Search Results (343)

With the continued advancement of low-carbon campus transformation and the increasing penetration of renewable energy, campus integrated energy systems have become key infrastructure for green campus development. However, the highly random nature of student behavior causes dynamic fluctuations in electricity, heating, and cooling loads, creating major challenges for real-time supply-demand balance and economic system scheduling. To address this problem, this paper takes student behavior uncertainty as the core disturbance factor and proposes a flexible architecture-driven autonomous adaptation and multi-energy complementary optimization strategy. A closed-loop operation paradigm of signal–response–complementarity–regulation is established, in which dynamic electricity price signals, comfort-oriented guidance, and campus functional energy-zone division are combined to form a multi-level autonomous response chain. To improve solution efficiency, the electromagnetic wave propagation algorithm is further enhanced, and a Multi-Objective Electromagnetic Wave Propagation Algorithm (MEMWPA) is developed. Wave-impedance matching and energy-flux-density feedback mechanisms are introduced to strengthen convergence performance in complex multi-objective optimization problems. Comparative case studies show that the proposed strategy can effectively smooth the net load curve, reduce the campus peak load by 26.73%, and increase the load factor by 14.533 percentage points, thereby improving both operational flexibility and energy efficiency. Full article

Global supply chains are vital for sustainable development, yet firms often struggle to translate digital transformation into substantial environmental and social outcomes aligned with the SDGs. This study explores how digital technologies facilitate sustainable development through dynamic capabilities and green supply chain integration (GSCI). Using Dynamic Capabilities Theory, we propose and test a serial mediation framework with a two-wave, multi-country survey of senior supply chain and sustainability managers (n = 300), supplemented by archival ESG data from Bloomberg, Refinitiv, and CSMAR (2019–2023). Structural equation modeling shows that digital technologies contribute to sustainability outcomes only indirectly, by strengthening firms’ sensing, seizing, and transforming capabilities that drive internal and external green integration. Results suggest that policymakers should shift from hardware subsidies to ‘capability-oriented’ frameworks, incentivizing digital–green innovation hubs to help firms translate data into systemic sustainability integration. Full article

Market gardening is increasingly discussed as a sustainability-oriented farming model with the potential to support resilient, locally embedded food systems and to contribute to food security through diversified fresh-produce supply, short value chains, and closer producer–consumer relations. However, limited empirical evidence exists on the competences and training needs required for its professional and agribusiness development. This study examines perceived competence confidence and training priorities for market gardening across Ireland, Greece, France, Germany, and Austria. The research draws on 53 interviews with education and training providers and a cross-sectional survey of 275 respondents, including practitioners, advisory actors, and institutional stakeholders. The survey was structured around EntreComp, DigComp, and GreenComp to assess entrepreneurial, digital, and sustainability competences. The findings show that practitioners reported relatively strong confidence in motivation, vision, ethical thinking, environmental responsibility, and local contextual awareness, but weaker confidence in market research, resource mobilisation, record-keeping, planning, digital farm management, online sales, technical troubleshooting, stakeholder engagement, and participatory sustainability action. Advisory and institutional respondents rated entrepreneurial and sustainability competences as highly important, while digital competences were also considered relevant but showed stronger cross-country variation. The study concludes that market gardening education should move beyond technical horticultural instruction and adopt an integrated, competence-based curriculum combining entrepreneurial, digital, green, and practice-oriented learning. The findings highlight competence-development priorities that may strengthen market gardening and its potential contribution to local food availability, resilient short value chains, and food security. Full article

Upstream small- and medium-sized enterprises (SMEs) in emerging economies often face severe credit constraints. These constraints hinder green transformation by limiting green R&D investment and production capacity. To address this, we develop a Stackelberg-based governance strategy selection framework. We first analyze cost-sharing (CS) and equity-sharing (ES) contracts and then extend them by incorporating external financing, where the retailer’s contractual commitment serves as an operational guarantee. This integration leads to two incentive-financing bundles, namely CS-F and ES-F. Three main findings emerge. First, capital constraints fundamentally shape the feasibility of green supply chain governance by creating a trade-off between green R&D and physical production. Specifically, the CS contract is feasible only within an intermediate capital range, whereas the ES contract is infeasible. Second, the incentive-financing bundles relax capital constraints and expand the feasible governance region. Although all feasible governance strategies promote green R&D investment, the ES-F bundle remains more sensitive to parameter variations. Third, the optimal governance strategy depends primarily on firms’ capital conditions, shifting across CS, CS-F, and ES-F. Notably, a distributive-efficiency paradox emerges: even when the ES-F bundle yields greater total surplus, a higher sharing ratio violates the retailer’s individual rationality and prevents its adoption. We introduce an asymmetric Nash bargaining mechanism to address this paradox. The mechanism determines transfer payments endogenously and restores the efficient governance outcome. Overall, our findings help supply chain managers select appropriate governance strategies based on observable firm-level capital conditions. Full article

Background: Managing agrologistics supply chains under infrastructure scarcity requires integrative, spatially explicit decision-support tools. This study develops a macro-level digital twin of the multimodal agricultural supply chain in Kazakhstan’s Almaty region to optimize freight allocation and guide strategic investment planning. Methods: Our methodology integrates Earth observation data (ESA WorldCover 10 m) with a large-scale multimodal road–rail graph network (1.39 million nodes) to identify 135 crop production clusters. Using linear programming in MATLAB, we optimize the regional distribution of 322.2 thousand tons of seasonal maize, wheat, and soybeans while localizing new storage silos using Green Field Analysis. Results: The baseline simulation reveals a critical storage capacity deficit, yielding a Capacity Coverage Ratio of only 23.8%. However, implementing optimal multimodal rail-road routing mathematically reduces the Logistics Cost Index from 8,642,195 to 4,716,175 units, achieving overall cost savings of 45.4%. Conclusions: The proposed digital twin and its performance metrics provide a scientifically grounded, data-driven toolkit for public–private partnerships, ensuring robust infrastructure investment localization and facilitating the transition toward the Agriculture 4.0 paradigm. Full article

As the global agri-food system faces escalating climate-related challenges, developing localized low-carbon short food supply chains (SFSCs) has become a vital strategy for sustainable agriculture. To elucidate the psychological drivers of green consumer behavior within this context, this study integrates the Stimulus–Organism–Behavior–Consequence (SOBC) framework with the Theory of Planned Behavior (TPB). The aim is to investigate the continuous purchase intentions of Taiwanese consumers for organic cocoa. Data collected via an online survey from 377 consumers with prior cocoa consumption experience were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that personal attitudes and perceived behavioral control positively drive consumption intentions, whereas subjective norms do not. This suggests that consumption behaviors rely on substantive product evaluation rather than social pressures. Additionally, green product attributes and environmental values significantly enhance TPB constructs. Importantly, consumption intentions translate positively into perceived consumer effectiveness and continuous purchase intentions. By elucidating the psychological mechanisms underlying sustainable food choices, this study highlights the value of Taiwan’s “Tree-to-Bar” model. Practically, the findings highlight potential implications for policymakers and agribusinesses regarding how environmental attributes are communicated through front-of-pack (FOP) labels that emphasize local production and low-carbon mileage. Such approaches may help make environmental information more accessible to consumers, although their effectiveness should be evaluated in future research. Full article

Under the backdrop of the global economic transition towards high-quality development, green innovation has emerged as a pivotal driver in the pursuit of Sustainable Development Goals. However, enterprises often face financing constraints and high-risk challenges when engaging in green technology innovation. As a novel financial model that integrates financial resources with industrial operations, supply chain finance (SCF) has emerged as a potential solution. This study aims to investigate whether SCF effectively promotes corporate green innovation and to analyze its underlying mechanisms. Drawing on data from China’s A-share listed firms, this study measures corporate green innovation using patent data, which are identified from the IncoPat database based on the WIPO Green Inventory’s IPC classifications. Concurrently, firms’ deployment and depth of engagement in supply chain finance are assessed via textual analysis. The empirical findings demonstrate that SCF exerts a significant positive impact on fostering corporate green innovation. Mechanism analysis further uncovers that SCF enhances green innovation capabilities primarily through two pathways: mitigating financial constraints and accelerating the process of digital transformation. Results from the heterogeneity tests demonstrate that such an incentivizing impact is predominantly pronounced among enterprises characterized by superior ESG performance. Furthermore, our empirical investigation reveals a distinct inverted U-shaped pattern characterizing the nexus between SCF and corporate green innovation, which implies that an excessive dependence on SCF could ultimately impede innovative activities. We provide firm-level empirical evidence that deepens the understanding of SCF’s role in fostering green innovation, revealing that SCF is a key instrument for financial resources to integrate into the green transition. Policymakers and managers should utilize and develop SCF within a reasonable scale and focus on digital upgrading to achieve sustainable economic growth. Full article

Against the backdrop of increasing global uncertainty and the growing acceptance of sustainable development principles, enhancing supply chain resilience has become a core issue for enterprises in managing risks and ensuring operational security. Based on a review of the literature and theoretical analysis, this study constructs an evaluation system comprising 12 third-level indicators across three dimensions: proactive defense capability, green operational capability, and collaborative recovery capability. When determining whether there are interdependent relationships among the indicators, this study introduces an extended Bayesian fusion method based on trapezoidal fuzzy numbers to evaluate and confirm these relationships, thereby reducing biases arising from subjective judgments. By quantifying experts’ assessments of the relationship strength and confidence levels between indicators using trapezoidal fuzzy numbers, this method effectively integrates the opinions of multiple experts, reducing the randomness and subjectivity associated with individual judgments. During the ANP weight calculation stage, to overcome the ambiguity and uncertainty inherent in traditional pairwise expert comparisons, trapezoidal fuzzy numbers were similarly used to quantify the comparison results. These were then defuzzified using the mean area metric to construct a precise judgment matrix. Finally, using the publicly available annual reports and ESG disclosure data from three multinational corporations—one in the semiconductor manufacturing sector (Company T), one in industrial digital manufacturing (Company S), and one in the food and beverage industry (Company N)—as empirical samples, the cross-industry applicability and validity of the constructed evaluation system were verified. The results demonstrate that this method can systematically reflect the key factors influencing sustainable supply chain resilience and their weighting structure. Full article

This study examines how green supply chain management (GSCM) contributes to long-term supply chain viability (SCV) and whether supply chain resilience (SCRES) mediates this relationship. Drawing on dynamic capabilities theory, GSCM is conceptualised as a set of structured operational practices, SCRES as an adaptive capability, and SCV as a higher-order outcome reflecting sustained supply chain functioning under prolonged disruption. A cross-sectional survey was administered to 420 manufacturing firms in Saudi Arabia. GSCM and SCV were modelled as higher-order multidimensional constructs, whereas SCRES was modelled as a single reflective construct. The model was estimated using a two-stage hierarchical component approach, and structural relationships were tested using PLS-SEM with 5000 bootstrap resamples. GSCM was positively associated with SCRES (β = 0.465, p < 0.001) and SCV (β = 0.263, p < 0.001), and SCRES was positively associated with SCV (β = 0.438, p < 0.001) and partially mediated the GSCM–SCV relationship (indirect effect = 0.204; VAF = 43.7%). The model accounted for 21.7% of the variance in SCRES and 36.9% in SCV. The results integrate GSCM, resilience, and viability within a capability-based mediation framework and indicate that green practices are associated with long-term viability primarily through resilience capability. The findings carry direct implications for manufacturers operating under the policy ambition of Saudi Vision 2030 and the Saudi Green Initiative. Full article

This research concentrates on the electric vehicle (EV) industry in China and Japan. China is the largest and Japan the third-largest auto production country after the U.S. This study explores the current and future transition to battery electric vehicles and hybrid electric vehicles in Japan and China. Three Japanese auto companies, Toyota, Honda, and Nissan, and BYD from China are studied in this research. Toyota, Honda, and Nissan are actively pursuing the development of hybrid electric vehicles in Japan. Meanwhile, the research examines the Chinese EV company BYD, which is a major global competitor in the EV industry. This study compares the companies in terms of their strategies, strengths, weaknesses, and export destinations and delineates their competitive strategies and outlooks. In addition, the study examines the elements of the supply chain needed for building EVs, such as lithium, nickel, and cobalt. Furthermore, this research discusses some of the issues with EVs, such as the challenges related to the production and recycling of batteries and the implications as far as green and sustainable practices regarding EVs in the selected countries are concerned. The final part of this research explores how the production of EVs can affect the global reduction of carbon emissions. The findings of this study indicate that the transition to EVs depends on the structural position as far as the supply chain, the manufacturing of electric batteries, charging stations, and the size of the operations are concerned. The results indicate that BYD is in a stronger position in terms of the infrastructure necessary for the production of EVs. Meanwhile, Japanese auto companies are focused on hybrid EVs due to infrastructure related to EV batteries, supply sources, and charging stations. In addition, this research provides informative insights into the future of electric vehicles in the global market. The study offers recommendations for a comprehensive approach that integrates national policies, technological innovation, and the environmental impact of the transition to electric vehicles on a global scale. Full article

The purpose of this study was to examine the influence of green supply chain management on organizational sustainability, where technology innovation and environmental performance are taken as mediating factors. The focus of this study was on the increasing need for better protection of the environment and the increasing demands of the sustainable development of industries, especially in developing countries, where there are limited empirical data available on sustainability activities. The collected sample comprised 387 managers and technologists from Libyan manufacturing companies using a survey instrument and a stratified random sampling technique. Validity scales were used, and the measurements were done using the five-point Likert scale. The data analysis involved the use of PLS-SEM, where SmartPLS 4.0 was used. It entailed the analysis of the measurement model as well as the structural model, with the bootstrapping being done for 5000 samples. The findings show that GSCM significantly affects the OS. Specifically, it has a positive impact on environmental performance (EP) and technological innovation (TI), which, in turn, enhance the OS. Among the mediating factors, the EP was found to be the strongest predictor and mediator of the OS, followed by TI. The developed model proved to have a high explanatory power, with a coefficient of determination (R²) of 0.660. Thus, the integration of GSCM with innovation and environmental activities can lead to the successful achievement of sustainability objectives among manufacturing enterprises. The study’s limitations are associated with its cross-sectional design and its focus on managers. Future research could employ longitudinal designs and examine other contexts, such as digital transformation, the institutional environment, and the organizational culture. Full article

Highly perishable strawberries demand strict post-harvest time management, making accurate short-term yield prediction central to optimizing modern greenhouse production and supply chain scheduling. However, existing models that rely excessively on isolated environmental factors exhibit delayed responsiveness to actual crop physiological dynamics and struggle with integrating multimodal data. To overcome these limitations, we propose a short-term method for predicting greenhouse strawberry yield that integrates visual phenology with meteorological sequences. The proposed method was validated using a multimodal dataset acquired from 150 tracked greenhouse strawberry plants over a 72-day monitoring period (11 December 2025, to 20 February 2026), incorporating continuous microclimate records and an image repository of 784 original images annotated into five distinct phenological classes (flower, green, white, pink, and red). First, using our improved YOLO11-SC model, we effectively resolve challenges of complex illumination and dense foliage occlusion, achieving high-precision automated extraction of five consecutive strawberry phenological stages. Second, by fusing these visual markers with meteorological time series (e.g., temperature, humidity, and light intensity), we construct a multimodal spatiotemporal feature matrix. To accommodate diverse smart agriculture application scenarios, we designed two distinct prediction architectures: on servers with ample computing power, a Bidirectional Temporal Convolutional Network with self-attention (BiTCN-SA) to achieve highly accurate predictions; and for resource-constrained IoT edge nodes, a lightweight machine learning ensemble (Stack-LGR). Experimental results demonstrate that, in predicting the cumulative mature fruit yield within the next harvesting cycle, BiTCN-SA achieves strong performance with a coefficient of determination ($R^2$) of 0.958 and a root mean square error (RMSE) of 3.154. Simultaneously, the edge-deployed Stack-LGR ensemble maintains stable prediction accuracy ($R^2$ = 0.892) while ensuring acceptable inference latency. This study mitigates the latency limitations of single-environment-driven models. It provides a solution for precise crop yield prediction and tiered computational deployment, with good predictive performance, deployment adaptability, and methodological reference value. Full article

Food safety systems are increasingly challenged by globalized supply chains, emerging contaminants, and the need for rapid decision-making before contaminated products reach consumers. Although conventional methods remain essential for confirmatory analysis, their dependence on centralized facilities, specialized personnel, and time-intensive workflows limits their suitability for real-time monitoring. Sustainable nanotechnology offers a promising approach to address these limitations by enabling rapid, sensitive, portable, and resource-efficient contaminant detection. This review critically examines recent advances in nano-enabled platforms for detecting foodborne pathogens, toxins, pesticide residues, heavy metals, allergens, and other food-related contaminants. Emphasis is placed on colorimetric, fluorescent, electrochemical, surface-enhanced Raman scattering, and biosensor-based systems employing sustainable nanomaterials, including biopolymer nanoparticles, carbon-based nanostructures, metal and metal oxide nanoparticles, quantum dots, and hybrid nanocomposites. The roles of green synthesis, low-toxicity materials, reduced solvent use, and safe-by-design strategies are evaluated in relation to environmental sustainability and practical implementation. The integration of nanosensors with smart packaging, portable devices, Internet of Things platforms, artificial intelligence, and data-driven risk assessment is also discussed. Key challenges include matrix interference, reproducibility, sensor stability, scalability, regulatory approval, environmental fate, and consumer acceptance. Continued progress will require validated, scalable, and environmentally responsible technologies capable of reliable operation under real-world food system conditions. Full article

The palladium market represents a critical role in supporting key industrial sectors and facilitating the energy transition, as it is widely used in the automotive industry, electronics, chemical manufacturing, and hydrogen energy. These sectors influence a steady demand amid tightening environmental regulations and the development of green technologies. The aim of this study is to assess the structural transformation of the global palladium market through 2030 and to project Russian palladium production for 2026–2028 amid the energy transition by applying economic-mathematical methods, including linear regression, the Grey forecasting model, exponential smoothing, and Autoregressive Integrated Moving Average (ARIMA) time-series modeling. Particular attention is paid to the analysis of factors influencing the dynamics of the global palladium market, including the electrification of transportation, the substitution of palladium with alternative materials, and changes in global supply chains. The simulation results showed that the exponential smoothing model possesses the highest predictive accuracy, enabling it to estimate future palladium production volumes. The market is undergoing a structural transformation: declining demand from the traditional automotive sector is partially offset by the development of new applications in hydrogen energy, electronics, and advanced materials, suggesting that technological improvements can compensate for the loss of conventional demand segments. The key findings are (1) exponential smoothing (R² = 0.9812) outperforms linear regression, Grey model, and ARIMA; (2) Russian palladium production is projected at 74–130 tonnes (2026), 63–141 tonnes (2027), and 54–150 tonnes (2028); and (3) the decline in automotive demand is partially offset by new applications. Our findings confirm the need for Russian producers to adapt their strategies to the structural transformation of global demand, deepen domestic processing, and develop new high-tech applications for palladium to maintain their competitive positions amid the energy transition. Full article

This research investigates how CE initiatives, interpreted as manifestations of corporate social responsibility, shape green value co-creation, green collaborative culture, and green supply chain integration across both supplier and customer contexts. The proposed conceptual framework also explores the possibility that digital maturity can moderate these interrelations, based on signaling theory. Empirical results, obtained through PLS SEM and NCA on a data sample of 493 suppliers and customers, confirm that CE practices have a significant positive impact on green value co-creation, which, in turn, influences the green collaborative behavior of the actors and the integration of the supply chain. The moderating role of digital maturity is reinforced in the linkages between green value co-creation, collaboration, and integration. Thereby, their effectiveness is strengthened. This study adds to the literature by proposing an integrative relationship between CE practices and outcomes within the supply chain dyad, offering a rare empirical study of relationships between suppliers and organizations in an emerging economy, and shedding light on the boundary condition of digital maturity within these relationships. The results have significant implications for managers seeking to maximize their sustainability performance through circular practices and digital capabilities. Full article