大数据能力对农业科技企业创新的影响：一个有调节的中介效应模型

目前学者们较为关注大数据能力对于企业创新的影响研究，但大多笼统探究大数据能力对企业创新的直接影响，深入探究其中介机制和调节机制的研究尚未完善，立足于农业科技企业的研究更是缺乏。本文基于动态能力理论，深入探究大数据能力对农业科技企业创新的影响机制，以双元组织学习为中介变量，以市场导向为调节变量，建立可调节的中介模型。基于181家农业科技企业样本，结果表明：大数据能力对企业创新具有显著正向影响；探索式学习和利用式学习在大数据能力和企业创新间均具有正向中介作用；市场导向增强了利用式学习在大数据能力与企业创新之间的中介作用；而对探索式学习在大数据能力与企业创新之间的中介作用未发挥显著的调节作用。

The Impact of Big Data Capability on Agri-Tech Firm Innovation: A Moderated Mediation Model

Whether big data capabilities have positive impacts on firm innovation have attracted much scholarly attention in recent years. However, most of the scholars just generally explore the direct relationship between big data capabilities and firm innovation, the in-depth research on the potential mediator and moderator in this important link are still sparse, especially on the agri-tech firm context. Invoking the dynamic capability theory, we develop a moderated mediation model in which organizational learning mediates the interactive effects of big data capabilities and market orientation on firm innovation. Our hypotheses were tested using a sample of 181 Chinese agri-tech firms. The results reveal that big data capabilities have significant positive efforts on firm innovation. Both exploratory learning and exploitative learning fully mediate the link between big data capability and firm innovation. The mediation effect of exploitative learning is positively contingent upon market orientation, however, market orientation does not positively moderate the mediation effect of exploratory learning.