大数据企业技术创新效率影响机制研究

Research on the impact mechanism of technological innovation efficiency of big data enterprises

企业创新的过程是多输入、多产出的复杂过程,为准确掌握企业在创新过程中的具体情况,基于创新价值链视角构建我国大数据企业技术创新效率评级体系。以大数据板块境内79家上市公司为研究对象,将企业创新过程划分为技术开发、物料转化、效益产出三个阶段,通过数据包络分析模型测算各阶段创新效率,运用Tobit模型分析影响因素。研究结果表明:我国大数据企业创新效率存在阶段性差异,与效益产出阶段相比,技术开发、物料转化阶段的效率较低;大数据行业的技术研发没有以市场为导向,技术开发制约着整体效率的提升;企业需要根据自身特点合理配置资源,避免投入冗余,以提高创新效率。

The enterprise innovation process is a complex process with multiple inputs and multiple outputs.In order to accurately grasp the specific situation of the enterprise in the innovation process,this paper constructs the technology innovation efficiency rating system of big data enterprises in China based on the perspective of innovation value chain.Taking the 79 listed companies in the big data sector as the research object,the enterprise innovation process is divided into three stages:technology development,material transformation and benefit output.The innovation efficiency of each stage is measured through a data envelopment analysis model,and the influencing factors are analyzed by Tobit model.The research results show that there are stage differences in the innovation efficiency of big data companies in China.compared with the benefit output stage,the efficiency of technology development and material conversion stage is lower;the technology research and development of the big data industry is not market-oriented,and technology development restricts the overall improvement of efficiency;and in the influencing factors of innovation efficiency,enterprises need to reasonably allocate resources according to their own characteristics to avoid input redundancy,so as to improve innovation efficiency.