The Power of AI-Generated Content: Evidence From the Peer-to-Peer Accommodation Market

As a technological breakthrough, large language models stand to revolutionize operations in many industries, including the tourism sector. Despite the transformative potential of artificial intelligence (AI)-generated content (AIGC), its role in marketing performance remains unclear. This research used a prediction–interpretation–inference machine learning framework to evaluate how AIGC affects Airbnb listings’ performance. Specifically, we scrutinized AIGC’s efficacy under two conditions (i.e., with an AIGC tool serving as a language assistant vs. a content creator) and examined the impacts of prompt design strategies. Three key findings emerged. First, the prompt design strategy greatly influenced AIGC’s effectiveness. Second, AIGC did not uniformly enhance listing performance: although it boosted revenue and bookings for underperforming listings, its impact on low-performing listings was limited and not as strong as anticipated. AIGC may even negatively influence high-performing listings. Third, the AIGC tool appeared more effective as a language assistant (vs. a content creator) for underperforming listings.

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Publication Details

Journal
Journal of Travel Research
Published
2025-04-24
DOI
https://doi.org/10.1177/00472875251332951
Citations
10
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
22.84

Funders

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article

The Power of AI-Generated Content: Evidence From the Peer-to-Peer Accommodation Market

Ningyuan Fan, Zhi‐Ping Fan, Xiang Li, Chao Liu
10 citations
Journal of Travel Research
FinTech, Crowdfunding, Digital Finance
22.84
article

The Power of AI-Generated Content: Evidence From the Peer-to-Peer Accommodation Market

Ningyuan Fan, Zhi‐Ping Fan, Xiang Li, Chao Liu
article en
10 citations

Abstract

As a technological breakthrough, large language models stand to revolutionize operations in many industries, including the tourism sector. Despite the transformative potential of artificial intelligence (AI)-generated content (AIGC), its role in marketing performance remains unclear. This research used a prediction–interpretation–inference machine learning framework to evaluate how AIGC affects Airbnb listings’ performance. Specifically, we scrutinized AIGC’s efficacy under two conditions (i.e., with an AIGC tool serving as a language assistant vs. a content creator) and examined the impacts of prompt design strategies. Three key findings emerged. First, the prompt design strategy greatly influenced AIGC’s effectiveness. Second, AIGC did not uniformly enhance listing performance: although it boosted revenue and bookings for underperforming listings, its impact on low-performing listings was limited and not as strong as anticipated. AIGC may even negatively influence high-performing listings. Third, the AIGC tool appeared more effective as a language assistant (vs. a content creator) for underperforming listings.

Journal of Travel ResearchVol. 65(5)
City University of Hong Kong (HK), Nankai University (CN), Temple University (US), Northeastern University (CN)
National Natural Science Foundation of China, China Scholarship Council, Higher Education Discipline Innovation Project
Openalex Percentile: Top 1%
FinTech, Crowdfunding, Digital Finance
22.84
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