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This study empirically examines the impact, mechanisms, and heterogeneity of artificial intelligence (AI) on innovation in manufacturing enterprises, using data from Chinese A-share listed companies (2011-2022).Using fixed-effects models and mediation analysis, we find that AI significantly drives innovation in manufacturing, a conclusion supported by various robustness checks.The development of AI enables manufacturing enterprises to achieve cost savings and workforce upgrading.Mechanism analysis identifies two key channels through which AI fosters innovation: increasing talent compensation and widening wage disparities.Heterogeneity tests reveal stronger innovation effects in non-state-owned enterprises, firms in the mature and declining stages, industries with lower concentration, and enterprises located in central and eastern China.Further analysis shows that AI's impact on substantive innovation is non-linear and moderated by technological intensity and economic uncertainty.Based on these findings, we propose policy recommendations, including the steadfast promotion of intelligent transformation, stage-differentiated implementation, enhanced talent cultivation and policy support, and the accelerated realization of AI's innovation potential.

Green and sustainable development is unstoppable. The digital economy has driven great changes in production methods and has become a key strength in reshaping global economic structure and achieving sustainable development. Cities are both the mainstay of economic growth and the main source of various environmental pollution problems. Therefore, studying the relationship between urban digital economy and urban green total factor productivity is of great significance. Based on panel data from 252 cities in China 2011–2019, a two-way fixed effects model was used to examine the impact of urban digital economy on urban green total factor productivity. The empirical results indicate that: (1) Urban digital economy has a significant positive impact on urban green total factor productivity. (2) Urban technological-innovation-level and human-capital-structure of play a mediating role in the impact. (3) This impact has regional heterogeneity and resource-based type heterogeneity. The research conclusions are not only valuable supplements to previous research, but also providing reliable instructions for implementing a flexible digital economy policy.

To verify the importance of optimizing a business environment and improving the level of human capital structure to promote economic development, this study employs a panel data of 30 Chinese provinces from the period 2008–2019 and utilizes the spatial Durbin model and quantile regression model to analyze the relation between a business environment, human capital structure upgrading, and economic development quality. We find that the quality of economic development has a strong spatial correlation and the improvement in the business environment promotes human capital structural upgrading and economic development quality. Human capital structural upgrading plays a significant intermediary role, through which improvement in the business environment affects economic development quality. Considering the huge differences in the level of economic development in different regions of China, we also conduct a regional heterogeneity analysis. We find that the promotion effects of the business environment and advanced human capital structure on economic development quality are significant within the sample period, and their promotion effects are significantly heterogeneous and asymmetric across quartiles, indicating that there is heterogeneity in the intensity of dependence of economic development quality on advanced human capital structure and business environment at different stages of economic development. Moreover, by observing the impact trends in the eastern, central, and western regions, we find that the impact of the business environment and human capital structure on the quality of economic development varies somewhat across provinces. This suggests that the eastern and central regions need to strengthen the optimization of the business environment, while the eastern and western regions should pay more attention to the improvement of the level of the advanced human capital structure.

Grounded in the Supply Chain Innovation and Application Pilot Policy, this study examines listed companies on China’s A-share market from 2009 to 2023, employing a difference-in-differences model to analyze the impact of supply chain digitalization on corporate ESG performance and its underlying mechanisms. The findings indicate that supply chain digitalization facilitates the improvement of corporate ESG performance by alleviating financing constraints, promoting digital technology innovation, and optimizing human capital structure. Heterogeneity analysis reveals that this effect is more pronounced in firms with greater board diversity, CEO–Chair duality, and higher market attention. This study extends the existing body of research on supply chain digitalization and thereby provides robust empirical evidence for policymakers and corporate managers to further promote enhanced ESG performance and advance sustainable development initiatives.

The manufacturing sector’s pursuit of green transformation amidst the digital revolution presents a critical challenge. Using a comprehensive panel dataset from 2012 to 2022, we analyze how digital technology, through its influence on a firm’s human capital structure, impacts green innovation. Our findings show that digital technology significantly boosts a firm’s green innovation efficiency. We identify two distinct mechanisms: digitalization indirectly enhances efficiency by reconfiguring the workforce to decrease the proportion of production personnel, while it directly drives innovation by increasing the share of sales and technical staff. The analysis also reveals a dual effect of an expanding internal compensation gap, which intensifies the displacement of production workers while weakening the firm’s ability to attract and retain core talent. Further heterogeneity analysis reveals that the impact of digital technology on green innovation efficiency is more significant in high-tech industries, non-capital-intensive industries, and non-heavily polluting industries. These findings provide a deeper understanding of the interdependent mechanisms linking digital transformation to sustainable innovation, offering valuable insights for managers and policymakers aiming to strategically align digital, human, and organizational factors for green development.

The construction industry is in urgent need to transition away from its rough development and management practices. It is essential to embrace a sustainable development path to enhance core competitiveness, promote resource intensification, and prioritize environmental friendliness. The digital transformation uses information and data as the key elements to promote the transformation of traditional industries to become more intelligent and green. This ushers in new opportunities for transformation in the construction industry, marking a significant turning point for its evolution. This paper explores the impact of digital transformation on the green development of construction companies and its inner mechanism. Based on the panel data of the listed companies in China’s construction industry from 2015 to 2021, the two-way fixed effect, mediating effect, moderating effect, and threshold effect models are used to test the relationship between them. The results indicate that digital transformation significantly promotes the green development of construction companies. Additionally, this result still holds after robustness and endogeneity tests. This effect is more significant in state-owned, larger companies situated in regions with weaker digital economy development. In addition, the intensity of regional environmental regulations strengthens the impact of digital transformation on green development. However, it has a threshold effect. In the test of mediating effect, it has been found that green innovation and corporate human capital structure can serve as mediators. In the general trend of digital change, the drive towards the sustainable development of construction companies offers micro-empirical evidence that the digital economy empowers green development in China.

In China, exploring the relationship between human capital and green economy in the context of economic transformation can promote the construction of an ecological civilization and high-quality economic development. This paper is dedicated to assessing the impact of human capital stock, human capital structure, and the difference between the two on China’s green economy. Using the super-efficiency slack-based measure (SBM) model, this paper evaluated the green total factor productivity (GTFP) of 30 Chinese provinces to assess the greenness of its economy and analyzed its spatiotemporal evolution from 2000 to 2017. A spatial error model (SEM) was established to explore the impact of human capital on green economy. The results show that (1) the GTFP of China increased continuously from 0.219 to 0.457, showing a regional spatial differentiation of “eastern region > central region > western region.” The spatial gaps of the green economy in the east-west and north-south directions are narrowing. (2) Moran’s I index and Moran’s I scatter plot indicate a significant spatial correlation between human capital and China’s green economy. The local spatial correlation between human capital and green economy is mainly characterized by “high-high” and “low-low” types of agglomeration. (3) The effects of human capital stock and human capital structure on green economy were both positive, with coefficients of 0.0005 and 0.1601, respectively, but the effects of human capital structure were not significant. (4) The results of regional regression show that the difference between the human capital impact coefficients on green economy in the eastern and midwestern regions is small. The impact of human capital stock and human capital structure on green economy is consistent with the national level results. It can be preliminarily concluded that the development of China’s green economy relied more on improving the human capital stock than on the improvement of the human capital structure. This study further enriches the literature on the green economy and provides information that can support government policy-making.

PurposeThe purpose of this paper is to add to the existing research about how corporate performance is influenced by their basic research (BR) investment. On this basis, the authors examined the moderating effect of human capital structure (HCS) on the relationship between BR investment and corporate performance.Design/methodology/approachHypotheses were tested using static and dynamic models to analyze a large-scale data of Chinese A-share listed companies.FindingsThis study provides empirical evidence that contributes to the research about how private BR investment influences corporate performance in the digital age. In addition, human resource is an important dynamic ability for enterprise development. Based on the dynamic capability theory, further research finds that the human resources practice on the knowledge stock can enhance the company’s dynamic capability, thereby enhancing the company’s core competitiveness.Research limitations/implicationsThe results may be affected by the context of the data set. This study considers the influence of private research investment type on corporate performance, further studies considering the influence of specific contextual variables, such as corporate industry differences, could yield richer insights that would help validate the results of this study.Practical implicationsThis study provides useful information for managers. As well as increasing the investment in the BR of enterprise and creating the necessary conditions to increase the competitiveness of enterprise, they should strive to adjust the structure and quality of researchers involved in BR projects.Originality/valueThis research contributes to the enterprise’s BR investment and the management of human capital resource. It points that the investment of BR positively influences the corporate performance. In addition, the increasing of high-skilled labor’s proportion positively promotes the promotion of BR investment on corporate performance.

In last few years, air pollution has caused many issues in China. With the flourishing of education, the relationship between advanced human capital structure (AHCS) and air pollution deserves thoughtful consideration. Therefore, this article uses a dynamic panel model to analyze the effect of AHCS on air pollution with data from 31 Chinese provinces from 2014 to 2020. Considering the potential endogenous problem of AHCS affecting air pollution, the system generalized method of moments method is employed to overcome endogenous bias. Empirical results reveal that, in China, AHCS significantly worsens air pollution. By comparing the dynamic panel model with the traditional static panel model, traditional mean regression was found to overestimate the impact of AHCS on air pollution. Then we explored the mechanism by which AHCS affects air pollution and found that industry structure, urbanization, per capita disposable income, and industry cluster mediate the effect of AHCS on air pollution. Finally, some policy implications are proposed to improve AHCS and air pollution control.

Green development is crucial to global natural resource conservation, environmental improvement and sustainable development. Furthermore, resource-based cities’ green development is more challenging compared with that of other types of cities. On such basis, it is a necessity to understand the green development level of such cities. Therefore, we introduce green development efficiency (GDE), which is a key indicator for measuring green development. This paper takes China’s 112 resource-based cities during 2010–2019 as its research object, and examines their GDE using the Super-SBM-Undesirable model. Moreover, industrial structure upgrading (ISU) and human capital structure upgrading (HCSU) have important implications for green development. To further explore the influence of ISU and HCSU on GDE, this paper employs a fixed effect model, an interaction effect model and a threshold model. Finally, considering the differences between different resource-based cities, the heterogeneity of ISU and HSCU on GDE in four types of China’s resource-based cities is also explored. It is found that (1) although GDE is on the track of steady improvement, the overall GDE was still relatively low during 2010–2019, with an average GDE of about 0.8; (2) ISU, HCSU and their interaction can promote GDE in resource-based cities and with the intensity of industrial structure increasing, the interaction effect of ISU and HSCU on GDE in resource-based cities shifts from positive to negative; (3) there exists heterogeneity in the direct effect and interaction effect of ISU and HCSU among four types of resource-based cities (i.e., mature cities, growing cities, declining cities and regenerating cities). Our findings offer a data reference for the green and sustainable development of China’s resource-based cities, and also a method reference for other countries’ resource-based cities.