制造业企业数据价值释放:效应与机制

Unraveling the value release path of data element in manufacturing enterprises:Effects and mechanisms

数字技术应用不断深化推动多源异构数据的收集、流通、交互与价值实现,使得经济运行机制发生变革.本文从技术创新视角衡量企业的数据驱动能力,将数据驱动能力和数据要素引入生产函数,剖析数据要素赋能制造业企业降本增效的内在机制,研究表明:1)数据的产生、分享和应用可显著提升制造业企业的生产效率;2)进一步对比不同技术密集度企业数据价值释放的进程与差异发现,数字技术应用和数据要素的投入有效降低了低、中技术制造业企业的制造成本以及高技术企业的销售费用;3)当高技术企业具备更强大的数据驱动能力时,其生产成本反而增加了,表明我国高技术制造业企业尚未实现数据驱动下的产业转型升级.此外,本文基于产业关联理论和产业集聚理论,将空间因素纳入分析框架,研究发现:产业链视角下,制造业生产全流程、全产业链、全生命周期数据的融通与开发利用,通过提高区域产业链的协同效能,从而进一步提升企业的生产效率.本研究拓展了数字经济理论与机制分析的研究内容,为充分释放数据要素价值,优化资源要素配置效率提供证据支持.

The ongoing progress in digital technology has simplified the collection,dissemina-tion,interaction,and realization of multi-sourced and heterogeneous data,resulting in changes in the economic operation mechanisms.This paper measures the“data-driven ability”of enterprises from a technological innovation perspective and integrates data elements and an enterprise’s“data-driven ability”into the production function.This provides fresh theoretical insights into the intrinsic mechanism by which data elements enable manufacturing companies to reduce costs and improve efficiency.We then get the following results:1)The generation,sharing,and appli-cation of data can significantly enhance the production efficiency of manufacturing companies;2)Further comparison of the processes and differences in the release of data value in companies of different technology intensities reveals that the current application of digital technology and the input of data elements can effectively reduce the manufacturing cost of low tech(LT)and medium tech(MT)manufacturing companies and the sales cost of high-tech(HT)companies;3)Interestingly,when HT companies exhibit stronger data-driven abilities,their production costs tend to rise,indicating that China’s HT manufacturing companies are yet to achieve a success-ful transition in production models.Furthermore,based on the industrial correlation theory and industrial agglomeration theory,this paper incorporates spatial factors into the analytical framework.The findings indicate that,from the industrial chain perspective,the integration and development utilization of data across the entire manufacturing process,industry chain,and product lifecycle can improve the collaborative efficiency of the regional industrial chain.This in turn can further enhance the production efficiency of companies.This research enriches the theory and mechanism analysis of digital economy and provides evidence support for further promoting the value release of data elements and optimizing the efficiency of resource allocation.