Operation Strategy of “Cloud Tourism” Platform Based on Big Data Technology
- DOI
- 10.2991/978-94-6463-064-0_85How to use a DOI?
- Keywords
- big data; virtual tourism; operation strategy
- Abstract
The cloud tourism experience platform uses big data and virtual technology to construct a virtual tourism environment. It can change the marketing model of tourism companies and the consumption model of tourists. Based on big data analysis, this article explains the operation strategy of the cloud travel platform from three aspects: the acquisition and analysis of the multi-dimensional data information of the cloud travel platform, the construction of the platform experience quality feedback information data, and the design of the cloud travel platform service function. The platform can improve the effectiveness of the virtual system in terms of interactivity, control, vividness, information quality and display. The cloud tourism platform can create a theme image of tourist attractions, help users achieve the goal of traveling everywhere without leaving home and realize a dynamic two-way cycle between cloud tourism and on-site tourism, thereby further promoting the development of the tourism industry.
- Copyright
- © 2023 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 - Yujie Bai PY - 2022 DA - 2022/12/27 TI - Operation Strategy of “Cloud Tourism” Platform Based on Big Data Technology BT - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022) PB - Atlantis Press SP - 835 EP - 842 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-064-0_85 DO - 10.2991/978-94-6463-064-0_85 ID - Bai2022 ER -