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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.

Digital technology is gradually penetrating into all kinds of business of green innovation and green development. However, China’s industrial Internet technology foundation is weak. Scholars’ researches on the impact of digital green strategic orientation (DGSO) on digital green innovation performance (DGIP) and the intermediary role of digital green business model innovation (DGBMI) is relatively backward. Therefore, it is particularly important to divide the dimensions of DGSO from the perspective of DGBMI to describe the mechanism of DGIP. In this study, multiple regression approach was used to test the effect of DGSO on DGIP. The mediating role of DGBMI was explored through 562 questionnaires. In addition, the study divides the DGSO into three dimensions: green market orientation (GMO), digital green technology orientation (DGTO), and government orientation. DGBMI is divided into two dimensions: efficiency type and integration type. The results are as follows. (1) GMO, DGTO and government orientation all have positive effects on the improvement of DGIP. (2) GMO has a greater impact on integration DGBMI (IDGBMI). The influence of DGTO on efficient DGBMI (EDGBMI) is more significant. (3) Government orientation has a positive impact on EDGBMI. The influence of DGSO on DGIP can be realized through the intermediary role of EDGBMI and IDGBMI. The essence of this research is to help enterprises understand the characteristics of internal and external environment and make digital-green strategy-oriented choices to improve their DGIP. This study has a certain theoretical contribution to elucidating the influence of DGSO on DGIP and the mediating role of DGBMI. This study also provides a practical basis for enterprises’ digital green innovation practice based on their own environmental optimization and matching of DGSO to improve competitiveness.

Low carbon and digitalization are the general trends of manufacturing upgrading and transformation. Digital technology enables the whole process of green manufacturing and breaks down the spatial barrier. To achieve the dual carbon goals, the pressure-state-response (PSR) model, in which digital technology enables the green innovation of the manufacturing industry, was theoretically analyzed in this study. The measurement system of the digital green innovation (DGI) in the manufacturing industry was constructed according to the PSR framework. An evaluation model based on the analytic hierarchy process and the deviation maximization technique for order preference by similarity to an ideal solution method was constructed to measure the level of DGI. The results of this study from Chinese manufacturing are as follows. (i) The measurement system of the level of DGI in manufacturing industry includes a pressure system, state system and response system. (ii) In the past five years, the comprehensive index of the DGI in manufacturing industry has generally shown a trend of fluctuating rise. There are overall low and unbalanced phenomena in all regions. The gap decreased from 0.1320 to 0.1187, showing a gradually narrowing trend. (iii) Compared with other regions, the composite index of DGI is generally higher in the regions with a better ecological environment in the east and a more developed economy in the north. State parameters are higher than pressure and response parameters in most areas. (iv) Compared with other regions, the composite index of DGI in western and southern regions is lower, and the parameters of pressure, status and response are basically coordinated. (v) The application degree of digital technology, the emission intensity of waste water/exhaust gas of output value of one hundred million yuan and the expenditure intensity of digital technology adopted by enterprises are the key influencing factors of DGI in the manufacturing industry. This study not only proposed an evaluation index system of the digital green innovation level, but also puts forward policy guidance and practical guidance of digital technology to accelerate the green and intelligent manufacturing industry.

Although building enterprises are actively developing towards the direction of an integrated building supply chain (IBSC), they still face many difficulties in digital green innovation (DGI) activities. The purpose of this study is to reveal the interaction mechanism between the digital integration degree, green knowledge collaboration ability, and the DGI performance of IBSC enterprises in DGI activities under the influence of environmental characteristics of the integrated supply chain. In this study, firstly, a hierarchical regression method and a structural equation model are used to empirically study the static mechanism of DGI among enterprises in the IBSC. Secondly, this study adopts a complex system theory to construct a logistic dynamic analysis model to explore a dynamic evolution mechanism. The results of the study are as follows. (i) The digital integration degree and green knowledge synergy ability of the IBSC are conducive to improvements in digital green innovation performance among the enterprises involved in this chain. The digital integration degree of this chain is the dominant factor affecting the performance of digital green innovation among these enterprises. (ii) The digital network capability of this chain has a significant impact on its digital integration degree but has no significant effect on green knowledge synergy ability. The quality of digital relationships in the IBSC affects both the digital integration degree and green knowledge synergy ability. It has a higher impact on the digital integration degree than on the synergy ability of green knowledge. The resilience of the IBSC can effectively promote the improvement of digital integration and green knowledge synergy ability, but has no significant effect on digital green innovation performance. (iii) In the early stage of an IBSC, the effect of the digital integration degree on DGI performance is more obvious. Over the long term, under the effect of different digital relationship qualities of the IBSC, green knowledge collaboration ability plays a pivotal role. Improving this ability is conducive to the continuous improvement of DGI performance.

Digital green innovation management activities are the core of low-carbon intelligent development of prefabricated construction enterprises (PCEs) for sustainable urban development. PCEs have to seek joint venture partners to avoid the financial risk of digital green innovation projects. The purpose of this study is to develop a conceptual partner selection framework for the digital green innovation management of prefabricated construction towards urban building 5.0. In this study, first, symbiosis theory and six analysis methods were integrated to innovatively build a 3W1H-P framework system for the joint venture capital partner selection of digital green innovation projects. Second, the dual combination weighting method was innovatively proposed to avoid subjective and objective deviation in attribute weight and time weight. Finally, empirical research was carried out to verify the scientific nature, reliability, and practicability of the framework system and selection model. The results of this study show that the framework system and selection model proposed can be used to assist PCEs to select joint investment partners of digital green and innovative projects for sustainable urban development.

In the context of carbon peak and carbon neutrality, digital green innovation development is becoming more and more important for enterprises. In order to effectively improve green competitiveness and increase profits, photovoltaic building materials enterprises must choose digital green innovation projects for investment. The purpose of this study is to build a reasonable investment project selection framework system and propose appropriate methods for photovoltaic building materials enterprises to help them correctly choose digital green innovation investment projects. This study firstly combines relevant theories and digital green innovation characteristics of target investment projects to build a framework system for photovoltaic building materials enterprises to select investment projects. Secondly, this study innovatively proposes a dynamic intuitionistic fuzzy multi-attribute group decision-making method considering the interaction between attributes. Finally, this study takes Yingli Group as the research object and conducts an empirical study on it to verify the scientific nature and reliability of the framework system and method selection. The results show that the framework system includes four aspects: external support system, commercialization expectation, project operation ability and project operation resources. Yingli Group should choose project A3 for cooperation. The framework system and method proposed in this study are feasible and can help Yingli Group correctly choose digital green innovation investment projects. At the same time, this study also brings positive enlightenment to other photovoltaic building materials enterprises in the world when choosing digital green innovation investment projects.

PurposeThe aim of this study is to (1) construct a standard framework for assessing the capability of bioenergy enterprises' digital green innovation partners; (2) quantify the choice of partners for digital green innovation by bioenergy enterprises; (3) propose based on a dual combination empowerment niche digital green innovation field model.Design/methodology/approachFuzzy set theory is combined into field theory to investigate resource complementarity. The successful application of the model to a real case illustrates how the model can be used to address the problem of digital green innovation partner selection. Finally, the standard framework and digital green innovation field model can be applied to the practical partner selection of bioenergy enterprises.FindingsDigital green innovation technology of superposition of complementarity, mutual trust and resources makes the digital green innovation knowledge from partners to biofuels in the enterprise. The index rating system included eight target layers: digital technology innovation level, bioenergy technology innovation level, bioenergy green level, aggregated digital green innovation resource level, bioenergy technology market development ability, co-operation mutual trust and cooperation aggregation degree.Originality/valueThis study helps to (1) construct the evaluation standard framework of digital green innovation capability based on the dual combination empowerment theory; (2) develop a new digital green innovation domain model for bioenergy enterprises to select digital green innovation partners; (3) assist bioenergy enterprises in implementing digital green innovation practices.

Purpose The new generation loves to interact with digital technologies. On the other hand, due to the soaring digital innovation trends, sustainability is crucial in higher educational institutes (HEI), necessitating investigating the factors that lead to green innovations. Therefore, drawing on the Stimulus-organism-response approach (SOR) and dynamic capability view, the current study examines the intricate relationship between digital leadership, dynamic capability, knowledge sharing, green digital mindset and green digital innovation in higher education settings. Methods This research utilized the three-wave (T1 = digital leadership, dynamic capability, T2 knowledge sharing, green digital mindset, T3 = green digital innovation) research approach to collect the data in a one-month time lag from the top management of universities working in China. At T3, 425 filled questionnaires were received, which were utilized for the final data analysis. SmartPLS 4.0 was employed for data analysis. Results The results present mixed findings, as digital leadership was an insignificant predictor of green digital innovation. However, Dynamic capability and knowledge sharing underscore the crucial role of both as predictors to foster green digital innovation in Chinese universities. Furthermore, the study reveals the significant mediating role of knowledge sharing between digital leadership, dynamic capability and green digital innovation. Conclusion This study postulates that knowledge sharing and green digital innovation will be stronger in the presence of a green digital mindset in Higher education institutions. HEIs should ensure a dynamic culture that adapts technology and sustainability principles to remain at the forefront of digital and green innovation.

As environmental pressures intensify and digital technology advances rapidly, many countries, including China, are looking to more effectively heed social and environmental responsibilities by effectively integrating digital technology with traditional industries. Digital green innovation is gradually becoming a necessary direction for enterprises in various countries as they strive for high-quality development. How enterprises can achieve digital green innovation through the duality of digitalization and sustainability has become a crucial research question. However, existing research rarely addresses the mechanisms that lead to the formation of digital green innovation within enterprises. This study uses a sample of 305 manufacturing enterprises in China. Based on strategic orientation theory, this study introduces the concept of digital sustainability orientation, integrating both digital and sustainability orientations. A model is constructed to examine the impact of digital sustainability orientation on digital green innovation in enterprises, analyzing the mechanism of action through the mediation of capability reconfiguration and the moderation of environmental scanning. The study finds that digital sustainability orientation significantly positively impacts digital green innovation, highlighting the integrated effect of digital and sustainability orientations. The findings indicate that digital sustainability orientation significantly positively impacts digital green innovation, whereas a single strategic orientation does not effectively promote digital green innovation; capability reconfiguration partially mediates the relationship between digital sustainability orientation and digital green innovation in enterprises; and environmental scanning positively moderates the relationship between digital sustainability orientation and capability reconfiguration and further influences the mediating role of capability reconfiguration. This study contributes to the advancement of digital sustainability theory in the field of digital green innovation; moreover, the results of this study offer significant practical insights for enterprises aiming to successfully implement digital green innovation.

In the context of China’s “dual carbon” strategy, building materials enterprises (BMEs) are in a critical period of digital and green transformation. Their diverse ownership structure and complex industrial types make them important objects of research. To address gaps in the existing literature, particularly regarding executive cognitive structure segmentation, ecological scenario (ES) influence mechanisms, and enterprise heterogeneity, this study uses Chinese BMEs as samples and incorporates industry characteristics, such as strong policy-driven conditions, a complete industrial chain, and diverse ownership types, to explore the relationship between executive cognition, ability reconstruction, and digital green innovation (DGI) performance (DGIP). Executive cognition is conceptualized through two dimensions: environmental protection cognition and digital intelligence cognition (DIC). A comprehensive test is conducted using fuzzy set qualitative comparative analysis (fsQCA). The results show that (1) both executive cognition and capability reconstruction (CR) significantly promote DGIP, and executive cognition has a positive effect on CR; (2) competency reconfiguration plays a mediating role in the influence of executives’ cognition on innovation performance, with the ES having a positive moderating effect on the relationship between the two types of cognitive role competency reconfiguration; (3) the influence of executive cognition varies depending on the nature of the enterprise and the industry; and (4) three types of performance improvement paths emerge: environmental-cognition-driven, cognitive ability connection, and ES-guided paths. The research’s contributions include (1) dividing executive cognition into two dimensions to enrich its conceptualization; (2) introducing the ES to reveal the dynamic mechanisms of cognition–ability–performance; and (3) conducting a heterogeneity analysis based on the nature of enterprises to deepen insights into paths of differentiated influence. This study provides a theoretical basis and practical inspiration for BMEs to enhance their DGIP.