Research on Tourism Applications Based on RMP Theory——Fun Mini Programs
- DOI
- 10.2991/978-94-6239-598-5_13How to use a DOI?
- Keywords
- Travel mini-program; RMP theory; Personalized tourism; Technological innovation
- Abstract
Based on the RMP theory perspective, this paper conducts an in-depth study of the “Fun Travel” mini-program. This mini-program integrates abundant tourism resources to meet users’ needs for personalized, convenient, and high-quality travel experiences, featuring functions such as itinerary planning, weather and clothing recommendations, scenic spot outfit color suggestions, and attraction information display and recommendations. Through collaborations with regional suppliers, it provides users with accurate and timely travel information, enhances travel efficiency, and promotes tourism innovation. The paper also analyzes the technical challenges faced by the mini-program and the evolving demands of users, proposing corresponding solutions. Finally, it summarizes the research findings and outlines future development directions, including technological innovation, functional expansion, deepened collaborations, in-depth exploration of personalized services, multi-channel partnership expansion, upgraded application of intelligent technologies, and integration of sustainable tourism concepts.
- Copyright
- © 2026 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Haiyong Shen AU - Jiayue Geng PY - 2026 DA - 2026/02/26 TI - Research on Tourism Applications Based on RMP Theory——Fun Mini Programs BT - Proceedings of the 2025 6th International Conference on Big Data and Social Sciences (ICBDSS 2025) PB - Atlantis Press SP - 114 EP - 125 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6239-598-5_13 DO - 10.2991/978-94-6239-598-5_13 ID - Shen2026 ER -