Digitalisation dynamics in SMEs: An approach from systems dynamics and artificial intelligence
本研究利用欧盟统计局Flash Eurobarometer No. 486数据集（16,365家中小企业），结合回归分析与机器学习，从非线性复杂视角揭示中小企业数字化转型中内部能力与外部支持的交互作用及其最优组合。
This paper addresses the study of digitalisation dynamics in SMEs. Improving on existing research and its methodological limitations, we provide an understanding of the digital transformation in SMEs by approaching the research from a non-linear and complex perspective. We empirically test our hypotheses using the Eurostat Flash Eurobarometer No. 486 data set, with a final sample of 16,365 SMEs. Our first contribution shows that an adequate understanding of digital transformation not only implies the identification of drivers of digitalisation but also a grasp of how these drivers act, highlighting the differential effect that internal capabilities and external support of the company in interaction have on digital transformation. Moreover, the results show that the effect of interactions between variables is transferred to the output variable in a non-linear process, which may contain an optimum produced by a differential combination of input variables. Second, the paper extends the research methodology, emphasising the importance of combining classic regression analysis with machine-learning techniques. Thus, using a systemic approach, we conclude that the combination of the explanatory power of regression models and machine learning allows us to quantify and explain how variables act, solving complex and non-linear problems.