Search Results (113)

Carbon pricing can change manufacturers’ material choices, while the costs of managing the residual waste remain geographically uneven. We formulate a manufacturer–regulator bilevel model for a household plastic-waste closed-loop supply chain with quantity-dependent recycled-bale prices, activity-specific carbon accounts, physical interregional waste routing, and a proportional regional cost-burden standard. The lower level is explicitly a single coordinating-regulator linear program rather than a game among independent regions. Its primal constraints, dual constraints, and strong-duality equality are embedded in the manufacturer problem; binary-continuous products are exactly linearized using the manufacturer’s SOS1 price-grid variables. Thus, every reported policy point is obtained from the same 12-region mixed-integer equilibrium formulation. Across 36 central policy combinations, HiGHS reports a zero mixed-integer programming gap, and the largest feasibility and optimality residual is $5.24\times {10}^{-8}$. Raising the carbon tax from 0 to 10 USD/tCO₂ increases the real recycling rate (RRR) from 15.33% to the bale-capacity limit of 29.85% and reduces physical emissions by 11.64%. Tightening the allowed regional burden deviation from 25% to 5% reduces the standard deviation of normalized residual-waste cost burden by 77.89% and interregional residual-waste transfers by 77.05%, but does not change the RRR. This zero-recycling effect overturns the earlier assumption-driven result: a pure routing-based cost-balancing rule cannot mechanically stimulate the manufacturer’s recycled-input demand. A global analysis of 300 parameter sets and five independent regional samples re-solves 1800 equilibrium models; all have a zero solver gap and pass the residual audit. Carbon-induced RRR increases have a median of 17.03 percentage points, while strict-versus-loose burden-threshold changes in RRR are zero in every set. The results distinguish carbon efficiency, regional cost incidence, and fiscal incidence and show that policy complementarity must be demonstrated through endogenous decision links rather than imposed response functions. Full article

International oil price volatility poses severe risks to macroeconomic stability and energy security, presenting complex policy challenges for China as it simultaneously pursues economic growth and a low-carbon transition. To bridge the gap between general equilibrium reallocation and transition quality, this study couples an 18-sector recursive dynamic computable general equilibrium (CGE) model with a super-efficiency slacks-based measure (SBM) model to evaluate China’s macroeconomic path and green total factor productivity (GTFP) from 2023 to 2045. We simulate a permanent 200% international oil price shock starting from 2026—conceived as a tail-risk stress test—together with alternative shock scenarios of varying magnitude and persistence (P50, P100, and a five-year temporary variant of P200_5Y), and evaluate four counterfactual policies under the P200 stress-test condition: household transfers (Tran_HG), price regulation (P_REG), structural tax reduction (T_RED), and energy-transition acceleration (Delta_ENE). The shock triggers imported cost-push inflation and a regressive shift toward coal, with the long-run damage governed jointly by shock magnitude and persistence; since GTFP deteriorates monotonically with shock size, the apparent emission reductions under extreme shocks suggest a contraction-driven “efficiency illusion” rather than genuine green improvements. Individually, P_REG and T_RED are effective only as temporary shields, Tran_HG provides the strongest welfare protection but amplifies the high-carbon rebound, and Delta_ENE uniquely improves resilience and green efficiency simultaneously. Building on these results, a combined policy package (COM) is further designed and simulated, which exhibits positive complementarities; it cuts the 2026 GDP loss by about 70%, turns GDP and welfare losses into net gains by 2043 and 2040, respectively, and delivers favorable green-transition outcomes. These findings call for coordinated, phased policy packages in which fiscal space rotates from emergency shields to demand-side repair and, ultimately, to electrification-led structural transformation. Full article

In the context of global climate change and China’s “Dual Carbon” target, the misallocation of carbon emission reduction responsibilities and low regulatory efficiency urgently require analysis and resolution. Based on China’s 2020 MRIO and carbon emission inventory data, this study integrates multi-regional input–output models and complex network theory to construct an embodied carbon emission (ECE) transfer network at the provincial-industrial level and analyze its structural characteristics. Drawing on complex network control theory, this paper proposes a heuristic node-ranking strategy to identify driver nodes for full controllability of the ECE transfer network and compare its regulatory effect with other topological indicators. The findings reveal: (1) At the provincial level, embodied carbon emissions show a distinct transfer pattern from central provinces to southeast coastal or economically developed regions. Jiangxi, Anhui, Shandong, etc., are net outflow provinces, while Jiangsu, Beijing, Guangdong, etc., are net inflow provinces. (2) At the industrial level, secondary industry is the main net inflow industry, and primary industry is the main net outflow industry. The secondary industries in Guangdong, Henan, etc., have high betweenness centrality, acting as “hub” nodes for carbon transmission. Community detection shows that the largest community in China is centered on the secondary and tertiary industries of Jiangsu, Henan, Guangdong, etc., and the network overall exhibits small-world characteristics. (3) Compared with other control strategies, the designed algorithm achieves the best control effect: it realizes full network controllability with the minimum number of control nodes (26), and the shortest reachable paths from the control node set to non-control nodes, meaning policy signals imposed on control nodes transmit at the fastest speed. (4) Among the control node set, 22 key control nodes are mostly secondary and tertiary industries, located at the center of the transfer network and ranking high in net outflow or inflow, belonging to the core nodes of the ECE transfer network. This study provides a scientific basis and methodological support for clarifying the attribution of carbon transfer responsibilities and formulating differentiated collaborative regulatory policies. This paper establishes a qualitative matching mechanism between network control inputs and carbon tax, emission quotas and industrial regulation to connect controllability theory and practical carbon governance. Full article

This study develops an inventory model for deteriorating products within a dual-warehouse system under carbon tax regulation. The framework is motivated by supply chains for perishable goods where storage constraints, product deterioration, environmental costs, and financing decisions arise simultaneously. The model considers an owned warehouse and a rented warehouse with higher holding cost, where the rented facility is utilized first. To capture realistic operational conditions, the model integrates time-dependent holding costs, trend-based demand, preservation technology investment to reduce deterioration, and a two-tier trade credit scheme. Carbon tax is incorporated as an environmental cost component, while preservation technology directly influences the deterioration rate, creating a trade-off between investment and waste reduction. The proposed model is examined through numerical analysis based on parameter settings representative of perishable products such as organic dairy items. The objective is to determine the optimal replenishment cycle time, preservation investment, and order quantity that minimize the total cost within the dual-warehouse system. Numerical results indicate an average optimal cycle time of approximately 0.57 years, preservation investment of about 1.32 dollars, and order quantity near 459 units. The average total cost is around 1056 dollars, with a minimum observed cost of approximately 964 dollars. The findings highlight the significant impact of preservation technology and carbon taxation on profitability and sustainability. Full article

In the digital economy era, computing power, as a novel factor of production, serves as a vital engine for driving high-quality economic development. Building upon China’s traditional 42-sector input–output table, this paper incorporates computing power networks as a new sector to construct a 43-sector dynamic input–output (IO) model. Based on this framework, a Dynamic Stochastic General Equilibrium (DSGE) analysis framework is constructed to systematically reveal the dynamic transmission mechanism of computing power within industrial linkages and capital accumulation. From an energy perspective, energy consumption is implicitly captured through carbon emissions and energy structure, which together reflect the scale, efficiency, and composition of energy use in computing power networks. The findings show that the optimal computing power allocation follows a temporal evolution pattern from the service sector to the manufacturing sector, with ICT manufacturing’s computing power quota reaching 31% by 2030. An investment inflection point occurs in 2026, aligning with the digital infrastructure cycle of China’s 14th Five-Year Plan. The “Eastern Data, Western Computing” strategy reduces unit carbon emissions from computing power by 41%. Policy simulations demonstrate that R&D tax credits generate a 2.9-fold multiplier effect through industrial linkages, boosting GDP by 2.3%. The integrated IO-DSGE framework developed in this study provides a quantitative tool for the full-cycle management of “construction–application–regulation” in computing power networks. It holds significant theoretical value and practical implications for enhancing resource allocation efficiency and promoting green, climate-friendly development. Full article

This study investigates whether and how climate and environmental governance policy uncertainty shapes corporate tax avoidance. Using a comprehensive panel of 25,316 firm-year observations from 4700 Chinese listed firms over 2002–2024, we document that both climate and environmental governance policy uncertainty are associated with significantly lower effective tax rates, reflecting changes in firms’ tax planning behavior under policy uncertainty. Further, we show that this effect is economically and statistically transmitted through firms’ financing conditions. A battery of identification strategies, including lagged specifications, propensity score matching, and entropy balancing, confirms the robustness of the findings. Cross-sectional analyses further reveal that the effect is more pronounced among carbon-intensive, climate-sensitive, and less regulated firms. These findings imply that policy instability in climate and environmental governance may unintentionally incentivize corporate tax avoidance, thereby undermining both fiscal capacity and the effectiveness of environmental policy frameworks. Full article

In the context of global climate change and industrial low-carbon transition, whether environmental taxes can simultaneously promote environmental and economic benefits by stimulating corporate green investment remains a central issue in academic research. Existing studies have reached mixed conclusions regarding the effects of environmental taxes, emphasizing either the “innovation compensation” effect or the “crowding-out” effect. However, this binary perspective overlooks the internal boundary conditions under which environmental taxes operate, particularly the roles of market competition and firm-level resource endowments. In particular, limited attention has been paid to how competitive market environments shape firms’ responses to environmental regulation. To address this gap, this study develops an integrated analytical framework that combines external market competition with internal firm endowments. Using China’s 2018 Environmental Protection Tax Law as a quasi-natural experiment and a panel dataset of Chinese listed firms from 2009 to 2024, this study employs a Difference-in-Differences (DID) approach to examine the impact of environmental taxation on corporate green investment. The results show that: (1) the environmental protection tax significantly promotes corporate green investment, with substantial heterogeneity across firm size, ownership structure, and regional institutional environments; (2) market competition serves as an important external moderating mechanism, as intensified competition strengthens firms’ incentives to pursue technological differentiation through green investment, thereby generating an “escape-competition effect”; and (3) from an internal perspective, the effectiveness of environmental taxation is also shaped by firm endowments. High investment activity provides the necessary resource buffer to support strategic pivots, whereas rapid revenue growth and high financial slack (excessive cash ratio) generate strategic inertia, thereby attenuating firms’ responsiveness to the tax shock. This study not only provides empirical evidence from China on the mechanisms through which environmental taxes influence corporate green transformation, but also offers important policy implications for improving environmental tax systems in other countries. Full article

The sustainable transition of power systems is currently hindered by fragmented carbon pricing systems and insufficient cross-market synergies. Considering this, we herein construct a system dynamics model of carbon tax regulation under conditions integrating electricity markets, carbon emission trading (CET) markets, and tradable green certificate (TGC) markets using Vensim PLE 7.3.5 software. We also propose a price-matching mechanism and implementation pathway for carbon taxation and CET to advance low-carbon sustainable development. The simulation results show that the introduction of a carbon tax at an initial rate of 50 CNY per ton significantly improves renewable energy investment returns. Moreover, effective coordination between the carbon tax and CET reduces carbon emissions from the power system, delivering benefits in terms of both environmental and socio-economic sustainability. We further identify a dynamic coordination scheme consisting of a carbon tax with an initial rate of 50 CNY per ton, which is appropriate when the CET prices stabilize at approximately 60 CNY per ton. An initial rate of 30 CNY per ton is more suitable when the CET prices rise above 100 CNY per ton. These findings verify the optimal matching rules for carbon tax intensity under different carbon allowance price levels, and they also provide quantitative policy tools and empirical support for the scenario-based regulation of carbon pricing systems to achieve sustainable energy transition goals. Full article

To address the “greenwashing” trust crisis induced by information asymmetry in sustainable supply chains, this study develops a comprehensive game-theoretic model integrating Stackelberg and evolutionary game theories (EGT). We quantitatively investigate the dynamic interactions among multi-dimensional consumer preferences, blockchain implementation costs, and boundedly rational government interventions. Our analysis yields three core contributions. First, we analytically reveal the “double-edged sword effect” of blockchain adoption. While structural transparency unlocks a trust dividend, exorbitant technological costs trigger a “budget crowding-out effect.” Quantitative results demonstrate that breaching the absolute Feasibility Threshold completely cannibalizes the environmental budget, driving substantive green investments strictly to zero. Second, EGT analysis proves that isolated punitive carbon taxes trap supply chains in a suboptimal “shallow greening” equilibrium. A composite tax-subsidy policy is structurally required to expand the feasible cost space and hedge against technological risks. Finally, we formulate a dynamic policy exit mechanism. As blockchain infrastructure matures and the endogenous green premium effectively offsets implementation costs, regulators must systematically phase out subsidies and converge toward a single-taxation regime to prevent corporate policy arbitrage and alleviate long-term public financial burdens. Full article

Environmental taxation, as a market-based regulatory instrument, has the potential to internalize pollution externalities while also promoting the shared goals of environmental protection and economic development. This study investigates the impact of China’s Environmental Protection Tax in 2018 on corporate green investment using a Difference-in-Differences (DID) model and a dataset of A-share listed businesses from 2012 to 2023. Our empirical results show that environmental taxation strongly increases green investment among heavy-polluting enterprises, a finding that holds significant across a range of robustness tests. According to mechanism analysis, the policy functions through two principal channels: an innovation effect that encourages technical upgrades and a financing effect that reduces information asymmetry and credit constraints. Furthermore, the policy has a threshold characteristic: enterprises with higher pollution intensity show more pronounced improvements in ESG performance and investment incentives. This paper gives policy evidence for integrating environmental taxation with green finance to enhance sustainable development, as well as theoretical insights and practical implications for accelerating business low-carbon transition under environmental regulation. Full article

China’s Environmental Protection Tax (EPT), introduced in 2018, provides a useful setting for examining whether pollution-oriented regulation can also deliver carbon-mitigation benefits and whether such benefits depend on prior low-carbon policy exposure. Using panel data for 285 Chinese prefecture-level cities from 2002 to 2022, this study first estimates a difference-in-differences model exploiting cross-provincial variation in the post-2018 EPT shock and then applies a triple-difference framework to examine whether prior exposure to the Low-Carbon City (LCC) and Carbon Emissions Trading (CET) pilots was associated with stronger EPT effects. The results show that, on average, the EPT reduced PM2.5 concentration, carbon emissions, and carbon intensity by approximately 3.7%, 9.6%, and 10.8%, respectively, although the evidence is stronger for the two carbon-related outcomes than for PM2.5. The clearest and most stable heterogeneous evidence appears for carbon intensity, especially for the LCC-only group; the Dual group shows the largest point estimate, but its external validity is limited. Further analysis suggests that post-EPT changes in industrial structure upgrading and green invention patent grants were more visible in cities with prior low-carbon policy exposure. Overall, the findings indicate that prior low-carbon policy exposure was associated primarily with a stronger EPT effect on carbon intensity. Full article

This article integrates sustainability principles into a three-echelon supply chain for deteriorating items with imperfect quality, consisting of a single vendor, a third-party logistics enterprise (3PL), and a single buyer, with a focus on balancing economic efficiency with environmental responsibility. The vendor is assumed to operate an imperfect production system, resulting in products of imperfect quality. The 3PL undertakes all transportation activities, while the buyer conducts a quality inspection process to detect defective items, which is subject to Type-I and Type-II errors. Aside from that, the inventory model also assesses carbon emissions arising from various operational activities including energy usage during production, warehousing, and disposal processes, and fuel consumption in transportation, for which the above members of the supply chain are accountable. Afterward, carbon management policies such as a carbon tax and carbon cap-and-trade are considered to regulate total supply chain emissions. The objective is to minimize the joint expected total cost by simultaneously optimizing shipment frequencies and the replenishment cycle for the buyer within carbon emission constraints. An iterative solution procedure is developed to address the problem. A numerical example and sensitivity analysis are provided to demonstrate the model’s applicability and to explore the influence of critical parameters. Finally, the study presents managerial insights, along with conclusions and recommendations for future research directions. Full article

This study investigates trade-in channel selection in a closed-loop supply chain under a hybrid carbon policy framework that integrates cap-and-trade and carbon taxation. Game-theoretic models are developed for three manufacturer-led channels: manufacturer trade-in (M-CX), retailer trade-in (R-CX), and third-party trade-in (T-CX). The analysis examines pricing strategies, profitability, and carbon emission reductions across these channels. The key findings are as follows: (1) Carbon tax consistently compresses manufacturer profits, whereas cap-and-trade mechanisms exhibit a non-linear U-shaped effect. Manufacturer profits remain highest under the M-CX channel, irrespective of policy intensity. (2) Retail prices are most sensitive to carbon policies under the T-CX channel, where trade-in rebates increase with carbon intensity. The R-CX channel sustains higher retail prices and rebates than M-CX, while T-CX surpasses both under conditions of high carbon intensity. (3) Carbon emission reductions decline sharply under M-CX and R-CX as policy stringency increases. In contrast, the T-CX channel establishes a buffering mechanism through rising rebates, exhibiting the slowest rate of decline. At low carbon intensity, T-CX yields the lowest reduction levels; however, under high intensity, it overtakes the other channels to achieve the highest reduction. This study offers insights for manufacturers’ channel selection and government policy coordination under hybrid carbon regulation regimes. Full article

Against the background of carbon neutrality, the government’s carbon regulations have had a profound impact on the distributed energy sharing behavior of industrial parks. To deeply explore the interactive relationship between distributed energy sharing in industrial parks and government regulation, this paper constructs a three-party evolutionary game model composed of the government, core enterprises and supporting enterprises; endogenizes government behavior; and integrates inter-enterprise contractual mechanisms into the evolutionary framework. By establishing a revenue payment matrix and a replication dynamic equation, the stability conditions and system evolution paths of the strategy choices of each subject are analyzed, and numerical simulations are conducted. The results show that there are multiple evolutionary stable equilibria in the system, among which the equilibrium where core enterprises actively share, supporting enterprises actively share, and the government actively regulates carbon is the ideal state. Cost-sharing contracts and cooperative penalty contracts play a significant role in promoting the participation of supporting enterprises in sharing and curbing “free-riding” behavior, respectively. The changes in government subsidy rates and carbon tax rates have a crucial impact on the evolution of corporate strategies. Quantitatively, the carbon tax rate exhibits a threshold effect; enterprises shift to positive energy sharing when the tax rate exceeds 0.8, while a subsidy rate above 0.4 leads the government to withdraw from regulation. This indicates that a reasonable design of carbon regulations can help achieve coordinated energy emission reduction between the government and enterprises. The findings provide theoretical support for optimizing carbon regulations and designing cooperation strategies. Full article

The liner shipping industry is thriving in the low-carbon transition, and optimizing operational strategies for liquefied natural gas (LNG) dual-fuel ships has become a research hotspot. This research examines the impacts of the carbon tax, emission control area (ECA) policies, fuel price discounts and methane slip rate on fuel management strategies. Firstly, to reduce liner operating costs and adhere to ECA policies, this study develops a basic optimization model. Further, the model is extended to take into account the impact of fuel price discounts. Secondly, by linearizing multiple nonlinear terms, the operational strategies are obtained. Thirdly, taking a real vessel sailing between the Far East and Northwest Europe as a case study, this study identifies the ports for LNG and very low sulfur fuel oil (VLSFO) bunkering, determines the bunkering amounts and calculates the planned speeds. Furthermore, sensitivity analyses are conducted on fuel price difference, carbon tax rate and methane slip rate. Results show that fuel price difference, carbon tax rate, methane slip rate and fuel price discount exert a significant impact on ship operational decisions. To ensure the effectiveness of maritime decarbonization regulations, authorities should monitor ship engines with high methane slip rates. This study offers important references for shipping enterprises to meet ship emission policies and simultaneously cut operational costs. Full article