[2603.20062] The End of Rented Discovery: How AI Search Redistributes Power Between Hotels and Intermediaries

Computer Science > Information Retrieval arXiv:2603.20062 (cs) [Submitted on 20 Mar 2026] Title:The End of Rented Discovery: How AI Search Redistributes Power Between Hotels and Intermediaries Authors:Peiying Zhu, Sidi Chang View a PDF of the paper titled The End of Rented Discovery: How AI Search Redistributes Power Between Hotels and Intermediaries, by Peiying Zhu and 1 other authors View PDF HTML (experimental) Abstract:When a traveler asks an AI search engine to recommend a hotel, which sources get cited -- and does query framing matter? We audit 1,357 grounding citations from Google Gemini across 156 hotel queries in Tokyo and document a systematic pattern we call the Intent-Source Divide. Experiential queries draw 55.9\% of their citations from non-OTA sources, compared to 30.8\% for transactional queries -- a 25.1 percentage-point gap ($p < 5 \times 10^{-20}$). The effect is amplified in Japanese, where experiential queries draw 62.1\% non-OTA citations compared to 50.0\% in English -- consistent with a more diverse Japanese non-OTA content ecosystem. For an industry in which hotels have long paid OTAs for demand acquisition, this pattern matters because it suggests that AI search may make hotel discovery less exclusively controlled by commission-based intermediaries. Comments: Subjects: Information Retrieval (cs.IR); Artificial Intelligence (cs.AI) ACM classes: H.3.3; I.2.7; K.4.4; J.4 Cite as: arXiv:2603.20062 [cs.IR]   (or arXiv:2603.20062v1 [cs.IR] for this vers...