数据赋能驱动文化产业创新效率的非线性研究——基于STR模型的实证检验

Nonlinear on Innovation Efficiency of Cultural Industry for Data Empowerment--Analysis Based on STR Model

本文通过梳理大数据与文化产业创新指标,构建2012年1月—2017年12月月度时间序列的STR模型,验证数据赋能与中国文化产业创新效率的非线性关系。研究结果显示,数据赋能增速提高对文化产业创新效率的影响大于数据赋能增速下降对文化产业创新效率的冲击,其影响具有结构变迁非线性;检验数据赋能对文化产业创新效率产生的“阈值”效应,在数据赋能增速趋近零时文化产业创新效率转变较快,其影响具有速度增长非线性。将非线性理论内嵌于文化产业创新,分析大数据影响中国文化产业创新效率的作用机理,为研究数据赋能文化经济理论与STR模型的产业应用提供双重借鉴。

By sorting out the big data and innovation indicators of the cultural industry,this paper constructs a STR model of monthly time series(from January 2012 to December 2017),to verify the nonlinear correlation of data empowerment and innovation efficiency in China s cultural industry.It is found that increase of data empowerment has greater impact on the innovation efficiency of cultural industry than decrease of data empowerment,showing a nonlinear structural change.It also verifies that the changing of data empowerment has threshold effect on innovation efficiency of the cultural industry.Specifically,when the growth rate of data empowerment approaches zero,the innovation efficiency of the cultural industry changes rapidly,showing a nonlinear growth rate.By embedding the non-linear theory into the cultural innovation industry,this paper analyses the mechanism of big data affecting the innovation efficiency of Chinese cultural industry deeply,in order to provide reference for the research of the cultural economy theory of data empowerment and STR model industry application.