Search Results (101)

Numerous construction enterprises have insufficient efficiency in resource utilization for construction and demolition waste (CDW), restricting global circular economic development. How to improve resource utilization has become an urgent problem. While existing studies have extensively explored operational decisions in CDW resource supply chains, insufficient attention has been given to construction enterprises’ information misreporting and its interaction with on-site conversion efficiency. This paper aims to elucidate the mechanism of action of misreporting and systematically analyzes its effects on the pricing decisions of the CDW supply chain. Drawing on information misreporting theory, this study constructs a Stackelberg game model involving construction firms and recycled building materials manufacturers, and compares supply chain decision-making behaviors under two scenarios: information misreporting and honest disclosure. The main conclusions are as follows: (1) misreporting alters recycled building material pricing and profit distribution by affecting manufacturers’ supply capacity expectations; (2) higher on-site conversion efficiency enhances CDW treatment ability and affects stakeholders’ profits; and (3) misreporting is related to on-site conversion efficiency and onsite conversion costs—enterprises prefer misreporting for short-term gains under low on-site conversion efficiency or high costs, while higher on-site conversion efficiency makes truthful disclosure conducive to long-term stable returns. This paper reveals the CDW supply chain decision-making mechanism from enterprises’ perspective, providing a new theoretical basis and practical value for CDW utilization and supply chain optimization. Full article

The rapid growth of the sharing economy has improved resource utilization in car-sharing, yet it has also sharpened market competition and diversified user demand. A persistent obstacle is the low coordination efficiency between asset-heavy operating companies and traffic-driven platforms, whose misaligned objectives waste social resources. This paper uses differential game theory to analyze their dynamic coordination strategies and benefit allocation mechanisms. The Nerlove–Arrow model captures the evolution of brand goodwill, while the company’s decisions on station layout, vehicle dispatch, and pricing, together with the platform’s advertising investment, form the core decision variables in a two-party game framework linking the asset side and the traffic side. Compared with the non-cooperative Nash equilibrium, the cooperative mode removes the double marginalization effect, strengthens the investment incentives of both parties, and raises the system’s steady-state goodwill and total profit, achieving a Pareto improvement. To ground the cooperative framework in rigorous theory, we supply a verification theorem confirming that the linear candidate value functions satisfy the Hamilton–Jacobi–Bellman equations over the entire admissible state space. A formal proof of instantaneous rationality ensures that neither party falls into a cooperation trap on the horizon $[0,T]$, and the asymptotic stability of the steady-state goodwill trajectory is established. We further endogenize the revenue-sharing coefficient through a generalized Nash bargaining model that admits asymmetric bargaining structures, and introduce a Stackelberg leadership benchmark as a third comparative regime. Sensitivity analyses with respect to the discount rate and user heterogeneity confirm the robustness of the findings. A dedicated discussion section bridges the gap between idealized parameterization and data-driven calibration, describing practical pathways via A/B testing, user churn metrics, and econometric estimation of demand parameters. The results offer a scientific decision-making reference for strategic cooperation in the car-sharing industry. Full article

Given the global increase in beef consumption, cull dairy cows are an underutilized resource, mostly destined for low-value ground beef, despite their potential for premium cuts. This review summarizes recent evidence on pre- and post-mortem strategies specifically aimed at improving meat quality in cull dairy cows, addressing a topic that has been little studied. Finishing diets notably increased intramuscular fat by 112% after 4 months of feeding, enhanced carcass yield, and reduced shear force. Wet aging can improve tenderness by approximately 30% during the first 7 days when combined with finishing diets at a lower operating cost, whereas dry aging enhances intense flavors, albeit with greater losses due to dehydration. Innovations such as vascular rinsing and mechanical tenderizing show promising results, although their adoption is limited by technical requirements and costs. The implementation of these strategies can generate economic benefits by revaluing discarded meat (≈25% higher retail price) and sustainability by reducing waste in livestock systems. However, heterogeneity in breed, age, and management requires adapted approaches. Additional studies integrating productive, sensory, and economic aspects, as well as research on consumer acceptance, are needed to facilitate their adoption on an industrial scale and contribute to more efficient and sustainable meat production. Full article

The advancement of rural urbanization has led to a steady increase in construction and demolition waste (CDW) in rural areas; its dispersed nature complicates management efforts, yet existing research has not sufficiently explored the synergistic effects of subsidies and transportation costs. In this paper, a Stackelberg game model is constructed among the government, farmers, and manufacturers within the framework of a reward–penalty mechanism (RPM), and rural governance efficiency is introduced to characterize regulatory enforcement losses. Furthermore, on the basis of existing research and discussions with experts in the construction industry, this study conducted numerical simulations of key parameters by integrating multiple data sources and calibrating parameters. The aim was to analyze the mechanisms through which key factors—such as differences in subsidy structures and transportation costs—influence the decision-making behavior of farmers and manufacturers, as well as the equilibrium outcomes of the supply chain. The results indicate that (1) the reward–penalty mechanism has a significant and nonlinear effect on the decision-making of the parties involved; (2) although subsidy intensity promotes technological investment, its impact on revenue and pricing varies because of transportation cost constraints; (3) the proportion of additional subsidies for farmers is key to policy coordination, and a reasonable subsidy structure can simultaneously improve both economic and environmental performance; and (4) as a key constraint, farmers’ transportation costs play a significant moderating role in the effectiveness of regulatory measures. This paper reveals the decision-making mechanisms of rural CDW resource recovery supply chains under multiple constraints from a farmer-led perspective, providing a reference for promoting rural CDW resource recovery. Full article

Food waste presents a significant challenge to sustainable development, resulting in annual economic losses of more than USD 1 trillion. It contributes to 8–10% of global human-caused greenhouse gas emissions and accounts for nearly 30% of agricultural land use. Households are responsible for over half of this waste, with fruits and vegetables being the most frequently discarded items. This highlights the urgent need to promote sustainable consumption habits. This 2024 study surveyed a sample of 923 individuals who consume at least one of four categories: fresh fruits, fresh vegetables, processed fruits, or processed vegetables. It used cluster analysis to segment consumers based on the amount of food waste and fruit and vegetable losses. Three distinct segments were identified. Cluster 1 (Proactive & aware, 56%): Characterised by high environmental awareness (approximately 75%) and efficient food management skills, such as frequent shopping list preparation (48%), resulting in the lowest wastage levels. Cluster 2 (Convenient & situational, 38%): Driven by “convenience waste” mechanisms, where lack of time, poor portioning (44%), and a lack of culinary ideas lead to moderate waste levels despite mid-range awareness. Cluster 3 (Disorganised & wasteful, 6%): Reveals a significant attitude–behaviour gap; despite declaring a desire to limit waste, this group reported the highest perceived levels of waste. This is partly explained by the reverse sunk cost fallacy, where produce from own cultivation is devalued due to the absence of a market price. The findings emphasise that food waste is not a monolithic phenomenon but results from diverse behavioural deficits. The results provide a foundation for tailored behavioural interventions (nudges) and educational strategies to enhance food management skills and contribute to the achievement of sustainable development goals (SDGs). Full article

Stock price forecasting remains an extremely challenging problem due to the non-stationary nature of financial markets. Recent deep learning approaches model complex stock correlations by learning temporal patterns from individual stock series and then aggregating cross-stock information. However, existing methods select which alpha factors to trust using static projections of market features, ignoring how market regimes evolveover the lookback window—a “recovering from a crash” regime and a “new bull market” produce similar instantaneous statistics but require different factor selections. Moreover, standard MSE training objectives weight all stocks equally, wasting gradient signal on mid-ranked stocks that never enter a long–short portfolio. To address these issues, we introduce StockMamba, a State-Space Gated Stock Transformer with Rank-Aware Optimization. StockMamba replaces static market gating with a Mamba-2 state-space model that scans market regime dynamics in linear time and produces time-varying factor gates via temperature-controlled softmax. For training, StockMamba pairs cross-stock attention and temporal distillation with a U-shaped Rank-Position Loss that concentrates gradients on the head and tail stocks where portfolio P&L is determined. Experiments on CSI-300 and CSI-800 with the Qlib pipeline show that StockMamba achieves 12.1% higher IC and 15.0% higher Rank IC over the MASTER baseline on CSI-300 (13.5% and 14.8% on CSI-800), with ablation studies confirming the contribution of each proposed module. A cross-market evaluation on S&P 500 further confirms that the gains generalize to a structurally different market (9.5% higher IC over MASTER), and a Kolmogorov–Smirnov test on the learned factor gates provides statistical evidence that the gating mechanism is genuinely regime-dependent. Full article

A thermo-economic valuation framework is proposed to assign an economic value to industrial waste heat streams. The methodology integrates thermodynamic heat-quality degradation, represented through logarithmic mean temperature difference (LMTD)-based thermal decay, with market-indexed valuation using natural gas substitution benchmarks. To account for operational uncertainty, a Monte Carlo simulation and a two-state Markov chain were implemented to represent stochastic dispatch conditions of natural gas engines within an industrial park configuration. The results indicate that operational variability has a limited influence on waste heat valuation compared with the dominant effect of natural gas price indexation and transport-distance-related thermal degradation. Under the representative case study conditions, supplier revenues ranged from approximately USD 60,000 to USD 320,000 per year depending on prevailing gas prices, while consumers achieved estimated energy cost reductions between 22% and 62%. An exergy-based comparison was additionally performed to contextualize the thermodynamic quality of the recovered heat stream. The proposed framework provides a practical methodology for evaluating industrial waste heat under localized energy exchange and fuel substitution applications. Full article

The high-value utilization of construction and demolition waste is critical for sustainable development in the building sector. However, in construction and demolition waste (CDW) recycling supply chains, existing studies lack a systematic analysis of pricing mechanisms for such recycled CDW as substrate products, particularly regarding interest coordination and the quantification of green value. To reveal the bargaining mechanism between farmers as recyclers and processors and supermarkets as retailers under an asymmetric bargaining structure, this study applies Nash bargaining theory to construct a dynamic game model. The study revealed that (1) when the green degree of a product reaches a certain level, it can obtain a sustainable market premium and create a stable income space for both parties. (2) The relative strength of the bargaining power between the two sides significantly affects the impact of market base scale changes on profit distribution. When the bargaining power of the supermarket is lower than the threshold and the bargaining power of the farmers is higher than the threshold, the difference in profit between the farmers and the supermarket is negatively correlated with the market base scale of the CDW as a substrate. (3) The green sensitivity level of consumers affects the difference in profit of the main body with the government subsidy to farmers. This level is determined by the value of the green sensitivity coefficient of consumers and presents a differentiated adjustment effect in different value ranges, which in turn affects the transmission direction of government subsidies to profit distribution. (4) When the green sensitivity coefficient and the green communication intensity of farmers and the investment level are lower than the corresponding critical values, the difference in social welfare with or without subsidies is positively correlated with the amount of the subsidy. This study provides decision support for farmers and supermarkets in designing rational bargaining strategies and offers insights for improving coordination and sustainability in construction and demolition waste recycling supply chains. Full article

The transition toward sustainable food systems requires innovative approaches to managing perishable products, where inefficient inventory practices contribute significantly to global food loss and environmental degradation. This study develops a circular-economy-oriented inventory optimisation framework for dairy supply chains that integrates environmental externalities and waste valorisation pathways into operational decision-making. Departing from traditional linear “produce–consume–dispose” models, this study embeds three core sustainability mechanisms into a stochastic dynamic-programming framework: (1) progressive environmental cost internalisation aligned with EU Emissions-Trading System carbon pricing, capturing both waste-related emissions and cold-chain energy footprints; (2) circular-economy value-recovery channels that redirect near-expiry products to secondary applications (animal feed, biogas production, industrial processing) rather than disposal; and (3) deterioration-aware demand management that minimises resource throughput while maintaining service levels. Empirical calibration using Ukrainian dairy industry data demonstrates that sustainability-integrated inventory policies reduce waste generation by 4.8–10% relative to conventional approaches, with high-deterioration products showing the greatest potential for improvement. The authors identify a critical threshold in the circular economy: when salvage recovery rates exceed 35%, waste becomes an economic and ecological asset, fundamentally altering the sustainability calculus of inventory decisions. Environmental costs account for 4.6% of total operating expenses at current carbon prices, a share projected to increase substantially as climate regulations tighten. The findings provide actionable guidance for dairy supply chain stakeholders pursuing the Sustainable Development Goals (SDGs 2, 12, 13): processors should establish circular-economy partnerships that achieve salvage rates above 35%, implement product-specific policies for high-deterioration items, and proactively integrate carbon pricing into inventory optimisation. The framework bridges sustainable operations theory and circular economy practice, offering a replicable model for transitioning perishable food supply chains toward closed-loop, low-waste configurations that simultaneously reduce environmental impact and enhance economic performance. Full article

Reducing food waste and promoting green consumption have emerged as critical priorities in the transition toward a more sustainable food system. Purchasing near-expired food (NEF) offers a pathway to address both issues simultaneously, yet the mechanisms underlying consumers’ intentions toward such products remain underexplored. This research investigates these mechanisms through two complementary studies conducted in China, focusing on near-expired bread as a representative product category. Study 1 (N = 1154) draws on the stimulus–organism–response (SOR) framework to examine how key factors shape consumers’ purchase intentions toward near-expired bread. The results show that price discounts and longer remaining shelf life increase purchase intentions by enhancing perceived value and reducing perceived risk. Moreover, consumers’ normative beliefs with regard to food waste avoidance positively predict purchase intentions through heightened moral satisfaction. Study 2 (N = 746) employs a 2 × 3 between-subjects factorial experiment to test two types of retail interventions for near-expired bread: discount messages (50% vs. 10% off) and information framing (gain-framed vs. loss-framed). Extending Study 1, this experiment introduces two additional dependent variables—product attitudes and perceived environmental external benefits—to capture a broader range of consumer responses. ANCOVA results reveal that consumers with higher environmental concern exhibit stronger purchase intentions, more favorable product attitudes, and greater perceived environmental external benefits. Price discount messages significantly influence purchase intentions and product attitudes, whereas information framing affects purchase intentions and environmental external benefits. Notably, the two interventions interact to shape consumers’ perceptions of environmental external benefits. Together, these studies advance a comprehensive understanding of near-expired bread purchases and offer empirical guidance for designing effective retail communication strategies to promote green consumption and reduce food waste. Full article

Consumer food waste is a major global challenge to sustainable development, generating massive carbon and water footprints, exacerbating food insecurity, and undermining the United Nations Sustainable Development Goals. While extensive research has documented individual and contextual drivers of consumer food waste, critical gaps remain in understanding how core marketing tools shape wasteful behavior, particularly the unintended post-purchase consequences of ubiquitous price promotions. Addressing this gap, we unpack the psychological mechanism underlying the classic social dilemma of promotions: short-term individual economic savings from discounts conflict with long-term collective ecological welfare. Across four rigorous studies, including a real-world field experiment in a university canteen, we establish a causal effect of price promotions on increased consumer food waste behavior. We further demonstrate that this effect is mediated by enhanced perceived resources: price promotions generate subjective feelings of windfall gains and resource abundance, which in turn increase consumers’ willingness to discard edible food. We identify two practical actionable boundary conditions that attenuate this pro-waste effect: the impact of price promotions on food waste is eliminated when consumers focus on money spent (rather than money saved) from the transaction, and when they perceive their spending as exceeding their psychological budget. Our findings advance the literature on price promotions and sustainable consumption by documenting a previously unrecognized hidden cost of promotional marketing, unpacking the micro-psychological foundations of the social dilemma in food waste decisions, and providing evidence-based, actionable implications for policymakers, food retailers, and food service operators to curb promotion-induced food waste. Full article

The circular economy paradigm offers a critical framework for addressing agricultural sustainability challenges, yet limited empirical evidence exists regarding how ecological innovations create simultaneous value across environmental, economic, and social dimensions. This study examines stakeholder value creation mechanisms through a 200-day longitudinal case study (March–October 2025) of Fuyang, China’s ecological transformation utilizing exciton-mineral technology for livestock waste valorization. The mixed-methods approach combined environmental monitoring, economic performance data, social surveys (n = 4523), and governance document analysis across operations processing 3000–4500 tons of poultry waste monthly. Results indicated significant environmental improvements including 99.4% odor reduction (NH₃: 999 → 5.6 ppm), 387% soil biodiversity increase, and 42% methane emission reduction. Economic benefits included +20% farmer net profit and +57% egg price premium. Social outcomes encompassed 96.2% resident satisfaction and complete elimination of odor complaints. Governance innovation established China’s first permit-free bio-mineral production system. The findings suggest that ecological innovations embedding circularity as automatic outcomes, rather than requiring behavioral coordination, can accelerate circular agriculture transitions beyond policy mandates, pointing to a potentially scalable model for sustainable production–consumption systems in developing economies. Full article

Agri-food supply chains are highly exposed to freshness deterioration, demand uncertainty, and information asymmetry. In practice, upstream suppliers may strategically misreport freshness-related information to influence downstream procurement decisions, which can amplify inefficiency and increase food loss and waste. This study develops an analytical framework that integrates (i) strategic freshness misreporting by an informed supplier, (ii) endogenous investment in blockchain-enabled traceability that improves information credibility at a cost, and (iii) contract design for supply chain coordination. We consider a two-echelon agri-food supply chain with stochastic demand and freshness-dependent valuation, and characterize equilibrium operational decisions under centralized and decentralized settings. The results reveal how misreporting reshapes optimal order quantities, wholesale prices, and profit allocation, and identify conditions under which misreporting increases expected waste and undermines sustainability performance. We then examine how traceability investment changes the incentives of both parties, leading to adoption thresholds and potential incentive misalignment under decentralization. Finally, we design revenue-sharing, cost-sharing, and combined contracts and derive parameter regions that coordinate the blockchain-enabled agri-food supply chain and generate Pareto improvements for both the supplier and the retailer. Numerical experiments illustrate the comparative statics and quantify the trade-offs among profitability, transparency, and waste reduction. Relative to existing blockchain-enabled agri-food supply chain models, the framework jointly endogenizes supplier misreporting of freshness, blockchain-based traceability investment, and contract parameters, thereby uncovering new adoption thresholds and coordination regions that tightly link transparency decisions to food loss and waste. The findings provide actionable guidance for using digital traceability and contract mechanisms to curb opportunism, enhance coordination, and support sustainable agri-food supply chains. Full article

The demand for computing power has increased at a rate never seen before due to the quick development of artificial intelligence (AI) technologies and applications. Consequently, AI data centers, referring to computing facilities specifically designed for large-scale artificial intelligence workloads, have become one of the fastest-growing electricity consumers globally. Therefore, it is essential to understand the load characteristics of AI data centers and their impact on the grid. This paper provides a comprehensive review of the evolving energy landscape of AI data centers. Specifically, this paper (i) presents the energy consumption structure in AI data centers and analyzes the key workload features and patterns in four stages, emphasizing how high power density, temporal variability, and cooling requirements shape total energy use, (ii) examines the impacts of AI data centers for power systems, including impacts on grid stability, reliability and power quality, electricity markets and pricing, economic dispatch and reserve scheduling, and infrastructure planning and coordination, (iii) presents key technological, operational and sustainability challenges for AI data centers, including renewable energy integration, waste heat utilization, carbon-neutral operation, and water–energy nexus constraints, (iv) evaluates emerging solutions and opportunities, spanning grid-side measures, data-center-side strategies, and user-side demand-flexibility mechanisms, (v) identifies future research priorities and policy directions to enable the sustainable co-evolution of AI infrastructure and electric power systems. The review aims to support utilities, system operators, and researchers in maintaining reliable, resilient, and sustainable grid operation in the context of the rapid development of AI data centers. Full article

Egypt’s municipal solid waste (MSW) sector faces persistent challenges due to increasing generation rates, limited recovery, and a high organic fraction, motivating the selection of appropriate biological treatment options within Mechanical–Biological Treatment (MBT) systems. This study compares composting-based MBT and biodrying-based MBT for a case application in Alexandria, Egypt, using an integrated techno-economic and greenhouse gas (GHG) assessment. Discounted cash-flow modelling was applied using defined CAPEX and OPEX, along with revenue from recovered products. GHG accounting used documented emission factors and activity data against an unmanaged landfill baseline representative of current disposal practices. The system boundary covers waste reception and mechanical processing, biological treatment, process energy use, and residual disposal. Results show that composting achieves higher financial performance (NPV USD 2.55 million) than biodrying (NPV USD 0.99 million), while delivering a 48.5% reduction in net system GHG emissions relative to the baseline. Sensitivity analysis indicates that the comparative ranking is primarily driven by electricity prices, revenue assumptions, CAPEX, and baseline-related emissions parameters. Under the defined assumptions, composting is the preferred MBT biological pathway for the analyzed case, and interpretations are limited to the evaluated boundaries. Full article