Research on the Efficiency of Financial Technology in the Pearl River Delta Region

Hongyi Chen

doi:10.54691/bcpbm.v15i.287

Authors

Hongyi Chen

DOI:

https://doi.org/10.54691/bcpbm.v15i.287

Keywords:

The Pearl River Delta Region (PRD); Fin-Tech; DEA-Malmquist Index Model.

Abstract

The deep integration of science and financial industry has become an important development strategy for building an innovation-driven country. As the forefront of China's reform and opening up, the Pearl River Delta region shoulders the important task of studying the development and influencing factors of Fin-Tech efficiency. Based on the panel data of nine major cities in the Pearl River Delta region from 2010 to 2018, this paper selects input and output indicators from aspects of manpower and capital, and uses DEA-Malmquist index model to measure the efficiency of Fin-Tech. The results demonstrate that during the period studied, the annual average Fin-Tech efficiency in the Pearl River Delta region presents an alternately fluctuating trend of "up-down". Among the inner cities, there are significant differences in the efficiency of Fin-Tech due to different regional development. Moreover, this paper explores the reasons from the aspects of macro economy, policy regulation and local development, and provides corresponding suggestions.

Downloads

Download data is not yet available.

References

Sfinga, I., & Niklis, D. (2011). EVALUATION OF BANK EFFICIENCY WITH THE DEA APPROACH: A COMPARISON OF EUROPEAN COMMERCIAL BANKS. Journal of Computational Optimization in Economics and Finance, 3(2), 115-131. Retrieved from https://search.proquest.com/scholarly-journals/ evaluation- bank-efficiency-with-dea-approach/docview/1728422463/se-2?accountid=162699.

Branda, M., & Kopa, M. (2012). DEA-risk efficiency and stochastic dominance efficiency of stock indices*. Finance a Uver, 62(2), 106-124. Retrieved from https://search.proquest.com/scholarly-journals/ dea-risk-efficiency-stochastic-dominance-stock/docview/1020691776/se-2?accountid=162699.

Seol, H., Lee, H., Kim, S., & Park, Y. (2008). The impact of information technology on organizational efficiency in public services: A DEA-based DT approach. The Journal of the Operational Research Society, 59(2), 231-238. Doi: http://dx.doi.org/10.1057/palgrave.jors.2602453.

Jiang Ruixue. (2020). Research on enterprise diversification, resource distribution and wealth distribution based on DEA (Ph.D. thesis, University of Science and Technology of China).

Ren Yuquan. Research on the financing efficiency of listed companies in the new energy automobile industry chain based on the DEA model [D]. Zhejiang University, 2020.

Liu Zhaohong. (2020). Research on the mitigation effect of the development of science and technology finance on the financing constraints of SMEs.

Wang Juan. (2020). Research on the impact of financial technology on the performance of commercial banks.

Xu Yuming, Xiong Qizhe and Jiang Yun (2020). Analysis of the measurement and related characteristics of the science and technology financial development index. Finance and Economics (12), 42-48. doi: 10.19622 / j.cnki.cn36-1005 / f.2020.12.005.

Wu Xuefen. Research on the efficiency of science and technology finance in the western region [D]. Shenzhen University, 2018.

Sun Zhongyan. (2020). An empirical study on the efficiency and influencing factors of domestic regional science and technology finance.

Zhou Yuan. Research on the efficiency of science and technology finance in the Guangdong-Hong Kong-Macao Greater Bay Area [D]. Shenzhen University, 2019.

Yan Bo, Du Jun & Pan Hong. (2019). The status quo, problems and countermeasures of scientific and technological collaborative innovation in the Pearl River Delta region. Science and Technology Management Research (01), 87-96. Doi.

Huang Ruifen & Qiu Mengyuan. (2016). Internal scientific financial efficiency evaluation based on Malmquist index and SFA model. Science and Technology Management Research (20), 43-48. doi: CNKI: SUN: KJGL.0.2016-20-009.

Deng Xue, Chen Chuangjie, Shen Lu & Liang Ying. (2020). Performance evaluation of technology finance based on Malmquist-DEA model-take Guangdong Province as an example. Science and Technology Management Research (21), 64-72. doi: CNKI: SUN: KJGL.0.2020-21-008.

Zhang Peng, Li Linxin and Zeng Yongquan. (2021). Research on the evaluation of scientific and technological innovation efficiency in the Guangdong-Hong Kong-Macao Greater Bay Area based on DEA-Malmquist index. Industrial Technology Economy (02), 12-17. doi: CNKI: SUN: GHZJ.0.2021-02-002.