Exploring the influencing factors of carbon neutralization in Chinese manufacturing enterprises

How environment and technology affect the regional manufacturing industry development

To help the manufacturing industry achieve high-quality development, it is urgent to identify the factors that affect the development of regional manufacturing. Compared to previous regression models, this article attempts to discover the nonlinear effects of different factors on regional manufacturing industry development (RMID) and their future impact trends. Based on the theory of new structural economics, we used order parameter analysis to examine the impact of environmental pollution and technology on RMID. The results indicate that: (1) The half of the cities promote industrial growth, but there are still three other situations: development slow down (3/21), a slight downward trend (5/21), and recession (2/21). (2) The two-thirds of cities adopt green development to promote industrial growth, while the development of other cities slows down (3/21), and some cities have a slight downward trend (4/21). The conclusion is as follows: (1) Through comparison, it is found that the impact of environment and technology on the RMID remains roughly synchronous, but currently the environmental promotion effect is greater. (2) We have found four technological development paths and can extend three green development models, effectively promoting RMID's green technology development. These suggestions will lay the foundation for promoting RMID.

Antecedent configuration pathways for manufacturing-enterprise digital servitization: Based on a technology-organization-environment theoretical framework

The expeditious advancement and elevation of the manufacturing industry's transformation and upgrading represent pivotal strides for China in its ascent toward the upper echelons of the global manufacturing value chain. Currently, China's manufacturing-industry transformation faces the dual-lag quandary of digitalization and servitization. The notion of digital servitization elucidates the interdependent relationship between digitalization and servitization, unveiling the mechanisms underlying the formation of digital servitization. This holds significant implications for advancing the comprehension of digitalization and servitization and, crucially, facilitates the acceleration of China's manufacturing sector transitioning from production-centric to service-centric paradigms. Harnessing the technology-organization-environment (TOE) theoretical framework, we constructed a model elucidating the driving factors underpinning manufacturing digital servitization. By employing the fuzzy-set qualitative comparative analysis (fsQCA), we explored strategic decisions and path dependencies in the transformation of manufacturing digital servitization, offering valuable insights to foster China's manufacturing sector in its digital-servitization journey. The following findings were obtained. (1) A singular condition was insufficient as a prerequisite for manufacturing digital servitization and necessitated the coordinated alignment of multiple variables. (2) Three pathways existed for achieving manufacturing digital servitization: TOE, organization-environment collaborative-oriented, and technology-organization collaborative-oriented. (3) The progression of manufacturing digital servitization resulted from the collective impact of numerous factors, exhibiting a characteristic of different paths leading to the same destination. Various manufacturing enterprises pursued distinct trajectories to achieve digital servitization, contingent upon their unique circumstances. These findings have the potential to provide valuable insights for effectively fostering manufacturing digital servitization.

Technology empowerment: Digital transformation and enterprise ESG performance-Evidence from China's manufacturing sector

In light of the long-term constraints posed by the "dual carbon" objective, can digital technology emerge as a transformative solution for enterprises to embark on a sustainable development trajectory? The existing body of research has yet to reach a consensus. In order to shed further light on the intricate relationship between digital transformation and ESG performance of enterprises, this study empirically examines the mechanisms and boundaries through which digital transformation influences ESG performance, based on observational data from A-share manufacturing listed companies in Shanghai Stock Exchange and Shenzhen Stock Exchange spanning from 2011 to 2021. The findings demonstrate that digital transformation exerts a significant positive impact on the ESG performance of manufacturing enterprises. Mechanism analysis reveals that the enabling effect of digital transformation primarily enhances company transparency, thereby fostering continuous improvements in ESG performance among manufacturing enterprises. The performance expectation gap will give rise to the phenomenon of "stop-loss in time" and impede the promotional impact of digital transformation. Further investigation into industrial characteristics and industry competition intensity indicates that state-owned enterprises and those operating within highly competitive environments experience more pronounced effects of digital transformation on their ESG performance. This study expands the mechanism and boundary of digital transformation on ESG performance of manufacturing enterprises, and provides a new perspective for manufacturing enterprises to realize the collaborative transformation of digital and green.

Digital economy, innovation factor allocation and industrial structure transformation-A case study of the Yangtze River Delta city cluster in China

The attainment of regional high-quality development necessitates the critical role of the digital economy in facilitating the transformation of industrial structures. This study intends to investigate the effect of the digital economy on industrial structure transformation from the perspective of innovation factor allocation using a panel dataset of 41 cities in the Yangtze River Delta region for the period from 2011 to 2020. This paper considers four dimensions to measure the level of industrial structure transformation i.e. industrial structure servitization, industrial structure upgradation, service industry structure upgradation and industrial interaction level. The results of the study suggest that the digital economy can significantly improve industrial structure transformation. The results remain consistent even after several robustness checks. Further, the analysis of the mechanism of action shows that the digital economy can promote industrial structure transformation by optimizing the innovation factor allocation. The study provides several policy implications for the digital economy and its role in the promotion of industrial structure transformation.

Sustainable development of environmental protection talents training: Research on the behavior decision of government, university and enterprise under the background of evolutionary game

Environmental protection talents training (EPTT) is recognized as a key prerequisite for maintaining environmental sustainability, and in order to study the influence of each player on EPTT. This paper innovatively constructs a tripartite evolutionary game model of government, university and enterprise. The equilibrium points and evolutionary stabilization strategies of each participant are solved by replicating the dynamic equations, and the behaviors of each subject in EPTT are analyzed so as to clarify the behavioral characteristics and optimal strategies of the government's participation in EPTT. The results show that enterprises occupy a more important position in influencing government decisions. The government should reduce the financial incentives for enterprises and replace them with greater policy support. Meanwhile, the government should actively promote the cultivation mechanism that integrates universities and enterprises. The results of the study can provide a decision-making basis for the government to promote the sustainable development of EPTT.

Study on the spatial distribution of urban carbon emissions at the micro level based on multisource data

Global warming is currently an area of concern. Human activities are the leading cause of urban greenhouse gas intensification. Inversing the spatial distribution of carbon emissions at microscopic scales such as communities or controlling detailed planning plots can capture the critical emission areas of carbon emissions, thus providing scientific guidance for intracity low-carbon development planning. Using the Sino-Singapore Tianjin Eco-city as an example, this paper uses night-light images and statistical yearbooks to perform linear fitting within the Beijing-Tianjin-Hebei city-county region and then uses fine-scale data such as points of interest, road networks, and mobile signaling data to construct spatial characteristic indicators of carbon emissions distribution and assign weights to each indicator through the analytic hierarchy process. As a result, the spatial distribution of carbon emissions based on detailed control planning plots is calculated. The results show that among the selected indicators, the population distribution significantly influences carbon emissions, with a weight of 0.384. The spatial distribution of carbon emissions is relatively distinctive. The primary carbon emissions are from the Sino-Singapore Cooperation Zone due to its rapid urban construction and development. In contrast, carbon emissions from other areas are sparse, as there is mostly unused land under construction.

Industrial Coagglomeration, Green Innovation, and Manufacturing Carbon Emissions: Coagglomeration's Dynamic Evolution Perspective

The achievement of China's low-carbon development and carbon neutrality depends heavily on the decrease of manufacturing carbon emissions. From coagglomeration's dynamic evolution perspective, by using panel-threshold-STIRPAT and mediation-STIRPAT models, this study examines the relationships among industrial coagglomeration, green innovation, and manufacturing carbon emissions and explores the direct and indirect function mechanisms. Panel data of China's 30 provinces from 2010 to 2019 are employed. The results imply that, first, the impact of industrial coagglomeration on manufacturing carbon emissions is nonlinear and has significant threshold effects. Industrial coagglomeration negatively affects manufacturing carbon emissions, and as the coagglomeration level deepens, the negative effect has a diminishing trend in marginal utility. Once the coagglomeration degree exceeds a certain threshold, the negative impact becomes insignificant. At present, for 90% of China's regions, an increase in industrial coagglomeration level can help reduce manufacturing carbon emissions. Second, green innovation is a vital intermediary between industrial coagglomeration and manufacturing carbon emissions. It is a partial intermediary when industrial coagglomeration is at a relatively lower-level stage and a complete intermediary when industrial coagglomeration is at a relatively higher-level stage. These findings reveal the significance of optimizing industrial coagglomeration and the level and efficiency of green innovation to decrease carbon emissions.