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Driven by the development of the global digital economy, knowledge management in industrial enterprises offers more possibilities for green innovation. Based on the perspective of external knowledge sources, this study aims to construct a panel regression model to explore the relationship between digital economy and industrial green innovation efficiency.

Panel data from 30 regions in China from 2011 to 2020 were selected as research samples. All data are obtained from national and provincial statistical yearbooks. Coupling coordination degree analysis, entropy method, panel regression analysis, robustness test and threshold effect test by Stata 16.0 were used to test the hypotheses.

The empirical results demonstrate the hypotheses and reveal the following findings: the digital economy is positively related to industrial green innovation efficiency and external knowledge sources, and external knowledge sources mediate the relationship between them. Moreover, based on the threshold test results, the digital economy has a double-threshold effect on industrial green innovation efficiency.

Based on the perspective of external knowledge sources, the proposed mediating mechanism between the digital economy and industrial green innovation efficiency has not been established previously, further enriching the research on the antecedents and outcomes of external knowledge sources. Moreover, this study estimated the direct influence mechanism and double-threshold effect of the digital economy on industrial green innovation efficiency from theoretical and empirical analysis, thus responding to the call of scholars and adding to existing research on how the digital economy affects the green transformation of industrial enterprises.

Employees’ knowledge management, which influences creativity, is a pivotal resource in organizational innovation activities, as it helps activate the knowledge resource pool and improves knowledge flow. Using social information processing theory, this study aims to construct a cross-level model to examine how knowledge hiding plays a role in the relationship between leader–member exchange differentiation (LMXD) and employee creativity.

This study surveyed 754 leader–employee matching samples from 127 teams in China innovation enterprises at two time points. Confirmatory factor analysis, convergent analysis, hierarchical regression analysis and bootstrapping method by SPSS and AMOS were used to test the hypotheses.

The empirical results demonstrate the cross-level model’s efficiency and reveal the following findings: Team-level LMXD is negatively related to employee creativity, whereas it is positively related to knowledge hiding; knowledge hiding is negatively associated with employee creativity; thus, knowledge hiding plays a mediating role in the relationships between them.

Based on the knowledge-hiding perspective, this study analyzed an underlying mechanism between LMXD and employee creativity, thereby further enriching the literature on the influence of knowledge management. This proposed connection has not been established previously. Moreover, the findings respond to the reasons for the inconsistent conclusions of previous literature on the cross-level relationship between LMXD and employee creativity based on the social information processing theory. It thus clarifies the cross-level influence path, as well as provides a theoretical basis for further research on the relationship between the two.