制造企业数字创新能力识别及选择方法研究
Identification and Selection Method for Digital Innovation Capability of Manufacturing Enterprises
摘要: “数字创新能力”是近年来创新创业领域涌现出的新构念,是为了实现创新目标而对组织数字资源有效利用和部署的能力。本文以制造企业“智改数转”为研究对象,运用扎根理论方法,识别出制造企业数字创新能力要素,然后以竞优评析理论为基础,构建体现能力优势多样性特征的选择方法,最后以徐工集团选择创新试点为例,验证方法的科学性。研究表明,制造企业数字创新能力主要包括数字认知能力、智能分析能力和数据整合能力;选择方法以权重系数刻画能力优势特征,在认同个体差异基础上计算比较结果,最大限度集合整体优势,排序的结果有利于决策者多角度权衡。据此,研究结论不仅揭示数字创新能力的构成要素,构建选择方法,而且对制造企业在数智转型过程中管理数字能力、提升转型整合绩效具有启示意义。
Abstract: “Digital innovation capability” is a new concept emerging in the field of innovation and entrepreneurship in recent years, which refers to the ability to effectively use and deploy organizational digital resources in order to achieve innovation goals. This paper takes “intelligent transformation and number transformation” of manufacturing enterprises as the research object, use the grounded theoretical method to identify the elements of digital innovation ability of manufacturing enterprises, and then builds a selection method reflecting the diversity characteristics of capability advantages based on the competitive excellence evaluation theory. Finally, the selection innovation pilot of Xugong Group is taken as an example to verify the scientificity of the method. The research shows that the digital innovation ability of manufacturing enterprises mainly includes digital cognition ability, intelligent analysis ability and data integration ability. The selection method uses weight coefficient to describe the ability advantage characteristics, calculates the comparison results on the basis of the identification of individual differences, and sets the overall advantage to the maximum extent. Therefore, the research conclusions not only reveal the components of digital innovation capability and the construction and selection methods, but also have implications for manufacturing enterprises to manage digital capability and improve transformation integration performance in the process of digital intelligence transformation.
文章引用:杨涛. 制造企业数字创新能力识别及选择方法研究[J]. 电子商务评论, 2025, 14(9): 286-296. https://doi.org/10.12677/ecl.2025.1492913

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