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Does digital transformation matter to green innovation: based on TOE framework and configuration perspective

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Abstract

Green innovation is a guarantee for achieving high-quality economic development. However, the complex cause-and-effect relationship between digital transformation and green innovation has not been systematically studied. Digital transformation not only is about technology but also requires organizational and environmental support. Therefore, this study investigates the relationship between digital transformation and green innovation based on the TOE (technology-organization-environment) framework and configuration theory. A fuzzy set qualitative comparative analysis of data from 1948 listed companies reveals that, first, there is no necessary condition that leads to high green innovation, but digital achievements play a more general role in leading to high green innovation; second, three paths to achieve high green innovation are identified. These different configurations indicate multiple paths and complex cause-and-effect relationships to achieve high green innovation. Third, green innovation is a digital technology-based innovation, but in most cases, it also requires organization and environment support. This study can provide some theoretical and practical guidance for enterprises to enhance their green innovation capabilities through digital transformation and promote the achievement of high-quality company development.

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Funding

This research was funded by the National Natural Science Foundation Council of China under Project No. 71661029 and Scientific Research Funds in Yunnan Province Department of Education in 2022 under No. 2022Y481.

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  1. School of Logistics and Management Engineering, Yunnan University of Finance and Economics, Kunming, 650221, China

    Weili Yin

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  1. Weili Yin
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Weili Yin: writing—original draft, review, editing, and polishing.

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Yin, W. Does digital transformation matter to green innovation: based on TOE framework and configuration perspective. Environ Sci Pollut Res 30, 100046–100057 (2023). https://doi.org/10.1007/s11356-023-29438-0

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