Search Results (112)

Firms increasingly face disruptions arising from technological change, supply chain instability, and uncertain policy environments, making enterprise resilience a key concern for both managers and policymakers. As firms operate within interconnected digital and supply chain systems, this study examines whether digital intelligence policy and supply chain coordination policy are jointly associated with enterprise resilience. Using a firm-year panel of Chinese A-share listed companies from 2010 to 2024, we investigate AI innovation pilot zones and supply chain innovation pilots, with a particular focus on whether their coexistence is associated with a complementarity premium. The results suggest that both AI innovation pilot zones and supply chain innovation pilots are positively associated with enterprise resilience. The interaction between the two policies is significantly positive, providing evidence consistent with an additional joint-policy association beyond their separate associations. Dynamic analysis supports the parallel trend assumption and suggests that the estimated complementarity association becomes stronger over time. Mechanism tests provide channel-consistent evidence that joint policy exposure is associated with higher values of the digital-transformation indicator, stronger supply chain coordination, and greater resource reconfiguration. Heterogeneity analysis further suggests that this association is more pronounced among non-state-owned firms, firms in supply-chain-dependent industries, firms located in cities with stronger digital infrastructure, and firms with higher risk exposure. These findings highlight the potential importance of coordinated policy design for supporting firm-level resilience. Full article

As global markets navigate the dual transition of digitalization and sustainability, the risk of “digital greenwashing” has emerged as a critical corporate governance challenge. Utilizing a comprehensive dataset of Chinese A-share listed firms from 2018 to 2024—an ideal laboratory characterized by rapid regulatory shifts and unique state-market dynamics that provide highly generalizable insights for other emerging economies—this study empirically investigates whether corporate digital transformation acts as a genuine driver for Environmental, Social, and Governance (ESG) enhancement or merely serves as a symbolic disclosure tool. Fortified by rigorous identification strategies, including Propensity Score Matching and Lewbel heteroskedasticity-based instrumental variable estimations, the results confirm that digitalization serves as an incremental yet statistically significant driver for corporate sustainability. Crucially, mechanism analyses reveal a “full moderation” effect: the positive impact of digitalization on ESG performance is completely activated only in the presence of premium external assurance (e.g., Big 4 audits). Without high-quality IT auditing to act as a credibility enforcer and verify the substance of digital signals, technological adoption alone fails to yield significant ESG improvements. Furthermore, a nuanced structural asymmetry is identified: foundational data infrastructures (Cloud Computing and Big Data) directly enhance quantifiable Environmental and Governance metrics, whereas premium audits are strictly required to activate the “soft,” qualitative Social dimension. Finally, the synergy exhibits distinct boundary conditions. It is heavily concentrated within high-pollution industries where digital transition acts as a regulatory survival imperative rather than mere market expansion, and its reliance on external assurance is fundamentally driven by the market-signaling needs of non-State-Owned Enterprises (non-SOEs) rather than the policy-distorted mandates of SOEs. These findings offer critical theoretical extensions and policy implications for standardizing digital-audit infrastructures globally. Full article

Server-side capacity dimensioning in operator-managed Over-The-Top (OTT) and Internet Protocol Television (IPTV) systems requires analytical methods that can account for heterogeneous traffic classes, differentiated subscription tiers, and strict grade-of-service (GoS) constraints. This paper proposes a capacity-planning framework based on a full-availability group (FAG) model and the Kaufman–Roberts recursion for evaluating class-specific blocking probabilities in multi-class OTT/IPTV delivery systems. The framework combines recursive occupancy-distribution computation with an incremental capacity search procedure to determine the minimum server-side delivery capacity satisfying differentiated blocking targets for free, standard, and premium subscription tiers. Three provisioning strategies are analysed within a unified model: dedicated server pools, a shared non-prioritised resource pool, and a shared prioritised resource pool. The analytical results are validated by discrete-event simulation and then used to compare the required capacities under the considered strategies. For the analysed six-class scenario, the shared server configuration reduces the required capacity by 3.82% compared with the dedicated architecture, while the prioritised shared configuration reduces it by 12.44%, while preserving stricter GoS protection for higher-priority traffic. The proposed framework provides network operators with a reproducible analytical tool for translating blocking-probability constraints into concrete server-capacity requirements and infrastructure-planning decisions. Full article

The European Union aims to achieve the target of 25% of land under organic farming by 2030. Italy reached the share of 18.7% in 2022, although significant regional differences persist. This study analyzes farms’ conversion response in the Lazio region (Italy) using a dynamic version of the AGRITALIM agro-economic supply model on a sample of 578 FADN farms. Addressing the limitations of static modeling frameworks that assume full conversion, this study aims to simulate individual farm conversion choices over time, by accounting for conversion and maintenance phases costs and price premiums. This framework tests the hypotheses that a dynamic modeling approach can highlight nuanced responses and that increases in Common Agricultural Policy (CAP) payments are able to increase organic conversion rates. Results show limited effects of increased economic support: the 2023–2027 CAP reform, characterized by higher support, leads to a 5.1% increase in the area under organic farming, while a 40% increase in financial support generates an expansion of 12%. Farm responses are highly heterogeneous: rural provinces, larger and arable farms are more responsive, while smaller farms and livestock are less likely to convert. These findings highlight the need for integrated policy strategies combining financial support, reduced costs, technical assistance, and improved market access. The methodological approach adopted in this study provides a useful tool for supporting the design of targeted and effective policy interventions. Full article

With the rapid development of artificial intelligence (AI), its implications for income distribution have attracted increasing attention. As a key indicator of earnings differences between high- and low-skilled workers, the skill premium is important for distributional equity and sustainable economic and social development. Using AI-related patent data from Chinese listed firms, this paper constructs a firm-level measure of AI development and examines its impact on the skill premium within firms. The results show that AI development significantly increases the firm-level skill premium. Mechanism analysis suggests that AI increases the firm-level skill premium by substituting for low-skilled labor, improving firm productivity, promoting capital deepening, and facilitating technological upgrading. The main findings remain robust after addressing endogeneity using an instrumental variable approach and conducting a series of robustness checks, including alternative constructions and measures of the dependent variable, alternative measures of AI development, AI pilot zone policy shock tests, and alternative sample restrictions. Heterogeneity analysis further shows that the effect is more pronounced in non-state-owned firms, firms with higher levels of digitalization, and firms operating in industries with lower market concentration. Further analysis indicates that AI development may also reduce firms’ labor income share and widen income disparities across industries. These findings highlight the need to strengthen workers’ skills and adaptability, improve income distribution mechanisms, and promote a more balanced relationship between technological progress and social equity. Full article

The objective of this paper is to offer a mathematical formulation of economic value added (EVA) that incorporates distance-to-default (DD) and thus a default-free capital structure. The latter is extended via the weighted average cost of capital (WACC) to introduce a default-free EVA. The data include the nonfinancial firms listed in the DJIA30 and NASDAQ100 covering the period 1992Q2–2023Q3. The results of standard specification tests and the GMM estimator show that (a) DD causes an increase in WACC and thus, EVA decreases; (b) the interest coverage ratio can be used effectively to compensate for default risk, thus adjusting the default-free EVA positively; (c) both EVA and default-free EVA can effectively be managed via common determinants, namely, net working capital ratio, total liabilities to EBITDA, sales growth rate, debt–equity ratio, and earnings per share; (d) the positive impact of the inflation rate on both EVA and default-free EVA justifies the use of default-free EVA as a metric for equity risk premium; and (e) the robustness of the results via stochastic geometric Brownian motion shows that the determinants of default-free EVA are stable. This paper contributes to related studies by incorporating credit risk via the DD into default-free EVA. Full article

Extreme weather events have raised the frequency of power outages, posing critical challenges to the sustainability and resilience of modern power systems. In such cases, distributed energy resources (DERs) can effectively support the re-establishment of sustainable power supply for critical loads within the distribution network and reduce power outage losses. In this paper, a sustainable fault recovery framework based on an intentional islanding scheme is proposed to partition the distribution system in order to optimize the priority restoration of critical loads, while taking the operational constraints of the system into consideration. In addition, a blockchain-based P2P insurance mechanism is applied to mitigate the outage losses of the network’s users with a higher degree of security and transparency. By linking technical restoration decisions with financial risk-sharing mechanisms, the proposed framework improves economic sustainability and social equity among network users. For this purpose, a multi-layer, multi-objective optimization algorithm is proposed for optimal partitioning of the distribution network, management of DERs, and demand side management of flexible loads in order to minimize the outage losses and the insurance premium, while maintaining satisfactory performance of the network. To validate the feasibility of the proposed algorithm, the 45-node distribution network of Alexandria, Egypt is used. The results show that a reduction in peak load, outage losses, and operational costs are achieved, with an overall saving of 17.34%, in addition to a premium reduction of 41.3%. These results highlight the effectiveness of the proposed framework in enhancing the environmental, economic, and operational sustainability of distribution systems under outage conditions. Full article

Northeast China’s rust-belt cities have faced persistent concerns about stagnating labor productivity amid structural change. This paper examines how the productivity payoff to urban density depends on local economic structure and ownership composition using an annual panel of prefecture-level cities. We estimate two-way fixed-effects models with city and year effects and city-clustered standard errors, complemented by dynamic specifications and additional robustness checks. The results show a robust positive within-city association between population density and labor productivity. This density premium is structure-conditioned: the productivity payoff to density is significantly larger in city-years that are more industry-oriented. Information-theoretic measures further show that sectoral and ownership composition matter in distinct ways. A normalized entropy measure based on 19 all-city sectoral employment categories is positively associated with labor productivity, while its interaction with density is negative and significant, indicating that the density premium is weaker in more sectorally balanced city-years. A normalized four-category ownership entropy measure, constructed from SOE, private/self-employed, collective, and other employment shares, is positively associated with labor productivity and interacts positively with density, indicating a stronger density–productivity association in city-years with a more balanced ownership composition. Collectively, the findings suggest that urban density is not a uniform engine of productivity: its payoff depends on whether dense city economies are organized around productive sectoral linkages and a sufficiently balanced ownership environment. Overall, the evidence supports a conditional agglomeration view in which productivity dynamics in Northeast China reflect the interaction of density, structural orientation, sectoral dispersion, and ownership mixing. Full article

Post-quantum cryptography (PQC) artifacts are one to three orders of magnitude larger than their classical counterparts and must be segmented via ISO-TP across a shared CAN-FD bus while coexisting with periodic safety-critical traffic. No prior work has quantitatively mapped the transport-level feasibility of these artifacts under realistic multi-electronic control unit (ECU) contention. This paper presents a validated discrete-event simulator and evaluates 29 parameter sets from nine algorithm families—spanning the KpqC final portfolio, NIST FIPS 203–205 standards, and the draft FIPS 206—across 534 scenarios classified as feasible, borderline, or infeasible. Results show that key encapsulation mechanism (KEM) feasibility is scenario-dependent: domain scale and startup coordination dominate over algorithm choice, with 4-ECU staggered deployments feasible for all Level-1 candidates, while 16-ECU simultaneous startup is universally infeasible. For digital signatures, FN-DSA achieves the best transport feasibility due to its compact signature, while HQC is uniformly infeasible and SLH-DSA is nearly uniformly infeasible, quantifying the CAN-FD bandwidth premium of algorithmic diversity. System-side traffic shaping—staggered startup and reserved bus windows—outperforms algorithm substitution as a mitigation strategy. To the best of our knowledge, these findings constitute the first design-space map of PQC artifact transport on CAN-FD and provide actionable deployment guidelines for post-quantum transition. Full article

Against the backdrop of China’s dual-carbon goals and the growing emphasis on sustainable development, ESG information has become an important non-financial signal in capital markets; yet whether and how it is priced by investors remains unclear. Using a sample of 2018–2024 Chinese A-share listed firms, this study examines the relationship between corporate ESG ratings and firm market value, with a particular focus on the mediating role of institutional ownership and investor heterogeneity. We find that firms with higher ESG ratings exhibit significantly higher market value, indicating that the market assigns a valuation premium to favorable ESG evaluations. Mediation analyses further show that higher ESG ratings are associated with increased institutional ownership, which in turn enhances firm value. Heterogeneity analyses reveal that this mediating effect is primarily driven by long-term institutional investors, whereas medium-term and short-term institutions neither respond systematically to ESG ratings nor transmit ESG rating information into firm valuation. In additional analyses, we show that ESG rating divergence significantly weakens the positive valuation effect of ESG ratings by increasing informational uncertainty and reducing the credibility of ESG rating signals. Overall, this study provides new evidence on the investor-based mechanisms underlying ESG rating-based pricing and highlights the importance of improving the transparency and comparability of ESG ratings in China’s capital market. Full article

Using a panel of Chinese A-share listed companies from 2007 to 2022, this study examines how firms’ structural positions in patent citation networks affect innovation efficiency. We construct a firm-level patent citation network and use betweenness centrality to capture firms’ brokerage-oriented positions in knowledge flows. Based on firm- and year-fixed-effects models, instrumental-variable estimation, and robustness checks, we find that stronger brokerage positions significantly improve innovation efficiency. Mechanism analyses show that this effect operates through two channels: cross-domain knowledge recombination and organizational boundary spanning. Firms in stronger brokerage positions are more likely to access technologically heterogeneous external knowledge and interact with a wider range of external knowledge-bearing entities, thereby improving the efficiency with which innovation inputs are transformed into patent-based outputs. We further find that digital transformation negatively moderates the relationship between brokerage centrality and innovation efficiency. This suggests that digital transformation reduces firms’ marginal dependence on external brokerage positions by strengthening internal data-processing, coordination, and knowledge-integration capabilities. Additional analyses show that the positive effect of brokerage centrality is broadly shared across ownership groups. Regional heterogeneity is more evident in the stronger brokerage premium observed in the western region than in the eastern region. Full article

Kazakhstan is one of the world’s major wheat producers and exporters, playing an important role in regional and global food security. However, increasing quality requirements in domestic and export markets have exposed limitations in the country’s capacity to consistently supply high-quality spring bread wheat (Triticum aestivum L.). This review aims to assess the current status of spring wheat grain quality in Northern Kazakhstan, identify the main factors driving its variation, and outline pathways for quality improvement. The analysis is based on published literature, official statistics, national quality standards, and recent data on wheat production, grading, breeding systems, agronomic practices, and trade patterns. The review reveals that wheat production is dominated by medium-quality grain (primarily class 3), while high-quality classes suitable for premium and improver markets represent a small share. Compared with major exporters such as Canada, the United States, and Australia, Kazakh wheat is generally inferior across key quality parameters. Structural constraints include the limited integration of quality assessments within breeding programs, insufficient laboratory infrastructure, weak agroecological zoning by quality classes, and suboptimal agronomic management, particularly regarding nitrogen use. Environmental heterogeneity and climate change further influence the yield–quality balance. Overall, the findings suggest that improving wheat grain quality in Kazakhstan will require coordinated advances in breeding, agronomy, institutional capacity, and market alignment, enabling a gradual shift toward a more competitive, quality-oriented wheat production system. Full article

Under China’s “Dual Carbon” strategy, carbon transparency has become a critical determinant of corporate competitiveness. Using a dataset of Chinese A-share listed companies from 2010 to 2023, this study constructs an integrated theoretical framework combining signaling theory and the “real effects” hypothesis to investigate the impact of carbon information disclosure (CID) on firm value. The results demonstrate a significant positive relationship between CID quality and firm value, a finding that remains highly robust against the exogenous macro-policy shock of the 2020 Dual Carbon goals. A primary conceptual contribution lies in identifying Green Mergers and Acquisitions (M&A) as a vital mediating strategic mechanism. High-quality CID acts as a credible commitment device that triggers internal problemistic search, compelling firms to undertake substantive green M&A to fulfill environmental claims, thereby establishing a “transparency-to-strategy-to-value” continuum. Furthermore, heterogeneity analysis indicates that the valuation premium is markedly more pronounced in non-state-owned enterprises (Non-SOEs) and non-heavily polluting industries, reflecting their reliance on transparency to alleviate capital constraints and signal “green competitiveness.” These findings confirm that the capital market prices carbon disclosure as a high-quality strategic asset rather than a mere compliance cost, offering targeted empirical evidence for policymakers to refine standardized disclosure frameworks and for investors to screen for substantive “Green Alpha.” Full article

Elucidating the molecular mechanisms underlying beef quality differences is crucial for precision breeding of high-quality cattle. In this study, we first characterized the myofibrillar morphology of high-quality (H group) and low-quality (L group) beef samples using hematoxylin–eosin (HE) staining. Transcriptomic and metabolomic analyses were then conducted to reveal the molecular regulatory basis of quality variation. HE staining revealed highly significant differences in muscle fiber area and diameter between H and L groups (p < 0.01), along with significant differences in muscle fiber density (p < 0.05), but no significant differences in muscle fiber perimeter. Furthermore, by focusing on five core metabolic pathways shared across the transcriptome and metabolome datasets, 30 differentially expressed genes (DEGs) and 14 differentially accumulated metabolites (DAMs) were identified. Pearson correlation analysis revealed synergistic regulation between DEGs and DAMs: AMPD2 modulates umami flavor by regulating inosine accumulation via the purine metabolism pathway; ACOX3 promotes unsaturated fatty acid synthesis and intramuscular fat deposition through carbohydrate metabolism; genes in the glycolysis/gluconeogenesis pathway maintain post-slaughter muscle pH homeostasis, thereby influencing beef tenderness. Collectively, this study integrates morphological and molecular evidence to elucidate the multi-level basis of beef quality formation, providing key candidate genes, metabolites, and pathways for molecular breeding. These findings offer comprehensive theoretical and technical support for the sustainable development of the premium beef industry. Full article

Sustainable finance and carbon risk have attracted substantial interest from both practitioners and scholars. This paper integrates the income-based environmental responsibility framework with financial asset pricing models to investigate how carbon transition risk propagates along value chains and impacts asset returns. By utilizing the Ghosh supply-driven input–output model to quantify downstream value chain carbon emissions as a proxy for the dependence of a company’s revenue streams on high-carbon downstream clients, we construct a novel downstream carbon risk factor (DMC) by sorting stocks into portfolios based on this exposure and forming a factor mimicking long short portfolio. We then integrate this DMC factor into the Fama–French five-factor framework to propose a six-factor model capable of capturing value chain risk transmission. Empirical results of Chinese A-share listed companies demonstrate that firms with high DMC exposure, being vulnerable to carbon transition shocks such as carbon pricing, offer a significant risk premium even after controlling for traditional financial characteristics. This finding provides robust evidence for the carbon premium hypothesis in the world’s largest emerging market and contributes a theoretically grounded and empirically implementable framework for integrating value chain carbon risk into asset pricing analysis. Full article