| Title | Unlocking paths for transforming green technological innovation in manufacturing industries |
|---|---|
| ID_Doc | 30883 |
| Authors | Gao, J; Feng, QH; Guan, T; Zhang, WF |
| Title | Unlocking paths for transforming green technological innovation in manufacturing industries |
| Year | 2023 |
| Published | Journal Of Innovation & Knowledge, 8, 3 |
| Abstract | The double externalities of green technological innovation and disadvantages of the traditional extensive development of manufacturing industries hinder the transformation of green technological innovation in manufacturing industries. Traditional research based on behavioral logic rarely focused on the subjective will of innovation subjects or the impact of environmental regulation. To unlock the development dilemma of manufacturing industries from the coupling perspective of dual logic of behavior and concept, the concept of function is introduced into this analysis along with the influence of behavioral logic. This helped to construct the model of system dynamics wherein green technology innovation in manufacturing is analyzed under the influence of environmental regulation. The subsystems of willingness, behavior, and benefits of green technological innovation were divided by a systematic analysis of the double impact factors inside and outside manufacturing. Based on the index data from 2011 to 2019, Vensim software was used for simulation. Unlocking paths for transforming green technological innovation in the manufacturing industry were designed. The conclusions show that environmental regulation positively improves the economic, social, and environmental performance of manufacturing industries. Additionally, manufacturing can unlock the dilemma by reducing the intensity of command-and-control, improving the intensity of market-based incentives, and actively stimulating public participation in environmental regulation. & COPY; 2023 The Authors. Published by Elsevier Espana, S.L.U. on behalf of Journal of Innovation & Knowledge. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
| https://doi.org/10.1016/j.jik.2023.100394 |
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