Search Results (67)

To address the challenges of complex multi-channel signal coupling and insufficient long-term temporal dependency characterization in remaining useful life (RUL) prediction of rotating machinery, this paper proposes a multivariate time series forecasting framework integrating multi-channel information fusion and a self-attention gated augmentation unit (SGAU). First, a multilayer perceptron (MLP) explicitly models nonlinear coupling among channels; SGAU replaces the conventional feed-forward network in the Transformer encoder, using multi-head self-attention outputs as gating signals to adaptively regulate feature transformation. Second, multi-channel signals are predicted via this framework; high-dimensional feature vectors are extracted to construct multi-channel Gaussian mixture models (GMMs). Third, Jensen–Shannon divergence (JSD) quantifies deviations between the target and initial data clusters; centroid distance evolutionary trajectory is fused with JSD to construct the health indicator (HI). Continuous HI predictions yield the RUL prediction curve. Experiments on a self-designed wind turbine gearbox platform and the XJTU-SY bearing dataset demonstrate that the proposed framework outperforms baseline methods on Mean Square (MS), Root Mean Square (RMS), and Energy metrics, with average error reductions of 6.6% and 12.1% in the horizontal and vertical directions on the gearbox dataset and 20.9% and 32.3% on the bearing dataset, confirming its effectiveness and generalization capability. Full article

Urban shrinkage has become a critical constraint on China’s pursuit of high-quality economic development. As a core driver of new-quality productive forces, digital technological innovation warrants systematic examination for its role in mitigating urban shrinkage. Given the current lack of research on multidimensional measures of urban shrinkage and the mechanisms through which digital technologies influence this phenomenon, this study utilizes panel data from 269 prefecture-level and higher cities in China from 2014 to 2022. By employing two-way fixed-effects models, mediation models, and threshold regression models, the study systematically examines the impact, mechanisms, and nonlinear characteristics of digital technology innovation on urban shrinkage. The empirical results demonstrate that digital technological innovation has a significant mitigating effect on urban shrinkage; this conclusion holds even after conducting a series of robustness tests, including replacing the core explanatory variable, accounting for lag effects, using SYS-GMM estimation, and adjusting the sample range. Heterogeneity analysis indicates that the mitigating effect is more pronounced in shrinking cities, peripheral cities, resource-based cities, and cities with lower educational attainment. Mechanism analysis reveals that agricultural-related innovation acts as a mediating channel, whereas rural entrepreneurship exhibits a “partial masking effect” in the relationship between digital technological innovation and urban shrinkage. Moderation analysis further shows that higher levels of ecological environmental resilience amplify the inhibitory effect of digital technological innovation. Finally, threshold regression results identify a significant double-threshold effect, with the mitigating impact of digital technological innovation emerging only after exceeding the first threshold value of 5.690. Based on these findings, this study recommends implementing differentiated digital-technology-driven innovation strategies, with agriculture-related innovation serving as a strategic entry point to stimulate regional innovation and entrepreneurial vitality. At the same time, strengthening ecological resilience should be promoted to support coordinated green and digital transformation. These findings provide empirical evidence for the formulation of differentiated urban digital transformation policies aimed at mitigating urban shrinkage. Full article

Despite its rich cultural heritage, the Yellow River Basin (YRB) faces challenges of ecological fragility and unbalanced development that constrain residents’ welfare improvement. Cultural–tourism integration (CTI)—aimed at creating employment, optimizing industrial structure, and improving public services—is increasingly promoted as a pathway to enhance people’s livelihood and well-being (PLW). Grounded in industrial integration theory and welfare economics, this study examined the impact effects, transmission mechanisms, and spatial spillovers of CTI on PLW. Panel data from 75 prefecture-level cities in the YRB, spanning 2011 to 2023, were utilized, and multi-dimensional indices were constructed for both CTI and PLW. Impact effects, mediating mechanisms, and spatial spillovers were examined through kernel density estimation, a dynamic system generalized-method-of-moments (SYS-GMM) model, mediation analysis, and a spatial Durbin model (SDM). The results showed that CTI and PLW both improved over time and displayed a spatial pattern of “midstream and downstream leading, upstream lagging”. CTI significantly promoted PLW, after controlling for dynamics and endogeneity (SYS-GMM coefficient = 0.130, p < 0.01). Industrial structure upgrading acted as a positive mediator, whereas digital infrastructure exhibited a short-term suppressing (negative mediating) effect, implying a phased mismatch between CTI investment priorities and digital input. Spatial estimates further indicated that CTI generated positive spillovers, improving PLW in neighboring cities, in addition to local gains. These findings suggest that basin-wide coordination and better alignment between CTI projects and digital infrastructure are essential for inclusive and sustainable well-being improvements, supporting regional progress toward the Sustainable Development Goals. Full article

Against the backdrop of China’s digital rural revitalization, this study investigates the impact of information infrastructure construction (IIC) on rural inclusive green growth (RIGG) using panel data from 29 Chinese provinces (2011–2022). The findings demonstrate that IIC significantly promotes RIGG, a conclusion robust to two-way fixed effects, SYS-GMM estimations, and various robustness checks. This positive effect extends to the core dimensions of inclusive growth and green growth. Quantile regression reveals that the marginal effect of IIC is stronger in provinces with initially lower RIGG levels, suggesting its potential to narrow regional development gaps. Heterogeneity analysis further indicates a more pronounced impact in the central region compared to eastern and western regions. Mechanism tests confirm that rural labor mobility (RLM) serves as a critical transmission channel, where IIC fosters RIGG by accelerating labor movement, with this effect exhibiting persistence over time. These findings underscore the importance of regionally tailored IIC strategies to effectively promote sustainable and resilient rural development. Full article

Amid escalating concerns over air pollution and demographic shifts, industrial robots have emerged as a key solution to enhancing energy efficiency, reducing emissions, and fostering economic growth. However, existing research often overlooks their role in shaping green total factor productivity (GTFP), a critical measure of environmentally sustainable economic performance. This study investigates the relationship between industrial robot applications (IRAs) and high-quality economic development (HQED) by integrating theoretical modeling and empirical analysis. Using panel data from 32 countries (16 developed and 16 developing) over the period of 1993–2019, classified according to the 2023 International Monetary Fund (IMF) standards, this study employs fixed-effects models, system generalized method of moments (SYS-GMM), and threshold regression models to assess IRA-induced impacts on HQED. The findings reveal that IRAs significantly contribute to HQED, with a stronger effect observed in developing economies. Moreover, a threshold effect exists, wherein environmental regulations (ERs) mediate the effectiveness of IRAs in improving GTFP. Additionally, IRAs drive HQED through foreign direct investment (FDI) and technological innovation (TI). These results provide empirical evidence and policy insights for leveraging industrial automation to promote sustainable economic growth across different national contexts. Full article

The pharmaceutical industry has been developing rapidly in recent years, and concerns have been widely raised about social responsibility for the safety of people’s lives. This research aims to investigate the impact of CSR on CFP of listed pharmaceutical companies in China. This study was based on the data of pharmaceutical listed companies from 2010 to 2020 as a sample and built regression models for the effects of pharmaceutical corporate social responsibility (CSR) on corporate financial performance (CFP) based on the indirect effects of technological innovation and media coverage. The two-way fixed effect method, the systematic generalized method of moments estimation (SYS-GMM), and the Bootstrap method are adopted for the regression analysis of the model. The research found that (1) CSR positively affected CFP; (2) CSR positively affected technological innovation, while technological innovation partially mediated between CSR and CFP; and (3) both positive and negative media coverage negatively moderated the relationship between CSR and CFP as well as the relationship between CSR and technological innovation. In addition, both positive and negative media coverage negatively moderates the mediation path of “CSR–corporate innovation–CFP”. Full article

Environmental challenges, particularly the emission of greenhouse gases (GHGs), pose significant threats to global sustainability. Sustainability requires achieving economic growth and social progress while minimizing environmental degradation, improving resource efficiency, and ensuring long-term ecological balance. At present, many studies have shown that carbon taxes may negatively impact the economy. However, environmental regulations also drive firms to pursue green technological innovations, thereby promoting progress. Previous studies on the regulatory measure of carbon taxes have often overlooked the potential influence of green technological progress on economic outcomes. To address these gaps, our research selected panel data from 30 provinces in China, spanning from 2005 to 2021, and employed the System Generalized Method of Moments (SYS-GMM) to evaluate the effect of carbon taxes on green total factor productivity (GTFP) and green total factor energy efficiency (GTFEE). The regression results, representing the green technological progress coefficient, are then incorporated into the China Energy-Environment-Economic Analysis 2.0 (CEEEA2.0) model. We also add carbon tax recovery to this model in order to analyze their economic impact from the new perspective of green technological progress. The SYS-GMM findings suggest that carbon taxes positively impact GTFP and GTFEE, with impact coefficients of 7.2% and 3.4%, respectively. The CEEEA2.0 model reveals that, without considering green technological progress, the introduction of carbon taxes negatively impacts the economy. However, this impact may turn into a positive one when green technological progress is considered. Additionally, carbon tax recovery measures help mitigate economic losses or enhance gains. Overall, this study offers a fresh perspective for modeling carbon tax implementation and holds both theoretical and practical significance and provides actionable insights into designing carbon tax policies that balance economic growth, social equity, and environmental sustainability. Full article

This study investigates the relationship between corporate shared institutional equity (SIE) holders and eco-transparency reporting (ETR). Specifically, it examines three distinct types of SIE: (1) common institutional shareholders with industry peers, (2) the average count of unique institutional owners holding shares in both the focal company and its peers, and (3) the total percentage of SIE within the focal company. The findings indicate that firms with higher levels of SIE are more likely to disclose ETR, signaling a commitment to enhancing public trust and aligning with governmental expectations. Furthermore, the study explores the impact of SIE across different stages of the firm’s life cycle, revealing that the influence of SIE on ETR is more pronounced during the growth and mature stages. The results remain robust even when alternative thresholds for SIE are applied, such as adjusting from a 5% to a 3% threshold. To account for potential misspecification and omitted variables, propensity score matching (PSM), System generalized method of moments (Sys GMM) and two-stage least squares (2SLS) methods were employed. This research contributes to the literature by highlighting the role of shared institutional ownership in promoting environmental transparency, offering novel insights into how institutional investors can drive corporate sustainability practices across different firm life cycles. Full article

Environmental sustainability concerns have led to an increased focus on climate finance, resulting in substantial investments to boost financial sector development. However, recently, climate initiatives have encountered multiple policy uncertainties. This study aims to empirically investigate the impact of U.S. climate policy uncertainty (CPU) on Indian financial inclusion, in addition to exploring the moderating role of institutional quality on the aforementioned relationship. To achieve the above objectives, we first constructed two separate indexes for financial inclusion using the weighted method and principal component analysis. Next, to empirically estimate the above relationship, we employed the two-step system-generalized method of moments (Sys-GMM) and the sequential (two-stage) linear panel data model (SELPDM) on the sample data from 2000–2022. The Sys-GMM estimate test validated that climate policy uncertainty negatively influences India’s financial inclusion. However, institutional regulation and governance assist in moderating the negative influence of U.S. climate policy uncertainty on Indian financial inclusion initiatives. Furthermore, the study also confirmed that various dimensions of institutional regulation and governance exert a positive and significant effect on financial inclusion. Finally, the study validates that economic growth and technological advancement assist financial inclusion initiatives in India. The study is an original work and offers several policy recommendations. Full article

Agricultural science and technological innovation (ASTI) provides important opportunities to enhance agricultural welfare. Based on comparative advantage, value chain, and resource dependence theories, this study employed a variety of econometric models, including fixed effects (FEs), panel-corrected standard errors (PCSEs), feasible generalized least squares (FGLSs), and the systematic generalized method of moments (SYS-GMM), to investigate the impacts of ASTI on farmers’ income using data from a panel of 31 Chinese provinces spanning from 2012 to 2021. Our results reveal that ASTI contributes significantly positively to income growth, but its effects are not uniform: the central and western regions benefit more from ASTI compared to the eastern region. Moreover, as the level of ASTI increases, its positive impact on income growth diminishes. However, regions with higher levels of rural human capital—measured by educational attainment and skills—experience a more pronounced amplification of ASTI’s benefits on income. Additionally, aging populations in both urban and rural areas initially enhance the influence of ASTI on farmers’ income, but this effect diminishes as demographic gaps widen. Full article

The Chinese government has adopted a significant low-carbon transition strategy aimed at enhancing resource efficiency, advancing ecological conservation, and augmenting societal well-being. This research employs the super efficiency SBM model to evaluate the ecological well-being performance (EWP) within the Huaihe River Ecological Economic Belt. Subsequently, it employs the Sys-GMM model and conducts a threshold effect analysis to regressively examine the impact of the low-carbon transition on EWP. The key findings are as follows. The EWP in the Huaihe River Ecological Economic Belt is relatively low; cities with higher economic development levels tend to exhibit lower EWP scores. The impact of the low-carbon transition on EWP is contingent upon the level of regional economic development and exhibits a singular threshold effect predicated on the economic development level as the threshold variable. Specifically, when economic development is at a low level, an intensification of the low-carbon transition results in a decline in EWP within the Huaihe River Ecological Economic Belt. Conversely, when the economic development level surpasses the threshold, the low-carbon transition facilitates the enhancement of EWP. This study’s principal contribution lies in elucidating the intricate relationship between the low-carbon transition and sustainable development. Full article

The challenge of balancing economic and social benefits has emerged as a critical issue for corporate sustainable development. Environmental, social, and governance (ESG) criteria are key considerations for enterprises aiming to enhance both social and economic benefits simultaneously. Based on the upper echelons theory, differences in cognitive foundations and values brought about by top management team heterogeneity can influence corporate decisions. Taking A-share listed companies in China from 2011 to 2022 as samples, we construct a two-way fixed-effects model by firm and year to explore the impact of top management team heterogeneity on corporate ESG performance, and we introduce top management incentives as a moderating variable to further analyze the underlying mechanisms. Our results demonstrate that the gender heterogeneity, functional background heterogeneity, and overseas background heterogeneity of top management teams have significant positive impacts on corporate ESG performance, and monetary compensation incentives and control incentives to top management teams play a positive moderating role, while equity incentives exhibits a negative moderating effect. These findings remain robust across alternative measures of corporate ESG ratings and monetary and control incentives, and through the SYS-GMM model test and instrumental variable approach to address endogeneity. This research contributes to the literature on corporate ESG by validating and extending the understanding of how top management team characteristics affect organizational outcomes, and it provides practical guidance for enhancing corporate ESG practices. The implications of this study suggest that to enhance corporate ESG performance, enterprises should prioritize the promotion of top management team heterogeneity and tailor their incentive mechanisms accordingly. Full article

Urbanization affects economic production activities and energy demand, as well as lifestyle and consumption behavior, affecting carbon dioxide emissions. This study constructs the System Generalized Method of Moments (Sys-GMM) model of the impact of urbanization rate on carbon dioxide emissions based on panel data of 136 countries and regions in the world from 1990 to 2020, grounded on the extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model. This study found that (1) there is a negative relationship between urbanization rate and CO₂ emissions from 1990 to 2020. (2) The impact of the urbanization rate on CO₂ emissions is heterogeneous. An increase in urbanization rate in non-OECD countries significantly reduces CO₂ emissions, while the effect is not significant in OECD countries. (3) The carbon intensity of fossil energy consumption moderates the relationship between urbanization rate and CO₂ emissions, weakening the effect of urbanization rate on CO₂ emissions. Based on these findings, policy recommendations such as promoting urbanization and increasing the regulation and control of fossil energy carbon intensity are proposed. Full article

To explore the connotation and development level of China’s new quality productivity, this paper constructs an index system based on innovation, greenness, and productivity. This system is used to describe the development level of China’s new quality productivity. Using relevant data from 30 provincial administrative regions in China from 2011 to 2021, the entropy weight-TOPSIS method was employed to measure the index system. The development level of new quality productivity in China and its four major economic regions was analyzed through the three dimensions of the index system. Additionally, this paper examines the impact of new quality productivity on China’s industrial restructuring and integrates environmental regulation to elucidate the interaction mechanisms among these factors. An econometric regression model is further constructed to verify the effect of new quality productivity on industrial structural change and to examine the moderating role of environmental regulation. The results of this study show that there is a regional imbalance in the level of development of new quality production in China, with the level of development of new quality productivity in the eastern region being significantly higher than that in the central, western, and northeastern regions. However, on the whole, the new quality productivity of the four major regions has been in a state of continuous improvement during the period under investigation, and the spatial gap has been constantly decreasing. The benchmark regression coefficients, sys-GMM regression coefficients, and diff-GMM regression coefficients for new quality productivity and industrial rationalization are −0.6228, −0.1121, and −0.0439, respectively, and they are negatively correlated. The regression coefficients of the sys-GMM and diff-GMM of the interaction terms of environmental regulation and new quality productivity are −0.0051 and −0.0045, and there is a negative moderating effect of environmental regulation between new quality productivity and industrial structure rationalization. The benchmark regression coefficient, the sys-GMM regression coefficient, and the diff-GMM regression coefficient of new quality productivity and industrial upgrading are 2.5179, 0.7525, and 0.3572, respectively, and there is a positive correlation between the two. The regression coefficients of sys-GMM and diff-GMM for the interaction terms of environmental regulation and new quality productivity are 0.0380 and −0.0167, and there is a positive moderating effect of environmental regulation between new quality productivity and industrial structure upgrading. Full article

Advancing the construction and application of new quality productive forces is an essential prerequisite for achieving high-quality agricultural development and expediting the establishment of agricultural powerhouses. This study aims to elucidate the internal mechanisms through which new quality productivity contributes to high-quality agricultural development and to explore practical pathways for enhancing agricultural quality through its promotion. Utilizing panel data spanning 2012 to 2021 from 30 provinces and municipalities in mainland China, the entropy method is employed to gauge levels of new quality productivity and high-quality agricultural development. Additionally, employing research methodologies including SYS-GMM and threshold effect models, this study empirically investigates how the advancement of new quality productivity influences high-quality agricultural development. Our research reveals the following key findings: (1) The development of new quality productive forces significantly enhances high-quality agricultural development, exhibiting a heterogeneous distribution pattern favoring the “eastern region > western region > central region” and “northern region > southern region”. (2) New quality productive forces can bolster the level of high-quality agricultural development by fostering innovation, coordination, openness, and shared development within its subsystems. However, they may impede progress by inhibiting improvements in green development within the subsystems. (3) The results of the threshold effect test demonstrate that the promotion effect of the development of new quality productive forces on high-quality agricultural development escalates with the level of high-quality agricultural development. Specifically, as the level of high-quality agricultural development exceeds the first threshold value of 0.1502, the promotion effect becomes significant; crossing the second threshold value of 0.2010 further amplifies this effect. This paper’s primary marginal contribution involves empirically analyzing the potential nonlinear effects of advancing new quality productivity in enhancing the level of high-quality agricultural development. This enriches empirical research on how new quality productivity fosters the development of high-quality agriculture. Full article