Developing a Conceptual Partner Selection Framework: Digital Green Innovation Management of Prefabricated Construction Enterprises for Sustainable Urban Development

Analysis of influencing factors on review efficiency of multidisciplinary scientific research projects using DEMATEL with a 5-point scale

In the wake of advancing technology and the convergence of diverse disciplines, collaborative research across academic sectors has become instrumental in fostering innovation and tackling multifaceted challenges. The inherent complexity of such multidisciplinary endeavors, characterized by a myriad of research trajectories and a spectrum of expertise, poses significant challenges to effective review. This study aims to identify and analyze the factors influencing the review efficiency of multidisciplinary scientific research projects to ensure their smooth development and improved quality. To address this challenge, we employ the Decision Making Trial and Evaluation Laboratory (DEMATEL) method with a 5-point scale. First, we introduce an indexing framework to systematically identify factors influencing the appraisal of multidisciplinary efforts. This framework is then complemented by expert-driven questionnaires, harnessing domain-specific insights to ascertain the significance and interconnectedness of these factors. Using the DEMATEL method, we distill the data to identify key influencing factors that enhance review efficiency for multidisciplinary projects. Our findings provide pragmatic strategies and policy guidance, equipping institutional bodies and program leads with tools to refine the review process of multidisciplinary scientific research projects.

Study on the impact of digital economy on industrial collaborative agglomeration: Evidence from manufacturing and productive service industries

In the digital era, digital economy has a far-reaching impact on the collaborative agglomeration of manufacturing and service industries. This research aims to examine the economic relationship between digital economy and industrial collaborative agglomeration. Based on a panel data set of 286 Chinese cities, this research employs Tobit model, moderating effect model, and mediating effect model to conduct data analysis. It is found that digital economy has a nonlinear relationship with industrial collaborative agglomeration, and this relationship is a U-shape. Moderating effect analysis reveals that government intervention significantly regulates the role of digital economy in industrial collaborative agglomeration. Mediating effect analysis indicates that digital economy promotes industrial collaborative agglomeration through entrepreneurial activity. Heterogeneity analysis shows that the facilitating effect of digital economy on collaborative agglomeration in high-end industries comes earlier than in middle- and low-end industries. Moreover, this research finds that digital economy plays a significant role in industrial collaborative agglomeration in central and western regions of China but not in the eastern region. To enhance the impact of digital economy on industrial collaborative agglomeration, it is crucial to strengthen the engagement of the government and ensure the availability of digital technology.

Projection-driven optimization framework for risk assessment of "dual carbon" audit in power grid enterprises with q-rung orthopair fuzzy MAGDM

Power grid enterprises are the backbone of promoting clean and low-carbon energy transformation, playing an important role in achieving carbon peak and carbon neutrality. It is very necessary to audit the implementation of the "dual carbon" work of power grid enterprises, in order to better implement the national "dual carbon" policy and serve the development of the national economy. The risk assessment of "dual carbon" audit in power grid enterprises is multiple-attribute group decision-making (MAGDM). In this study, in light with projection measure technique and bidirectional projection measure technique, four forms of projection measure technique with q-rung orthopair fuzzy sets (q-ROFSs) are conducted. Then, two weighed projection techniques are conducted to manage the MAGDM. Finally, a numerical example for risk assessment of "dual carbon" audit in power grid enterprises and comparative analysis is utilized to verify the developed techniques. The major contribution of this research is constructed: (1) entropy technique is implemented to determine the weight values in line with score number (SN) and accuracy number (AN); (2) two weighed projection techniques are implemented to put forward MAGDM with q-ROFSs; (3) the numerical example for risk assessment of "dual carbon" audit in power grid enterprises is implemented to show the two weighed projection techniques under q-ROFSs; and (4) comparative studies are constructed with existing techniques.

Digital economy and urban economic resilience: The mediating role of technological innovation and entrepreneurial vitality

Drawing on the diffusion of innovation theory, we argue that the development of digital economy has a positive effect on urban economic resilience. Using panel data from 284 cities in China from 2011 to 2018, we empirically examine the relationship between digital economy and urban economic resilience. We find a positive and significant link between them, mediated by technological innovation and entrepreneurial vitality. Moreover, the heterogeneity analysis shows that the impact of digital economy is most pronounced in smaller cities, with its effects diminishing in larger cities and megacities. Our results underscore the importance and the direction of fostering digital economy development.

The impact of technological innovation on the green digital economy and development strategies

To investigate the interplay among technological innovation, industrial structure, production methodologies, economic growth, and environmental consequences within the paradigm of a green economy and to put forth strategies for sustainable development, this study scrutinizes the limitations inherent in conventional deep learning networks. Firstly, this study analyzes the limitations and optimization strategies of multi-layer perceptron (MLP) networks under the background of the green economy. Secondly, the MLP network model is optimized, and the dynamic analysis of the impact of technological innovation on the digital economy is discussed. Finally, the effectiveness of the optimization model is verified by experiments. Moreover, a sustainable development strategy based on dynamic analysis is also proposed. The experimental results reveal that, in comparison to traditional Linear Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and Naive Bayes (NB) models, the optimized model in this study demonstrates improved performance across various metrics. With a sample size of 500, the optimized model achieves a prediction accuracy of 97.2% for forecasting future trends, representing an average increase of 14.6%. Precision reaches 95.4%, reflecting an average enhancement of 19.2%, while sensitivity attains 84.1%, with an average improvement of 11.8%. The mean absolute error is only 1.16, exhibiting a 1.4 reduction compared to traditional models and confirming the effectiveness of the optimized model in prediction. In the examination of changes in industrial structure using 2020 data to forecast the output value of traditional and green industries in 2030, it is observed that the output value of traditional industries is anticipated to decrease, with an average decline of 11.4 billion yuan. Conversely, propelled by the development of the digital economy, the output value of green industries is expected to increase, with an average growth of 23.4 billion yuan. This shift in industrial structure aligns with the principles and trends of the green economy, further promoting sustainable development. In the study of innovative production methods, the green industry has achieved an increase in output and significantly enhanced production efficiency, showing an average growth of 2.135 million tons compared to the average in 2020. Consequently, this study highlights the dynamic impact of technological innovation on the digital economy and its crucial role within the context of a green economy. It holds certain reference significance for research on the dynamic effects of the digital economy under technological innovation.

Artificial intelligence and green product innovation: Moderating effect of organizational capital

Green product innovation (GPDI) is crucial for addressing ecological issues and essential for enterprises' green operations and long-term growth. Digitization offers new possibilities for enhancing corporate green practices. Nevertheless, previous studies have predominantly addressed the association between overall digitalization and corporate green innovation, and research on the outcome of specific digital technology categories on green innovation is lacking. Within this framework, this study broadens the investigation into the connection between distinct categories of digital technologies and corporate green innovation. The period 2013-2022 was selected as the sample observation period, with companies listed on China's A-share market as the study objects. The fixed-effects model was applied to investigate the impact of artificial intelligence (AI) on firms' GPDI while exploring the interaction effect of firms' organizational capital. The findings indicate that AI is beneficial to GPDI in businesses. This effect is enhanced by employee and board human capital but diminished by board social capital. These results remained valid after two-stage least squares regression. This study broadens the utilization of the resource-based view and dynamic capacity theory in business implementation. Furthermore, it extends the resulting study of AI and provides a digital enhancement pathway for corporate GPDI. This study has significant theoretical and practical implications.

What drives the green development behavior of local governments? A perspective of grounded theory

Although the elements that lead local governments to adopt sustainable development behaviors have been examined, the underlying processes that local governments adopt to accomplish green development behavior (GDB) lack systematic theoretical analysis. This study aims to investigate the determinants influencing local governments' implementation of GDB from the organizational internal and external perspectives. This study employed grounded theory to analyze the data and develop an influencing factor model of local government green development behavior (GDB-LG) after interviewing 53 Chinese local officials. Additionally, through integrating process organization research with new institutional theory, the mechanism that explains how these elements influence GDB was investigated. The results of the study demonstrate that the influencing factors model could give municipal governments clear guidance when creating sensible green development policies, further enhancing the efficacy of GDB.

Digital economy and institutional dynamics: striving for equitable public service in a digitally transformed era

Background

The rapid emergence of China's digital economy has sparked profound interest in the complex interplay between digitalization and the provision of public services. This study aims to delve deeper into how the development of the digital economy impacts the level of equalization in public service delivery and evaluates whether institutional factors can moderate this transformation. Against the backdrop of pursuing "common prosperity," this research provides valuable guidance for policymaking and strategic planning. It ensures that the ascent of the digital economy not only elevates the standards of public services but also fosters their equitable distribution, thereby advancing the cause of social equity.

Methodology

The study utilized the System Generalized Method of Moments (GMM) model along with longitudinal trend data spanning from 2009 to 2018. This approach facilitated an in-depth analysis of the relationship between the digital economy and the level of equalization in public service delivery. The application of this model provided deeper insights into the impact of the digital economy on public service equalization and the identification of underlying mechanisms.

Findings

This study reveals a complex paradox that the digital economy is exacerbating regional disparities in the provision of basic public services. Furthermore, the research underscores the pivotal role of institutional environments in mitigating the adverse effects of the digital economy on public service provision. By examining the interplay between digital economy growth and institutional frameworks, the study suggests that adaptable and robust institutions are essential for harnessing the digital economy's benefits while minimizing its potential drawbacks.

Conclusion

In conclusion, the findings from this study offer substantial insights into the dual impact of the digital economy on public service provision, enriching the ongoing discourse on digital transformation and social equity. The research underscores the significance of strategic policy reforms and institutional adjustments to harness the transformative power of the digital economy, promoting equitable access to public services and advancing the goal of "common prosperity" in the digital age.

Incentive mechanism of multiple green innovation behaviors of equipment manufacturing enterprises: A managers, green coordination groups and employees perspective

Employees play a pivotal role in the implementing of green development strategies and the attainment of dual-carbon objectives within manufacturing enterprises. Effective motivation of employees, fostering consensus on environmental protection, increased engagement in environmental initiatives, and the cultivation of employee cohesion are all vital for fostering green development within these enterprises. This paper seeks to elucidate the roles of general managers, green coordination groups (GCG), and employees in actualizing green behaviors. Furthermore, it advocates for a double incentive model to be employed in the implementing of green strategies within manufacturing enterprises. The research reveals that multiple factors, including incentive intensity, green capability, effort cost, risk aversion, and green variance, significantly influence the formulation of incentive contracts for green behaviors. The motivation level of the general manager directly impacts the efforts of the GCG, the organization's green climate, the manager's individual efforts, and indirectly influences the motivation and efforts of employees towards green behaviors. Notably, the influence of the organization's green climate on employees surpasses than on the manager, underscoring the imperative for collaboration efforts between the general manager and GCG to instill green behaviors among employees. Hence, it is imperative for the general manager and GCG to collaborate not only on critical aspects of green strategy implementation but also in fostering green behaviors among employees. This collaboration will facilitate the development of a multi-layer incentive mechanism aimed at promoting and facilitating the adoption of green behaviors among employees, thus contributing to the advancement of theory regarding employees' green behaviors and offering practical guidance for effectively realizing dual-carbon targets and achieving high-quality development within enterprises.

Research on urban economic centrality in the perspectives of knowledge stocks and flows

In light of the profound advancements in information and communication technologies ushering in the knowledge economy, the urban space is undergoing a transformation from the traditional "space of places" to the emerging "space of flows." This shift poses questions about the influence of knowledge flows on urban economic centrality. This paper seeks to address this knowledge gap by introducing a theoretical framework that elucidates how knowledge contributes to urban economic centrality. Our analysis focuses on both intra-city knowledge stocks and inter-city knowledge flows. Empirical findings in China highlight that knowledge stocks based on R&D and education levels, along with knowledge flows, significantly and positively influence all four dimensions of centrality. In contrast, knowledge spatial agglomeration within the knowledge stocks exhibits a significant positive correlation solely with power centrality. Additionally, although the knowledge stock structures don't yield significant results in the diffusion centrality model, for agglomeration and power centralities, a combination of specialized knowledge and telecommunications enhances urban economic centrality, while face-to-face communication strengthens the positive impact of diverse knowledge on urban economic centrality. The results suggest implementing knowledge-based policies tailored to different nodes in the city network is expected to promote sustainable competitiveness in the urban system.

Threshold effect of technological innovation on carbon emission intensity based on multi-source heterogeneous data

It is of much importance to clarify the impact of technological innovation on carbon emission intensity for the low-carbon transformation of China's economy. This study, based on the panel data of 30 Chinese provinces and municipalities from 2010 to 2020, measures and analyzes the carbon emission intensity and the level of technological innovation, establishing a spatial econometric model to study the spatial spillover effect and a panel threshold model to analyze the nonlinear influence of technological innovation level on carbon emission intensity. The findings are as follows: First, the overall carbon emission intensity in China shows a decreasing trend from 2010 to 2020, with the average dropping from 3.09 in 2010 to 1.98 in 2020; Second, the spatial autocorrelation results reveal that the level of technological innovation and carbon emission intensity in China are obviously aggregated in the global spatial distribution pattern. Third, the regression results of the spatial econometric model show that the direct effect of technological innovation on carbon emission intensity is significantly negative at the level of 1%, that is, the improvement of the technological innovation in a certain area has a significant inhibitory effect on carbon emission intensity. Fourth, based on the level of economic development, there is a significant three-threshold effect of the level of technological innovation on carbon emission intensity in China, and the influence of the level of technological innovation on carbon emission intensity varies in the direction of existence and coefficient values within different threshold intervals. As economic development reaches the third interval, the technological innovation level has the most significant inhibition on carbon emission intensity. These findings enriches the research of the nonlinear relationship between technological innovation and carbon emission intensity, clarifies the spatial spillover effect and threshold effect between among them, and provides inspiration for better promote the low-carbon transformation of economy.

Spatial-temporal coupling coordination and interaction between digitalization and traditional industrial upgrading: a case study of the Yellow River Basin

The realization of coupling coordination between digitalization and traditional industrial upgrading in the Yellow River Basin holds significant practical value for promoting high-quality industrial development in the region. In order to assess this coupling coordination, we utilized inter-provincial panel data from nine provinces in the Yellow River Basin, covering the period from 2011 to 2020. Through the application of a coupling coordination degree model, we calculated the degree of coupling coordination and relative development between digitalization and traditional industrial upgrading. Additionally, we conducted a spatial-temporal analysis to identify the characteristics and trends of digitalization and traditional industrial upgrading. Furthermore, we constructed a panel VAR model to examine the interactive relationship between these two factors. The findings are as follows: (1) overall, over the study period, the degree of coupling coordination between digitalization and traditional industrial upgrading in the Yellow River Basin transitioned from a disordered state to a run-in stage. The corresponding development type changed from a low steady state to a co-existence of low and medium steady states. Notably, the levels of digitalization, traditional industrial upgrading, and coupling coordination all exhibited a gradual increase, while the relative development degree declined. (2) The coupling coordination degree between digitalization and traditional industrial upgrading in the Yellow River Basin demonstrated significant regional variation. Provinces displaying a "high-high" agglomeration distribution and "low-low" agglomeration distribution were concentrated in the middle and lower reaches, as well as the upper reaches, of the Yellow River. Furthermore, there was a positive spatial autocorrelation between these regions. (3) Both digitalization and traditional industrial upgrading exhibit self-reinforcing mechanisms, and a long-term dynamic correlation exists between them.

How to optimize dust pollution control in opencast coal mines: Analysis of a joint social regulation model based on evolutionary game theory

The carbon peaking and carbon neutrality goals drive innovation in pollution governance systems, unleashing the potential of social supervisory forces to achieve coordinated governance by multiple stakeholders. In order to improve dust pollution control in opencast coal mines, this study combines prospect theory with evolutionary game theory, analyzing the evolutionary game process of coordinated governance activities of coal mining enterprises, local regulators, and social camps in the management of dust pollution against the backdrop of national supervisions. The research indicates that the perceived value of dust pollution has a significant impact on the strategic choices of the three agents involved in the game. Coal mining enterprises tend to be risk averse, and by reducing the cost of dust pollution control and increasing the additional benefits of pollution control, it can promote pollution control behavior by coal mining enterprises. Local regulators are also risk averse, but not sensitive to risk benefits. Strengthening pollution subsidy incentives and environmental fines can help promote dust pollution control behavior by coal mining enterprises. However, increasing the strength of the rewards strategy is not conducive to local regulators' own regulatory responsibilities, and environmental fines have limited binding effects. The strategic choices of social camps' supervision have a restrictive effect on the strategic choices of coal mining enterprises and local regulators, promoting the evolution of equilibrium results in the direction of maximizing social benefits. When coal mining enterprises actively governance pollution, local regulators strictly regulated, and social camps do not monitor, the system reaches its optimal equilibrium state. The research results clarify the mechanism and specific effects of social supervision of opencast coal mine dust pollution control, guide the participation of the public in dust pollution control, and regulate the behavior strategies of coal mining enterprises and local regulators, providing the scientific basis for management.

Optimal operation mode selection of sponge city PPP projects using IFSS-prospect theory and VIKOR approach: a case study in China

The construction of sponge city (SC) public private partnership (PPP) projects is considered to be a feasible measure to solve the "water problems" in China. To ensure the success of SC PPP projects, how to select an appropriate operation mode for SC PPP projects is an urgent problem to be solved. In this paper, first, the evaluation index system of operation mode is established from the aspects of project characteristics, government capabilities, project benefits, project implementation, and cooperative partnership. Second, the DEMATEL method and entropy method are introduced to overcome the drawbacks of a single method, and the combination weights are calculated by game theory. Finally, the decision-making model based on intuitionistic fuzzy soft set (IFSS)-prospect theory and VIKOR approach is constructed to select operation mode for SC PPP projects. In this paper, the framework is applied to select an operation mode for the Qingshan demonstration zone project, and its feasibility and effectiveness are verified through sensitivity analysis and comparative analysis. The results show that BOT is the optimal operation mode for SC PPP projects, and government capabilities and project implementation are critical factors to be considered when selecting an operation mode. This study can provide guidance to the government in the OMS of SC PPP projects and improve the sustainability of the projects.

How to effectively prevent alienation behavior of prefabricated construction developers: an optimization analysis of regulatory strategies

Prefabricated buildings (PBs) contribute to sustainable development, and their development largely depends on the active participation of developers. However, based on the characteristics of different stages of PBs' development and the goals of "14th Five-Year Plan" for architecture in China, it is an urgent practical problem for the government to encourage developers' active participation while regulating their alienation behavior. To address such problem, this paper uses the evolutionary game method to explore the government's reasonable regulatory strategies for developers' behavior in different development stages of PBs. Meanwhile, this paper explores the boundary of government's regulatory strength on PBs based on actual situation in China, which help the government to drive high-quality development of PBs with effective policy resources. Results reveal that the strict regulatory strategies have limited effects in the incubation stage of PBs. In the growth stage, it is necessary to adjust the regulatory strategies appropriately. The dynamic linear regulatory strategy can enable the PBs to achieve the phased goal, and the dynamic nonlinear regulatory strategy can help to achieve the optimal goal of PBs in China. In the maturity stage, the government does not need to deliberately regulate due to the considerable profits of developers. The regulatory strategy of "light reward and heavy punishment" is better when it is adopted to promote the development of PBs in the growth stage. The research also provides valuable suggestions for government regulators to formulate reasonable and dynamic regulatory policies for PBs.

SEM-Based Analysis of Carbon Emission Reduction Pathway Study during the Materialization Stage of Prefabricated Buildings: Evidence from Shenyang and Guiyang, China

In recent years, in the process of promoting prefabricated buildings, problems such as waste of resources and energy have been present, which have seriously hindered the realization of carbon emission reduction benefits of prefabricated buildings. Especially during the materialization stage of prefabricated buildings which involves the most engineering activities and the most extensive sources of carbon emissions, it is urgent to further meet the low-carbon development of the construction industry. This study takes the 4 substages of design and development, component production, transportation, and installation during the materialization stage as the point of penetration and identifies the carbon reduction impact pathways based on the 3E (Environment-Economy-Energy) system theory in 5 dimensions: government policy, management mode, technology level, economy input, and energy structure. The data are collected through the questionnaire survey, and structural equation modeling (SEM) is utilized to examine the hypothesis and impact dimensions of the study. The results confirm that the management mode has the strongest effects on carbon emission reduction, followed by government policy, economy input, and technology level, and the energy structure has the weakest effects. This study presents the key carbon reduction pathways during the materialization stage of prefabricated buildings and provides recommendations for different participants to optimize policy guidance, strengthen management supervision, accelerate technology research and development, increase economy input, and optimize energy structure, with a view to achieving low-carbon governance capacity, management mode, technology system, capital, and energy utilization, and also enriches the theory in the field of prefabricated buildings carbon emission reduction, which can better achieve low-carbon development of prefabricated buildings.

Enhancing engineering ethics education (EEE) for green intelligent manufacturing: Implementation performance evaluation of core mechanism of green intelligence EEE

The characteristics of green intelligent (GI) engineering ethics emphasize the necessity of GI engineering ethics education (EEE). The ethics education of GI engineering is in the development stage, and it is urgent to fully understand the significance of evaluating the development of GI EEE. Only based on the GI manufacturing situation system to understand the implementation status of the core education of EEE can we objectively grasp the improvement space of GI EEE. In this study, the corresponding indicators were selected from three dimensions of cultivation education, collaborative education, and situational education to form the element community of evaluation indicators. The fuzzy analytic hierarchy process and the fuzzy comprehensive evaluation method were used to empirically evaluate the implementation of the key mechanism of GI EEE. The results are as follows. (1) The key education of GI EEE includes cultivation education of micro dimension, collaborative education of medium dimension, and situational education of macro dimension. (2) The most important education is to strengthen the ethics education of GI engineering in the training process of college students. The coordination of GI EEE is becoming more and more important, and the integration and construction are the important pursuit of GI EEE. (3) The cultivation education, collaborative education, and situational education of GI EEE are all at a general level. (4) There is not only a gap between theory and practice in GI EEE but also insufficient attention to localization and coordination issues. The willingness of the government to participate in the ethical education of GI engineering is very insufficient. The optimized space of training education includes teaching cases and full-cycle ethical education.

Insight into the Balancing Effect of a Digital Green Innovation (DGI) Network to Improve the Performance of DGI for Industry 5.0: Roles of Digital Empowerment and Green Organization Flexibility

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.