eprintid: 49943 rev_number: 6 eprint_status: archive userid: 23303 importid: 106 dir: disk0/00/04/99/43 datestamp: 2024-12-13 10:39:35 lastmod: 2024-12-13 10:39:35 status_changed: 2024-12-13 10:39:35 type: article metadata_visibility: show creators_name: Wen, Yingting creators_name: Laporte, Sandra creators_idrefppn: 265304105 creators_idrefppn: 156964309 creators_affiliation: EM Lyon creators_affiliation: Toulouse School of Management creators_halaffid: 520525 title: Experiential Narratives in Marketing: A Comparison of Generative AI and Human Content ispublished: pub subjects: subjects_GESTION abstract: As generative AI technologies advance, understanding their capability to emulate human-like experiences in marketing communication becomes crucial. This research examines whether generative AI can create experiential narratives that resonate with humans in terms of embodied cognition, affect, and lexical diversity. An automatic text analysis reveals that while reviews generated by ChatGPT 3.5 exhibit lower levels of embodied cognition and lexical diversity compared with reviews by human experts, they display more positive affect (Study 1A). However, human raters struggle to notice these differences, rating half of the selected reviews from AI higher in embodied cognition and usefulness (Study 1B). Instances of hallucination in AI-generated content were detected by human raters. For social media posts, the more sophisticated ChatGPT 4 model demonstrates superior perceived lexical diversity and leads to higher purchase intentions in unbranded content compared with human copywriters (Study 2). This paper evaluates the performance of large language models in generating experiential marketing narratives. The comparative studies reveal the models’ strengths in presenting positive emotions and influencing purchase intent while identifying limitations in embodied cognition and lexical diversity compared to human-authored content. The findings have implications for marketers and policymakers in understanding generative AI’s potential and risks in marketing. date: 2024-10-28 date_type: published publisher: American Marketing Association — AMA id_number: 10.1177/07439156241297973 faculty: gestion divisions: CRM keywords: large language models, product description, embodied cognition, affect keywords: lexical diversity, consumer perception language: en has_fulltext: FALSE doi: 10.1177/07439156241297973 view_date_year: 2024 full_text_status: none publication: Journal of Public Policy and Marketing place_of_pub: Chicago refereed: TRUE issn: 0743-9156 oai_identifier: oai:tsm.fr:2894 harvester_local_overwrite: abstract harvester_local_overwrite: pending harvester_local_overwrite: note harvester_local_overwrite: date harvester_local_overwrite: issn harvester_local_overwrite: creators_idrefppn harvester_local_overwrite: creators_halaffid harvester_local_overwrite: publisher harvester_local_overwrite: place_of_pub oai_lastmod: 2024-12-11T10:26:11Z oai_set: tsm site: ut1 citation: Wen, Yingting and Laporte, Sandra (2024) Experiential Narratives in Marketing: A Comparison of Generative AI and Human Content. Journal of Public Policy and Marketing.