人工智能行业研发投入、创新策略与企业绩效 ——基于112家上市企业的实证研究

R&D, innovation strategy and company performance in AI industry: Evidence from 112 China’s A-list companies

摘要:

基于双元理论，以2015—2019年人工智能A股上市公司作为研究样本，收集整理企业R&D、专利申请、ROA等数据，研究研发投入、创新策略与企业绩效三者的相关关系。实证结果表明，探索式创新负向调节企业绩效（不显著）；利用式创新正向调节企业绩效（不显著）；加入调节变量研发投入（R&D）后，探索式创新显著正向影响企业绩效，利用式创新则显著负向调节企业绩效；稳健性样本检验的结论与此一致。研究结论可为人工智能企业提供创新思路，为创新管理提供决策参考。

Abstract:

Based on innovation ambidexterity, 112 A-list companies of AI industry in 2015—2019 are selected as research objects; their R&D, patent application, ROA and other data are collected to explore the interrelationships among R&D, innovation strategy and company performance. The empirical results show that there exists negative correlation between exploration innovation strategy (EXP) and company performance (ROA) in an insignificant way, but positive correlation between exploitation (USE) and ROA insignificantly. With the addition of moderating variable R&D, EXP significantly and positively affects ROA, while USE has an inverse effect. Stability test result proves the same result. The research conclusion can provide innovation strategy for AI entrepreneurs and supply reference for innovation management and policy making.