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Purpose The purpose of this paper is to examine the influence of the innovation ability of universities (IAU) on the efficiency of University–Industry knowledge flow and investigate whether the level of provincial innovative agglomeration (PIA) moderates the relationship between IAU and the efficiency of the University–Industry knowledge flow. Design/methodology/approach This study uses the super-efficiency data envelopment analysis model to measure knowledge research efficiency (KRE) and knowledge transformation efficiency (KTE) and then studies the influencing mechanism of the two kinds of efficiency using the spatial Tobit model with panel data from 2008 to 2017. Findings The results show that the overall KRE in Chinese universities is higher than the KTE. IAU has a significantly positive impact on KRE and KTE. PIA has a significantly inverted U-shaped influence on KRE and KTE and positively moderates the promoting effect of IAU on KRE and KTE. Research limitations/implications Due to the limitations of the data, this paper only selects several secondary indicators to measure KRE and KTE with reference to previous studies. Practical implications This study enriches the future research of University–Industry cooperation and knowledge flow and it is conducive to promoting the efficiency of University–Industry knowledge research and transformation from the perspective of universities, enterprises and local governments. Originality/value This study proposes the concept of University–Industry knowledge flow and divides the knowledge flow into the knowledge research stage and the knowledge transformation stage based on the knowledge supply chain theory. Moreover, the paper expands the theoretical framework of the impact of IAU on the efficiency of University–Industry knowledge flow and provides findings on the moderating effect of PIA.

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The importance of enterprise digitization is growing. This study examines the influence of digitization on enterprise growth performance (GP), taking into account the mediating effects of strategic change (STR) and the moderating effects of dynamic capability (DY). Through an empirical examination of panel data for listed A‐share manufacturing enterprises in China from 2016 to 2020, we document a positive relationship between digitization and GP. Our results also indicate that STR plays a mediating role between digitization and GP while DY positively moderates the promoting effect of digitization on GP. This research helps to improve our understanding of the effect mechanism and boundary conditions of digitization in relation to GP. Further, our conclusions can offer guidance to help managers make informed decisions about enterprise digitization.