数智赋能的发展道路能促进科技型中小企业的技术突破和跨界融合,进而影响其专精特新成长。本文揭示了在技术创新的中介作用下,数智赋能对科技型中小企业专精特新成长的作用机理,本文基于366份企业问卷数据,利用结构方程模型,实证检验了数智赋能对科技型中小企业专精特新成长的影响机制以及技术创新的中介效应。研究结果表明:1) 数智赋能作为当前企业转型升级的重要驱动力,对技术创新活动产生了显著的正向促进作用。2) 技术创新在科技型中小企业专精特新的成长过程中扮演了关键的中介角色。具体来说,技术创新作为数智赋能与企业成长之间的桥梁,有效传递了数智化转型带来的积极效应,促进了企业整体竞争力和成长潜力的提升。本研究拓展了数智赋能、技术创新与专精特新企业成长领域的研究视野,为科技型中小企业如何在复杂多变的市场环境中实现高质量发展提供了理论支持和实践经验。The development path empowered by digital intelligence can promote technological breakthroughs and cross-border integration of technology-based small and medium-sized enterprises, thereby affecting their specialized and innovative growth. This article reveals the mechanism of the role of digital intelligence empowerment in the specialized and innovative growth of technology-based small and medium-sized enterprises under the mediating effect of technological innovation. Based on 366 enterprise questionnaire data, this article empirically tests the impact mechanism of digital intelligence empowerment on the specialized and innovative growth of technology-based small and medium-sized enterprises and the mediating effect of technological innovation using structural equation modeling. The research results indicate that: 1) Digital intelligence empowerment, as an important driving force for current enterprise transformation and upgrading, has a significant positive promoting effect on technological innovation activities. 2) Technological innovation plays a crucial intermediary role in the growth process of technology-based small and medium-sized enterprises that specialize in innovation and specialization. Specifically, technological innovation serves as a bridge between digital empowerment and enterprise growth, effectively conveying the positive effects of digital transformation and promoting the overall competitiveness and growth potential of enterprises. This study expands the research perspective of digital intelligence empowerment, technological innovation, and the growth of specialized and innovative e
从"独立性差"角度出发,提出了ISE准则下的"独立性差"估计新方法(difference of independence estimation,DOIE).从数学模型上证明该算法与单类SVM等价且可用于解决分类问题.当数据集规模较大时,该算法的优势在于可...
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从"独立性差"角度出发,提出了ISE准则下的"独立性差"估计新方法(difference of independence estimation,DOIE).从数学模型上证明该算法与单类SVM等价且可用于解决分类问题.当数据集规模较大时,该算法的优势在于可用较少样本点表示两数据集中样本点间的关系,在保证精度的前提下,提高运算速度.该算法还可应用于两数据集独立性判断、检测流数据分布改变点的位置.若退化为单类数据集,可应用于概率密度估计.Benchmark和UCI数据集上的实验表明,该算法具有较好的性能.
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