{"title":"一个全新的世界,一个新的奇妙的观点:用生成式人工智能绘制消费者研究中未开发的领域","authors":"Kiwoong Yoo, Michael Haenlein, Kelly Hewett","doi":"10.1007/s11747-025-01097-2","DOIUrl":null,"url":null,"abstract":"<p>Integrating generative artificial intelligence (AI), particularly large multimodal models (LMMs) like ChatGPT, into the research process offers significant opportunities for marketing scholars. This manuscript provides a field guide into the potential advantages and possible limitations of using LMMs in different stages of consumer research, including idea generation, theory development, pretesting and pilot testing, data collection for experimental designs, data analysis, and reporting. We illustrate LMMs’ capabilities by replicating the consumer research stages of 35 articles from five marketing journals using ChatGPT-4o. Our findings suggest that LMMs enhance the efficiency and effectiveness of consumer research, though their performance varies across stages. LMMs excel in developing theoretical frameworks and collecting data for experimental designs, offer moderate support for idea generation, pre-/pilot testing, and reporting but perform less effectively in data analysis (e.g., silicon sampling). This manuscript underscores generative AI’s potential in consumer research and calls for further exploration into ethical guidelines and best practices to ensure high-quality work.</p>","PeriodicalId":17194,"journal":{"name":"Journal of the Academy of Marketing Science","volume":"139 1","pages":""},"PeriodicalIF":9.5000,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A whole new world, a new fantastic point of view: Charting unexplored territories in consumer research with generative artificial intelligence\",\"authors\":\"Kiwoong Yoo, Michael Haenlein, Kelly Hewett\",\"doi\":\"10.1007/s11747-025-01097-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Integrating generative artificial intelligence (AI), particularly large multimodal models (LMMs) like ChatGPT, into the research process offers significant opportunities for marketing scholars. This manuscript provides a field guide into the potential advantages and possible limitations of using LMMs in different stages of consumer research, including idea generation, theory development, pretesting and pilot testing, data collection for experimental designs, data analysis, and reporting. We illustrate LMMs’ capabilities by replicating the consumer research stages of 35 articles from five marketing journals using ChatGPT-4o. Our findings suggest that LMMs enhance the efficiency and effectiveness of consumer research, though their performance varies across stages. LMMs excel in developing theoretical frameworks and collecting data for experimental designs, offer moderate support for idea generation, pre-/pilot testing, and reporting but perform less effectively in data analysis (e.g., silicon sampling). This manuscript underscores generative AI’s potential in consumer research and calls for further exploration into ethical guidelines and best practices to ensure high-quality work.</p>\",\"PeriodicalId\":17194,\"journal\":{\"name\":\"Journal of the Academy of Marketing Science\",\"volume\":\"139 1\",\"pages\":\"\"},\"PeriodicalIF\":9.5000,\"publicationDate\":\"2025-04-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the Academy of Marketing Science\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1007/s11747-025-01097-2\",\"RegionNum\":1,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Academy of Marketing Science","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1007/s11747-025-01097-2","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS","Score":null,"Total":0}
A whole new world, a new fantastic point of view: Charting unexplored territories in consumer research with generative artificial intelligence
Integrating generative artificial intelligence (AI), particularly large multimodal models (LMMs) like ChatGPT, into the research process offers significant opportunities for marketing scholars. This manuscript provides a field guide into the potential advantages and possible limitations of using LMMs in different stages of consumer research, including idea generation, theory development, pretesting and pilot testing, data collection for experimental designs, data analysis, and reporting. We illustrate LMMs’ capabilities by replicating the consumer research stages of 35 articles from five marketing journals using ChatGPT-4o. Our findings suggest that LMMs enhance the efficiency and effectiveness of consumer research, though their performance varies across stages. LMMs excel in developing theoretical frameworks and collecting data for experimental designs, offer moderate support for idea generation, pre-/pilot testing, and reporting but perform less effectively in data analysis (e.g., silicon sampling). This manuscript underscores generative AI’s potential in consumer research and calls for further exploration into ethical guidelines and best practices to ensure high-quality work.
期刊介绍:
JAMS, also known as The Journal of the Academy of Marketing Science, plays a crucial role in bridging the gap between scholarly research and practical application in the realm of marketing. Its primary objective is to study and enhance marketing practices by publishing research-driven articles.
When manuscripts are submitted to JAMS for publication, they are evaluated based on their potential to contribute to the advancement of marketing science and practice.