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Technological innovation and environmental performance: evidence from China

Yuying Wu (South China University of Technology, Guangzhou, China)
Min Zhang (Queen's Management School, Queen's University Belfast, Belfast, UK)
Zhiqiang Wang (South China University of Technology, Guangzhou, China)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 19 April 2024

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Abstract

Purpose

This study empirically investigates the impacts of technological innovation and operational efficiency on environmental performance and the moderating effects of environmental orientation.

Design/methodology/approach

We develop a conceptual framework based on the Porter Hypothesis. We collect a sample of 850 listed firms in China between 2010 and 2019. The fixed effect model was used to analyse the data.

Findings

The empirical findings reveal that technological innovation indirectly enhances environmental performance through operational efficiency and partially mediates this impact. We also find that environmental orientation strengthens the positive impacts of technological innovation and operational efficiency on environmental performance.

Originality/value

This study contributes to the literature by revealing that technological innovation is positively associated with operational efficiency and environmental performance, which suggests that technological innovation can simultaneously enhance business and environmental performance. Hence, this study provides empirical support for the Porter Hypothesis. The results also extend the Porter Hypothesis by revealing how technological innovation affects environmental performance and under what conditions technological innovation has a greater impact on environmental performance.

Keywords

Acknowledgements

Zhiqiang Wang appreciates the support of grants under National Social Science Foundation of China [23BGL050].

Citation

Wu, Y., Zhang, M. and Wang, Z. (2024), "Technological innovation and environmental performance: evidence from China", Industrial Management & Data Systems, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IMDS-11-2023-0804

Publisher

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Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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