Research on Effect Reasoning on Enterprise Digital Transformation Performance with Big Data Analysis

Abstract

Due to the various differences between modern enterprises and traditional enterprises, many scholars have noticed that the research results of traditional mature enterprises can not be fully applied to the relevant research of modern digital enterprises. Therefore, many new theories have emerged in the field of digital transformation research in recent decades. In the course of many years of development, there have been more studies on its definition, conception dimension and measurement. Although some scholars have realized that effect reasoning will play a role in the performance of enterprise digital transformation, there are relatively few empirical studies on the impact of effect reasoning on the performance of enterprise digital transformation. Digital transformation refers to the realization of significant technological change by enterprises through digital technology, and its essence is a process of continuous exploration. This study is carried out to reveal the impact of the effect reasoning on enterprises’ digital transformation with big data analysis from a process perspective. The results show that the effect reasoning and failure learning improves enterprise digital transformation performance. Empirical learning theory is used for the research context. It is helpful to enrich and develop the theoretical research on management innovation, and understand and guide Chinese enterprises to realize digital transformation with big data analysis.