An Analysis of The Problem of Tourist Destination Selection about Vacation and Non Vacation Through Analytic Hierarchy Process
- DOI
- 10.2991/978-94-6463-042-8_44How to use a DOI?
- Keywords
- Tourist destination; Analytic hierarchy process; Factor weight
- Abstract
On holidays, tourism will face some problems that are not usually available, such as rising costs, traffic congestion, crowded population and so on. Therefore, the choice of tourist destination will be different from that in ordinarytimes. The data used in this paper comes from CEPS and has high authority. This paper uses analytic hierarchy process to calculate the different changes of five different factors: diet, cost, accommodation, traffic and scenery during the holiday, which leads to the change of people's interest in the scenic spot. After the calculation is completed, the result needs to be checked, and the CR is obtained by calculating Ci and RI, so that the CR value is less than 0.1, so as to prove that the settlement result is effective. This paper calculates people's optimal choice of tourist destination in ordinary times through analytic hierarchy process, and then changes the weight of factors, so as to select the most promising tourist destination again.
- 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 - Xuyang Sun PY - 2022 DA - 2022/12/29 TI - An Analysis of The Problem of Tourist Destination Selection about Vacation and Non Vacation Through Analytic Hierarchy Process BT - Proceedings of the 2022 International Conference on mathematical statistics and economic analysis (MSEA 2022) PB - Atlantis Press SP - 301 EP - 307 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-042-8_44 DO - 10.2991/978-94-6463-042-8_44 ID - Sun2022 ER -