Advances in Economics, Management and Political Sciences
- The Open Access Proceedings Series for Conferences
Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
Series Vol. 51 , 01 December 2023
Open
Access | Article
The Impact of Scientific Research Level on Financing for High-tech Enterprises in China: Machine Learning Analysis Based on the STAR Market
* Author to whom correspondence should be addressed.
Abstract
Amid the prevailing trend of technological supremacy, the scientific research level plays a pivotal role in elevating economic growth and national comprehensive strength. As crucial forces propelling industrial advancement and economic expansion, high-tech companies share an intricate relationship between scientific research level and enterprise strengths. This study delves into the influence of research level on the financing capacity of enterprises in the STAR market. It employs Ordinary Least Squares (OLS) regression and Gradient Boosting Regression Trees (GBRT) techniques to analyze data between 2019 and 2022. The findings underscore that patent research capabilities and research investment intensity are key factors impacting financing capacity. Specifically, patent quantity exhibits a negative correlation with Asset-liability ratio (ALR), while research investment intensity shows a positive correlation. On the other hand, patent quantity correlates positively with commercial credit financing (CCF) capacity, whereas the proportion of research personnel correlates negatively. The GBRT analysis further validates the significant impact which patent quantity and research investment have on financing capacity. This suggests that high-tech companies should focus on enhancing research efficiency and the proportion of research personnel, while also carefully considering the degree of emphasis on innovation. These measures can balance CCF and debt ratio considerations. The study provides essential decision-making insights for managers and investors of technology-driven firms, emphasizing the significance of technological innovation in business development. Also, it offers guidance for optimizing corporate development and personnel structures in the technology and innovation sectors.
Keywords
finance, GBRT, star market
References
1. Song, H., Xuanming, N., Junchao, Z. and Huimin, Z. (2020) Can Government-sponsored Venture Capital Promote the Technological Innovation: An Empirical Study of Chinese High-tech Start-up Enterprises. Management Review, 32, 110-121.
2. Liping, S., Xiangrong, J. and Chong, Y. (2015) Research on the Index System for Evaluating Corporate Innovation Capability. Science Research Management, S1, 122-126.
3. Yao, L. and Hanqing, S. (2022) Determinants of Financing for High-tech Enterprises in China:Machine Learning Analysis Based on the STAR Market. Journal of Financial Research, 507, 132-151.
4. Aziz, S., Dowling, M. and Hammami H. (2022) Machine learning in finance: A topic modeling approach. European Financial Management, 28, 744-770.
5. Fang, W., Xuanyi, W. and Shuo, C. (2020) Machine Learning in Economic Research: A Review and Prospect. The Journal of Quantitative & Technical Economics | J Quant Tech Econ, 4, 146-164.
6. Linjie, S., Linshao, S. and Zhigang, L. (2007) Research on the Evaluation of Financing Capability for Technology-based Small and Medium-sized Enterprises. Science of Science and Management of S.&.T., 5, 146-150.
7. Zhanyun, C., Wenjie, Y. and Yunyun, S. (2014) A Study on Factors Influencing the Financing Capability of Small and Medium-sized Enterprises: Based on Data from SME Board Listed Companies. Communication of Finance and Accounting, 5, 76-78.
8. Zeye, H. (2023) Analysis of Factors Influencing the Financing Capability of Technology-based Small and Medium-sized Enterprises. Business & Economy, 03, 82-84.
9. Zeye, H. (2023) Analysis of Factors Influencing the Financing Capability of Technology-based Small and Medium-sized Enterprises. Business & Economy, 03, 82-84.
10. Yao, L., Yeqing, Z., Bo, L. and Haoyu, Z. (2020) Managerial individual characteristics and corporate performance: Evidence from a machine learning approach. Journal of Management Sciences in China, 23, 120-140.
11. Qianwei, Y. (2013) Financial Development, Commercial Credit Financing, and Firm Growth: Empirical Evidence from Chinese A-Share Listed Companies. Research on Economics and Management, 9, 86-94.
12. Linmu, L. and Chong, W. (2017) Tax and Fee Burden, Innovation Capability, and Firm Upgrading: Empirical Evidence from Listed Companies on the ‘New Third Board’. Economic Research Journal, 52, 119-134.
13. Xiaodong, L., Jie, J. and Shiwu, Z. (2011) Regular Employee Compensation, Company Size, and Growth: Empirical Evidence from Panel Data of Chinese Listed Companies. Journal of Tsinghua University(Science and Technology), 12, 1908-1916.
14. Lushi, Y. and Xin X. (2012) Research on Executive Compensation Incentive Policies in Innovative Enterprises. Science & Technology Progress and Policy, 29, 119-122.
Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Authors who publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open Access Instruction).
- Volume Title
- Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
- ISBN (Print)
- 978-1-83558-149-0
- ISBN (Online)
- 978-1-83558-150-6
- Published Date
- 01 December 2023
- Series
- Advances in Economics, Management and Political Sciences
- ISSN (Print)
- 2754-1169
- ISSN (Online)
- 2754-1177
- DOI
- 10.54254/2754-1169/51/20230632
- Copyright
- 01 December 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited