Research on AI-Enabling Strategies for OTA Platforms
This study examines the effectiveness of the application of artificial intelligence (AI) technologies in online travel agent (OTA) platforms and the limitations they face, focusing on analyzing their impact on platform operational efficiency and user experience. Through the SWOT analysis framework and user satisfaction assessment methodology, the study provides an in-depth analysis of the application of key technologies such as AI recommendation systems, intelligent customer service, dynamic pricing, and backend automated operation, as well as user experience. The analysis finds that AI technology performs significantly in enhancing personalized services, optimizing resource allocation and improving market responsiveness, but it also exposes problems such as data privacy, algorithmic bias and lack of user trust. The study discusses the strengths, weaknesses, opportunities and threats of AI technology from the perspective of actual cases and theories, and puts forward improvement suggestions for OTA platforms, including optimizing the transparency and diversity of recommender systems, enhancing the fairness and user-friendliness of dynamic pricing, improving the ability of intelligent customer service to handle complex issues, and promoting the application of the technology on small and medium-sized platforms through industry collaboration and policy support. In addition, the study highlights the potential of AI in sustainable tourism, suggesting that technological innovation and strategy optimization can be used to promote the long-term development of the tourism industry and user satisfaction. This study provides important theoretical references and practical guidance for the in-depth application of AI technology in OTA platforms.
Authors
- Yihan Guo
Institutions
- Beijing Jiaotong University (CN)
Publication Details
- Journal
- Highlights in Business Economics and Management
- Published
- 2025-04-29
- DOI
- https://doi.org/10.54097/945gaq27
- Primary Topic
- IoT and Edge/Fog Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00