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J. Hefei Univ. Tech. (Nat. Sci.)

合肥工业大学学报(自然科学版)

JOURNAL OF HEFEI UNIVERSITY OF TECHNOLOGY (NATURAL SCIENCE)

Competent Authorities: Ministry of Education of the People's Republic of China

Sponsor by: Hefei University of Technology

ISSN 1000-1646, CN 34-1001/N

Empirical research on evaluation method for R&D in technology enterprises based on multi-model integration

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基于多模型联用的科技企业 R&D 评测方法与实证研究

Journal Information

J. Hefei Univ. Tech. (Nat. Sci.), Dec.2025, Vol.48 No.12: 1689-1696

DOI: 10.3969/j.issn.1003-5060.2025.12.016

Authors

NAN Guojun

(School of Resources and Environmental Engineering, Hefei University of Technology, Hefei 230009, China)

Abstract and Keywords

Abstract: This paper uses stepwise least squares regression, quantile regression, and grey prediction models to form a multi-model integrated method for evaluating the influencing mechanisms and future trends of enterprise research and development (R&D) investment. The results show that the multimodel integrated evaluation method can accurately and intuitively assess the current status of R&D investment in technology enterprises. Regional production levels, government fiscal allocations for science and technology, and enterprise contributions are the three core drivers of R&D funding growth. Government fiscal support demonstrates cross-level sustained effectiveness, with regression coefficients remaining stable in the range of 0.953-1.085, highlighting the stable leveraging role of policy-driven innovation investment. Some enterprises may experience a growth rate adjustment of 3.2%-5.7% over the next five years, signaling structural risks from overreliance on single entities. Based on these findings, the paper proposes the construction of a gradient policy system, enhancing the inclusivity and stability of fiscal support, and fostering collaborative innovation among small, medium, and large enterprises. This study provides theoretical and methodological support for regional innovation policymaking and enterprise R&D investment optimization.

Keywords: enterprise research and development(R&D) investment; least squares regression; quantile

作者信息

南国君

(合肥工业大学资源与环境工程学院, 安徽合肥 230009)

摘要和关键词

摘要: 文章运用逐步最小二乘回归、分位数回归、灰色预测模型构成多模型联用方法,系统评测企业研究与开发(research and development, R&D)经费投入的影响机制及未来趋势。研究结果表明:基于多模型联用的评测方法,可精准直观地评测科技企业R&D经费投入的现状;地区生产水平、政府财政科技拨款、企业投入是驱动R&D经费增长的核心因素;政府财政支持具有跨层级的持续有效性,其回归系数稳定在0.953~1.085之间,凸显政策端对创新投入的稳定撬动作用;部分企业未来5年增速可能回调3.2%~5.7%,提示过度依赖单一主体的结构性风险。该文提出构建梯度化政策体系,强化财政支持的普惠性、稳定性,推动大中小企业协同创新等建议,为区域创新政策制定和企业研发投入优化提供理论方法支撑。

关键词: 企业研究与开发（R&D）经费投入；最小二乘回归；分位数回归；灰色预测模型；多模型联用方法中图分类号：F273.1 文献标志码：A 文章编号：1003-5060（2025）12-1689-08

Funding

国家自然科学基金资助项目（62073113）；安徽省科技创新战略与软科学研究重点资助项目（202206f01050028）和2025年高校中青年教师培养行动资助项目（JNFX2025090）

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