Venture capital is characterized by high risk, high returns, and a focus on innovative sectors.These attributes are closely aligned with the essence of new quality productivity, making the relationship between the two worthy of exploration.This paper empirically examines the impact and mechanisms of venture capital on enterprises' new quality productivity using data on venture capital activities from 2011 to 2023 and listed companies on the SME board, growth enterprise market, and STAR Market.The findings reveal that venture capital significantly enhances enterprises' new quality productivity.The mechanism analysis indicates that venture capital promotes the improvement of enterprises' new quality productivity by promoting breakthrough innovation in enterprises, alleviating enterprises' financing constraints and enhancing their risk-taking capabilities.Further analysis indicates that the positive effect of venture capital on new quality productivity is more pronounced for enterprises facing greater financing constraints.Additionally, non-state-owned enterprises, high-tech firms, technology-intensive industries, and enterprises in eastern regions exhibit stronger effects of venture capital in boosting new quality productivity.The conclusions of this study provide empirical evidence and policy references for China's strategic decisions to leverage venture capital in empowering technological innovation and advancing new quality productivity.
Driven by the dual forces of global green transformation and digitalization, digital-green synergy in the supply chain has become a critical driver for specialized and sophisticated SMEs to achieve high-level green innovation.From the perspective of both vertical and horizontal synergy, this study takes A-share listed specialized and sophisticated enterprises in Shanghai and Shenzhen as the research sample and employs the fsQCA method to explore the configurational pathways through which digital-green synergy in the supply chain fosters green innovation in these firms.The findings reveal that the interactive alignment among the digitalization and greening levels of specialized and sophisticated enterprises themselves, their suppliers, and their customers gives rise to multiple, equifinal, and asymmetrical causal pathways toward green innovation.Specifically, the study identifies four distinct pathways to achieving high-level green innovation: the"internally driven"pathway, the"supplier-led unidirectional synergy"pathway, the"customer-led unidirectional synergy"pathway, and the"fully bidirectional supply chain synergy"pathway.These findings suggest that different types of specialized and sophisticated SMEs can achieve green innovation goals through differentiated synergy strategies.Digital-green synergy in the supply chain fully leverages the systemic interaction of all elements within the supply chain, providing both theoretical insight and practical guidance for enhancing the green innovation capacity and sustainable development of specialized and sophisticated SMEs.
Against the backdrop of deepening reforms and accelerating the cultivation of new quality productivity, enhancing the resilience of industrial and supply chains has become a critical pathway to achieving high-quality economic development.This study employs balanced panel data from 285 prefecture-level cities in China from 2009 to 2023 to empirically examine the spatial spillover effects of new quality productivity on regional industrial and supply chain resilience, as well as the underlying mechanisms.The findings reveal that improvements in new quality productivity significantly enhance resilience and exhibit notable spatial spillovers, primarily through the alleviation of regional labor and capital misallocation.Heterogeneity analysis further indicates that non-resource-based, non-transport hub, and small to medium-sized cities benefit more prominently.These results offer important policy implications for place-based reform strategies, optimized resource allocation, and the cultivation of new growth drivers, thereby contributing to regional balanced development and stronger industrial and supply chain resilience.
As a core factor of production in the digital age, data has emerged as a crucial driving force in promoting and empowering the innovative development of the real economy.Grounded in resource scheduling theory, the study selects panel data from China's A-share market for"specialized, refined, distinctive, and innovative"enterprises during the period of 2011 to 2024 as the research sample.This paper empirically investigates the impact and underlying mechanisms through which data elements influe-nce enterprise innovation resilience.The findings indicate that data elements significantly enhance the innovation resilience of"specialized, refined, distinctive, and innovative"enterprises, primarily via four channels: increasing R&D investment, alleviating financing constraints, reducing principal-agent costs, and optimizing human capital structure.Moreover, data elements exhibit a more pronounced positive effect on the innovation resilience of non-high-tech enterprises, large-scale enterprises, and labor-intensive industries.This research offers a theoretical foundation and practical insights for"specialized, refined, distinctive, and innovative"enterprises to foster their innovation resilience by leveraging data elements within the context of digital transformation.
Data element allocation is a strong pillar for deepening the application of low-altitude technology and enriching the application scenarios of low-altitude economy, and has become a strong driving force for high-quality development of low-altitude economy. With 2014-2024 as the starting and ending time of the study and 30 provinces in China as research samples, the benchmark regression model and the intermediary effect test model are used to quantitatively investigate whether data element allocation can effectively promote the high-quality development of low-altitude economy and the role channels of scientific and technological innovation. It is pointed out that data element allocation has a significant positive enabling effect on the high-quality development of low-altitude economy. After endogeneity study and robustness test, this conclusion is confirmed again. The mechanism analysis results show that scientific and technological innovation is an important channel for data element allocation to promote high-quality development of low-altitude economy. The results of heterogeneity analysis show that in the southern region, the region with higher financial development level and the region with higher intellectual property protection intensity, the data element allocation has a stronger promoting effect on the high-quality development of low-altitude economy.
Green innovation is a key factor in promoting the transformation and upgrading of the industrial structure and high-quality economic development. International division of labor and cooperation provides enterprises with access to global innovation resources. This study analyzes the impact mechanism of internationalization breadth on enterprise green innovation, and conducts empirical research on Chinese A-share listed enterprises from 2013 to 2022. Results show that the expansion of enterprises' internationalization breadth significantly enhances the green innovation of parent enterprises through the spillover of green technology from host countries and the alleviation mechanism of financing constraints. The risk preference of executives and the level of enterprise environmental responsibility have a positive moderating effect on this relationship. Heterogeneity analysis reveals that state-owned enterprises, non-heavily polluting enterprises, non-high-tech enterprises, and enterprises located in the eastern and northeastern regions have more significant green innovation effects from the expansion of internationalization breadth; Technology-seeking investments and investments in countries with strong innovation capabilities and strict environmental regulations have more prominent green innovation effects. Expansion analysis shows that internationalization breadth has no significant impact on non-green innovation, verifying its unique role in green innovation; the promotion effect of internationalization scale on green innovation is weaker than that of internationalization breadth, and the impact of internationalization depth on green innovation is not significant, highlighting the unique value of internationalization breadth. This study deepens the theoretical understanding of the relationship between corporate participation in international circulation and green innovation, and provides useful policy insights for enhancing enterprise green innovation capabilities under the new development paradigm.
This study employs the QVAR-DY approach to examine the risk spillover relationship between new energy mineral import prices and green industries in the stock market. Building on this, the TVP-VAR model is used to further explore the underlying mechanisms driving such spillovers. The results show that, from a static perspective, there is significant bidirectional risk spillover between new energy mineral import prices and green industry indices, with stronger spillovers observed under extreme market conditions. In particular, during extreme upward market phases, new energy minerals act as net transmitters of risk, while green industries serve as net receivers. From a dynamic perspective, the intensity and direction of spillovers are highly sensitive to shifts in the economic and financial environment. Following the Russia-Ukraine conflict, new energy minerals (such as cobalt, nickel, copper, and silicon) largely functioned as net risk transmitters, whereas production-oriented green industries became net receivers. The mechanism analysis indicates that spillovers exhibit a sharp initial impulse response, with the shock intensity ranked from highest to lowest as: China's low-carbon transition index, exchange rate fluctuations, and China's economic policy uncertainty. Notably, the effects of policy uncertainty are the shortest in duration. Based on these findings, investors are advised to dynamically adjust their green investment portfolios in response to fluctuations in mineral import prices. Policymakers should strengthen supply chain security mechanisms to stabilize the green economic transition, and regulators should enhance oversight of spot and futures markets and deepen international resource cooperation to jointly mitigate systemic financial risks.
In the context of the information age, is the clustering of the data industry a new breakthrough point for promoting high-quality economic development, and also a new opportunity for improving the ecological environment? We selected panel data from 41 cities in the Yangtze River Delta region from 2006 to 2023 and empirically tested the environmental pollution control effects and mechanisms of digital industry agglomeration using fixed effects model, mediation effect model, moderation effect model, and spatial panel model. Research has found that the agglomeration of digital industries has environmental pollution control effects, and this effect has spatial spillover characteristics; The agglomeration of digital industries can improve the quality of urban environment by enhancing the strength of urban external economic connections and promoting internal economic agglomeration; Local government intervention can strengthen the environmental pollution control effect of digital industry agglomeration; The purification effect of digital industry agglomeration on environmental pollution is more effective in second tier and above cities, cities with undisclosed PITI index, and demonstration cities of "Broadband China". Finally, based on the research findings, relevant policy recommendations are proposed, which are of great significance for achieving the coordinated development of digitalization and greening and promoting sustainable development in China.
Reducing carbon emissions with digital economy is an important embodiment of developing new quality productivity. From the perspective of new quality productivity, the "digital" and "green" elements of economic development are prominent, and it is of great practical significance to explore the impact of digital economy on carbon emissions. In this paper, digital economy and carbon emissions are integrated into the same analytical framework by constructing mathematical models, and spatial Durbin model, threshold space Durbin model and semi-parametric threshold space Durbin model are used to systematically analyze the mechanism and path of the impact of digital economy development on carbon emissions in various provinces in China from 2011 to 2021. The results show that the spatial spillover effect between digital economy and carbon emissions is significant. Local carbon emissions can affect neighboring carbon emissions through the combined effects of geographical location, economic correlation and economic geography. The spatial lag term of digital economy has a threshold effect. When the marketization level exceeds the thres-hold value, the digital economy will promote the growth of carbon emissions in the surrounding areas to a larger extent. Heterogeneity analysis reveals that regardless of whether it is the eastern, central or western regions, the digital economy significantly suppresses local carbon emissions and promotes adjacent carbon emissions. Meanwhile, after marketization exceeds the threshold value, the effect of the digital economy on adjacent carbon emissions varies in different regions. After setting the digital economy as a non-para-metric item, it is found that it has an obvious nonlinear effect on carbon emissions, which is generally inverted "N" type. The research conclusion provides strong support for our country in promoting the development of digital economy and realizing the double carbon goal.
Digital green transformation is the core goal and important focus of improving new quality productivity, and its coo-rdinated development and deep integration provide continuous momentum for economic growth. This paper systematically analyzes the conceptual mechanism of digital green collaborative transformation, creatively distinguishes the transformation and development of the two into four categories: the green transformation of the digital industry itself, the digital transformation of the new energy industry in the traditional industry, the digital green transformation of the traditional energy industry and the digital and green collaborative transformation of the traditional industry in general. Enrich the theoretical connotation of digital green collaborative transformation. The study finds that digital greening focuses on manufacturing, construction, information and communication, transportation and energy industries, promoting the transformation and upgrading of the manufacturing industry, promoting carbon reduction and efficiency of green buildings, accelerating the high-quality development of the information and communication industry and the transportation industry, and the "digital intelligence and dual carbon" industrial ecology has been initially formed. China's digital and green development promotes low-carbon transformation in key areas with breakthroughs in digital technology applications, but it also faces challenges such as unclear synergy mechanism paths, incomplete institutional guarantees, unbalanced synergy degrees, and insufficient support capabilities of various factors. To promote "dual coordination", we should focus on optimizing the allocation of resources in key industries, standardizing low-carbon standards and data use systems, promoting the deepening and deve-lopment of digital transformation in the whole society, and forming new quality productivity aggregation elements in all fields.
Under the background of digital transformation of the global economy, data factor marketization has become an important driving force to increase the technological complexity of enterprises' exports. Based on this, this paper selects the data of Shanghai and Shenzhen A-share listed companies in the manufacturing industry from 2010 to 2023 to explore the impact of data factor marketization on export technology complexity. The results show that data factor marketization has a significant effect on export technology complexity, and this effect is more obvious for large-scale enterprises, enterprises located in cities along the Belt and Road and technology-intensive enterprises. The analysis of the mechanism of action reveals that the digital transformation of enterprises is the channel through which the marketization of data factors enables export technological complexity, and that financial agglomeration plays a positive role in regulating the process of the marketization of data factors enabling export technological complexity. The findings provide empirical evidence and policy insights for accelerating the high-quality development of export trade and promoting high-level opening-up.
As artificial intelligence advances, digital and intelligent (DI) technologies have become deeply integrated into enterprise development, making DI transformation a key strategy for upgrading the real economy. Using data from A-share listed firms in Shanghai and Shenzhen (2013~2024), this study builds a moderated mediation model to examine the relationships among DI technology application, internal control, and information disclosure quality, and explores the moderating role of marketization. Results show that DI technology significantly enhances disclosure quality, especially in state-owned, high-tech, and less concentrated industries. Internal control partially mediates this relationship, while marketization positively moderates the DI-disclosure link, mainly by strengthening the effect of DI technology on internal control. These findings enrich research on the economic consequences of DI technologies and the determinants of disclosure quality, offering practical insights for advancing DI transformation and business model innovation.
In the digital audit reform, how the openness of government public data affects the quality of government audit has attracted much attention. In this paper, the public data open platforms successively launched by various prefecture-level cities in China are used as quasi-natural experimental evidence, and the double difference method is used to explore the influence effect of public data open on the quality of government audit and its internal mechanism.It is found that the openness of public data can significantly improve the quality of government audit, and it also plays a role in improving the efficiency of information search and matching, audit independence and public gathering.Heterogeneity analysis shows that the openness of public data plays a significant role in improving the quality of government audit in areas with high aggregation effect, strong financial capacity and excellent institutional environment.Based on the above research, this study focuses on how open public data can empower the improvement of government audit quality, and provides reference ideas for ensuring the rational use of public resources and enhancing national go-vernance capabilities.
To further analyze the impact of digital technology transformation on the economic benefits of manufacturing enterprises, this paper taking manufacturing enterprises listed on the A-share market from 2014 to 2024 as the research objects, an empirical study is conducted on the impact of digital technology transformation on the economic benefits of manufacturing enterprises.Among them, the economic benefits of manufacturing enterprises are selected as the dependent variable, digital technology transformation as the independent variable, the degree of competition and the intensity of innovation input as the moderating variables, and enterprise scale, enterprise life cycle, shareholders' equity ratio, and return on assets as the control variables.The impact of digi- tal technology transformation on the economic benefits of manufacturing enterprises is verified through regression analysis.The results show that digital technology transformation is positively promoting the improvement of economic benefits for manufacturing enterprises.The degree of competition has an enhancing effect on the improvement of economic benefits of manufacturing enterprises promoted by digital technology transformation.The intensity of innovation input has an enhancing effect on promoting the economic benefits of manufacturing enterprises through digital technology transformation.Based on the empirical results, this paper holds that to further enhance the economic benefits of manufacturing enterprises and fully leverage the role of digital technology transformation, it can be achieved from the following three aspects: promoting digital technology transformation and cultivating digital technology ta-lents; enhance the competitive level of manufacturing enterprises and promote scientific and technological innovation; increase the intensity of innovation investment and rationally expand the scale of enterprise operation.
An in-depth study of the perception of economic policy uncertainty of enterprises is helpful to cope with the ove-rall impact of rising economic policy uncertainty.Based on the theories of information asymmetry and signal transmission, this paper analyzes the impact of venture capital intervention on the perception of uncertainty of enterprises' economic policies.The results show that venture capital intervention can significantly improve the perception of uncertainty in enterprises' economic policies.The financial background of corporate executives plays a moderating role in the improvement of the perception of economic policy uncertainty by venture capital intervention.Mechanism analysis shows that venture capital intervention improves the perception of econo- mic policy uncertainty by reducing the volatility of corporate cash flow and promoting the digital transformation of enterprises.Heterogeneity analysis shows that the improvement effect of venture capital intervention on the perception of economic policy uncertainty is more significant in state-owned enterprises, enterprises in the eastern region, non-labor-intensive enterprises and high-tech enterprises.The research in this paper is helpful to comprehensively understand the impact of venture capital intervention on firms' perception of economic policy uncertainty.
Against the backdrop of the rapid development of the digital economy, data has become a key strategic resource.However, traditional balance sheets struggle to reflect the status of data assets and liabilities, making the construction of a Data Ba- lance Sheet (DBS)of great significance.This study employs methods such as literature research and case analysis to conduct an in- depth exploration of issues related to DBS.Based on the characteristics of data assets-including their non-physical nature-and data liabilities, which arise primarily from compliance requirements, the study designs core elements of DBS, such as the accounting entity, scope, principles for accounting recognition and measurement, and statement structure.It also identifies challenges in the preparation process, including difficulties in legal rights confirmation, lack of valuation standards, and weak technical support, and proposes corresponding solutions.The research findings indicate that DBS can provide support for corporate decision-making and play a crucial role in promoting enterprises' digital transformation and the development of the digital economy.
