A Study on the Impact of Digital Finance on Innovation of Photovoltaic Enterprises-Based on Panel Data of Listed Photovoltaic Companies
- DOI
- 10.2991/978-94-6463-638-3_28How to use a DOI?
- Keywords
- digital finance; financing constraints; photovoltaic companies
- Abstract
This study explores the impact of digital finance on the innovation of listed PV companies based on panel data of listed PV companies from 2018-2022. The article summarizes the data through descriptive statistics, elaborates the relationship between variables using correlation analysis, and further explores the path of financing constraints through panel regression models. It is found that the development of digital finance has a significant positive impact on the innovation of PV listed companies, and the impact is heterogeneous, with larger companies being promoted more significantly by digital finance. Digital finance provides PV listed enterprises with more convenient financing channels, reduces financing costs, improves information transparency, improves risk control and other paths, so that they can obtain more innovation opportunities and resources, thus promoting their technological innovation and business model innovation.
- Copyright
- © 2024 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 - Ying Zhang AU - Hongshao Duan AU - Xinlong Wu PY - 2024 DA - 2024/12/30 TI - A Study on the Impact of Digital Finance on Innovation of Photovoltaic Enterprises-Based on Panel Data of Listed Photovoltaic Companies BT - Proceedings of the 5th International Conference on Economic Management and Big Data Application (ICEMBDA 2024) PB - Atlantis Press SP - 280 EP - 288 SN - 2352-5428 UR - https://doi.org/10.2991/978-94-6463-638-3_28 DO - 10.2991/978-94-6463-638-3_28 ID - Zhang2024 ER -