Search Results (336)

This paper investigates the relationship between environmental information disclosure (EID) quality and green technology innovation (GTI) using panel data from Chinese A-share listed companies over 2008–2024. EID quality is measured by a 27-indicator index, and GTI by the number of granted green patents. Based on 39,075 firm-year observations with firm and year fixed effects and firm-level clustered standard errors, the results show that EID quality is significantly and positively associated with GTI, and this association remains robust to a series of checks, including the exclusion of municipalities, a one-period lagged explanatory variable, propensity score matching, and entropy balancing, among other approaches. The mechanism analysis provides evidence consistent with two channels: EID quality is positively associated with Environmental, Social and Governance (ESG) performance and analyst coverage, each of which is positively associated with GTI. The EID–GTI association is also stronger under stronger board environmental expertise, audit quality, government subsidies, and market competition, and in firms with higher managerial myopia. Heterogeneity analysis shows that the positive association is stronger in state-owned enterprises and weaker in heavy-polluting industries and in regions with higher marketization. The study offers updated micro-level evidence on the role of EID quality in corporate green transformation, with implications for regulators and practitioners. Full article

As interactions between digital and physical technologies intensify, understanding their implications for corporate green innovation has become increasingly important. Using panel data on Chinese A-share listed firms from 2008 to 2024, this study investigates the relationship between digital–physical technological integration and both the quantity and quality of green innovation while considering potential endogeneity concerns. The empirical evidence shows that firms with a higher degree of digital–physical technological integration tend to generate more green innovation outputs and achieve higher green innovation quality. Additional analyses show that digital–physical technological integration is positively associated with knowledge depth, knowledge breadth, receipt of general government support, and environmental information disclosure quality, providing evidence consistent with the proposed knowledge, resource, and information explanations. Heterogeneity analysis reveals that the relationship is more pronounced for digital product manufacturing and digital technology applications, and among larger, more mature, and less financially constrained firms. At the regional level, the relationship is stronger in regions with more advanced digital infrastructure, stronger intellectual property protection, and a more favourable business environment. This study advances current understanding of the relationship between digitalisation and green innovation and offers implications for designing differentiated innovation policies across firms and regions. Full article

Environmental sustainability has become an increasingly critical issue in the inland shipping sector. The adoption of green-fuelled vessels, data-driven speed optimization enabled by digital and intelligent technologies, and the use of shore power during berthing can substantially reduce harmful emissions from shipping activities and enhance environmental performance. This study investigates the evolutionary stable strategy (ESS) of inland shipowners’ green initiatives under government subsidy schemes. Firstly, a decision-making framework is developed by incorporating price elasticity, market competition, green investment, and subsidy intensity, through which pricing, subsidies, demand, and profit decisions are jointly modeled. Secondly, a game-theoretic model involving two market participants under three alternative strategies is constructed, together with an effective solution approach. Thirdly, based on evolutionary game theory, the equilibrium strategies ultimately adopted by the majority of inland shipowners are derived, and sensitivity analyses of key parameters are conducted. The results indicate that: (1) shipowners implementing green strategies can achieve higher economic returns, and green strategies are expected to be adopted by approximately 71.55% of inland shipowners in the long-term; (2) governments should increase subsidy intensity in the early stage of green strategy development, while gradually reducing subsidies once the market reaches a stable equilibrium. The findings provide theoretical insights for inland shipowners’ strategic decisions in environmentally conscious markets and offer policy implications for governments seeking to design stable and effective subsidy mechanisms to promote the green transition of inland shipping services. Full article

With the acceleration of port electrification, the recycling of retired batteries has become an emerging challenge for green port development and sustainable maritime logistics. Digitalized recycling technologies can improve battery traceability, condition assessment, and recycling coordination, but their implementation requires substantial investment. This study investigates how government subsidy mechanisms influence digitalized retired battery recycling decisions in green ports. A digitalized reverse supply chain consisting of a battery manufacturer, a retailer, and green ports as end users is considered. Based on a two-stage Stackelberg game framework, two policy scenarios are developed and compared: a no-government-subsidy (NG) scenario and a government-subsidy (TG) scenario. The analytical results demonstrate that government subsidies can promote digital technology adoption, enhance recycling demand, and improve supply chain profitability when green ports have strong preferences for digitalized recycling services and when digital investment costs remain within a reasonable range. The numerical simulations further indicate that the effectiveness of subsidies depends on the interaction between green port preference and the manufacturer’s digital investment cost coefficient. The findings provide theoretical and managerial implications by revealing how government subsidies, green port digital preferences, and digital investment costs jointly influence recycling decisions and supply chain performance. Specifically, the results suggest that governments should design differentiated subsidy mechanisms according to digital technology maturity and market conditions, manufacturers should optimize digital investment strategies in reverse supply chains, and green ports should strengthen digital traceability and coordination capabilities to improve retired battery recycling efficiency. Full article

As the global sustainability agenda and carbon neutrality goals continue to advance, climate policy has become an important governance instrument for promoting firms’ green and low-carbon transformation. Adjustments in policy timing, regulatory intensity, and enforcement arrangements may create uncertainty for firms’ long-term technological investment and their capacity to sustain this transformation. Accordingly, this study focuses on corporate innovation resilience and examines firms’ ability to maintain, adjust, and recover innovation activities amid climate policy fluctuations. Using Shanghai and Shenzhen A-share-listed firms from 2010 to 2023, this study matches firm-level data with prefecture-level climate policy uncertainty indicators based on firms’ registered locations and empirically examines the impact of climate policy uncertainty on corporate innovation resilience. The results show that climate policy uncertainty is positively associated with corporate innovation resilience. This finding remains robust after changing fixed-effect specifications, adjusting the clustering level of standard errors, excluding special-year observations, and conducting instrumental variable, entropy balancing, and placebo tests. Mechanism tests provide evidence consistent with the channels of corporate sustainable transformation, external attention pressure, and managerial sustainable governance capability. Heterogeneity analysis further shows that this positive association is more pronounced in regions with stronger environmental regulation and among firms receiving higher government environmental subsidies. At the industry level, the effect is mainly observed among heavy-polluting firms and non-high-tech firms. These results indicate that the association is stronger where sustainable transition pressure or policy support is greater. This study extends the firm-level consequences of climate policy uncertainty from innovation quantity and green innovation to the adaptive capacity of corporate innovation systems and provides evidence on how firms sustain innovation while long-term low-carbon transition goals are implemented under fluctuating climate policies. Full article

New energy vehicles constitute a crucial component of low-carbon economic systems and green development initiatives. Supported by government subsidy policies, the new energy vehicle industry has achieved remarkable development in recent years. This study conducts an empirical analysis based on panel data of 93 listed new energy vehicle enterprises from 2012 to 2022 to explore the impacts of government subsidies on corporate R&D investment. Using Stata 17.0, we use return on assets, debt-to-asset ratio, enterprise size and operating efficiency as control variables. A two-way fixed-effect model is selected via the Hausman test, followed by linear regression analysis. Furthermore, a dynamic panel vector autoregression (PVAR) model is employed to examine the dynamic interaction between government subsidies and corporate R&D investment. This research perspective overcomes the limitations of traditional static innovation policy research, effectively supplements the empirical evidence on long-term policy incentive effects in the new energy vehicle industry, and enriches the theoretical and empirical literature on the intrinsic dynamic correlation between government subsidies and corporate innovation investment. The empirical results show that government subsidies exert a significantly positive effect on firms’ R&D investment, and that there exists a stable long-term two-way positive interaction and dynamic equilibrium between the two. However, such mutual promotion effects are economically weak in magnitude, and the long-term evolutionary trends of both variables are predominantly dominated by their respective internal self-reinforcing inertia. In view of the limited incentive contributions of existing subsidy policies, the results of this study suggest the need to optimize the precision and targeting of government subsidy mechanisms to amplify policy incentive efficiency, while enterprises should fully leverage their endogenous R&D inertia to strengthen their independent innovation capabilities. The presented findings provide empirical evidence and policy guidance for the promotion of stable R&D innovation and high-quality development of the new energy vehicle industry. Full article

Green collaborative innovation is a complex socio-technical system involving interactions among governments, universities, enterprises, and financial institutions. However, existing studies often examine these actors separately or focus on bilateral relationships, limiting the understanding of how multi-agent strategies jointly evolve toward sustainable innovation. This study develops a four-player evolutionary game model incorporating regional governments, universities, local enterprises, and green financial institutions to investigate the dynamic evolution of green collaborative innovation under bounded rationality. The model integrates fiscal incentives, technology commercialization returns, financial constraints, reputation effects, and social advocacy mechanisms to explore the conditions under which collaborative strategies emerge and stabilize. Theoretical analysis identifies the evolutionary conditions of different strategic combinations, while numerical simulations examine how key factors influence the evolution process. The results reveal that enterprise deep green transformation plays a central role in shaping the evolution of the entire collaborative innovation system. Government subsidies and financial constraints jointly influence enterprises’ transformation decisions, while technology commercialization returns and research support determine universities’ incentives for green R&D. Green financial institutions contribute not only through capital provision, but also through environmental risk assessment and market-based governance. In addition, social advocacy indirectly affects the evolutionary process by influencing reputation-related incentives and strengthening institutional accountability. This study contributes to green innovation and systems science research by providing a multi-agent evolutionary framework that explains the interactions among policy, technology, finance, and institutional factors. The findings suggest that effective green collaborative innovation requires coordinated governance mechanisms that integrate fiscal support, financial regulation, technology transfer, and social supervision. Full article

Environmental issues such as climate change and cumulative emissions have intensified debate on the effectiveness of public environmental protection expenditure. Traditional Pigouvian taxes and subsidies mainly target instantaneous flow externalities. However, it is difficult to resolve dynamic stock externalities that accumulate over many years, such as climate change and cumulative greenhouse gas emissions, through taxation policies alone. This situation requires the government to make direct environmental protection expenditure to support the ecosystem’s natural assimilation capacity and reduce the rate at which pollution accumulates. This study specifically examines the relationship between stock externalities and environmental protection expenditure within the context of the Turkish economy, which is highly industrialised and under pressure to comply with international environmental commitments such as the European Green Deal and the Paris Climate Agreement. In the study’s empirical analysis phase, long-term relationships between macroeconomic variables and pollution stocks were tested using Fourier cointegration methods and econometric time series analyses. The analysis revealed a long-term co-movement (cointegration) relationship between the series, indicating that public environmental protection expenditures and industrial emissions move in the same direction over the long term. FMOLS and DOLS estimates indicate that environmental protection expenditures are positively associated with industrial emissions in the long run (FMOLS coefficient = 2.1125; DOLS coefficient = 2.0375), whereas renewable energy consumption exerts a negative effect on emissions (FMOLS coefficient = −1.4391; DOLS coefficient = −1.4967). These results suggest that environmental protection expenditure in Türkiye is not independent of current production and industrialisation dynamics, and that its emission-reducing effects are influenced by technological transformation processes. Full article

As digital technologies continue to evolve, intelligent manufacturing technology represented by industrial robots has been increasingly integrated into various stages of enterprise production and operational activities. This trend has created new opportunities for enterprises to advance green transformation and enhance the level of sustainable green innovation. Based on data from Chinese A-share listed firms, this study empirically examines the effect of industrial robot application on sustainable green innovation of enterprises. The study finds that industrial robot application significantly enhances sustainable green innovation of enterprises. The underlying mechanisms mainly operate through the optimization of human capital structure and government-specific subsidies. Meanwhile, industrial robot application exhibits significant peer spillover effect, which can generate demonstration and pressure transmission effects among enterprises within the same industry and region, thereby promoting the coordinated improvement of sustainable green innovation. Heterogeneity analysis further reveals that the promoting effect of industrial robot application on sustainable green innovation is more pronounced in non-state-owned enterprises, labor-intensive enterprises, enterprises whose executives have an environmental background, and enterprises in regions with stricter environmental regulation. Furthermore, the establishment of regional environmental courts can strengthen the positive effect of industrial robot application on sustainable green innovation of enterprises. The results of the extended analysis further demonstrate that the contribution of industrial robot application to sustainable green innovation mainly stems from its ‘’leverage effect’’ on overall corporate innovation activities, rather than from the ‘’crowding-out effect’’ caused by compressing other technological innovation activities. This study not only enriches the literature on the environmental effects of industrial robot application but also provides new insights into how enterprises can leverage intelligent technologies such as industrial robots to achieve green transformation. Full article

Green innovation performance (GIP) in new energy enterprises emerges from complex interactions among technological, organizational, and institutional resource subsystems, yet existing research predominantly applies linear, single-factor approaches that fail to capture this systemic complexity. Drawing on the Resource-Based View (RBV) and systems thinking, this study employs fuzzy-set qualitative comparative analysis (fsQCA) on a sample of 54 Chinese A-share listed new energy enterprises—spanning wind power, solar power, hydrogen energy, energy storage, and new energy equipment manufacturing—observed over the 2019–2023 period, to examine the configurational pathways through which these firms achieve high GIP. Green patent grants serve as the outcome measure, and six conditions spanning three resource subsystems are considered: digital transformation and R&D intensity (technological subsystem), firm size and ownership structure (organizational subsystem), and government subsidies and carbon emission performance (institutional subsystem). Three key findings emerge. First, none of the six conditions is individually necessary for high GIP (all consistency scores below 0.90), indicating that high GIP reflects combinations of resources rather than a single driver. Second, the six sufficient configurations identified collapse into two distinct pathway clusters: a “SOE digital-empowerment-driven” cluster, in which digital transformation combines with R&D investment, government subsidies, or organizational scale within state-owned enterprises, and a “resource–capability synergy and substitution” cluster, in which scale resources, R&D investment, and policy support combine with or substitute for digital transformation regardless of ownership. Third, digital transformation appears in five of the six pathways, indicating that it functions as a key—but not universal—enabling element whose effectiveness depends on its alignment with other system components. Beyond confirming that multiple, equally valid resource combinations lead to high GIP, this study’s principal contribution is to embed RBV within an explicit systems framework, showing how technological, organizational, and institutional resources interact as subsystems of a single socio-technical system, and to translate the resulting configurations into differentiated, pathway-specific guidance for enterprises and policymakers navigating the low-carbon energy transition. Full article

Understanding when coordinated cooperation emerges in multi-agent systems, and when it fails, is a central question in the study of complex socio-economic dynamics. This paper develops a tripartite evolutionary game among three boundedly rational populations—local governments, agribusinesses, and smallholder farmers—and applies it to the diffusion of green agricultural technology, using conservation tillage in Northeast China’s black soil region as a concrete setting. The model incorporates a performance-based subsidy that is disbursed only upon realized adoption, thereby foreclosing subsidy capture. We derive the replicator dynamics, analyze the asymptotic stability of all eight pure-strategy equilibria, and, for the regime in which the system fails to converge, construct a first integral analytically and verify its conservation numerically to machine precision. Four findings emerge. First, the intuitively ideal fully coordinated state is dynamically unstable; the stable desirable outcome is one in which the government withdraws while the market sustains adoption. Second, under low initial willingness the system does not converge to any evolutionarily stable strategy but enters a sustained, conservative (center-type) oscillation—a policy-reversal trap that transient interventions cannot extinguish, placing the dynamics within the class of Hamiltonian-like evolutionary systems. Third, a sharp critical threshold in initial willingness partitions the state space into distinct basins of attraction, rendering policy effectiveness state-dependent. Fourth, within the modeled trap, credible penalties and enhanced agribusiness service capacity can engineer escape, whereas untargeted farmer subsidies are markedly less effective and may even deepen the oscillation. These results recommend treating public intervention as a transitional, regime-aware catalyst with a built-in exit. Beyond the agricultural setting, the analysis illustrates how conservative oscillations and multiple basins shape the controllability of multi-agent cooperation systems. Full article

Achieving the Sustainable Development Goals (SDGs) requires countries to simultaneously advance renewable energy transitions, environmental innovation, carbon efficiency, and sustainable governance mechanisms. Although previous research has extensively examined sustainability transitions and environmental sustainability, comparative assessments integrating renewable energy, environmental innovation, carbon efficiency, fiscal instruments, and fossil fuel dependency remain limited. Using 2023 data from 31 OECD countries, the study analyzes eight sustainability-related indicators through an integrated CRITIC-ARAS multi-criteria decision-making framework. The CRITIC method is employed to determine objective criterion weights, while the ARAS method evaluates countries’ performance relative to an ideal sustainability profile. The findings reveal considerable differences in sustainability performance across OECD countries. CO₂ emissions from air transport per capita emerge as the most influential criterion within the weighting structure. According to the results, Slovenia, Iceland, and Norway demonstrate the strongest transition performance. Countries with higher renewable electricity generation, stronger environmental innovation support, lower transport-related emissions, and lower fossil fuel dependency generally achieve better outcomes. Sensitivity analysis supports the overall stability of the ranking structure under alternative weighting scenarios, although the exclusion of the highest-weighted criterion produces noticeable ranking shifts for some countries. The results indicate that sustainability performance depends not only on environmental outcomes but also on countries’ ability to coordinate renewable energy policies, environmental innovation, fiscal instruments, and decarbonization strategies. From a policy perspective, the findings emphasize the importance of renewable energy expansion, environmental taxation, transport decarbonization, environmental R&D support, and fossil fuel subsidy reform for strengthening long-term sustainable development strategies. This study contributes to the sustainability assessment literature by providing a comparative and policy-oriented framework for benchmarking sustainability-oriented green transition performance across countries through integrated environmental, energy-related, and innovation-based indicators. Full article

Amid the ongoing global green transformation and the deepening implementation of the “dual carbon” goals, the sustained enhancement of firms’ green innovation capabilities is crucial for driving high-quality development. This study utilizes panel data from A-share listed companies spanning the period from 2013 to 2023, and conducts an empirical analysis to examine how ESG performance influences firms’ sustained green innovation and its underlying effects and mechanisms. The results reveal that ESG performance exert a statistically significant positive effect on firms’ sustained green innovation. This finding remains robust across a range of robustness checks, including Heckman’s two-step method, propensity score matching (PSM), alternative ESG measures, models incorporating lagged variables, and other checks. The mechanism analysis reveals that ESG performance improves firms’ capacity to maintain green innovation and continuously accumulate its outcomes by alleviating financing constraints and reducing operational risks. Government subsidies and digitalization positively moderate the effect of ESG performance on firms’ sustained green innovation. Furthermore, the heterogeneity analysis demonstrates that the promoting effect of ESG performance on sustained green innovation is more pronounced among non-heavy-polluting firms, large-scale firms, and state-owned firms. The findings of this study provide a theoretical foundation for firms to effectively integrate ESG resources and further enhance sustained green innovation, and they also offer valuable insights into how firms can build a sustainable innovation ecosystem. Full article

The open sharing of data as a factor of production is an important institutional mechanism for promoting sustainable innovation in the digital economy. Using Chinese A-share listed firms as the research sample and exploiting the staggered rollout of government open data (GOD) platforms across prefecture-level cities as a quasi-natural experiment, this paper constructs a staggered difference-in-differences (DID) model to examine the effect of GOD on green collaborative innovation (GCI) and its underlying mechanisms. The results show that GOD significantly promotes GCI, indicating that open government data can help firms strengthen collaboration in green innovation and contribute to more sustainable development. Mechanism analysis shows that GOD promotes GCI through four channels: increasing government subsidies, reducing information asymmetry, raising public environmental awareness, and advancing corporate digital transformation. Heterogeneity analysis reveals that the innovation-promoting effect of GOD is more pronounced in large cities, non-resource-based cities, and southern cities, and is more salient among state-owned enterprises, capital-intensive firms, and mature firms. This paper provides empirical evidence on the microeconomic effects of market-oriented data allocation and highlights the role of GOD in supporting GCI, corporate sustainable transformation, and the sustainable development of the digital economy. Full article

Industrial prosperity provides an important foundation for rural revitalization. Rural industrial development should increase economic benefits while protecting the environment and improving farmers’ livelihoods. Rural industrial green transformation involves financial institutions, rural enterprises, local governments, and farmers. The roles of these stakeholders change across different stages of rural industrial development. This study analyzes stakeholder behavior across different stages of rural industrial development and constructs a four-party evolutionary game model to examine the evolutionarily stable strategies of the system. The results show that environmental regulation, green financial support, the relative profitability of green production, and farmer participation jointly shape rural industrial green transformation. Stronger initial environmental regulation can accelerate coordination, but regulation alone cannot ensure stable green transformation. Environmental penalties primarily affect enterprise production decisions. Under the baseline parameter setting, the approximate lower-bound threshold is $F^{\ast }\approx 1.60$. Green production also requires a minimum profitability advantage. Under the same baseline setting, the approximate threshold is $\Delta H^{\ast }\approx 0.20$. Subsidy policies mainly accelerate strategic adjustment, but their additional effects weaken as support increases. Based on these findings, this paper proposes maintaining effective regulatory deterrence, improving the profitability of green production, optimizing subsidy design, and strengthening benefit-sharing and risk-sharing mechanisms. Full article