Under the background of double carbon target and digital intelligence era, the innovation resources and innovation environment that manufacturing enterprises rely on have shown exponential growth. Digital green innovation (DGI) has gradually become the mainstream paradigm of innovation. How to achieve a balance between a local DGI network (LDGIN) and a remote DGI network (RDGIN) and how to use the role of digital empowerment and green organization flexibility to improve the performance of DGI are very important issues facing manufacturing enterprises at present. However, this problem has not been fully addressed in the existing research. In this study, the influence mechanism of LDGIN and RDGIN on the DGI performance of manufacturing enterprises was revealed, considering the moderating role of digital empowerment and green organization flexibility. The linear regression method was used to analyze the 562 valid data obtained by questionnaire survey. The results of this study are as follows. The effect of the DGI network on manufacturing enterprises’ DGI performance is heterogeneous because of LDGIN and RDGIN. The establishment of embedded links in a DGI network inevitably requires manufacturing enterprises to pay the corresponding costs. The over-embedding of manufacturing enterprises into RDGIN will have a negative impact on DGI performance. The balance between LDGIN and RDGIN has an important impact on manufacturing enterprises’ operation. The comprehensive balance and relative balance indexes constructed in this paper show that an appropriate balance can promote the improvement of the DGI performance of manufacturing enterprises. Digital transformation and organizational structure innovation are changing the business model of manufacturing enterprises and can regulate the relationship between the LDGIN and RDGIN and the DGI performance of manufacturing enterprises. The balance of DGI network embedding in practice shows the important role and enlightening significance of local and remote search in developing countries.
<abstract> <p>Green intelligent building materials is an effective way for building materials industry to reduce carbon. However, a small amount of research and development (R&D, unstable R&D investment and imperfect collaborative innovation mode hinder the development of green intelligent building materials industry. However, few scholars study the development mechanism of green intelligent building materials industry from the perspective of industrial chain considering the above obstacles. In this study, the game models under market mechanism and government regulation were constructed to analyze the income distribution mechanism for the development mechanism of green intelligent building materials industry. Finally, the questionnaire method was used to discuss the game strategy of collaborative innovation behavior among agents. The results are as follows. In the game strategy selection of collaborative innovation behavior among green intelligent building materials, factors such as database marketing maturity, information flow and technology volume generated by collaborative innovation, technical benefit coefficient, social benefit coefficient and profit and loss barrier factors are conducive to the collaborative innovation behavior of green intelligent building materials. When the market mechanism fails, the incentive effect of cost subsidy adopted by the government is more efficient and fast, and the driving force of achievement reward is more lasting. The combination of the two incentives is the best. Moderate supervision and punishment lower than the free rider income can not ensure fair competition among green intelligent building materials enterprises. The punishment above the threshold can effectively restrain the negative impact of free rider income and prospect profit and loss. This study not only theoretically expands the development theory of digital industry from the perspective of industrial chain by considering the maturity factor of database, but also provides policy guidance for the development of green intelligent building materials industry in practice.</p> </abstract>
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