A Study on the Impact of High-Speed Rail Opening on the Development of Tourism in Chengdu Based on the Gray Prediction Model
- DOI
- 10.2991/978-94-6463-010-7_10How to use a DOI?
- Keywords
- Coupling Coordination Degree; Tourism Industry; Regional Economy; Chengdu City
- Abstract
High-speed rail is an important catalyst for urban development and has a huge impact on the realization of urban tourism benefits and economic development. Through the establishment of regression analysis equation and grey prediction model, combined with the comparison with and without, this paper empirically analyzes the impact and contribution of high-speed rail to the economic growth of tourism in Chengdu. The empirical results show that in the first few years of the opening of the high-speed rail, the contribution to the economic aggregate and the optimization of the industrial structure is rapid and has a significant impact. In particular, the contribution of high-speed rail to Chengdu’s tourism revenue is more significant, much higher than the contribution rate of other indicators.
- 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 - Guanghong Li AU - Yuan Hu PY - 2022 DA - 2022/12/02 TI - A Study on the Impact of High-Speed Rail Opening on the Development of Tourism in Chengdu Based on the Gray Prediction Model BT - Proceedings of the 2022 International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2022) PB - Atlantis Press SP - 71 EP - 77 SN - 2589-4919 UR - https://doi.org/10.2991/978-94-6463-010-7_10 DO - 10.2991/978-94-6463-010-7_10 ID - Li2022 ER -