Search Results (3,342)

Based on microdata from A-share listed companies from 2016 to 2025, this study uses corporate digital governance capabilities as a threshold variable and combines an intermediary effects model with a threshold regression model to empirically examine the nonlinear impact of proprietary AI computing power investment on corporate green sustainable development performance, as well as its underlying transmission mechanisms and moderating boundaries. The study finds that there is a significant “N”-shaped nonlinear relationship between investment in proprietary AI computing power and corporate green sustainable development performance. This relationship primarily facilitates green empowerment by optimizing firms’ green pure technical efficiency, while having no significant effect on scale efficiency; green innovation plays a significant mediating role in this relationship, and investment in proprietary AI computing power can indirectly empower the improvement and upgrading of corporate green sustainable development by driving the iteration of green innovation. Digital governance capabilities exert a significant dual-threshold moderating effect on the green empowerment process of AI computing power; the green empowerment effects of computing power exhibit differentiated characteristics across different digital governance ranges, and a moderate level of digital governance can maximize the green development dividends of AI computing power. The study’s conclusions provide empirical support and decision-making references for enterprises to scientifically allocate AI computing power resources, establish appropriate digital governance systems, and advance the synergistic transformation of digitalization and green development. Full article

China’s “Dual Carbon” goals impose rigid constraints on high-emission industries, yet why similarly endowed large mining groups exhibit divergent green and low-carbon performance remains poorly understood. The existing literature predominantly relies on single-factor net-effect analyses, failing to capture the configurational complexity and causal asymmetry underlying transformation outcomes. To address this gap, we extend the Technology–Organization–Environment (TOE) framework by integrating a green practice dimension, constructing a TOE-P configurational model. Using balanced panel data of A-share listed mining companies from 2015 to 2025, we combine Necessary Condition Analysis (NCA) with dynamic fuzzy-set Qualitative Comparative Analysis (fsQCA) to identify the multiple conditions and combinational paths driving high green and low-carbon development. Our findings reveal three key insights. First, no single condition constitutes a necessary condition; high performance is inherently configuration-driven, requiring synergistic coordination among technology, organization, environment, and practice. Second, three equivalent paths, which are innovation breakthrough, regulation–innovation–practice synergy, and innovation-substitution-for-investment, emerge with green invention patents as the sole core condition shared across all paths, underscoring technological innovation as the foundational capability. Third, pronounced causal asymmetry exists between high and non-high outcomes; non-high performance stems from distinct mechanisms such as resource–practice decoupling rather than simply lacking success conditions. These results support differentiated, technology-driven transformation strategies and tailored policy designs for mining enterprises with varying resource constraints. Full article

Citrus processing generates massive volumes of citrus-processing by-products rich in polyphenols, pectin, and essential oils, yet most of these materials are disposed of with low-value utilization, causing biomass loss and environmental pressure. Physical-assisted extraction techniques represent promising strategies for recovering high-value bioactive components from citrus-processing by-products. This narrative review assesses mainstream conventional and physical-assisted extraction routes (acid-assisted, ultrasound-assisted, microwave-assisted, and supercritical CO₂ extraction) for phenolic compounds, pectin, and essential oils derived from citrus-processing by-products, summarizes optimal operational parameters, and compares their downstream food, biomaterial, and environmental remediation applications. Key findings demonstrate that ultrasound- and microwave-assisted extraction generally deliver higher extraction yields and better preservation of thermally sensitive bioactives relative to conventional reflux extraction; nevertheless, industrial-scale translation faces multiple bottlenecks, including high equipment investment, raw-material seasonal variability, incomplete solvent-recovery workflows, and scarce unified multi-dimensional evaluation benchmarks. Major limitations of existing research include the predominant focus on laboratory-scale yield optimization, with insufficient systematic quantitative comparisons covering energy consumption, product functional quality, life-cycle assessment (LCA), and techno-economic performance. Furthermore, thermal-driven oxidative degradation of d-limonene and polyphenols persists as a critical challenge hindering final product quality. Future perspectives highlight the need to establish standardized raw-material pretreatment protocols, combine chemical-based evaluation metrics and ISO 14040-compliant LCA frameworks to balance environmental benefits and economic profitability, and advance pilot-scale validation for hybrid coupled extraction processes. Key conclusions: although citrus-processing by-products possess enormous biorefinery potential, bridging laboratory-scale feasibility and industrial commercialization still requires joint progress in extraction-process optimization, safety validation, and circular-economy-oriented technical innovation. Full article

Innovation systems are commonly analysed through indicators of investment, performance, technological capacity, and research output, while less attention is paid to the composition of the research workforce. This article asks whether workforce composition can be understood as a structural dimension of national innovation systems and whether it is systematically associated with their capacity configuration. Using comparative 2023 data for 28 European and selected non-European national R&D systems, the study combines correlation analysis, a multidimensional capacity coordinate, and quadrant-based configurational mapping. Innovation-system capacity is operationalised through R&D intensity, innovation performance, and R&D expenditure per researcher. Workforce composition is measured by the share of women among researchers and is treated as a separate aggregate dimension rather than as a comprehensive measure of substantive inclusion. The results indicate a recurrent negative association between innovation-system capacity and the relative representation of women among researchers. Higher-capacity systems are more frequently positioned in configurations characterised by lower female representation, although cases combining high capacity with higher representation demonstrate that the pattern is not universal. The study does not establish causality, temporal development, or a deterministic trade-off. Sectoral, disciplinary, institutional, educational, and cultural factors may contribute to the observed cross-national differences. The article contributes to innovation-systems research by integrating aggregate workforce composition into systems-level analysis and by demonstrating how coordinate-based configurational mapping can reveal relationships that remain obscured in composite rankings. Full article

Scientific problem. Although digital transformation is widely regarded as a system-level enabler of regional innovation, regions with similar digital investment still display markedly different innovation outcomes, and the organizational channels that convert digital conditions into innovation performance remain insufficiently specified. Aim and method. Using panel data for 30 Chinese provinces from 2014 to 2019, this study conceptualizes State Key Laboratories (SKLs) as a specific institutional form of public research platforms (PRPs) and examines whether SKLs transmit the effect of regional digital transformation to regional innovation performance. We construct a Regional Digital Transformation Index using the entropy weight TOPSIS method and estimate its effects using two-way fixed effects models, IV estimation, policy shock DID, mediation analysis, and fsQCA. Results. Regional digital transformation is positively associated with regional innovation performance, and DID estimates based on the National Big Data Comprehensive Pilot Zone policy point in the same direction, with the average policy effect significant at the 5% level under province-clustered inference (p < 0.05). Mediation analysis shows that SKLs transmit part of this effect through both boundary-spanning functions. The external knowledge introduction channel, captured by international collaboration, carries the larger indirect effect (318.966, Sobel z = 2.14, p = 0.032), while the internal network diffusion channel, captured by the network hub function, carries a smaller indirect effect (93.285, Sobel z = 1.89, p = 0.059) whose cluster bootstrap interval excludes zero. H3a (external collaboration) is confirmed by both the Sobel test and the BCa bootstrap interval, while H3b (network hub) is supported by the BCa interval and marginally by the Sobel test. fsQCA further shows that superior innovation performance arises from multiple configurations of digital transformation, SKL boundary-spanning functions, human capital, and industrial base. Conclusion and future research. The findings suggest that digital transformation acts less as a standalone technological input than as a system-level enabling condition whose innovation effects depend on the boundary-spanning functions of public research platforms and their alignment with regional conditions. Future research could use laboratory- and firm-level data and dynamic configurational methods to trace these mechanisms over time. Full article

Cities increasingly use resilience policies to manage climate risk, but it remains unclear how these policies alter firms’ green strategies. Using a difference-in-differences design, we analyze 2011–2023 panel data for A-share listed firms around China’s Climate-Resilient City Construction (CRCC) pilot. CRCC exposure is associated with a higher text-based measure of corporate green transformation. The estimate is stable in parallel-trends and placebo tests, alternative outcome measures, exclusions of confounding policies and shocks, alternative specifications, double machine learning, pre-policy propensity-score matching, and instrumental-variable estimation. Mechanism estimates are consistent with three channels through which CRCC may affect firm behavior. CRCC strengthens executive green cognition, redirects environmental spending toward prevention, and supports green technological and management innovation. By contrast, the estimate for end-of-pipe investment is small and statistically insignificant. A pooled interaction test finds differences across firm life-cycle stages. Comparisons by city size, exemplary-city status, and supply-chain resilience remain descriptive because their grouping indicators are unavailable for pooled re-estimation. Spatial estimates reveal limited, non-monotonic spillovers. Overall, the results indicate that an urban adaptation policy can influence firm strategy, subject to the text-based outcome and the sample of Chinese listed firms. Full article

The Vietnamese textile and garment industry faces a critical sustainability paradox under the impending Carbon Border Adjustment Mechanism (CBAM). Firms are pressured to maintain high-volume export growth while aggressively minimizing carbon and resource intensity. To empirically resolve this tension, this study develops a novel three-phase benchmarking framework that integrates the Best–Worst Method (BWM), VIKOR, and Super-Efficiency Slacks-Based Measure (Super-SBM) under Variable Returns to Scale. Applied to 12 listed enterprises using 2024 fiscal data, the methodology first identifies Energy Intensity as the paramount strategic priority via the BWM. Next, VIKOR mathematically compresses six heterogeneous environmental, social, and governance (ESG) criteria into a single composite index, thereby eliminating standard Data Envelopment Analysis dimensionality constraints. The Phase 3 Super-SBM results reveal profound sector heterogeneity. The macro-scale giant VGT defines the absolute efficiency frontier with an unprecedented score of 18.6729 and zero operational slack. However, the λ reference matrix identifies mid-cap operators such as Tien Son Thanh Hoa and Binh Duong Garment as highly replicable, agile benchmarks for the broader industry. Crucially, the non-radial projection analysis uncovers hidden structural vulnerabilities. The data show that while certain firms possess massive operational buffers, others operate on the absolute edge of the efficiency frontier, leaving them dangerously exposed to impending carbon-taxation shocks. Furthermore, the model identifies critical instances of ESG decoupling in which green investments fail to yield proportional increases in export revenues. These findings suggest that addressing the sustainability paradox requires targeted structural interventions informed by diagnostic benchmarking. Policymakers and corporate executives must integrate open innovation frameworks and systematic problem-solving methodologies to structurally decouple economic output from fossil-fuel energy dependence and outdated labor-arbitrage models. Full article

Open government data is a key institutional arrangement in market-oriented data factor reforms. Using the staggered rollout of city-level government data platforms in China as a quasi-natural experiment and panel data of listed manufacturing firms (2011–2024), we employ a staggered difference-in-differences design to examine the effect of open government data on firms’ resource allocation efficiency. We find that government data platforms significantly reduce resource misallocation, a result robust to propensity score matching, exclusion of concurrent policy shocks, and double machine learning. Channel-level tests do not find statistically significant transmission through government transparency, firm digital innovation, or fiscal subsidy reallocation. Directional identification shows that the effect operates primarily as a corrective force on capital-overallocated firms by curbing inefficient investment, rather than as a relief effect on constrained firms, and is more pronounced in high-digital-intensity industries, smaller cities, and regions with lower digital development. By reducing the wasteful use of capital, labour, and energy and improving the information environment in factor markets, open government data offers a low-cost, institutionalized instrument for reconciling productivity growth with sustainable resource use, with direct relevance to the United Nations (UN) Sustainable Development Goals (SDGs). Full article

This study examines a two-echelon cross-border e-commerce (CBEC) supply chain under the joint constraints of technical barriers to trade (TBTs) and tariffs. To capture the cumulative nature of foreign-market access, the degree of trade barrier breakthrough is modeled as a continuous-time state that converts technological innovation and compliance updating into sustained market access. A differential game is developed to compare centralized, decentralized, and modified two-part tariff contract decisions. The main conclusions are as follows: (1) Decentralized decision-making causes insufficient technological innovation and compliance updating, reducing the steady-state breakthrough level and total supply chain profit. (2) The modified two-part tariff contract internalizes the benefit–cost mismatch between the manufacturer and the retailer, reproducing the centralized investment path and total profit. (3) Government support strengthens barrier-breaking incentives, while the effect of tariffs on decentralized investment depends on the balance between subsidy support and upstream tariff pass-through; tariffs nevertheless reduce the integrated channel margin and may invalidate the contract beyond a critical threshold. (4) Product-life-cycle analysis shows that technological innovation dominates during technology dividend periods, while compliance updating becomes more valuable during bottleneck periods. (5) Multi-scenario simulations and ±20% one-factor perturbations preserve the ranking C = MT > D. These findings extend dynamic supply chain coordination research by linking investment, realized market access, and contract incentives under dual trade barriers, and provide implications for the long-term economic sustainability of CBEC supply chains. Full article

The global ‘Blue Transition’ presents a critical policy dilemma for marine fisheries: how to achieve ecological sustainability and carbon neutrality while maintaining socio-economic vitality. This study addresses this challenge by analyzing the complex interplay between the ecological, social, and economic systems within China’s marine fisheries. Our research purpose is to identify effective governance pathways for a coordinated and sustainable transition. We developed a system dynamics model, informed by panel data from 2010–2022, to simulate the long-term outcomes of different policy scenarios. This approach allows us to move beyond static analysis and understand the dynamic feedback mechanisms that shape the fishery sector. Our analysis of historical data reveals that the overall system coordination improved initially but has since stagnated at a basic level. The most significant outcome of our simulations is the identification of the social system—encompassing technological innovation, governance, and human capital—as the central lever for progress. Our findings demonstrate that policies focused narrowly on either economic growth or ecological restoration are suboptimal. The optimal path to high-quality, sustainable development is an integrated strategy that prioritizes investment in the social system to mediate the conflict between economic and ecological goals. This provides a crucial insight for marine policy, suggesting that effective governance frameworks are the key enablers of a successful Blue Transition. Full article

China has emerged as one of the most influential actors in South–South scientific cooperation, progressively integrating agricultural innovation, technology transfer, and sustainable development into its international engagement strategy, with tropical agriculture positioned as a strategic domain in its relations with Latin America. However, despite China’s growing role as a driver of agricultural research collaboration, the specific mechanisms through which its institutions transfer knowledge and strengthen local scientific capacities in the Latin American region remain insufficiently studied, particularly in the case of Ecuador. This study adopted a qualitative scoping review methodology following PRISMA-ScR guidelines, screening 9199 records across Scopus, Web of Science, and SciELO, of which 61 documents were retained for thematic analysis. Results show that Chinese cooperation has evolved through three distinct phases: an initial phase centered on agricultural investment and resource-oriented cooperation (2000–2010); a second phase (2010–2018) characterized by the initial institutionalization of scientific and technological cooperation through bilateral agreements, joint action plans, researcher training, and institutional exchanges; and a third phase (2018–present), marked by the deliberate integration of science, technology, and innovation as central pillars of China’s engagement with Latin America, including long-term collaborative research, joint laboratories, scientific networks, and initiatives led by institutions such as the Chinese Academy of Tropical Agricultural Sciences (CATAS). In Ecuador, CATAS’s partnership with the National Institute of Agricultural Research (INIAP) illustrates China’s capacity to build joint research platforms, though sustained impact depends on long-term institutionalization, continuous financing, and transparent governance over genetic resources. The findings underscore China’s expanding support in shaping South–South agricultural cooperation and innovation, and the conditions required to translate this support force into durable, mutually beneficial scientific outcomes. From a public policy perspective, China and Ecuador could strengthen their international agricultural cooperation framework through long-term mechanisms supporting strategic scientific partnerships between the two countries, including multi-year joint research programs, dedicated funding instruments, researcher mobility, and institutional mechanisms for transparent governance of genetic resources and jointly generated intellectual property. Full article

Microgravity research has emerged as a rapidly evolving field at the intersection of space medicine, genomics, biotechnology, and precision medicine. Exposure to the space environment induces complex physiological and molecular adaptations that affect multiple biological systems, including immune regulation, metabolism, musculoskeletal function, and gene expression. Recent advances in genomics, multi-omics technologies, artificial intelligence, and bioengineering have substantially improved our understanding of biological adaptation to spaceflight and expanded opportunities for translational biomedical research. This review summarizes recent advances in genetic and biomedical research under microgravity conditions, with particular emphasis on molecular mechanisms, omics technologies, genome editing, microbiome research, regenerative medicine, and personalized healthcare approaches. Major experimental platforms, landmark spaceflight studies, and translational applications in infectious diseases, cancer biology, aging, tissue engineering, and pharmaceutical development are discussed. The review also highlights Saudi Arabia’s emerging contributions to genomic medicine and space biosciences through initiatives such as the Saudi Human Genome Program, the Saudi Pangenome Project, the Saudi Space Agency, and the BioGravity Initiative. Recent Saudi participation in human spaceflight and microgravity-associated biomedical research is discussed within the context of Vision 2030 and national investments in biotechnology and precision medicine. Collectively, advances in microgravity research are expected to contribute to the advancement of precision medicine and facilitate the development of innovative diagnostic and therapeutic strategies with significant implications for both human space exploration and terrestrial healthcare. Full article

Agricultural technological innovation is essential for sustainable agricultural modernization and rural development. However, agricultural technology enterprises often face persistent financing constraints because research and development (R&D) activities involve long investment cycles, high uncertainty, and delayed returns. Using a firm-level panel dataset of Chinese agricultural technology enterprises, this paper examines the effect of relational patient capital (RPC) on agricultural technological innovation by employing a two-way fixed-effects model. The results show that RPC significantly promotes agricultural innovation output. Mechanism analysis indicates that RPC enhances innovation through two channels. First, it facilitates firms’ digital transformation, thereby reducing R&D uncertainty and organizational costs. Second, it alleviates financing constraints by stabilizing cash flows to support R&D investment. The results remain robust after clustering standard errors, excluding the years affected by the COVID-19 pandemic, and employing lagged specifications. Heterogeneity analyses further reveal that the positive effect is more pronounced among small-scale enterprises and firms located in central and eastern China, where financing frictions and resource constraints are relatively more severe. By linking RPC to firm-level agricultural innovation, this study extends the literature on agricultural finance and innovation financing, highlighting the role of long-term, relationship-based capital in addressing market failures in agricultural R&D. The findings suggest that rural financial policies should encourage stable, long-term investment, strengthen financing support for small agricultural technology enterprises, and integrate patient capital with digital transformation initiatives to promote sustainable agricultural and rural development. Full article

Emerging industrial agglomeration drives green transformation through knowledge spillovers and economies of scale. However, its effects exhibit pronounced nonlinearity and heterogeneity, shaped by spatial externalities and development stages. This paper investigates 19 Chinese urban agglomerations over the period 2014 to 2023. Kernel density estimation based on enterprise-level Point-of-Interest (POI) data is used to characterize spatial agglomeration patterns across eight emerging sectors. A two-stage dynamic network super-efficiency SBM model decomposes Green Transition Efficiency (GTE) into resource utilization and pollution control sub-stages. An XGBoost-SHAP-GEO analytical framework, combined with partial dependence analysis, then identifies nonlinear driving mechanisms. The main findings are as follows: First, emerging industrial agglomeration intensifies and polarizes toward the eastern coast, whereas GTE displays a “high-west, low-east” pattern. This produces a significant spatial mismatch, rooted in the near-saturation of environmental carrying capacity in eastern regions, where congestion effects exceed knowledge spillover dividends. Second, geographic characteristics constitute the primary factor shaping GTE and operate through nonlinear interactions with industrial agglomeration and R&D investment. Notably, their moderation direction is reversible, suggesting that geographic endowments should be understood as “conditional assets” rather than fixed advantages. Third, nonlinear patterns across sectors are highly heterogeneous. The bio-industry is the only sector to achieve a J-shaped positive breakthrough. Information technology and new materials exhibit persistent inhibition, while related services display an extremely narrow threshold window with the deepest negative reversal. Thus, “moderate agglomeration” is a multidimensional concept that shifts dynamically with industry type and regional endowment. Fourth, driving mechanisms display stage-dependent evolution. The incubation stage relies on natural endowments and basic industrial pull, with the green bottleneck residing in resource utilization efficiency. The growth stage faces multiple tensions from coexisting positive and negative effects. The optimization stage shifts toward R&D innovation and industrial greening, marking a qualitative transformation from MAR externalities to Jacobs externalities. In addition, the non-significant linear coefficient in the 2SLS instrumental variable test is consistent with the inverted U-shaped nonlinear finding, further validating the necessity of a nonlinear analytical framework. These findings provide differentiated governance evidence for balancing industrial agglomeration with green sustainable development. Full article

Stable and efficient supply chain relationships are essential for small and medium-sized enterprises (SMEs) to strengthen competitive advantage and achieve sustainable growth. However, how resource-constrained SMEs overcome internal resource constraints and enhance competitiveness through supply chain integration remains underexplored. Taking China’s Supply Chain Innovation and Application Pilot Program (SCIAPP) as a quasi-natural experiment, this study uses panel data of SMEs from 2014 to 2024 and employs a SCIAPP significantly improves SMEs’ competitive advantage (${\beta }_1$ = 0.016, p < 0.01). Mechanism analyses reveal that SCIAPP enhances competitive advantage by mitigating the bullwhip effect and increasing innovation investment. The positive effect is stronger for firms with higher supply chain dependence, for non-capital-intensive firms, and for smaller firms. Further analysis shows that improvements in competitive advantage contribute to higher firm value. This study extends research on SMEs’ competitive advantage by demonstrating how government-led supply chain governance facilitates capability development among resource-constrained firms. The findings also provide implications for policymakers seeking to improve supply chain governance and promote the high-quality development of SMEs. Full article