Search Results (76)

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

As low-carbon supply chains increasingly integrate green transition strategies with digital transformation, coordinating high-cost green technology investments with data-driven marketing (DDM) becomes a complex managerial task. While these dual investments are essential for market growth, the inherent tension between economic efficiency and fairness concerns often triggers strategic friction phenomenon whose impact under cap-and-trade regulations remains insufficiently explored. This paper investigates the strategic implications of fairness concerns in a low-carbon supply chain in which a manufacturer invests in carbon emission reduction and a retailer engages in data-driven marketing (DDM), under a cap-and-trade regulation. We formulate four Stackelberg game models—Neutral Benchmark (NF), Retailer Fairness (RF), Manufacturer Fairness (MF), and Bilateral Fairness (BF)—to analyze the interplay between behavioral equity and economic efficiency. The main analytical results indicate that (1) fairness concerns universally function as an “efficiency tax” on the supply chain system, where the rational benchmark consistently yields the highest system efficiency. In contrast, bilateral fairness concerns lead to the worst performance due to double friction effects. (2) Counter-intuitively, the retailer can “weaponize” fairness concerns to extract surplus from the leader. Specifically, in environments with high carbon emission reduction costs, a fairness-concerned retailer compels the manufacturer to grant significant wholesale price concessions, thereby achieving higher profits than in a purely rational setting. (3) The manufacturer’s fairness creates a “Benevolence Trap” for the follower; to balance equity, a fair manufacturer tends to underinvest in green technologies, which severely contracts market demand and, unlike the retailer fairness scenario, fails to yield economic benefits for the retailer. (4) A critical “regime-switching” dynamic exists regarding the carbon trading price. While the retailer benefits from fairness strategies in nascent carbon markets, a pivot to rationality becomes optimal as carbon prices surge and efficiency dividends dominate. These findings offer novel managerial insights for supply chain members to navigate behavioral complexities and for policymakers to align incentive mechanisms. Full article

The paper introduces a real-time digital-twin controller that manages evacuation routes while operating GEEM for emergency energy management during building fires. The system consists of three interconnected parts which include (i) a physics-based hazard surrogate for short-term smoke and temperature field prediction from sensor data (ii), a router system that manages path updates for individual users and controls exposure and network congestion (iii), and an energy management system that regulates the exchange between PV power and battery storage and diesel fuel and grid electricity to preserve vital life-safety operations while reducing both power usage and environmental carbon output. The system operates through independent modules that function autonomously to preserve operational stability when sensors face delays or communication failures, and it meets Industry 5.0 requirements through its implementation of auditable policy controls for hazard penalties, fairness weight, and battery reserve floor settings. We evaluate the controller in co-simulation across multiple building layouts and feeder constraints. The proposed method achieves superior performance to existing AI/RL baselines because it reduces near-worst-case egress time ($T_{95}$ and worst-case exposure) and decreases both event energy $E_{\mathrm{e}\mathrm{v}\mathrm{e}\mathrm{n}\mathrm{t}}$ and CO₂-equivalent ${{CO}_2}_{\mathrm{e}\mathrm{v}\mathrm{e}\mathrm{n}\mathrm{t}}$ while upholding all capacity, exposure cap, and grid import limit constraints. A high-VRE, tight-feeder stress test shows how reserve management, flexible-load shedding, and PV curtailment can achieve trade-offs between unserved critical load $U_{\mathrm{e}\mathrm{n}\mathrm{e}\mathrm{r}\mathrm{g}\mathrm{y}}$ and emissions. The team delivers implementation details together with reporting templates to assist researchers in reaching reproducibility goals. The research shows that emergency energy systems, which integrate evacuation systems, achieve better safety results and environmental advantages that enable smart-city integration through digital thread operations throughout design, commissioning, and operational stages. Full article

Under the tightening carbon reduction policies, port microgrids face the challenge of optimizing the installed capacity of multiple power generation types to reduce operating costs and increase renewable energy penetration. We develop a bi-level cost-optimization framework in which the upper level decides long-term capacities (PV, wind, gas turbine, bio-fuel unit, and battery energy storage), and the lower level dispatches a multi-energy port microgrid (electricity–heat–cold) on an hourly basis with frequency regulation services. To ensure rigor and reproducibility, we (i) move the methodology upfront and formalize all constraints, (ii) provide a dedicated data–preprocessing pipeline for multi-region 50/60 Hz frequency time series, and (iii) map a policy intensity index to a carbon price and/or an annual cap used in the objective/constraints. The bi-level MILP is solved by a column-and-constraint generation algorithm with optimality gap control. We report quantitative metrics—annualized total cost, CO₂ emissions (t), renewable shares (%), and regulation cycles—across scenarios. Results show consistent cost–carbon trade-offs and robust capacity shifts toward storage and biofuel as policy tightens. All inputs and scripts are organized for exact replication. Full article

This study examines green investment and emission reduction strategies in a two-tier supply chain under dual-carbon regulation that combines a carbon tax with a cap-and-trade mechanism. A multi-stage dynamic game model is developed, in which the manufacturer reduces emissions through recycling efforts and investments in green technology. We compare optimal decisions under centralized, decentralized, and coordinated structures, and propose an enhanced bilateral cost-sharing contract to improve collaboration. Numerical experiments validate the theoretical results, and sensitivity analyses provide further insights. The results show that while both carbon tax and permit trading increase emission reduction, the carbon tax may lower manufacturer profit, underscoring the need for coordinated policy design. Benchmarking proves more effective than grandfathering in stimulating green investment, particularly under high carbon prices and strong consumer environmental preferences. The proposed contract alleviates free riding, enhances overall supply chain profitability, and improves emission reduction performance. Policy implications highlight the importance of prioritizing benchmark allocation, promoting consumer environmental awareness, and encouraging firms to integrate carbon asset management with technological innovation. This research provides both theoretical and practical insights for designing effective carbon policies and collaborative mechanisms in green supply chains. Full article

As one of the main sources of global greenhouse gas emissions, the low-carbon transformation and emission reduction in the construction industry are inevitable requirements for addressing climate change. Under cap-and-trade regulations, Carbon emission rights have become a key production factor. However, the price of carbon emission rights is highly random. Taking the EU carbon market in 2024 as an example, the carbon price fluctuated by more than 35%, soaring from 65 euros per ton to 80 euros per ton and then falling back. Such sharp fluctuations not only increase the cost uncertainty of enterprises but also complicate the investment decisions for emission reduction. Therefore, enterprises can enhance the flexibility of carbon emission rights trading decisions through option strategies, helping them hedge against the risks of carbon price fluctuations, and at the same time improve market liquidity and risk management capabilities. Against this background, based on the carbon cap-and-trade policy, this paper introduces the two-way option strategy into the construction supply chain game model composed of general contractors and subcontractors, and studies to obtain the optimal carbon reduction volume, carbon option purchase volume, maximum expected profit of general contractors, subcontractors and profit distribution ratio. This study shows that two-way options play a crucial role in optimizing supply decision-making and emission reduction strategies. Under the decentralized model, emission reduction responsibilities are often shifted to subcontractors by the general contractor, resulting in a decline in overall mitigation effectiveness. Furthermore, appropriately lowering the carbon emission benchmark can strengthen enterprises’ incentives for emission reduction and significantly enhance the profitability of the supply chain. The study further suggests that general contractors should enhance their competitiveness by developing environmentally friendly technologies and improving their ability to reduce emissions on their own. Meanwhile, subcontractors need to actively participate in the collaborative efforts through revenue-sharing contracts. This study reveals the strategic value of two-way carbon options in construction supply chain carbon trading and provides theoretical support for the formulation of carbon market policies, contributing to the low-carbon transition of the construction supply chain. Full article

To analyze the effects of remanufacturing subsidies and emission reduction investments on pricing and quality decisions under cap-and-trade regulation, four profit-maximization Stackelberg game models for a remanufacturing supply chain (RSC), i.e., without remanufacturing subsidies and emission reduction investments, with remanufacturing subsidies only, with emission reduction investments only, and with both remanufacturing subsidies and emission reduction investments, are constructed, derived, compared, and analyzed. Results show that government subsidies and emission reduction investments can improve profits for the RSC members, while possibly leading to more total carbon emissions. Furthermore, it is worth noting that profit growth and emission reduction can be achieved even though reducing remanufacturing subsidies in some scenarios. Moreover, increasing emission reduction targets will reduce profits of the RSC members but does not necessarily contribute to emission reduction. Therefore, to help the RSC improve profits and reduce emission, the policymaker should formulate differentiated policies based on the types of manufacturers. For the non-abating manufacturer, the government should set higher emission reduction targets and cut down subsidies; for the low-efficiency abating manufacturer, higher emission reduction targets and subsidies are more suitable. However, for the high-efficiency abating manufacturer, lower emission reduction targets and subsidies are more effective. Full article

Background: Sustainability is a critical concern in transportation, notably in light of governmental initiatives such as cap-and-trade systems and eco-label regulations aimed at reducing emissions. In this context, collaborative approaches among carriers, which involve the exchange of shipment requests, are increasingly recognized as effective strategies to enhance efficiency and reduce environmental impact. Methods: This research proposes a novel collaborative planning model for multimodal transport designed to minimize the total costs associated with freight movements, including both transportation and $C{O}_2$ emissions costs. Transshipments of freight between vehicles are modeled in the proposed formulation, promoting carrier coalitions. This study incorporated eco-labels, representing different emission ranges, to capture shipper sustainability preferences and integrated authority-imposed low-emission zones as constraints. A bi-objective approach was adopted, combining transportation and emission costs through a weighted sum method. Results: A case study on the Naples Bypass network (Italy) is presented, highlighting the model’s applicability in a real-world setting and demonstrating the effectiveness of collaborative transport planning. In addition, the model quantified the benefits of collaboration under low-emission zone (LEZ) constraints, showing notable reductions in both total costs and emissions. Conclusions: Overall, the proposed approach offers a valuable decision support tool for both carriers and policymakers, enabling sustainable freight transportation planning. Full article

Between 2013 and 2020, China had implemented a pilot cap-and-trade carbon emissions trading system (ETS) in some cities. Previous research has reported that this policy significantly reduces air pollution in the policy-implementing districts. However, whether and to what extent there are spatial spillover effects of this policy on air pollution in other regions has not been sufficiently analyzed. The research objective of this study is to quantitatively assess the spatial spillover effects of China’s carbon ETS on air pollution. Based on data from 288 Chinese cities between 2005 and 2020, this study employs a multiple linear regression approach to estimate the policy effects. Our study finds that the policy significantly reduces the concentrations of black carbon (BC), nitrogen dioxide (NO₂), organic carbon (OC), particulate matter less than 1 micron in size (PM₁), fine particulate matter (PM_2.5), and particulate matter less than 10 microns in size (PM₁₀) in non-ETS regions. This indicates that the carbon ETS has beneficial impacts on air quality beyond the areas where the policy was implemented. The heterogeneity tests reveal that the beneficial spatial spillover effects of the ETS can be observed across cities with different levels of industrialization, population density, economic development, resource endowments, and geographical locations. Further mechanism analyses show that although the policy does not affect the degree of environmental regulation in other regions, it promotes green innovation, low-carbon energy transition, and industrial structure upgrading there, which explains the observed spatial spillover effects. Full article

This study explores how carbon pricing and electricity market liberalization jointly contribute to China’s sustainable energy transition. Using a dynamic computable general equilibrium (CGE) model (CEEEA2.0), we simulate three policy scenarios—business as usual, emissions trading scheme (ETS) with regulated electricity prices, and ETS with market-based pricing—under a unified emissions cap. The results demonstrate that electricity market liberalization enhances carbon pricing efficiency by eliminating price distortions, leading to a 0.06% increase in GDP and a 12% reduction in emission abatement costs. However, liberalization also raises electricity and consumer prices, disproportionately affecting rural and low-income households. These findings underscore the need to balance economic efficiency and social equity in sustainability-oriented energy reforms. Our analysis emphasizes the importance of designing inclusive and just transition policies to ensure that carbon mitigation efforts support long-term environmental, economic, and social sustainability goals. Full article

This study investigates two pricing strategies within a vendor-buyer supply chain system under cap-and-trade regulation, emphasizing demand sensitivity to market price and green technology investment. The findings reveal that quantity discounts significantly enhance profitability across the supply chain by encouraging buyers to place larger orders, thereby benefiting vendors, buyers, and end consumers. A novel profit-sharing parameter is introduced to foster sustainable and mutually beneficial relationships between supply chain participants. A search algorithm is developed to determine the optimal solutions by using the profit-sharing mechanisms. The analysis yields three key insights: first, a critical cap threshold is identified, enabling supply chain participants to make informed strategic decisions based on the value of the cap; second, another critical cap threshold is derived to assist governments in setting feasible emission limits that incentivize vendors to invest in green technology—caps below this threshold may discourage such investments; third, a reasonable return on investment (ROI) benchmark is established to guide vendors in adopting effective green technology strategies. Numerical examples and sensitivity analyses are conducted to illustrate the theoretical framework and validate the findings. Full article

In response to the International Maritime Organization’s (IMO) 2020 sulfur cap and China’s stricter emission control policies, this study investigates the strategic interaction between port authorities and shipowners concerning air pollution emissions from ships in port areas. Using supervisory game theory, we construct a model that captures the cost–benefit trade-offs between inspection efforts by regulators and compliance behavior by ship operators. Empirical data from Guangzhou Port in 2020—including government inspection costs, fuel substitution costs, subsidy schemes, and fine levels—are incorporated into the model to simulate equilibrium outcomes. Results indicate that while the current level of inspection has a significant deterrent effect, the probability of full compliance remains low at 34.36%, highlighting the importance of a balanced regulatory approach combining inspection, fines, and subsidies. Policy implications suggest that increased financial incentives and stronger penalties can reduce both regulatory costs and non-compliance risks. This study contributes to the literature on maritime environmental governance by providing a quantitative supervisory framework grounded in real-world port data. Full article

Environmental protection and low-carbon life are the focus of global attention. This paper adopts Stackelberg’s game method to discuss channel selection. Two decision models are involved: (1) model P represents dual-channel structure of the manufacturer, and (2) model O represents dual-channel structure of the retailer. We examined the optimal pricing strategy, and profit distribution among stakeholders. This research showed that, compared to model O, model D always sells more products, and model D has a higher (manufacturer)/lower (retailer) profits than model O. The retailer’s offline price exhibits a linear decline. At the point of intersection (0.28, 45.5), the price in both models converge to an identical value. From an environmental perspective, model D is more environmentally friendly than model O when unit carbon price is small. Furthermore, the emission reduction rate is higher if consumers’ online preference coefficient is not high in model D. Through the lens of social welfare, the sales strategies employed in model O yield higher social welfare benefits compared to those in model D. For the entire supply chain, model O is the optimal choice if they focus on environmental performance and social welfare. The research provides application guidance for the sustainable development of enterprises. Full article

Cap-and-trade is widely recognized as an effective mechanism for curbing carbon emissions, and it significantly influences the operational decisions within supply chains. This study investigates a three-echelon closed-loop supply chain (CLSC) consisting of one original equipment manufacturer, one traditional retailer, and one independent third-party collector. The manufacturer invests in cleaner technologies to produce green products and remanufactures new products from used items recycled by the third-party collector. Considering different channel power structures, three Stackelberg game models are developed, and their optimal solutions are derived using the backward induction. Additionally, the combined effects of remanufacturing-related and carbon-related parameters on economic and environmental benefits as well as social welfare are investigated under different settings. Moreover, the derived results are validated via numerical simulation. The findings indicate that: (1) Each channel member is incentivized to act as the leader role within the CLSC to maximize profits. (2) A loose cap-and-trade regulation is conducive to enhancing the emission abatement rate, collection rate, and overall performance for the CLSC. (3) The retailer-led model is the best option for capturing more economic benefits and social welfare, while the third party-led model can always achieve the best environmental performance regardless of carbon trading price. These research findings can provide valuable insights for policymakers and decision makers engaged in CLSC. Full article

Integrating low-carbon design into products is crucial for reducing carbon emissions throughout their life cycle and promoting sustainable development. Addressing the uncertainty in the carbon footprint resulting from the unknown choice of product material solutions. This paper considers ABC (activity-based costing) along with the components’ carbon footprint and scrap return issues to illustrate the above challenge in a two-stage production-inventory system with imperfect processes. We determine the optimal production and sales strategies that maximize total profit per unit time. An algorithm is developed to identify these optimal solutions. To illustrate the effectiveness of the proposed model and algorithm, two numerical examples from the Taiwan die casting industry are presented. Additionally, a sensitivity analysis is conducted to provide valuable managerial insights. Full article