Assessment of Provincial Financial Agglomeration Level Based on Internet Big Data
- DOI
- 10.2991/wrarm-19.2019.10How to use a DOI?
- Keywords
- Level of financial agglomeration; Baidu index； Hesitant fuzzy linguistic term set; TOPSIS grey relation projection method
- Abstract
Scientific evaluation of China's financial agglomeration level is of great significance to promote the stable development of China's financial industry and give full play to the role of financial agglomeration in economic promotion. Aiming at the insufficient evaluation index system of financial agglomeration level and the lack of hesitation and fuzziness in evaluation methods, this paper introduces Baidu Search Index to construct an evaluation index system of financial agglomeration level from four aspects: financial industry, banking industry, securities industry and insurance industry. Based on the original data of 31 provinces (cities and districts) in China from 2013 to 2017, this paper evaluates the financial agglomeration level of 31 provinces (cities and districts) in China by using TOPSIS grey relational projection method with hesitation fuzzy language. The empirical results show that, in terms of time, except Tibet, the financial agglomeration level of the remaining 30 provinces (cities and districts) in China shows a trend of fluctuating growth, among which Guangdong, Beijing and Zhejiang rank the top three. Spatially, Beijing and Guangdong rank first and second in the financial agglomeration level, and the financial agglomeration level in the eastern coastal areas is significantly higher than that in the western areas.
- Copyright
- © 2019, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Xiaonan Huang AU - Mu Zhang PY - 2019/09 DA - 2019/09 TI - Assessment of Provincial Financial Agglomeration Level Based on Internet Big Data BT - Proceedings of the Sixth Symposium of Risk Analysis and Risk Management in Western China (WRARM 2019) PB - Atlantis Press SP - 51 EP - 56 SN - 1951-6851 UR - https://doi.org/10.2991/wrarm-19.2019.10 DO - 10.2991/wrarm-19.2019.10 ID - Huang2019/09 ER -