Search Results (259)

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

We investigate whether China’s Value-Added Tax (VAT) Credit Refund policy influences firms’ sustainable development capability (SDC), which reflects innovation-driven growth and green development. Exploiting the 2018 implementation of the VAT Credit Refund policy as a quasi-natural experiment, we employ a difference-in-differences (DID) approach and find causal evidence that the policy significantly enhances firms’ SDC. This suggests that fiscal instruments like VAT refunds are valued by firms as drivers of long-term sustainable and high-quality development. Our mediating analyses further reveal that the policy promotes firms’ SDC by strengthening artificial intelligence (AI) capabilities and facilitating intelligent transformation. This mechanism “AI Capability Building—Intelligent Transformation” aligns with the socio-technical systems theory (STST), highlighting the interactive evolution of technological and social subsystems in shaping firm capabilities. The heterogeneity analyses indicate that the positive effect of VAT Credit Refund policy on SDC is more pronounced among small-scale and non-high-tech firms, firms with lower perceived economic policy uncertainty, higher operational diversification, lower reputational capital, and those located in regions with a higher level of marketization. We also find that the policy has persistent long-term effects, with improved SDC associated with enhanced ESG performance and green innovation outcomes. Our findings have important implications for understanding the SDC through the lens of STST and offer policy insights for deepening VAT reform and promoting intelligent and green transformation in China’s enterprises. Full article

Improving green innovation quality is a critical component for speeding green transformation and generating high-quality growth. This study examines the link between the pilot zone for green finance reform and innovations (PZGFRI) policy and the quality of green innovation in Chinese A-share listed firms from 2010 to 2020. This study demonstrates that the PZGFRI may greatly enhance the quality of enterprises’ green innovation. Additionally, by promoting environmental investment and reducing financial barriers, we use the mediating effect model to confirm that the PZGFRI improves the enterprises’ quality of green innovation. Meanwhile, the heterogeneity analysis demonstrates that the PZGFRI is more successful in raising the green innovation quality in state-owned, large-sized, and heavily polluting businesses. Our study’s findings offer a strong theoretical basis for improving the PZGFRI and encouraging businesses to undergo high-quality transformation. Full article

Tropical forests continue to experience high levels of habitat loss and degradation, with wildfires becoming a frequent component of human-modified landscapes. Here we investigate the response of palm species to the conversion of old-growth forests to successional mosaics, including forest patches burned during wildfires. Palms (≥50 cm height) were recorded once in 2023–2024, across four habitat classes: terra firme old-growth stands, regenerating forest stands associated with slash-and-burn agriculture, old-growth stands burned once and twice, and active cassava fields, in the Tapajós-Arapiuns Extractive Reserve, in the eastern Brazilian Amazon. The flammability of palm leaf litter and forest litter were also examined to assess the potential connections between palm proliferation and wildfires. A total of 10 palm species were recorded in this social forest (including slash-and-burn agriculture and resulting successional mosaics), with positive, negative, and neutral responses to land use. Species richness did not differ among forest habitats, but absolute palm abundance was greatest in disturbed habitats. Only Attalea spectabilis Mart. (curuá) exhibited increased relative abundance across disturbed habitats, including active cassava field. Attalea spectabilis accounted for almost 43% of all stems in the old-growth forest, 89% in regenerating forests, 90% in burned forests, and 79% in crop fields. Disturbed habitats supported a five-to-ten-fold increment in curuá leaves as a measure of habitat flammability. Although curuá litter exhibited lower flame temperature and height, its lower carbon and higher volatile content is expected to be more sensitive to fire ignition and promote the spread of wildfires. The conversion of old-growth forests into social forests promotes the establishment of palm-dominated forests, increasing the potential for a forest transition further fueled by wildfires, with effects on forest resilience and social reproduction still to be understood. Full article

For high-growth firms, designing and implementing strategies to ensure the long-term sustainability of business models is a key priority. Although these strategies are carefully planned to achieve specific outcomes, these firms also encounter contextual factors inherent to entrepreneurship, as well as the potential negative consequences of operating as small- and medium-sized enterprises (SMEs). Consequently, they adapt emergent outcomes to secure positive scaling-up processes. A comprehensive analysis of 69 studies from 1978 to 2023 revealed that 34.8% used sales as the main indicator of high-growth outcomes, 18.8% considered employment to be the most important outcome, and 37.7% incorporated both. The assessment period for these studies spanned three to seven consecutive years. A subsequent review of the existing literature yielded 56 potential new outcomes, emphasising the existence of a diverse array of concepts and metrics with which to assess high-growth performance. The study confirmed sales and positive profits arising during the planning process as strategic outcomes. However, it was also demonstrated that geographical expansion and innovation become emergent outcomes in critical situations. The research also identified that external factors, including an adverse public environment, business context difficulties, and a favourable business environment, may influence the effect of the firm’s high growth. Full article

Amid the rapid development of the digital economy, data elements—emerging as a new type of production factor—are gradually becoming a key resource for enhancing corporate efficiency and promoting high-quality development. The marketization of data elements is also steadily progressing and playing an increasingly important role. Based on data from Chinese A-share listed companies spanning 2007 to 2023, this study systematically evaluates the impact of data element marketization on corporate investment efficiency using a Double Machine Learning approach. The findings reveal that data element marketization significantly improves investment efficiency. Mechanism analysis further demonstrates that such improvement is primarily driven by reduced information dispersion, enhanced risk-bearing capacity, and improved operational efficiency. Heterogeneity analysis indicates that these effects are more pronounced for firms in high-tech industries, high growth potential firms, enterprises located in regions with strong digital infrastructure, and firms experiencing overinvestment problems. This study provides empirical evidence on how the marketization of data elements in China enhances economic outcomes, improving corporate investment decisions, which could serve as a reference for other countries undergoing digital transformation. Full article

In the context of the explosive growth of the digital economy, how inter-organizational connectivity affects corporate ambidextrous innovation has emerged as a pressing issue in the current digital economy. Based on the perspectives of the innovation ecosystem and digital coupling, this paper explores the inner mechanism of this issue through structural modeling by using the data of China’s high-tech enterprise alliance cooperation from 2015 to 2022. It is found in the empirical study that the local efficiency and reach rate of the digital innovation ecosystem have an inverted U-shaped relationship with exploratory innovation, and the local efficiency and reach rate of the digital innovation ecosystem have a negative effect on firm exploitative innovation. In addition, the level of firms’ digital transformation mediates the relationship between the local efficiency, reach rate, and ambidextrous innovation. The level of market development plays a moderating role in the relationship between the local efficiency, reach rate, and ambidextrous innovation. The findings provide a theoretical basis for the digital innovation ecosystem to realize the role of a “resource pool” through structural connections, which in turn provides important guidance for the digital transformation and innovation development of high-tech enterprises. Full article

This study investigates the relationship between ESG performance and economic growth in BRICS nations from 2000 to 2020, aiming to understand how ESG practices influence development trajectories. By integrating economic theories with relevant conceptual frameworks, this study provides a comprehensive analysis of ESG dynamics in emerging economies. The purpose of this study is to determine how the economic growth of the BRICS countries between 2000 and 2020 was impacted by ESG performance at the national level. This work contributes to the body of knowledge by offering a fresh macroeconomic examination of the connection between economic growth and ESG performance in the BRICS nations, a topic that is still relatively unexplored in comparison to firm-level research. A significant knowledge gap on how developing economies strike a balance between rapid economic expansion and environmental and social sustainability is filled by the research’s use of a thorough national-level ESG framework. The study employed a dynamic panel auto regressive distributed lag (ARDL) model, utilising a dynamic pooled mean group (PMG) ARDL econometric technique for both short- and long-term estimates. The findings reveal a short-term negative relationship between ESG performance and economic growth in the BRICS countries, which implies that there are high transitional effects involved in sustainable growth solutions. It also highlights the structural and developmental heterogeneity among BRICS countries. Moreover, the study highlights that carbon emissions positively influence short-term economic growth, underscoring the challenge of balancing sustainability with the continued reliance on fossil fuels in these economies. However, the long-term results show that strong ESG practices ultimately positively affect economic growth, reinforcing the importance of investing in sustainable development for achieving high-quality, long-term prosperity. This conclusion emphasises that, while short-term trade-offs may exist, robust ESG frameworks are crucial for fostering enduring economic and environmental well-being. Full article

Climate change and environmental degradation necessitate green innovation (GI) to provide new solutions for sustainable economic growth. As many firms allocate scarce resources to green innovation, researchers, practitioners, and policymakers are keen to understand information disclosure on green innovation, particularly in company financial statements. This study empirically investigates the relationship between GI and conservative financial reporting. Using a dataset of 8945 unique firms, from 2001 to 2024, we discover a negative relationship between GI and conservative financial reporting. We further document that firms with high exposure to climate change exhibit a more pronounced negative relationship between GI and conservative financial reporting. In addition, we find that the presence of regulatory risks and public awareness, particularly after the adoption of the Paris Agreement, weakens the negative association between GI and conservative financial reporting. Our findings shed further light on information disclosure on green innovation, which is crucial for various stakeholders to utilize such information and make relevant decisions. Full article

As digital transformation becomes an increasingly central focus of national and regional policy agendas, parallel efforts are intensifying to stimulate innovation as a critical driver of firm competitiveness and high-quality economic growth. However, regional disparities in innovation capacity persist. This study proposes an integrated framework in which regionally tracked digital economy indicators are leveraged to predict firm-level innovation performance, measured through patent activity, across China. Drawing on a comprehensive dataset covering 13 digital economic indicators from 2013 to 2022, this study spans core, broad, and narrow dimensions of digital development. Spatial dependencies among these indicators are assessed using global and local spatial autocorrelation measures, including Moran’s I and Geary’s C, to provide actionable insights for constructing innovation-conducive environments. To model the predictive relationship between digital metrics and innovation output, this study employs a suite of supervised machine learning techniques—Random Forest, Extreme Learning Machine (ELM), Support Vector Machine (SVM), XGBoost, and stacked ensemble approaches. Our findings demonstrate the potential of digital infrastructure metrics to serve as early indicators of regional innovation capacity, offering a data-driven foundation for targeted policymaking, strategic resource allocation, and the design of adaptive digital innovation ecosystems. Full article

As China enters a high-quality development stage, balancing economic growth and environmental sustainability is essential. Can industrial intelligence reconcile these goals? Using theoretical modeling, this paper integrates production decisions, pollution emissions, and environmental regulations to construct a micro-level analytical framework incorporating technology choice and emission reduction investment. It theoretically explores how robot adoption affects firms’ emission reduction behaviors and empirically tests the model using data from Chinese listed companies (2011–2022). Results indicate that industrial robots significantly reduce firms’ pollution emission intensity through productivity boost, technological progress, and emission reduction effects. Additionally, heterogeneity analyses show that robots have stronger pollution-reducing impacts in heavily polluting industries, state-owned enterprises, and regions with stringent environmental regulations. Therefore, policymakers should encourage robot adoption based on local contexts, formulate differentiated environmental regulations, and implement targeted strategies to maximize robots’ emission reduction potential. Accelerating green and intelligent transformation of enterprises will further align ecological protection with sustainable economic and social development. Full article

In the context of China’s “dual carbon” goals and rising green trade barriers, green transformation is key to improving total factor productivity (TFP) and competitiveness in marine industries. This study uses panel data of Chinese listed marine enterprises (2014–2023) and a multidimensional fixed-effects model to examine how green innovation, export, and R&D investment jointly affect TFP. Results show that (1) green innovation has an inverted “S”-shaped nonlinear effect on TFP, with marginal returns rising, then accelerating, and finally declining; (2) positive synergies exist between green innovation and both exports and R&D, while the export–R&D interaction negatively affects TFP, indicating coordination challenges.; and (3) ownership heterogeneity matters, as state-owned enterprises benefit from stronger institutional support, mitigating negative effects, while private firms are more vulnerable due to weaker green technology mechanisms. This study emphasizes green innovation as a driver for sustainable productivity growth in marine enterprises and suggests policies that improve institutional frameworks, incentives, and resource allocation to support high-quality green innovation. Full article

The main mycotoxin found in apples is patulin (PAT), mostly produced by Penicillium expansum, during the storage of fruits. It is very difficult to control the quality of every fruit that enters the processing line, so there is a high probability that apple juice, applesauce, apple cider, even products intended for babies, contain moldy fruits, with PAT content. This review paper provides detailed information about the extrinsic and intrinsic factors that affect PAT prevalence in apples. Extrinsic factors, such as temperature, air composition in the storage room or packaging material, play a key role in infection with P. expansum and PAT accumulation. Lower temperatures often prevent fungal growth and the production of the mycotoxin, whereas higher or unstable temperatures can promote the buildup of the toxin in infected fruits. Controlled atmosphere storage appears to inhibit the accumulation of PAT in apples. In terms of internal composition, variations in the pH of the fruits and flesh firmness significantly impact fungal growth and PAT production in the fruits. The presence of ethylene, sucrose and polyphenols are some of the decisive chemical components that regulate PAT buildup. Susceptibility of different cultivars is also genetically driven, but the size of the decay area and the toxin-producing capacity of the fungal strain have noteworthy influence as well. Knowledge of these elements helps to understand the mechanisms of PAT production. Full article

Population aging is a critical demographic trend in China, creating both challenges and opportunities for sustainable development. As aging alters the structure of the workforce and capital demand, understanding its effect on productivity is essential to managing demographic transitions in China. This study investigates the causal impact of population aging on labor productivity, with a focus on the mediating role of the capital–labor ratio and heterogeneities across industries, skill levels, and regions. Using data from Chinese listed firms between 2011 and 2018, this paper employs industry- and year-fixed effects regression models to control for unobservable heterogeneity and conducts a formal causal mediation analysis. The analysis reveals that population aging significantly enhances labor productivity. Specifically, a one-percentage-point increase in the old-age dependency ratio is associated with a 1.47% increase in firm-level labor productivity. The capital–labor ratio emerges as a critical mechanism, mediating the relationship between aging and productivity by incentivizing firms to increase capital intensity in response to labor shortages. Approximately 72.4% of the total effect is mediated through changes in capital intensity. The findings highlight notable heterogeneities. Labor-intensive firms and low-skilled worker segments experience stronger productivity gains from aging compared with their capital-intensive and high-skilled counterparts. At the regional level, the productivity effects are most pronounced in first- and second-tier cities, while third-tier cities show negligible impacts, reflecting resource and structural constraints. This study underscores the dual role of population aging as a challenge and an opportunity. Policy recommendations include (1) expanding targeted fiscal support for capital investment and automation in aging-intensive industries; (2) promoting vocational training programs tailored to older workers and digital skills development; and (3) strengthening infrastructure and institutional capacity in third-tier cities to better absorb productivity spillovers from demographic adjustment. By addressing these demographic and productivity linkages, the study contributes to achieving Sustainable Development Goals 8 (Decent Work and Economic Growth), 9 (Industry, Innovation, and Infrastructure), and 10 (Reduced Inequalities), by promoting inclusive productivity growth, enhancing industrial adaptation to demographic change, and reducing regional and skill-based disparities.These findings offer valuable insights for policymakers and businesses navigating the complexities of aging economies. Full article

Family businesses play a vital role in the global economy as an organizational form that has evolved over time. However, Chinese family firms generally suffer from insufficient investment in research and development. Based on panel data of Chinese listed family firms from 2008 to 2022, this study investigates the impact of government green subsidies on family firms’ green innovation, along with the heterogeneity of such effects under different scenarios. The results show that government green subsidies significantly promote both strategic and substantive green innovation. The moderating effect analysis reveals that economic policy uncertainty weakens the baseline effect. Further analysis confirms that the positive impact of green subsidies is achieved by alleviating firms’ R&D funding constraints. Heterogeneity analysis indicates that green subsidies have a stronger effect on non-heavily polluting firms; they promote substantive green innovation more effectively in firms with low managerial green cognition, and strategic green innovation in those with high cognition. Additionally, the effects vary across the firm life cycle: green subsidies enhance strategic green innovation during the growth and maturity stages, and substantive green innovation during the growth and decline stages. This study reveals the mechanisms through which government green subsidies affect green innovation in family firms and offers policy implications for promoting sustainable development in the family business sector. Full article