Research on Digital Construction of Characteristic Towns in China under the Background of Digital Economy—Taking the Field Investigation in 6 Provinces and 6 Towns in China as an Example
- DOI
- 10.2991/978-94-6463-042-8_22How to use a DOI?
- Keywords
- Keywords-digital village; characteristic town; principal component analysis
- Abstract
The digital reform of characteristic towns can effectively promote the high-quality development of rural areas in China, bridge the digital divide between urban and rural areas, and stimulate new vitality in rural development. This paper uses the principal component analysis method to select 22 projects in 4 aspects of industry, culture, tourism and society, and conduct a comprehensive evaluation of 6 characteristic towns in the concentrated area of China's characteristic towns. According to the evaluation scores, the differences in the construction of characteristic towns in different regions in China are analyzed. Based on this, it is suggested that the government should optimize and improve the promotion of digital reform.
- 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 - Chaofan Huang AU - Lirong Rui AU - Yifan Zhu PY - 2022 DA - 2022/12/29 TI - Research on Digital Construction of Characteristic Towns in China under the Background of Digital Economy—Taking the Field Investigation in 6 Provinces and 6 Towns in China as an Example BT - Proceedings of the 2022 International Conference on mathematical statistics and economic analysis (MSEA 2022) PB - Atlantis Press SP - 139 EP - 150 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-042-8_22 DO - 10.2991/978-94-6463-042-8_22 ID - Huang2022 ER -