Search Results (1,031)

As global agriculture seeks to reconcile the dual imperatives of food security and environmental sustainability, this study examines the role of Internet access in promoting green agricultural production, specifically by reducing fertilizer and pesticide use. Using a panel dataset from 16 rural fixed observation points in Henan Province from 2009 to 2022, we find that Internet access significantly lowers per-unit farmland expenditures on fertilizers and pesticides by 6.0% and 7.3%, respectively. Mechanism analysis reveals that these positive effects operate through three main channels: improved information accessibility delivers timely agricultural data and guides input decisions; enhanced technical learning efficiency reduces barriers to adopting green technologies; and stronger market connectivity via e-commerce platforms shortens supply chains and provides price incentives. Heterogeneity analysis further identifies more pronounced effects among farmers with higher human capital (higher education, better health, younger age), higher production capital (greater mechanization, larger farmland, stronger decision-making capacity), lower livelihood capital (lower income, lower consumption, less communication expenditure), and higher spatial capital (residing in urban suburbs, poverty registration villages, and traditional villages). This study provides micro evidence for digital technology to empower sustainable agricultural development and provides policy implications for building a sustainable agri-food system. Full article

This paper develops a procedure for assessing both supply chain processes and strategic criteria in the context of platform-based supply chains, addressing the problem that organizations often invest in digital platforms without a clear understanding of how process effectiveness, process dysfunction, and strategic platform priorities jointly influence implementation success. The main research objective is to evaluate how effective and dysfunctional supply chain processes, together with prioritized strategic platform criteria, shape performance, productivity, and resilience outcomes in platform-based supply chain integration. The paper further discusses how identified dysfunctional processes and prioritized strategic criteria relate to operational vulnerabilities and resilience-building measures. The research adopts a multi-criteria decision-making (MCDM) approach to address the challenges of digital transformation and platform integration. An exploratory study was conducted applying the analytic hierarchy process (AHP) to evaluate functional and dysfunctional processes, complemented by the best worst method (BWM) to prioritize critical strategic criteria. The combined assessment highlights effective and dysfunctional processes while also identifying the most influential factors driving platform-based adoption and their potential implications for operational vulnerability and resilience. The results demonstrate how platform integration contributes to performance improvement, process alignment, and productivity gains across supply chain operations. The study contributes to both theory and practice by integrating MCDM techniques to support structured decision-making, enhancing responsiveness, resilience, and alignment with platform-oriented strategies. The primary contribution lies in providing a dual-level framework that enables supply chain managers to diagnose weaknesses, leverage strengths, and strategically guide the transition toward platform-based supply chain operations, with a measurable impact on organizational performance and productivity development. Full article

The development of cross-border hydrogen energy value chains involves complex interactions between technological, regulatory, and logistical subsystems. Static assessment models often fail to capture the dynamic response of these coupled systems to external perturbations. This study addresses this gap by proposing the Dual Carbon Cooperation Index (DCCI), a data-driven framework designed to quantify the synergy efficiency of the China–Korea hydrogen ecosystem. We construct a dynamic state estimation model integrating three coupled dimensions—Technology Synergy, Regulatory Alignment, and Supply Chain Resilience—utilizing an adaptive weighting algorithm (Triple Dynamic Response). Based on multi-source heterogeneous data (2020–2024), the model employs Natural Language Processing (NLP) for vectorizing unstructured regulatory texts and incorporates an exogenous signal detection mechanism (GPR). Empirical results reveal that the ecosystem’s composite synergy score recovered from 0.38 to 0.50, driven by robust supply chain resilience but constrained by high impedance in technological transfer protocols. Crucially, the novel dynamic weighting algorithm significantly reduces state estimation error during high-volatility periods compared to static linear models, as validated by bootstrapping analysis (1000 resamples). The study provides a quantitative engineering tool for monitoring ecosystem coupling stability and proposes a technical roadmap for reducing system constraints through secure IP data architectures and synchronized standard protocols. Full article

A well-designed layout for urban parks plays a crucial role in constructing livable cities and enhancing residents’ well-being. The provision of age-friendly park access is fundamental to building an elderly-friendly city. However, previous studies have lacked comprehensive analyses that integrate the distribution of the elderly population, park accessibility, park quality, environmental characteristics, and social equity within a unified framework. Specifically, the supply–demand imbalance mechanism underlying the spatial variations in accessibility has not been adequately addressed. This study employs an improved two-step floating catchment area (2SFCA) method, combined with Lorenz curves and urban park-adapted Gini coefficients, to examine the supply–demand relationship and allocation differences between the elderly population and parks at the neighborhood and community levels. The analysis highlights issues related to equity and accessibility and explores their spatial disparity and influencing factors. The key findings are as follows: (1) The classic 2SFCA model exhibits significant biases in evaluating park supply–demand relationships, accessibility, and equity at a fine-grained scale, indicating the necessity of high-precision modeling. (2) Park accessibility in the Old City of Nanjing follows a dual-ring pattern of high accessibility, contrasted with clustered areas of low accessibility, while accessibility equity shows a central–peripheral gradient. Overall equity is relatively low, with good walking accessibility within only about one-third of communities. (3) Park supply levels, neighborhood construction year, and plot ratios are the primary factors influencing park accessibility for elderly residents. The comprehensive aging index is positively correlated with the equity in park layout, whereas housing prices and neighborhood size do not exhibit a simple linear relationship with park accessibility or equity for elderly residents. These findings provide a comprehensive and realistic perspective for understanding elderly park accessibility and equity, offering decision-making references for enhancing urban livability, managing an aging society, and formulating spatial equity policies in the future. Full article

In recent years, with the growing intensity of extreme weather events, imbalances in energy supply and demand, and frequent regional conflicts, the stability of our energy systems faces increasing challenges. Against this backdrop, the green innovation ecosystem can optimize the energy system’s structure and operational efficiency by promoting multi-actor interaction and multi-element synergy, thereby enhancing its resilience. Accordingly, this study aims to reveal how the green innovation ecosystem drives improvements in energy resilience (ER) through factor configurations and to identify the pathways leading to high-ER outcomes. To address this, this study constructs a research framework of the “core layer–environmental layer–supporting layer” for the green innovation ecosystem, and selects seven conditional variables, namely dual green innovation, multidimensional environmental regulation, green finance, and digital infrastructure. Based on official Chinese statistics, panel data from 30 provinces were compiled, and the dynamic qualitative comparative analysis (QCA) method was used to analyze how multiple factors interacted from 2016 to 2022 to achieve high ER from a spatiotemporal perspective. The results show that: (1) There is no single necessary condition for achieving high ER. (2) Dual green innovation and public participation in environmental regulation play a universal role in achieving high ER. They are combined with green finance, market-based environmental regulation, and digital infrastructure, forming three configuration pathways for achieving high ER. (3) No significant time effect is observed. (4) Pronounced spatial heterogeneity exists. The eastern region focuses on the green finance-enabled pathway, the central region has a high coverage of all three pathways, and the western region has relatively weak overall adaptability. Based on these findings, this study argues that enhancing ER depends on the coordinated allocation of multiple factors, and there is no single optimal pathway. Policymakers should adopt a configurational mindset and select appropriate combinations of elements in light of regional development conditions to enhance ER. Full article

Artificial intelligence (AI) is increasingly regarded as a transformative enabler of sustainable logistics and supply chain management, particularly in the context of global energy transition and decarbonization efforts. This study provides a comprehensive conceptual and exploratory assessment of the multidimensional role of AI, highlighting both its potential to enhance energy efficiency and reduce greenhouse gas emissions, as well as its inherent environmental costs associated with digital infrastructures such as data centers. The findings reveal the dual character of digitalization: while predictive algorithms and digital twin applications facilitate demand forecasting, process optimization, and real-time adaptation to market fluctuations, they simultaneously generate additional energy demand that must be offset through renewable energy integration and intelligent energy balancing. The analysis underscores that the effectiveness of AI deployment cannot be captured solely through economic metrics but requires a holistic evaluation framework that incorporates environmental and social dimensions. Moreover, regional disparities are identified, with advanced economies accelerating AI-driven green transformations under regulatory and societal pressures, while developing economies face constraints linked to infrastructure gaps and investment limitations. The analysis emphasizes that AI-driven predictive models and digital twin applications are not only tools for energy optimization but also mechanisms that enhance systemic resilience by enabling risk anticipation, adaptive resource allocation, and continuity of operations in volatile environment. The contribution of this study lies in situating AI within the digital–green synergy discourse, demonstrating that its role in logistics decarbonization is conditional upon integrated energy–climate strategies, organizational change, and workforce reskilling. By synthesizing emerging evidence, this article provides actionable insights for policymakers, managers, and scholars, and calls for more rigorous empirical research across sectors, regions, and time horizons to verify the long-term sustainability impacts of AI-enabled solutions in supply chains. Full article

Origin warehouses, positioned at the critical “first mile” of the agri-food supply chain, profoundly influence supply chain power structures and profit allocation, as well as supply chain stability and sustainable development. To explore the role of origin warehouses in the agri-food supply chain, this study develops a three-level game model comprising a “planter–origin warehouse operator–seller” framework. Notably, this study conceptualizes the dual-functional “origin warehouse” as observed in practice, proposing two theoretical modes: the Logistics Center (LC) and the Supply Chain Center (SCC). By treating quality level, service level, and selling price decisions as endogenous variables, this study further reveals the interconnected decision-making mechanisms under different operational modes. Overall, the LC mode performs better in quality-driven markets, generating higher system profits and greater social welfare, whereas the SCC mode is superior when consumers are more price-sensitive or place greater value on service. Based on these findings, this study provides decision-making guidance for origin warehouse operators aiming to select the optimal mode under varying market conditions and proposes targeted coordination strategies to promote the high-quality development and economic sustainability of the agri-food supply chain. Full article

Nitrogen (N) fertilizers can promote soybean growth, nodulation, and nitrogen fixation to a certain extent. However, excessive nitrogen application inhibits the nitrogen fixation capacity of soybean nodules. In this study, three experimental materials were used to investigate the direct and indirect effects of localized exogenous nitrogen (Ammonium Nitrate, NH₄NO₃) on nodule nitrogen fixation in soybean. Three nitrogen supply methods were applied: bilateral nodulation dual-root soybeans, unilateral nodulation dual-root soybeans, and upper- and lower-layered soybeans. The root nitrogen accumulation of direct contact with exogenous nitrogen reached 72.61 mg/plant, 30.59 mg/plant, and 88.48 mg/plant, respectively, and its nitrogen accumulation ability was higher. Exogenous nitrogen inhibited nodule growth and nitrogen accumulation. Nodule development and nitrogenase activity were regulated both directly and indirectly by exogenous nitrogen, with a more pronounced inhibitory effect observed in the roots directly exposed to nitrogen. Experiment I demonstrated that the number and dry weight of nodules on the nitrogen supply side decreased by 35.04% and 40.00%, respectively, while the difference was not significant on the non-nitrogen supply side. Furthermore, the nodule system exhibited a substantial buffering effect on exogenous nitrogen. In Experiment I, no significant differences were observed in the number, dry weight, or nitrogenase activity of nodules on the non-nitrogen-supplying side. The number and dry weight of nodules in Experiment II decreased by 61.55% and 35.91%, respectively. The specific nitrogenase activity (SNA) and acetylene reduction assay (ARA) also decreased by 32.28% and 67.20%, respectively, showing significant differences. In Experiment III, the number and dry weight of nodules in the upper layers decreased by 23.70% and 15.12%, respectively. Furthermore, significant differences in nitrogenase activity were detected, indicating that the nodules exposed to exogenous nitrogen spontaneously initiated the nitrogen regulation mechanism. This partially offsets the inhibitory effect on the nitrogen fixation function of nodules on the indirectly exposed side. This study revealed that exogenous nitrogen supply significantly affected the growth efficiency and nodule nitrogen fixation function of soybean plants by regulating nitrogen absorption and resource allocation. The use of deep unilateral fertilization can ensure the nitrogen fixation capacity of nodules and nitrogen accumulation in soybean plants and provide theoretical support for improving nitrogen use efficiency and realizing scientific fertilization. Full article

Dual-channel retailing empowers the manufacturer to benefit from market opportunities by producing customized items that fulfill client requirements. The manufacturer and retailer sell customized products, which allow customers to express their chosen style to increase both the likelihood of customers making a purchase and their level of satisfaction with the product. This trend is demonstrated by the current study, in which customized consumer items are considered through online and offline channels. On the other hand, cybersecurity has become a crucial aspect of the digital era, ensuring the protection of sensitive data, networks, and systems from cyberattacks and unauthorized access. This study develops with a modern cybersecurity framework to protect against cyberattacks and increase customer trust. This model is based on customized product design, cybersecurity investment, advertisement investment, and increasing the green level of customized products. The model is solved using both centralized policy and vertical Nash policy. Numerical results indicate that centralized profit is 2.37% more than the decentralized profit. Without investing in customized products and cybersecurity, the profit of the supply chain decreases by 2.33% and 1.99% for the centralized method, 1.28% and 1.15% for the vertical Nash method for the retailer, and 1.85% and 1.38% for the vertical Nash method for the manufacturer. Full article

When new purchasers or products are added in the supply chain management system, the recommendation system will face severe challenges of data sparsity and cold start. A knowledge graph that can enrich the representations of both procurement managers and products offers a promising pathway to mitigate the challenges. This paper proposes a knowledge-aware recommendation network for supply chain management, called KnoChain. The proposed model refines purchaser representations through outward propagation along knowledge graph links and enhances product representations via inward aggregation of multi-hop neighbourhood information. This dual approach enables the simultaneous discovery of purchasers’ latent preferences and products’ underlying characteristics, facilitating precise and personalised recommendations. Extensive experiments on three real-world datasets demonstrate that the proposed method consistently outperforms several state-of-the-art baselines, achieving average AUC improvements of 9.36%, 5.91%, and 8.81%, and average accuracy gains of 8.56%, 6.27%, and 8.67% on the movie, book, and music datasets, respectively. These results underscore the model’s potential to enhance recommendation robustness in supply chain management. The KnoChain framework proposed in this article combines purchaser-aware attention with knowledge graphs to improve the accuracy of purchaser SKU matching. The method can help enhance supply chain resilience and reduce returns caused by over-ordering, inventory backlog, and incorrect procurement. In addition, the model provides interpretable recommendation paths based on the knowledge graph, which improves trust and auditability for procurement personnel and helps balance environmental and operational costs. Full article

Growing climate concerns and rising consumer awareness of sustainability have reshaped strategic interactions in platform-based supply chains. This study examines how a manufacturer and an e-commerce platform make channel and fulfillment decisions under cap-and-trade regulation. The manufacturer chooses between non-encroachment and agency encroachment, while the platform decides between conventional and sustainable fulfillment. To capture the dynamic adaptation of boundedly rational agents, we develop an evolutionary game model (EGT) and characterize the evolutionary stable strategies. The findings indicate the following: (1) Platform investment in sustainable fulfillment exerts a strategic stabilizer effect, effectively protecting the reselling channel by reducing the manufacturer’s incentive to encroach even under moderate commission rates; (2) there exists a regulatory substitution effect between carbon pricing and commissions, where high carbon prices force manufacturers to encroach for survival, while low commissions encourage encroachment for profit; (3) consumer sensitivity exhibits a critical threshold behavior, where a synchronized transition to joint sustainability is impossible unless awareness exceeds a specific tipping point. Managerial insights suggest that platforms should view green logistics as a retention strategy to prevent channel fragmentation, while policymakers must coordinate carbon taxation with consumer awareness campaigns to avoid locking the system into non-green equilibria. Full article

Fisheries are fundamental for food security, and enhancing fishery industry chain resilience (FCR) is essential for safeguarding national supply and promoting high-quality development. With the rapid advancement of new quality productivity (NQP), its integration into the fishery industry chain provides a critical pathway to resilience enhancement and modernization. Using provincial-level data from China between 2012 and 2022, this study evaluates FCR across 29 provinces. A dual machine-learning framework is applied to assess the effects of a provincial NQP index on FCR and its underlying mechanisms. The results show that NQP has a statistically significant positive effect on overall FCR, with estimated coefficients ranging from 0.221 to 0.223 across model specifications. Dimension-specific analysis reveals pronounced heterogeneity: NQP significantly enhances resistance and recovery capacity (rr) as well as innovation and transformation capacity (it), while exerting a negative effect on adjustment and adaptive capacity (aa). Its impact on green ecological restoration capacity (ger) is positive but not statistically significant. Regional heterogeneity analysis shows that the resilience-enhancing effect of NQP is more pronounced in coastal provinces than in inland regions. Mechanism analysis suggests that improvements in labor productivity constitute a key channel through which NQP strengthens FCR. These findings highlight the importance of regionally differentiated strategies for promoting resilient and sustainable fishery development. Full article

Based on the “dual-driven” framework, this study uses data from A-share listed agricultural companies from 2012 to 2022 to empirically test the mechanism by which agricultural Supply Chain Finance (SCF) affects the performance of core enterprises via the dual paths of “efficiency” and “responsibility.” Drawing on transaction cost theory and corporate social responsibility perspectives, the analysis reveals several key findings. First, SCF significantly improves enterprise performance by reducing transaction costs (coefficient = 0.117, p < 0.01), with transaction costs playing a partial mediating role. Second, fulfilling the social responsibility of connecting with and leading farmers negatively affects enterprise performance due to increased transaction costs (interaction term coefficient = −0.423, p < 0.1), creating a sustainable efficiency–responsibility tension. Third, supply chain concentration strengthens the efficiency path of SCF (interaction term coefficient = 0.002, p < 0.1). Non-state-owned enterprises, large-scale enterprises, and enterprises with executives having a financial background are more sensitive to the dual-driven mechanism. This study provides policy-relevant implications for supply chain governance that coordinate economic and social benefits. Full article

Under the “dual carbon” goals, enhancing the energy supply for communication base stations is crucial for energy conservation and emission reduction. An individual base station with wind/photovoltaic (PV)/storage system exhibits limited scalability, resulting in poor economy and reliability. To address this, a collaborative power supply scheme for communication base station group is proposed. This paper establishes a capacity optimization configuration model for such integrated system and introduces a hybrid solution methodology combining random scenario analysis, Nondominated Sorting Genetic Algorithm II (NSGA-II), and Generalized Power Mean (GPM). Typical scenarios are solved using NSGA-II to generate a candidate solution set, which is then refined under operational constraints. The GPM method is applied to determine the final configuration by accounting for attribute correlations. A case study on a Chinese base station group, considering uncertainties in renewable generation, demonstrates the feasibility and effectiveness of the proposed approach. Full article

The rapid growth of e-commerce demands innovative solutions for resilient and sustainable supply chains. This study explores the role of AI-driven demand forecasting (AIDF) and AI-driven waste reduction (AIDWR) in enhancing supply chain efficiency, minimizing operational waste, and fostering sustainability. Analyzing data from 539 samples via PLS-SEM, the findings highlight how AIDF optimizes demand accuracy, reduces overproduction, and minimizes stockouts, while AIDWR lowers resource consumption and mitigates environmental impacts. Operational Waste Reduction mediates AI’s effectiveness, aligning efficiency with sustainability goals and promoting adaptable, environmentally conscious supply chains. These insights guide e-commerce managers in leveraging AI for resilience and sustainable growth. The study underscores the transformative potential of AI to meet dual objectives of operational excellence and sustainability. Full article