人工智能对中小企业转型发展的贡献统计测度

Statistical Measurement of the Contribution of Artificial Intelligence to the Transformation and Development of Small and Medium-Sized Enterprises

摘要: 人工智能在推动企业技术升级方面已广为人知，但在中小企业转型发展中的作用却鲜有文献涉猎。本文旨在探讨人工智能对中小企业转型发展的贡献作用，从宏观和微观两个角度采用灰色预测模型和柯布–道格拉斯生产函数等统计方法，对这一贡献进行量化分析。首先，利用灰色预测模型结合2018年一季度至2024年一季度的企业收入和支出数据预测了企业的收入和支出，以评估人工智能引入后对企业经济的具体影响。其次，基于柯布–道格拉斯生产函数和斯诺模型，计算了人工智能在中小企业中的要素贡献率，以评估其对转型发展的具体贡献。本文通过构建柯布–道格拉斯生产函数模型，测算了资本、劳动力和技术水平等要素对全国代表性中小企业的贡献率，同时，利用斯诺模型分析了人工智能对产出的影响，发现人工智能对中小企业转型发展的贡献率较高，为中小企业制定转型发展策略提供了重要的参考依据。最后，为了进一步提高模型的预测精度和稳定性，本文采用支持向量回归(SVR)对灰色预测模型和柯布–道格拉斯生产函数模型进行优化，通过SVR模型训练，更准确地预测人工智能引入后企业的收入和支出，并评估其对转型发展的贡献。此外，SVR模型通过引入核函数，能够很好地处理非线性问题，从而提高了模型在实际应用中的适应性。研究发现，人工智能对中小企业转型发展具有推动作用，但其贡献不仅取决于人才策略等因素。因此，本文提出了完善人工智能政策、人才培养机制等建议，以促进中小企业更好地利用人工智能进行转型升级。该研究为人工智能与企业管理领域提供了转型发展的思路和方法。

Abstract: Artificial intelligence is well known in promoting technological upgrading of enterprises, but its role in the transformation and development of small and medium-sized enterprises is rarely covered in the literature. This paper aims to explore the contribution of artificial intelligence to the transformation and development of small and medium-sized enterprises, and to quantify this contribution by using statistical methods such as grey prediction model and Cobb Douglas production function from both macro and micro perspectives. Firstly, the gray prediction model is used to predict the income and expenditure of enterprises combined with the income and expenditure data of enterprises from the first quarter of 2018 to the first quarter of 2024, in order to assess the specific impact of the introduction of artificial intelligence on the enterprise economy. Secondly, based on Cobb Douglas production function and snow model, the factor contribution rate of artificial intelligence in small and medium-sized enterprises is calculated to evaluate its specific contribution to transformation and development. By constructing Cobb Douglas production function model, this paper estimates the contribution rate of capital, labor force and technological level to national representative small and medium-sized enterprises. At the same time, it uses snow model to analyze the impact of artificial intelligence on output, and finds that artificial intelligence contributes more to the transformation and development of small and medium-sized enterprises, which provides an important reference basis for small and medium-sized enterprises to formulate transformation and development strategies. Finally, in order to further improve the prediction accuracy and stability of the model, support vector regression (SVR) is used to optimize the grey prediction model and Cobb Douglas production function model. Through SVR model training, the income and expenditure of enterprises after the introduction of artificial intelligence can be predicted more accurately, and its contribution to transformation and development can be evaluated. In addition, SVR model can deal with nonlinear problems well by introducing kernel function, thus improving the adaptability of the model in practical application. It is found that artificial intelligence can promote the transformation and development of small and medium-sized enterprises, but its contribution depends not only on factors such as talent strategy. Therefore, this paper puts forward some suggestions to improve artificial intelligence policy and talent training mechanism in order to promote small and medium-sized enterprises to make better use of artificial intelligence for transformation and upgrading. This research provides ideas and methods for the transformation and development of artificial intelligence and enterprise management.