Research on Data Asset Value Assessment of Technology Manufacturing Enterprises under Digital Transformation—Taking Group M as an Example

随着数字经济快速发展，数字化转型成为企业建立竞争优势的重要途径。制造业企业在数字化与智能化发展过程中，在研、产、销特别是驱动销售模式向电商化、全渠道化转型等环节产生了许多数据资产。本文提出“改进超额收益法–层次分析法”双模型框架，针对科技制造企业数据资产协同性、知识隐蔽性、周期长期性三大特征，构建行业专属估值体系。基于剥离人力资本贡献、层次分析法量化数据资产权重，构建理论框架对科技制造企业数字化转型中产生的数据资产进行评估。选取M集团数据资产作为评估对象，分析验证了方法的合理性及可行性，为科技制造业数据资产评估体系提供了一定参考。In the context of the rapid development of the digital economy, digital transformation has emerged as a pivotal strategy for enterprises seeking to establish competitive advantages. In the context of digitalisation and intelligent development, manufacturing enterprises generate a substantial volume of data assets in the domains of research, production and sales, as well as in the transformation of the sales model towards e-commerce and multi-channelization. The proposed dual model framework of the “Improved Excess Return Method-Hierarchical Analysis Method” is presented as a means to construct an industry-specific valuation system for the three major characteristics of data asset synergy, hidden knowledge, and the long-term cycle of technology manufacturing enterprises. Based on the stripping of human capital contribution and the quantification of data asset weights by the hierarchical analysis method, a theoretical framework for the evaluation of data assets generated in the digital transformation of technology manufacturing enterprises is constructed. The data assets of Group M are selected as the assessment object, and the analysis verifies the reasonableness and feasibility of the method, which provides a certain reference for the data asset assessment system of the science and technology manufacturing industry.