY, LEISURE, SPORT & TOURISM","Score":null,"Total":0}
A methodological exploration of generative artificial intelligence (AI) for efficient qualitative analysis on hotel guests’ delightful experiences
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.
期刊介绍:
The International Journal of Hospitality Management serves as a platform for discussing significant trends and advancements in various disciplines related to the hospitality industry. The publication covers a wide range of topics, including human resources management, consumer behavior and marketing, business forecasting and applied economics, operational management, strategic management, financial management, planning and design, information technology and e-commerce, training and development, technological developments, and national and international legislation.
In addition to covering these topics, the journal features research papers, state-of-the-art reviews, and analyses of business practices within the hospitality industry. It aims to provide readers with valuable insights and knowledge in order to advance research and improve practices in the field.
The journal is also indexed and abstracted in various databases, including the Journal of Travel Research, PIRA, Academic Journal Guide, Documentation Touristique, Leisure, Recreation and Tourism Abstracts, Lodging and Restaurant Index, Scopus, CIRET, and the Social Sciences Citation Index. This ensures that the journal's content is widely accessible and discoverable by researchers and practitioners in the hospitality field.