Search Results (641)

The rapid development of digital technology is reshaping the global economic landscape. However, its impact on firms’ capacity utilization rate (CUR), particularly through technological innovation, remains unclear. This study investigates this issue by developing an endogenous growth model that connects digital technology to CUR. The empirical analysis is based on data from Chinese A-share manufacturing firms. The methods employed include quantile regression, instrumental variable techniques, and various tests to explore underlying mechanisms. CUR is calculated using a special model that looks at random variations, and digital transformation is assessed using text analysis powered by machine learning. The findings indicate that digital transformation significantly enhances CUR, especially for firms with average capacity utilization levels, but has a limited effect on low- and high-end firms. Moreover, technological innovation mediates this relationship; however, factors like “double arbitrage” (involving policy and capital markets) and “herd effects” tend to prioritize quantity over quality, which constrains innovation potential. Improvements in CUR lead to enhanced firm performance and productivity, generating industry spillovers and demonstrating the broader economic externalities of digitalization. This study uniquely applies endogenous growth theory to examine the role of digital transformation in optimizing CUR. It introduces the “quantity-quality” technology innovation paradox as a crucial mechanism and highlights industry spillovers to address overcapacity while offering insights for fostering sustainable economic and social development in emerging markets. Full article

Under intensified downward economic pressures on the economy, technological innovation is playing a pivotal role in the development of Chinese enterprises. Employees’ psychological safety significantly influences their innovative behaviors, as a climate of psychological safety fosters greater willingness among staff to engage in voice behaviors. Guanxi with a team leader may decrease this effect. This study analyzed survey data from 263 employees of China’s private manufacturing enterprises to explore the moderating role of guanxi with a team leader in the relationship between psychological safety climate and voice behavior. Results showed that psychological safety climate was positively correlated with promotive and prohibitive voices, and employees with a higher psychological safety climate were more likely to develop voice behavior. Guanxi with team leaders negatively moderated the relationship between psychological safety climate and promotive and prohibitive voices, and the association between psychological safety climate and promotive and prohibitive voices was strong when guanxi with a team leader was weak. This study expands the scope of the application of guanxi, with team leaders as a moderating variable. It helps leaders focus on the psychological safety climate of employees, maintain harmonious and friendly interpersonal relationships with employees, enable employees to spontaneously contribute to the development of the organization, and enhance cohesion in the organization. Full article

This paper examines the effect of digital innovation on cost stickiness in manufacturing firms, focusing on the underlying mechanisms and contextual factors. Using data from Chinese A-share listed manufacturing firms from 2012 to 2023, we find that, first, for each one-unit increase in the level of digital technology, the cost stickiness index of enterprises decreases by an average of 0.4315 units, primarily through digital process innovation and digital business model innovation, whereas digital product innovation does not exhibit a statistically significant impact. Second, manufacturing servitization and the optimization of human capital structure are identified as key mediating mechanisms. Digital innovation promotes servitization by transitioning firms from product-centric to service-oriented business models, thereby reducing fixed costs and improving resource flexibility. It also optimizes human capital by increasing the proportion of high-skilled employees and reducing labor adjustment costs. Third, the effect of digital innovation on cost stickiness is found to be heterogeneous. Firms with high financing constraints benefit more from the cost-reducing effects of digital innovation due to improved resource allocation efficiency. Additionally, mid-tenure executives are more effective in leveraging digital innovation to mitigate cost stickiness, as they balance short-term performance pressures with long-term strategic investments. These findings contribute to the understanding of how digital transformation reshapes cost behavior in manufacturing and provide insights for policymakers and firms seeking to achieve sustainable development through digital innovation. Full article

As the fundamental physical carrier for human production and socio-economic endeavors, enhancing urban land green use efficiency (ULGUE) is crucial for realizing sustainable development. To effectively enhance urban land green use efficiency, this study systematically examines the intrinsic relationship between industrial policies and ULGUE based on panel data from 286 Chinese cities (2010–2022), employing an integrated methodology that combines the Difference-in-Differences (DID) model, Super-Efficiency Slacks-Based Measure Data Envelopment Analysis model, and ArcGIS spatial analysis techniques. The findings clearly demonstrate that the establishment of the “Made in China 2025” pilot policy significantly improves urban land green use efficiency in pilot cities, a conclusion that endures following a succession of stringent evaluations. Moreover, studying its mechanisms suggests that the pilot policy primarily enhances urban land green use efficiency by promoting industrial upgrading, accelerating technological innovation, and strengthening environmental regulations. Heterogeneity analysis further indicates that the policy effects are more significant in urban areas characterized by high manufacturing agglomeration, non-provincial capital/non-municipal status, high industrial intelligence levels, and less sophisticated industrial structure. This research not only provides valuable policy insights for China to enhance urban land green use efficiency and promote high-quality regional sustainable development but also offers meaningful references for global efforts toward advancing urban sustainability. Full article

From the perspective of credit ratings, this paper studies the impact of air pollution on corporate credit costs and the impact mechanism. Based on 2007–2022 data on A-share listed companies in the Chinese capital market, this paper uses a two-way fixed effects model to examine the impact of air pollution on corporate credit costs and the impact mechanism. The results show that air pollution increases the credit costs for enterprises because air pollution affects the sentiment of rating analysts, leading them to give more pessimistic credit ratings to enterprises located in areas with severe air pollution. The moderating effect analysis reveals that the effect of air pollution on the increase in corporate credit costs is more pronounced for high-polluting industries, manufacturing industries, and regions with weaker bank competition. Further analysis reveals that in the face of rising credit costs caused by air pollution, enterprises tend to adopt a combination strategy of increasing commercial credit financing and reducing the commercial credit supply to cope. Although this response behavior alleviates corporations’ own financial pressure, it may have a negative effect on supply chain stability. This paper provides new evidence that reveals that air pollution is an implicit cost in the capital market, enriching research in the fields of environmental governance and capital markets. Full article

Tin is an indispensable metal for contemporary society owing to its extensive application. China is a major tin manufacturer and consumer worldwide. Nonetheless, the crucial characteristics of its tin metabolism remain limited. Therefore, a dynamic material flow analysis (MFA) from 2001 to 2022 was performed in this study to trace China’s tin flows and stocks. Findings show that China became a net tin exporter from a life cycle perspective, and annual tin consumption embodied in various final products varied between 49.3 kilo tons (Kt) in 2001 and 161.5 Kt in 2022, with home appliances and electronics being the dominant consumption sectors. A total of 913.3 Kt of tin became in-use stocks. In addition, the imported tin embodied in various final products varied between 13.9 Kt in 2001 and 21.6 Kt in 2022, with machinery being the dominant consumption sector. The exported tin embodied in various final products varied between 12.0 Kt in 2001 and 76.3 Kt in 2022, with machinery being the dominant consumption sector. Finally, this study proposes some suggestions, in view of the Chinese reality, like enhancing tin recycling, promoting tin geological prospecting, optimizing the structure of the tin trade, and promoting regional cooperation, to improve the supply security of tin resources. Full article

In light of the persistent environmental degradation driven by fossil fuels, developing new energy sources is essential for achieving sustainability. The recent surge in electric vehicle adoption has underscored the significance of new energy batteries. However, the supply chains of new energy battery manufacturers face multiple sustainability risks, which impede sustainable practice adoption. To tackle these challenges, leanness philosophy is an effective tool, and Industry 5.0 enhances its efficacy significantly, further mitigating sustainability risks. This study integrates the supply chain, leanness philosophy, and Industry 5.0 by applying quality function deployment. A novel four-phase hybrid MCDM model integrating the fuzzy Delphi method, DEMATEL, AHP, and fuzzy VIKOR, identified five key sustainability risks five core leanness principles, and eight critical Industry 5.0 enablers. By examining a Chinese new energy battery manufacturer as a case study, the findings aim to assist managers and decision-makers in mitigating sustainability risks within their supply chains. Full article

As Chinese firms play pivotal roles in global supply chains, multinational corporations face increasing pressure to ensure ESG accountability across their sourcing networks. Current ESG rating systems lack transparency in incorporating China’s unique industrial, economic, and cultural factors, creating reliability concerns for stakeholders managing supply chain sustainability risks. This study develops an explainable artificial intelligence framework using SHAP and permutation feature importance (PFI) methods to predict the ESG performance of Chinese firms. We analyze comprehensive ESG data of 1608 Chinese listed companies over 13 years (2009–2021), integrating financial and non-financial determinants traditionally examined in isolation. Empirical findings demonstrate that random forest algorithms significantly outperform multivariate linear regression in capturing nonlinear ESG relationships. Key non-financial determinants include patent portfolios, CSR training initiatives, pollutant emissions, and charitable donations, while financial factors such as current assets and gearing ratios prove influential. Sectoral analysis reveals that manufacturing firms are evaluated through pollutant emissions and technical capabilities, whereas non-manufacturing firms are assessed on business taxes and intangible assets. These insights provide essential tools for multinational corporations to anticipate supply chain sustainability conditions. Full article

Achieving the dual carbon goal and addressing escalating environmental challenges requires that manufacturing enterprises in China must pursue sustainability via green innovation strategies. A key rationale for green innovation is to overcome boundaries and acquire knowledge through boundary-spanning search. Additionally, leveraging artificial intelligence (AI) capabilities provides technical support throughout the innovation process. Thus, both boundary-spanning search and AI capabilities are crucial for achieving sustainability objectives. Drawing on organizational search and knowledge management theories, this paper aims to analyze how dual boundary-spanning search affects sustainability performance and green innovation. It also examines the moderating role of AI capabilities and constructs a moderated mediation model. We analyzed questionnaire data collected from 171 Chinese manufacturing companies over a 13-month period, employing hierarchical regression and bootstrap sampling methods using SPSS 27.0. Our findings reveal that both prospective and responsive boundary-spanning searches significantly enhance corporate sustainability performance. Furthermore, green innovation acts as a positive partial mediator between dual boundary-spanning search and corporate sustainability performance. Notably, AI capabilities positively moderate the relationship between dual boundary-spanning search and green innovation. They also strengthen the mediating effect of green innovation on the link between dual boundary-spanning search and corporate sustainability performance. Based on these findings, more resources should be allocated to boundary-spanning search while encouraging enterprises to pursue green innovation and develop AI capabilities. These efforts will provide robust support for sustainability performance in the manufacturing sector. Full article

With the rapid advancement of artificial intelligence and smart manufacturing technologies, the penetration of industrial robots into Chinese markets has profoundly reshaped the structure of the labor market. However, existing studies have largely concentrated on the employment substitution effect and the diffusion path of these technologies, while systematic analyses of how industrial robots affect labor resource allocation efficiency across different regional and industrial contexts in China remain scarce. In particular, research on the mechanisms and heterogeneity of these effects is still underdeveloped, calling for deeper investigation into their transmission channels and policy implications. Drawing on panel data from 280 prefecture-level cities in China from 2006 to 2023, this paper employs a Bartik-style instrumental variable approach to measure the level of industrial robot penetration and constructs a two-way fixed effects model to assess its impact on urban labor misallocation. Furthermore, the analysis introduces two mediating variables, industrial upgrading and urban innovation capacity, and applies a mediation effect model combined with Bootstrap methods to empirically test the underlying transmission mechanisms. The results reveal that a higher level of industrial robot adoption is significantly associated with a lower degree of labor misallocation, indicating a notable improvement in labor resource allocation efficiency. Heterogeneity analysis shows that this effect is more pronounced in cities outside the Yangtze River Economic Belt, in those experiencing severe population aging, and in areas with a relatively weak manufacturing base. Mechanism tests further indicate that industrial robots indirectly promote labor allocation efficiency by facilitating industrial upgrades and enhancing innovation capacity. However, in the short term, improvements in innovation capacity may temporarily intensify labor mismatch due to structural frictions. Overall, industrial robots not only exert a direct positive impact on the efficiency of urban labor allocation but also indirectly contribute to resource optimization through structural transformation and innovation system development. These findings underscore the need to account for regional disparities and demographic structures when advancing intelligent manufacturing strategies. Policymakers should coordinate the development of vocational training systems and innovation ecosystems to strengthen the dynamic alignment between technological adoption and labor market restructuring, thereby fostering more inclusive and high-quality economic growth. Full article

Corporate resilience, a critical metric assessing firms’ capacity to withstand risks, recover rapidly, and maintain growth in dynamic environments, has garnered increasing attention from academia and industry. This study employs China’s Green Factory certification policy within its green manufacturing system as a quasi-natural experiment, utilizing a multi-period difference-in-differences (DID) model to evaluate the impact of green manufacturing implementation on corporate resilience. Results confirm that Green Factory certification significantly enhances firms’ resilience. Mechanism analyses identify three reinforcing pathways: alleviating financing constraints, optimizing resource allocation efficiency, and fostering green technological innovation. Heterogeneity analyses reveal more pronounced effects among heavily polluting industries, firms with low reputations, and those with higher levels of managerial myopia. Furthermore, the certification exhibits significant spillover effects, transmitting resilience improvements to industry peers and geographic clusters. This research expands the theoretical boundaries of corporate resilience literature while offering practical implications and empirical evidence for enterprises undergoing green manufacturing transitions. Full article

At present, there is a lack of in-depth knowledge of the effects of heavy metal-related industries (HMIs) in China on the environment. Hunan Province, as a representative gathering place of HMIs, is among the regions in China that are the most severely polluted with heavy metals. This paper selected Hunan Province as the study area to analyze the development trend, characteristics of pollution emissions, and environmental impacts of seven HMIs based on emission permit information data from Hunan Province. The results of this study show that (1) from 2000 to 2022, the number of heavy metal-related enterprises in Hunan Province increased overall. Among the seven industries, the chemical product manufacturing industry (CPMI) had the largest number of enterprises, whereas the nonferrous metal smelting and rolling industry (NSRI) had the highest gross industrial product (27.6%). (2) HMIs in Hunan Province had significant emissions of cadmium (Cd), arsenic (As), and hydargyrum (Hg) from exhaust gas and wastewater. Heavy metal-related exhaust gas and wastewater outlets from the NSRI constituted 43.9% and 35.3%, respectively, of all outlets of the corresponding type. The proportions of exhaust gas outlets involving Cd, Hg, and As from the NSRI to total exhaust gas outlets were 44.27%, 60.54%, and 34.23%, respectively. The proportions of wastewater outlets involving Cd, Hg, and As from the NSRI to total wastewater outlets were 61.13%, 57.89%, and 75.30%, respectively. (3) The average distances of heavy metal-related enterprises from arable land, rivers, and flooded areas in Hunan Province were 256 m, 1763 m, and 3352 m, respectively. Counties with high environmental risk (H-L type) were situated mainly in eastern Hunan. Among them, Chenzhou had the most heavy metal-related wastewater outlets (22.7%), and Hengyang had the most heavy metal-related exhaust gas outlets (23.1%). The results provide a scientific basis for the prevention and control of heavy metal pollution and an enhancement in environmental sustainability in typical Chinese areas where HMIs are concentrated. Full article

This study aims to reveal the influence mechanism of innovation competition on the high-quality development of the manufacturing industry in Chinese local governments. Additionally, the study provides a theoretical basis for understanding how governments’ investment in science and technology breaks through key technological bottlenecks, enhances the innovation ability of enterprises, and promotes the high-quality development of the manufacturing industry. Based on balanced panel data of 269 prefecture-level and above cities in China from 2008 to 2021, the entropy value method is used to construct a comprehensive evaluation index of manufacturing development quality, and a two-way fixed-effect panel model is employed for the empirical analysis. The findings reveal that (1) for every 1% increase in local government investment in science and technology, the manufacturing high-quality development index will increase by 0.261%, indicating that local governments’ innovation competition significantly promotes the quality of manufacturing development; (2) enterprise innovation capacity plays a mediating role between government competition and manufacturing quality improvement; (3) the combined mechanism of innovation drive and promotion tournament results in a significant spatial strategic interaction of local governments’ innovation competition and a positive spillover effect on neighboring regions. Therefore, this study suggests that local governments implement different science and technology innovation investment strategies to optimize the allocation of innovation resources according to the regional manufacturing technology level. Full article

The Belt and Road Initiative (BRI) prioritizes infrastructure investment to enhance regional connectivity and foster sustainable economic development. Therefore, this empirical study aims to examine the impact of the BRI, specifically through Chinese foreign direct investment (CFDI) on sustainable growth in Bangladesh. The study employs the Mann–Kendall trend analysis and the generalized method of moments (GMM). For the Mann–Kendall trend analysis, sectoral FDI and output data from four major industrial sectors, obtained from Bangladesh Bank and CEIC for the period 1996–2020, are used to analyze trends in industrial development. Additionally, to assess the BRI’s role in sustainable development, this study compares green gross domestic product (GGDP) and gross domestic product (GDP) using a GMM analysis of CFDI inflows across 16 industrial sectors from 2013 to 2022, sourced from various databases. Findings reveal that CFDI significantly contributes to domestic industrial growth, particularly in the manufacturing and construction sectors. Although Bangladesh joined the BRI in 2016, a notable surge in CFDI appears from 2011–2012, partially driven by Bangladesh’s economic liberalization policies, and reflects early strategic investment consistent with China’s expanding economic diplomacy, which was later formalized under the BRI framework. The two-step system GMM results demonstrate that CFDI has a stronger impact on GGDP (0.0350) than on GDP (0.0146), with GGDP showing faster convergence (0.6027 vs. 0.1800), highlighting more robust and rapid sustainable growth outcomes. This underscores the significant Chinese investment in green sectors in Bangladesh. The study also demonstrates that the BRI supports the achievement of Sustainable Development Goals (SDGs) 7 (green energy) and 9 (sustainable infrastructure). These insights offer valuable direction for future research and policy, suggesting that Bangladesh should prioritize attracting green-oriented CFDI in sectors like energy, manufacturing, and construction, while also strengthen. Full article

There is no consensus in existing research on whether the application of digital technology diversification strengthens or weakens export resilience. This study fills this gap by exploring the influence mechanism of digital technology diversity on enterprise export resilience. Based on organizational inertia theory, dynamic capabilities perspective, and organizational learning theory, this study uses data from Chinese listed export manufacturing companies from 2019 to 2023 in order to empirically examine the relationship between digital technology diversity and enterprise export resilience. The results show that digital technology diversity significantly inhibits enterprise export resilience, supply chain finance plays a partially mediating role in this relationship, and digital interlock alleviates the inhibitory effect of digital technology diversity on supply chain finance. The findings provide guidance for the digital technology application strategy of export enterprises in adversity. Full article