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In recent years, both industry professionals and scholars have shown increased interest in the ability of big data management capabilities (BDMCs) to drive green innovation, emphasizing their potential in fostering environmentally sustainable practices. While many studies highlight the positive influence of big data technology on green innovation, there is a notable gap in understanding the managerial process required for such innovation. Moreover, the roles of green dynamic capabilities and environmental turbulence in this context are underexplored. This study aims to contribute to the existing literature by examining the mechanisms and boundary conditions of the relationship between BDMCs and green innovation. We gathered data from 266 Chinese manufacturing enterprises using questionnaires and analyzed the results using Partial Least Squares Structural Equation Modeling (PLS-SEM). Our findings indicate that, despite the inherent qualities of BDMCs such as rarity, applicability, nonreplicability, and non-substitutability, their influence on green innovation is reduced in the absence of effective green dynamic capabilities. Furthermore, our study suggests that environmental turbulence does not weaken the influence of BDMCs on green dynamic capabilities; rather, it amplifies the effects of BDMCs on green dynamic capabilities and their impact on two types of green innovation. This study provides new insights for manufacturing enterprises aiming to achieve green transformation. We also discuss the theoretical and practical implications of the research, along with its limitations.
Mao et al. (Mon,) studied this question.