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An adoption-implementation framework of digital green knowledge to improve the performance of digital green innovation practices for industry 5.0
Journal of Cleaner Production ; : 132608, 2022.
Article in English | ScienceDirect | ID: covidwho-1882160
ABSTRACT
Despite the current slowdown in global economic growth due to the impact of COVID-19, the digital economy is still performing well. Under the background of double carbon, green innovation and intelligent production of manufacturing enterprises have become the general trend of sustainable development. It is particularly important to study the integration of digital technology into green innovation and production processes to improve the performance of digital green innovation and the competitiveness of enterprises. However, the integration of digital technology and green innovation from the perspective of knowledge management has not been fully introduced into current literatures. In this study, hierarchical regression and fsQCA approaches were used to empirically verify the adoption process of digital green innovation activities and the impact of digital green knowledge creation on digital green innovation performance (DGIP), and explores the moderating effects of digital green risk perception (DGRP) and digital green complexity perception (DGCC) through 429 questionnaires from Chinese manufacturing enterprises. In addition, knowledge search is divided into three dimensions scientific digital green knowledge search (SDGKS), market digital green knowledge search (MDGKS) and supply chain digital green knowledge search (SCDGKS). The results show that i) SDGKS promotes exploitative digital green knowledge creation (EDGKC). MDGKS has a positive impact on both utilizing digital green knowledge creation (ADGKC) and EDGKC. SCDGKS promotes EDGKC. ii) The relationship between SDGKS and EDGKC is only moderated by DGCC (positive). The relationship between MDGKS and EDGKC is only moderated by DGCC (negative). The relationship between SCDGKS and EDGKC is moderated by DGRP (negative) and DGCC (negative). iii) There is an inverted U-shaped relationship between ADGKC and DGIP. There is a U-shaped relationship between EDGKC and DGIP. The essence of this study is to help manufacturing enterprises find external partners to improve their digital green innovation performance through external knowledge search partner selection. The conclusion of this study has certain theoretical contribution to the clarification of the complex process of digital green innovation. This study provides a theoretical basis for enterprises to select knowledge search partners according to their own environment to carry out digital green innovation activities smoothly. This study has practical value for enterprises to improve competitiveness, better survival and development process under the current environment.
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Full text: Available Collection: Databases of international organizations Database: ScienceDirect Language: English Journal: Journal of Cleaner Production Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: ScienceDirect Language: English Journal: Journal of Cleaner Production Year: 2022 Document Type: Article