制造企业数字化创新能力影响因素识别及评价

Identification of Influencing Factors and Evaluation of Digital Innovation Capability of Manufacturing Enterprises

摘要:

为突破数字技术应用难关，在实现对企业数字化创新能力评价分指标特性与目标层得分综合考察的同时增强评价结果的可量化性与精确度，基于投入与产出视角，从数字化创新专利产出、人才储备、资金获取、资源整合、经济基础5个维度构建企业数字化创新能力评价指标体系，提出采用随机森林算法和突变级数法进行评价，并以京津冀制造企业为例进行实证评价，同时分析识别影响其数字化创新能力的因素。结果发现：数字化创新人才储备对数字化创新产出能力的影响最大，资金获取次之，资源整合和经济基础的影响相对较小；现阶段京津冀制造企业数字化创新产出能力整体较弱，远低于数字化创新投入能力，且传统制造业与高技术行业相比仍存在较大差距；天津市和河北省的数字化创新能力普遍低于北京市。由此，建议京津冀地区从优化基础条件、提升人员素养、加强资源整合流动和构建创新生态系统等方面着手，进一步推动企业数字化创新发展。

关键词:数字化;数字化创新能力;随机森林算法;突变级数法;京津冀制造企业

Abstract:

In order to break through the barrier of digital technology application, and enhance the quantification and accuracy of evaluation results while comprehensively investigating the characteristics of sub-indexes and the score of the target layer in the evaluation of enterprise digital innovation capability, an evaluation index system for digital innovation capability of enterprise is constructed from five dimensions of digital innovation patent output, talent reserve, capital acquisition, resource integration and economic foundation based on the perspective of input and output. The random forest algorithm and catastrophe progression method were used for evaluation. Taking Beijing-Tianjin-Hebei manufacturing enterprises as samples, the empirical evaluation was carried out while the factors affecting their digital innovation capability were analyzed and identified. The research found that: the digital innovation talent reserve has the greatest impact on output capacity, followed by capital acquisition, and the impact of resource integration and economic foundation is relatively small; At this stage, the overall digital innovation output capability of Beijing-Tianjin-Hebei manufacturing enterprises is relatively weak, which is far lower than the digital innovation input capability, and there is still a big gap between the traditional manufacturing industry and the high-tech industry; The digital innovation capability of Tianjin and Hebei Province are generally lower than that of Beijing. Therefore, it is suggested that the Beijing-Tianjin-Hebei region should optimize basic conditions, improve personnel literacy, strengthen resource integration and flow, and build an innovation ecosystem to further promote the development of enterprise digital innovation.

Key words:digitalization; digital innovation capability; random forest algorithm; catastrophe progression method; Beijing-Tianjin-Hebei manufacturing enterprises;