OLS Model Based Research on Influential Factors of Financial Performance for Chinese Technology Companies
- DOI
- 10.2991/assehr.k.211209.402How to use a DOI?
- Keywords
- OLS Model; Influential Factors; Financial Performance; Chinese Technology Company
- Abstract
Based on 459 Chinese listed technology companies from the RESSET Finance Database, this paper explores the influential factors of the financial performance of Chinese technology companies. With the application of statistics software, the data are processed through Person correlation and OLS regression analysis. The research results demonstrate that financial leverage, operating leverage, and firm size are correlated with both long-term and short-term financial performance. Growth opportunity is only associated with short-term financial performance (ROA), and government ownership has a significant correlation with long-term financial performance (R&D). Contrary to the results of previous studies, a company’s liquidity is not correlated with financial performance. The study findings highlight the importance of company-specific characteristics to Chinese technology companies and conclude the following implications. First, companies should be vigilant on the use of debt to form a healthier financing structure. Second, for large companies, the importance of R&D investment should be stressed to maintain its competitiveness. Last, policymakers should better refine the subsidy policies to incentivize R&D investment in the private sector.
- Copyright
- © 2021 The Authors. Published by Atlantis Press International B.V.
- Open Access
- This is an open access article under the CC BY-NC license.
Cite this article
TY - CONF AU - Fangfei Jiang AU - Zhao Xi PY - 2021 DA - 2021/12/15 TI - OLS Model Based Research on Influential Factors of Financial Performance for Chinese Technology Companies BT - Proceedings of the 2021 3rd International Conference on Economic Management and Cultural Industry (ICEMCI 2021) PB - Atlantis Press SP - 2470 EP - 2479 SN - 2352-5428 UR - https://doi.org/10.2991/assehr.k.211209.402 DO - 10.2991/assehr.k.211209.402 ID - Jiang2021 ER -