Multi-party supply chain carbon emission management method based on subsidy and carbon right transaction

Abstract

The invention discloses a multi-party supply chain carbon emission management method based on subsidy and carbon right transaction, and the method comprises the following steps: S1, forming a mixed low-carbon policy based on a carbon right transaction mechanism and low-carbon subsidy, building a supply chain model, and carrying out the model setting; s2, performing mode analysis on the supply chain model in the step S1; and S3, performing performance analysis on the supply chain models in different modes in the step S2, and making a supply chain decision under the same subsidy budget. According to the multi-party supply chain carbon emission management method based on subsidy and carbon right transaction, four Stackelberg game models are provided to analyze decision-making conditions of suppliers, manufacturers and retailers in the supply chain under different low-carbon mixed policy scenarios, and results show that the supply chain carbon emission management method based on subsidy and carbon right transaction has the advantages that the supply chain carbon emission management efficiency is improved; the supplier participates in the green investment, so that the supply chain can be helped to achieve a better emission reduction effect and profitability, and under the same subsidy budget, the supply chain can be helped to achieve the lowest total emission based on the hybrid policy of the carbon right transaction of the grandparent quota allocation rule and the green investment subsidy.

Description

Technical Field

[0001] The present invention relates to the technical field of supply chain management, and in particular to a multi-party supply chain carbon emission management method based on subsidy and carbon rights trading. Background Art

[0002] Governments around the world have enacted carbon emission policies to control carbon emissions from human activities. Among them, carbon trading is a mechanism that combines government regulations and market tools, and is one of the most effective policies. The policy sets a carbon emission limit for each company, allowing the company to sell unused quotas or purchase additional excess quotas (Lin and Jia 2019). The carbon trading mechanism mainly applies two quota allocation rules, namely the grandfather rule and the baseline rule. Under the grandfather rule, the government will set a fixed total emission limit for the company based on its previous carbon emission record, called the carbon emission cap. However, under the baseline rule, the limit will no longer be a fixed value, but will be determined by the benchmark carbon intensity and the company's output value. The government determines the benchmark carbon intensity, and the total emission cap for a given company is calculated by multiplying the carbon intensity by the output value (Yang et al. 2020). At present, carbon trading systems based on these two quota allocation rules have been applied in practice. The implementation of carbon trading policies can effectively promote green investment by enterprises, but it may also bring greater financial pressure to enterprises. Therefore, in order to further promote the green transformation of enterprises, the government can also provide subsidy policies to encourage enterprises to take more green efforts.

[0003] Green investment subsidies and product subsidies are two typical subsidy policies. Under green investment subsidies, the government will share part of the green investment costs of enterprises, while product subsidy policies provide a certain amount of subsidies for each green product produced by enterprises.

[0004] In addition to regulatory pressure from the government, the development of the green product market has also become an incentive for companies to carry out carbon emission management. In recent years, consumers' green awareness has developed rapidly, which means that consumers will pay more attention to the greenness of products and tend to prefer products with lower carbon emissions. The potential profitability brought by green products makes consumers' green awareness an important driving force for companies to operate green investments (Gong et al. 2019).

[0005] Regulatory pressure from the government and potential market opportunities have prompted manufacturers to actively make green investments in their production operations. However, since carbon emissions exist at all stages of the supply chain, green investments by manufacturers can only achieve limited results. In addition to manufacturers, suppliers are also a major source of carbon emissions because they are responsible for raw material extraction or ingredient production. Therefore, it is of great significance to involve suppliers in carbon emission management. However, most previous studies have only analyzed green supply chain strategies based on manufacturers and retailers, such as the studies of Song and Gao (2018) and Chen et al. (2019). Only a few scholars have considered the green investment of suppliers in their research. For example, Ding et al. (2015) studied the pricing issues of suppliers and manufacturers in the context of low-carbon policies. Peng et al. (2018) studied the impact of contracts on suppliers and manufacturers, taking into account product uncertainty. However, the above studies only focused on a single low-carbon policy, without considering the impact of mixed low-carbon policies. Summary of the invention

[0006] The purpose of the present invention is to provide a multi-party supply chain carbon emission management method based on subsidies and carbon rights trading. The application of mixed low-carbon policies can promote enterprises to achieve higher emission reduction levels. The combination of carbon rights trading policies based on grandfathering rules and green investment subsidies is more suitable for developed and high-emission industries. The combination of carbon rights trading policies based on the baseline method and subsidy policies is more suitable for developing industries. Under the same budget conditions, the mixed policy of carbon rights trading based on grandfathering rules and green investment subsidies can help the supply chain achieve the lowest total emissions.

[0007] To achieve the above objectives, the present invention provides a multi-party supply chain carbon emission management method based on subsidy and carbon rights trading, comprising the following steps:

[0008] S1. Based on the carbon rights trading mechanism and low-carbon subsidies, a mixed carbon emission policy is formed, a supply chain model is established, and the model is set up;

[0009] S2, performing pattern analysis on the supply chain model in step S1;

[0010] S3. Perform performance analysis on the supply chain models of different modes in step S2 and make supply chain decisions under the same subsidy budget.

[0011] Preferably, in step S1, the carbon rights trading mechanism considers two quota allocation rules, namely the grandfather rule and the baseline rule. Under the grandfather rule, a total carbon emission quota for a certain period is set for the manufacturer, namely the carbon cap C;

[0012] Under the baseline rule, the allocated quota is not fixed but is proportional to the manufacturer’s production capacity, i.e., the emission intensity e multiplied by the product of wholesale price and output wQ;

[0013] The newsboy model is used to simulate market uncertainty, and the impact of consumers' green awareness g on product demand is considered. The product demand function D in the green market is defined as:

[0014] D=y+ε (1)

[0015] Where y = ag(E S +E M +E R -e S -e M ), a is the product demand in the original market, Es, E M , E R are the unit carbon emissions of suppliers, manufacturers and retailers, es and e M are the unit carbon emission reduction of suppliers and manufacturers, g(E S +E M +E R -e S -e M ) represents the impact of consumers’ green awareness on product demand, and ε is a random variable showing market uncertainty, where ε∈[A, B], a≥-a+g(E S +E M +E R ), E(ε)=μ, the product price p is set as a constant in the newsboy model; the Steinberg game model is used to simulate the coordination between the parties in the supply chain.

[0016] Preferably, step S2 specifically includes:

[0017] S21. Carbon emission total control and trading rules based on grandfathering rules, that is, analyzing the supply chain model under the carbon rights trading mechanism based on grandfathering quota allocation rules;

[0018] S22. Carbon emission total volume control and trading rules based on baseline management rules, that is, analyzing the supply chain model under the carbon rights trading mechanism based on the baseline quota allocation rules.

[0019] Preferably, step S21 specifically includes:

[0020] S211, Supply chain model under green investment subsidies;

[0021] For the supply chain under the grandfathered carbon trading and green investment subsidy policy, the retailer’s profit π R The function expression is:

[0022] π R =E[pmin(Q,D)+v(QD) + -t(DQ) + -wQ] (2)

[0023] The function expression consists of four parts, where (Q - D) + represents the unsold products, and (D - Q) + represents the unmet demand; the first part is the revenue, i.e., pmin(Q, D), the second part is the salvage value of the unsold products v(Q - D) + , where v is the residual value of the commodity, the third part is the penalty cost for product shortage, t is the penalty price per unit product, and the fourth part is the cost of purchasing products from the manufacturer, w is the wholesale price of the product;

[0024] Considering the impact of the hybrid low - carbon policy, the profit π of the manufacturer M function expression is:

[0025]

[0026] The manufacturer's profit includes wholesale revenue, subsidized green investment cost, and emissions trading cost. The wholesale revenue is the profit per unit product multiplied by the product order quantity Q. The government green investment subsidy coefficient is s(0 < s < 1), k is the manufacturer's green investment cost coefficient, and the carbon rights trading volume is the actual emissions after green investment minus the allocated quota, which is (E M - e M )Q - C. A positive value means the manufacturer must purchase quotas from the carbon market, while a negative value means the manufacturer sells the unused quotas to other companies in the carbon market;

[0027] The profit π of the supplier S function expression includes component wholesale revenue, production cost, and the cost of using green materials or energy, i.e.:

[0028] π S = (u - c1 - he S )Q (4)

[0029] where u is the component price, c1 is the supplier's unit production cost, and h is the supplier's green investment cost coefficient;

[0030] The total carbon emissions E of the entire supply chain includes the supplier's (E s - e S )Q, the manufacturer's (E M - e M )Q, and the retailer's carbon emissions E R Q, i.e.:

[0031] E = (E S - e S )Q+(E M - e M )Q+E RQ (5)

[0032] The decisions of the three supply chain parties are analyzed using backward induction, and the inventory factor r = Q - y is used to simplify the calculation:

[0033] r > ε indicates that the product is greater than the demand, resulting in a surplus of the product; r < ε means that the product is lower than the demand, leading to a shortage of the product;

[0034] Therefore, the profit function of the retailer becomes:

[0035] π R = E[p min(y + ε, y + r) + v(r - ε) + - t(ε - r) + - w(y + r)] (6)

[0036] Through the derivation of the retailer's profit function, the results are as follows:

[0037]

[0038] The optimal order quantity Q is:

[0039] Q = F -1 (r) + a - g(E S + E M + E R ) + g(e S + e M ) (8)

[0040] Among them, By substituting equation (8) into the profit function of the manufacturer π M the result then becomes:

[0041]

[0042] Among them, con = F -1 (r) + a - g(E S + E M + E R ), through the derivation of the manufacturer's profit function, the following conclusions are obtained:

[0043]

[0044] S212. The supply chain model under product subsidy;

[0045] According to the product subsidy policy, the government will provide a subsidy of mw for each green product produced by the manufacturer, where m is the subsidy coefficient (0 < m < 1) and w is the wholesale price of the manufacturer;

[0046] The expression of the retailer's profit function is:

[0047] π R =E[pmin(Q,D)+v(QD) + -t(DQ) + -wQ] (11)

[0048] The manufacturer's profit function expression is:

[0049]

[0050] The supplier's profit function expression is:

[0051] π S =(u-c1-he S )Q (13)

[0052] The total carbon emissions of the entire supply chain are:

[0053] E=(E S -e S )Q+(E M -e M )Q+E R Q (14).

[0054] Preferably, step S22 specifically includes:

[0055] S221. Supply chain model under green investment subsidies;

[0056] The retailer's profit function expression is:

[0057] π R =E[pmin(Q,D)+v(QD) + -t(DQ) + -wQ] (15)

[0058] The manufacturer's profit function expression is:

[0059]

[0060] Under the baseline rule, the manufacturer's emission allowance is the baseline emission intensity multiplied by the output value, that is, ewQ. Therefore, the trading volume of emission allowances is (E M -e M )Q-ewQ;

[0061] The supplier's profit function expression is:

[0062] π S =(u-c1-he S )Q (17)

[0063] The total carbon emissions of the entire supply chain are:

[0064] E=(E S -e S )Q+(E M -e M )Q+E R Q (18);

[0065] S222, Supply chain model under product subsidies;

[0066] The retailer's profit function expression is:

[0067] π R =E[pmin(Q,D)+v(QD) + -t(DQ) + -wQ] (19)

[0068] The manufacturer's profit function expression is:

[0069]

[0070] The supplier's profit function expression is:

[0071] π S =(u-c1-he1)Q (21)

[0072] The total carbon emissions of the entire supply chain are:

[0073] E=(e S -e1)Q+(e M -e2)Q+e R Q (22).

[0074] Preferably, in step S3, supply chain model performance analysis is performed based on supply chain performance and total carbon emissions.

[0075] Therefore, the present invention adopts the above-mentioned multi-party supply chain carbon emission management method based on subsidy and carbon rights trading, and the beneficial effects are as follows:

[0076] (1) This paper considers four hybrid policy scenarios, including carbon trading policies based on two quota allocation rules and two subsidy policies, and compares their impacts on supply chain profits and total carbon emissions; it determines the effectiveness of different hybrid policies in promoting supply chain carbon emission reduction under different conditions, and provides feasible management suggestions for the application of government low-carbon policies.

[0077] (2) Few scholars have studied the impact of different quota classification rules on corporate carbon emission decisions. This paper not only compares the two rules, but also explores the combination of carbon rights trading and subsidy policies, and considers the impact of consumers' green awareness on the green product market.

[0078] (3) The present invention also points out the importance of involving suppliers in green investment. In addition to manufacturers, suppliers are also the main source of emissions in the supply chain. Coordination between suppliers and manufacturers in green investment can help the supply chain achieve less total emissions and better profitability.

[0079] (4) Based on the proposed supply chain model, the present invention provides a scientific basis for all parties in the supply chain to make correct decisions in green investment and operation management.

[0080] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 It is an overall flow chart of an embodiment of a multi-party supply chain carbon emission management method based on subsidies and carbon rights trading of the present invention;

[0082] Figure 2 It is a model illustration diagram of an embodiment of a multi-party supply chain carbon emission management method based on subsidy and carbon rights trading of the present invention;

[0083] Figure 3 is the supply chain performance under different subsidy rates in the embodiment of the multi-party supply chain carbon emission management method based on subsidy and carbon rights trading of the present invention, wherein a is the impact of subsidies on supplier emission reduction, b is the impact of subsidies on manufacturer emission reduction, c is the impact of subsidies on total carbon emissions, d is the impact of subsidies on supplier profits, e is the impact of subsidies on manufacturer profits, and f is the impact of subsidies on retailer profits;

[0084] Figure 4 is the total amount of emissions under different carbon prices and green awareness coefficients in the embodiment of the multi-party supply chain carbon emission management method based on subsidies and carbon rights trading of the present invention, where a is the total carbon emissions of the supply chain under the GI scenario, b is the total carbon emissions of the supply chain under the GP scenario, c is the total carbon emissions of the supply chain under the BI scenario, and d is the total carbon emissions of the supply chain under the BP scenario;

[0085] Figure 5 It is a supply chain under a given subsidy budget in an embodiment of the multi-party supply chain carbon emission management method based on subsidy and carbon rights trading of the present invention, wherein a is the carbon emission reduction performance under different subsidy budgets under the background of grandfathering rule, and b is the profit performance under different subsidy budgets under the background of grandfathering rule;

[0086] Figure 6 It is a supply chain that adopts the benchmark C&T line method rule under a given subsidy budget in the embodiment of the multi-party supply chain carbon emission management method based on subsidy and carbon rights trading of the present invention, wherein a is the carbon emission reduction performance under different subsidy budgets under the background of the baseline method, and b is the profit performance under different subsidy budgets under the background of the baseline method;

[0087] Figure 7 It is a supply chain comparison under a given subsidy budget of an embodiment of the multi-party supply chain carbon emission management method based on subsidies and carbon rights trading of the present invention, wherein a is the carbon emission situation under the same subsidy budget of four mixed policies, and b is the total profit of the supply chain under the same subsidy budget of four mixed policies. DETAILED DESCRIPTION

[0088] The technical solution of the present invention is further described below through the accompanying drawings and embodiments.

[0089] Unless otherwise defined, technical or scientific terms used in the present invention shall have the common meanings understood by one having ordinary skills in the field to which the present invention belongs.

[0090] In recent years, many researchers have been focusing on the application of carbon emission cap-and-trade mechanisms. For example, Ghosh et al. (2020) studied the sustainable coordination of dual-channel supply chains under the C&T mechanism. Ji et al. (2020) studied production decisions and cap setting under the C&T mechanism and considered two contracts. Some researchers have compared the C&T mechanism with other low-carbon policies. For example, Chen et al. (2019) compared the performance of a composite supply chain model under five low-carbon policy scenarios. Lu et al. (2020) analyzed the decision-making coordination between manufacturers and retailers in production, replenishment, and green investment under carbon trading and carbon offset policies. Zhao et al. (2020) established a stochastic general equilibrium model to study the impact of carbon tax, carbon trading, and tax and trading policies. Wang and Choi (2020) studied the sustainable coordination among multiple parties in the supply chain under a flexible carbon cap-and-trade policy and compared the impact of three contracts on supply chain decisions. However, few researchers have considered different quota allocation rules when studying carbon rights trading mechanisms. Grandfathering rule and baseline rule are two typical allocation rules that are widely used in practice. Only a few scholars, such as Ji et al. (2017), Yang et al. (2020) and Chen et al. (2021), have compared the impact of these two rules in their research. However, they have not studied the application of hybrid low-carbon policies, nor have they considered the impact of suppliers' green efforts on the economic and environmental performance of the supply chain.

[0091] The subsidy policy provided by the government provides effective support for enterprises to carry out green investment. Therefore, in recent years, some researchers have focused on the problem of coordinated optimization of supply chain decisions under low-carbon subsidies (Guo et al. 2016, Chen et al. 2019). For example, Li et al. (2018) compared the impact of green product substitution and consumption subsidies on improving social welfare and found that consumption subsidies were more effective. Safarzadeh and Rasti-Barzoki (2019) showed that providing subsidies to manufacturers is more effective than providing subsidies to consumers and adopting taxes. Zhang and Yousaf (2020) studied the decision-making coordination optimization problem between manufacturers and retailers in the oil industry under the background of carbon taxes, low-carbon subsidies and consumer green awareness. However, these studies did not take into account the impact of suppliers' green efforts and carbon trading policy regulatory mechanisms.

[0092] Although many researchers have studied the impact of different low-carbon policies, only a few have considered the combined application of different policies. For example, Lin and Jia (2019) showed that providing subsidies can improve the effectiveness of enterprises in carrying out carbon emission reduction. Hussain et al. (2020) studied the optimization problem of green investment decisions under C&T and subsidy policies based on a simulation model. Zhao et al. (2020) applied a stochastic general equilibrium model to compare the environmental and economic impacts of a single low-carbon policy and a mixed low-carbon policy. However, these studies did not take into account the impact of different C&T quota allocation rules, and also ignored the green investment that suppliers can achieve. Therefore, the impact mechanism of mixed low-carbon policies still deserves further exploration.

[0093] The above content mainly focuses on the decision coordination optimization problem between manufacturers and retailers on green investment, production and pricing issues. However, the green efforts that may be made by suppliers, another major source of carbon emissions, are ignored. Only a few researchers have explored the green investment of suppliers. For example, Ding et al. (2016) studied the impact of carbon caps and low-carbon subsidies on the decisions of suppliers and manufacturers. Peng et al. (2018) studied the decision coordination optimization between suppliers and manufacturers under C&T policies. Sun et al. (2020) explored the coordination between a supplier and a manufacturer in green investment decisions in a duopoly green market. These works emphasize the importance of suppliers in promoting supply chain emissions reduction and demonstrate the importance of further exploring suppliers' green investments.

[0094] Considering the above discussion, this paper attempts to make up for the shortcomings of existing research by studying the production and green investment decision optimization problem in a supply chain consisting of one supplier, one manufacturer and one retailer. It will compare and discuss the impact of four hybrid low-carbon policies on supply chain sustainability and profitability.

[0095] As Figure 1 shown, the multi - party supply chain carbon emission management method based on subsidy and carbon rights trading includes the following steps:

[0096] S1. Based on the carbon rights trading mechanism and low - carbon subsidy, form a hybrid low - carbon policy, establish a supply chain model, and perform model settings;

[0097] To better analyze the influence of different parameters on the decisions of all parties in the supply chain, as Figure 2 shown, the present invention is oriented to the decision - making cooperation optimization among a supplier, a manufacturer, and a retailer. In the proposed model, the emission reduction levels are e S and e M which are used to represent the carbon emission reduction per unit of components / products achieved by the green efforts of the supplier and the manufacturer. Currently, two green investment methods are widely used, namely using green materials or energy, and developing green technologies or designing green products through green investment (Sun et.al.2020). The supplier usually chooses to use green materials or apply clean energy for production, and the green investment cost coefficient per component is he S (Li and Li, 2016). Green projects are widely used by manufacturers to improve the production process or develop greener product designs. A green investment project usually requires financial support at the beginning, and the total green investment cost of the whole project can be represented by ke M 2 At the beginning, the manufacturer can achieve emission reduction at low cost. However, when the manufacturer wants to further increase its emission reduction, the emission reduction cost will gradually increase.

[0098] To explore the influence of government policies on the carbon emission management of industrial enterprises, the present invention adopts a hybrid low - carbon policy composed of a carbon rights trading mechanism and low - carbon subsidy. Among them, the carbon rights trading mechanism considers two quota allocation rules, namely the grandfathering rule and the benchmark rule. Under the grandfathering mechanism, a total carbon emission quota, that is, a carbon cap C, is set for the manufacturer within a certain period; under the benchmark mechanism, the allocated limit is not fixed, but is proportional to the output value of the manufacturer, that is, the emission intensity e multiplied by the product of the wholesale price and the output wQ;

[0099] The proposed supply chain adopts two subsidy policies, namely green investment subsidy and product subsidy. For the green investment subsidy, the government will share part of the green investment cost for the manufacturer, that is, sk M 2 . The government green investment subsidy coefficient is s(0 < s < 1), and k is the green investment cost coefficient of the manufacturer. For the green product subsidy, the government will provide a subsidy of mw for each unit of green product produced by the manufacturer, where m is the subsidy coefficient (0 < m < 1), and w is the wholesale price of the manufacturer.

[0100] Considering that the market is not stable, retailers may miscalculate consumer demand. The newsboy model is used to simulate market uncertainty. Therefore, after considering the impact of consumers' green awareness on product demand, the product demand function in the green market is defined as:

[0101] D=y+ε (1)

[0102] Where y = ag(E S +E M +E R -e S -e M ), a is the product demand in the original market, Es, E M , E R are the unit carbon emissions of suppliers, manufacturers and retailers, es and e M are the unit carbon emission reduction of suppliers and manufacturers, g(E S +E M +E R -e S -e M ) represents the impact of consumers’ green awareness on product demand. Products with lower emissions will attract more green consumers, while products with higher emissions will make consumers prefer other alternative products. ε is a random variable that shows market uncertainty, where ε∈[A, B], a≥-a+g(E S +E M +E R ), E(ε)=μ, in order to better focus on the emission reduction decisions under government intervention and consumers’ green awareness as well as the order volume of green products, the product price p in the newsboy model is set to a constant.

[0103] In some resource-intensive industrial fields, the market price of products is quite stable, so enterprises must attract consumers by improving their reputation. Providing green products through green investment has become an important strategy for enterprises to attract more green consumers and maintain brand competitiveness. Therefore, many companies have made green investments under the premise of stabilizing product prices. The present invention uses the Steinberg game model to simulate the decision-making coordination optimization problem among all parties in the supply chain. Suppliers make decisions first, then manufacturers make decisions, and finally retailers.

[0104] Several assumptions are made for the proposed model:

[0105] (1) Market demand is non-negative: the worst case is that no one buys the product, otherwise the demand rate of the product is always positive.

[0106] (2) Both suppliers and manufacturers produce on a make-to-order basis.

[0107] (3) The proposed supply chain has no substitution effect in the market, and the information obtained by the three parties is symmetrical.

[0108] S2. Perform pattern analysis on the supply chain model under the four mixed low-carbon policies in step S1 to explore the impact of different policies on supply chain performance. Table 1 shows the signs of the optimal emission reduction levels and optimal order quantities of suppliers and manufacturers under the four mixed low-carbon policy scenarios.

[0109] Table 1 Decision variable symbols

[0110]

[0111] The supply chain model analysis includes:

[0112] S21. Carbon emission total control and trading rules based on grandfathering rules, that is, analyzing the supply chain model under the carbon rights trading mechanism and two different subsidy policies, including:

[0113] S211, Supply chain model under green investment subsidies;

[0114] For the supply chain under the mixed low-carbon policy background of C&T based on grandfathering rule and green investment subsidy, the profit function of retailers is expressed as:

[0115] π R =E[pmin(Q,D)+v(QD) + -t(DQ) + -wQ] (2)

[0116] The function expression consists of four parts, among which (QD) + Indicates unsold products, (DQ) + represents unmet demand, the first part is the revenue, i.e. pmin(Q,D), and the second part is the residual value of unsold products v(QD) + , where v is the residual value of the product. The third part is the penalty cost for product shortage, t is the penalty price of a single product, and the fourth part is the cost of purchasing the product from the manufacturer, w is the wholesale price of the product.

[0117] Taking into account the impact of mixed low-carbon policies, the manufacturer's profit π M The function expression is:

[0118]

[0119] The manufacturer's profit includes wholesale revenue, the subsidized green investment cost, and the emissions trading cost. The wholesale revenue is the unit product profit (wholesale price w - component cost u - production cost c2) multiplied by the product order quantity Q. The government green investment subsidy coefficient is s (0 < s < 1), k is the manufacturer's green investment cost coefficient, and the carbon credit trading volume is the actual emissions after green investment minus the allocated quota, that is, (E M - e M )Q - C. A positive value means the manufacturer must purchase quotas from the carbon market, while a negative value means the manufacturer sells the unused quotas to other companies in the carbon market.

[0120] The profit π S of the supplier in the function expression includes component wholesale revenue, production cost, and the cost of using green materials or energy, that is:

[0121] π S = (u - c1 - he S )Q (4)

[0122] where u is the component price, c1 is the supplier's unit production cost, and h is the supplier's green investment cost coefficient.

[0123] The total carbon emissions of the entire supply chain include the supplier's (E s - e S )Q, the manufacturer's (E M - e M )Q, and the retailer's carbon emissions E R Q, that is:

[0124] E = (E S - e S )Q + (E M - e M )Q + E R Q (5)

[0125] The decisions of the three supply chain parties are analyzed using backward induction, and the inventory factor r = Q - y is used to simplify the calculation:

[0126] r > ε means the product is greater than the demand, resulting in product surplus; r < ε means the product is less than the demand, resulting in product shortage;

[0127] Therefore, the retailer's profit function becomes:

[0128] π R = E[pmin(y + ε, y + r) + v(r - ε) + - t(ε - r) + - w(y + r)] (6)

[0129] By deducing the retailer's profit function, the results are as follows:

[0130]

[0131] The optimal order quantity Q is:

[0132] Q=F -1 (r)+ag(E S +E M +E R )+g(e S +e M ) (8)

[0133] in, By substituting equation (8) into manufacturer π M The profit function becomes:

[0134]

[0135] Where con = F -1 (r)+ag(E S +E M +E R ), through the derivation of the manufacturer's profit function, we can draw the following conclusions:

[0136]

[0137] Based on gc P The value of -(1-s)k has the following two cases for the complexity of the manufacturer's profit function:

[0138] (1) When gc P -(1-s)k<0, the optimal emission reduction level e for suppliers and manufacturers S1 and e M1 , and the retailer’s order quantity Q l yes:

[0139]

[0140] See the appendix for supporting evidence.

[0141] By substituting the above equation into equation (5), the total carbon emissions E1 of the supply chain can be calculated.

[0142] (2) When gc P -(1-s)k>0, in which case the manufacturer will choose the marginal solution to maximize its profit, that is, e M =0 or e M =E M, by comparing the profit at the emission reduction level of 0 with the profit at the emission reduction level of E, the manufacturer will choose the emission reduction level with the higher profit.

[0143] Given e M = 0, the supplier's emission reduction level is:

[0144]

[0145] The corresponding order quantity is:

[0146]

[0147] Proof evidence is shown in the appendix.

[0148] In the current situation, the total carbon emissions of the supply chain are:

[0149]

[0150] For the given e M = E M , the corresponding emission reduction level of the supplier and the order quantity of the retailer are:

[0151]

[0152] Proof evidence is shown in the appendix.

[0153] At this time, the total carbon emissions of the supply chain are:

[0154]

[0155] S212. The supply chain model under product subsidy;

[0156] According to the product subsidy policy, the government will provide a subsidy of mw for each green product produced by the manufacturer, where m is the subsidy coefficient (0 < m < 1) and w is the manufacturer's wholesale price.

[0157] The expression of the retailer's profit function is:

[0158] π R = E[pmin(Q, D)+v(Q - D) + -t(D - Q) + -wQ] (17)

[0159] The expression of the manufacturer's profit function is:

[0160]

[0161] The expression of the supplier's profit function is:

[0162] π S = (u - c1 - heS )Q (19)

[0163] The total carbon emissions of the entire supply chain are:

[0164] E=(E S -e S )Q+(E M -e M )Q+E R Q (20).

[0165] There are also two situations in which supply chain parties make decisions under the grandfather allocation rule and product subsidy policy:

[0166] (1) When gc P -k<0, the corresponding optimal supplier emission reduction level e S2 , the best manufacturer emission reduction level M2 And the optimal order quantity Q2 is:

[0167]

[0168] By substituting these equations for e S2 , e M2 and Q2 to formula (20), the total carbon emissions of the supply chain E2 can be calculated.

[0169] (2) When gc P -k>0, similar to the previous scenario, the manufacturer will choose e M =0 or e M =E M ;

[0170] Given e M =0, the supplier's corresponding emission reduction level e S That is, the retailer’s order quantity Q is:

[0171]

[0172] As it stands, the total carbon emissions from the supply chain are:

[0173]

[0174] Given e M =E M , corresponding to e S and Q is:

[0175]

[0176] As it stands, the total carbon emissions from the supply chain are:

[0177]

[0178] S22. Carbon emission management based on baseline management rules, that is, analyzing the supply chain model, benchmark rules and two different subsidy policies under the cap-and-trade carbon rights trading mechanism, including:

[0179] S221. Supply chain model under green investment subsidies;

[0180] The retailer's profit function expression is:

[0181] π R =E[pmin(Q,D)+v(QD) + -t(DQ) + -wQ] (26)

[0182] The manufacturer's profit function expression is:

[0183]

[0184] Under the benchmark rule, the manufacturer’s emission allowance is the benchmark emission intensity multiplied by the output value, i.e., ewQ. Therefore, the trading volume of emission allowances is (E M -e M )Q-ewQ;

[0185] The supplier's profit function expression is:

[0186] π S =(u-c1-he S )Q (28)

[0187] The total carbon emissions of the entire supply chain are:

[0188] E=(E S -e S )Q+(E M -e M )Q+E R Q (29)

[0189] Based on gc P -(1-s)k value, there are two situations in the decision-making of the supply chain parties:

[0190] (1) When gc P -(1-s)k<0, the optimal emission reduction level for suppliers and manufacturers, as well as the order quantity are:

[0191]

[0192] By substituting these equations for e S3 , e M3 By inserting Q3 into equation (29), the total carbon emissions of the supply chain E3 can be calculated.

[0193] (2) When gc P -(1-s)k>0, in which case the manufacturer will choose not to make green investments (e M =0) or minimize its emissions (e M =E M ).

[0194] Given e M =0, the supplier's corresponding emission reduction level e S And the retailer’s order quantity Q is:

[0195]

[0196] In this case, the total carbon emissions of the supply chain are:

[0197]

[0198] Given e M =E M , corresponding to e S and Q is:

[0199]

[0200] Then, the total carbon emissions of the supply chain should be:

[0201]

[0202] S222, Supply chain model under product subsidies;

[0203] The retailer's profit function expression is:

[0204] π R =E[pmin(Q,D)+v(QD) + -t(DQ) + -wQ] (35)

[0205] The manufacturer's profit function expression is:

[0206]

[0207] The supplier's profit function expression is:

[0208] π S =(u-c1-he1)Q (37)

[0209] The total carbon emissions of the entire supply chain are:

[0210] E=(e S -e1)Q+(e M -e2)Q+e RQ (38).

[0211] There are two situations for decision making:

[0212] (1) When gc P -(1-s)k<0,

[0213] The optimal emission reduction levels and order quantities for suppliers and manufacturers are:

[0214]

[0215] Substituting formula (39) into formula (38), the total carbon emissions of the supply chain E4 can be calculated.

[0216] (2) When gc P -(1-s)k>0, in which case the manufacturer will choose not to operate green investment (e M =0) or try to reduce its emissions (e M =E M ).

[0217] Given e M =0, the supplier's corresponding emission reduction level e S And the retailer’s order quantity Q is:

[0218]

[0219] In this case, the total carbon emissions of the supply chain are:

[0220]

[0221] Given e M =E M , corresponding to e S and Q is:

[0222]

[0223] In this case, the total carbon emissions of the supply chain are:

[0224]

[0225] Several propositions are proposed on the analytical solutions of the supply chain model in the above four cases.

[0226] Proposition 1: The higher the supplier's emission reduction level, the higher the manufacturer's emission reduction level. Higher emission reduction levels will also lead to larger order volumes.

[0227] Proof: According to equations (8) and (10), under the grandfathering rule and green investment subsidies, the relationship between the supplier's optimal emission reduction level, the manufacturer's optimal emission reduction level and the order quantity in the model is summarized as follows:

[0228]

[0229] It can be observed that when e S1 Increase, e M1 and Q1 will increase. The proof of the other three cases is the same as the above. The strengthening of green investment in suppliers will attract more consumers, which enables manufacturers to have more financial support to further reduce their carbon emissions. The increase in emission reduction levels of suppliers and manufacturers can attract more green consumers, which enables retailers to provide more order volumes.

[0230] Proposition 2: Under different mixed low-carbon policy scenarios, the relationship between suppliers’ optimal emission reduction levels is shown in Table 2, where GP is the supply chain model of C&T and product subsidies under the grandfather rule, BI refers to the model of C&T and green investment subsidies under the baseline method, GI refers to the model of C&T and green investment subsidies under the grandfather rule, and BP refers to the supply chain model of C&T and product subsidies under the baseline method.

[0231] Table 2 Comparison of emission reduction levels of the best suppliers

[0232] Scenario <![CDATA[GP(e S2 )]]> <![CDATA[BI(e S3 )]]> <![CDATA[GI(e S1 )]]> <![CDATA[△S1=e S1 -and S2 ]]> <![CDATA[△S2=e S1 -and S3 ]]> <![CDATA[BP(e S4 )]]> <![CDATA[△S3=e S2 -and S4 ]]> <![CDATA[△S4=e S3 -and S4 ]]>

[0233] Table 2 shows the signs of the differences in the emission reduction levels of the best suppliers under the four scenarios. Based on the analysis results of the emission reduction levels of the best suppliers mentioned above, the differences can be calculated as follows:

[0234]

[0235] Due to gc P -(1-s)k<0, when 2k(ms-sm)w+2gks(u+c2+c P E M )-gc P wm>0,△S1>0. This means that when this condition is met, suppliers will achieve higher emission reduction levels under green investment subsidies than under product subsidy policies. Similarly, when 2k(ms-sm)w+2gks(u+c2+c P E M -c P ew)-gc P wm>0, suppliers will achieve higher emission reduction levels under the green investment subsidy policy in the carbon trading market.

[0236] △S2>0 and △S3>0 means e S1 >e S3 and e S2 >e S4Therefore, under the same subsidy policy, the emission reduction level of suppliers under the carbon trading mechanism based on grandfathering rules is always greater than that under the baseline rule.

[0237] Proposition 3: The relationship between manufacturers’ optimal emission reduction levels under different low-carbon policy scenarios is shown in the following table.

[0238] Table 3 Comparison of emission reduction levels of the best manufacturers

[0239] Scenario <![CDATA[GP(e M2 )]]> <![CDATA[BI(e M3 )]]> <![CDATA[GI(e M1 )]]> <![CDATA[△M1=e M1 -and M2 ]]> <![CDATA[△M2=e M1 -and M3 ]]> <![CDATA[BP(e M4 )]]> <![CDATA[△M3=e M2 -and M4 ]]> <![CDATA[△M4=e M3 -and M4 ]]>

[0240] Table 3 shows the signs of the differences in the optimal supplier emission reduction levels under the four scenarios. Based on the analysis results of the optimal manufacturer emission reduction level in the previous section, the difference between the two can be calculated as:

[0241]

[0242] It can be seen that the relationship between the emission reduction level under the same measurement and control rule and different subsidy policies is quite complex and is affected by multiple parameters. Because △M2<0 and △M3<0, under the same subsidy policy, the manufacturer's emission reduction level is always higher under the baseline rule.

[0243] Through comparative analysis of suppliers’ emission reduction levels, it can be found that the grandfathering mechanism is more suitable for incentivizing suppliers to make green investments, while the baseline mechanism is more suitable for encouraging manufacturers to take more green efforts.

[0244] S3. Perform performance analysis on the supply chain models of different modes in step S2, make supply chain decisions under the same subsidy budget, analyze the performance of the supply chain model from the perspectives of supply chain performance and total carbon emissions, and discuss the impact of several important parameters on the profitability and sustainability of the supply chain.

[0245] The retail price is set to 273, the factory wholesale price is set to 220, the component selling price is set to 75, the currency unit is RMB, the residual value is set to 96, the penalty cost for order backlog is set to 20, and the production costs of suppliers and manufacturers are set to 45 and 80 respectively; for manufacturers, the green investment cost ratio is assumed to be 16 and the carbon emissions of each product are set to 100 kg; for suppliers, the green investment cost ratio is assumed to be 0.15 and the emissions of each component are set to 45 kg. The emissions of each product of retailers are set to 10 kg. According to the carbon emission trading data of China in 2019 provided by the International Green Finance Institute CUFE (2020), the average carbon price is set to 23 yuan / ton. For the carbon rights trading market adopting the grandfather rule, the carbon emission cap is set to 80 tons and the benchmark emission intensity is set to 0.4. The green sensitivity coefficient of consumers is set to 5. Assume that the a part of the demand function is 1500, and the demand risk is assumed to follow a normal distribution with characteristic coefficients of μ=100 and σ=50, where ε∈[-50,250].

[0246] Numerical results

[0247] Table 4 shows the numerical results of the supply chain model under different quota allocation rules and different subsidy policies. It can be seen that the application of subsidy policies can encourage manufacturers to reduce more carbon emissions, which puts less pressure on suppliers in terms of carbon emission reduction. Under the subsidy policy, the total carbon emissions of the supply chain are reduced, and the profitability of the three parties is improved. It shows the effectiveness of mixed low-carbon policies in improving the sustainability and profitability of the supply chain. Under the same subsidy ratio, the mixed policy of carbon rights trading based on the baseline method and product subsidies can help the supply chain achieve the lowest total carbon emissions.

[0248] Table 4 Numerical results

[0249]

[0250] Sensitivity analysis

[0251] The establishment of carbon trading market and the development of green product market have a significant impact on the sustainable development and profitability of supply chain. This paper explores the impact of several important parameters on supply chain performance under different mixed policy scenarios.

[0252] Figure 3 The supply chain performance under four mixed policy scenarios with different subsidy ratios is shown in Figure 1. GI represents the combination of C&T mechanism and green investment subsidy under grandfather rule, and GP represents the combination of C&T mechanism and product subsidy under grandfather rule. BI represents the combination of C&T mechanism and green investment subsidy under baseline method, and BP represents the combination of C&T mechanism and product subsidy under baseline method.

[0253] When the subsidy intensity increases, manufacturers will increase the emission reduction level of their products. Although suppliers will be more passive in emission reduction, the total carbon emissions of the supply chain will still decrease with the increase of subsidy ratio. In addition, providing higher subsidy intensity can also increase the profits of all parties in the supply chain. The difference in supply chain performance under the grandfather rule and the baseline rule is small, while the difference in supply chain performance under the two subsidy policies is more obvious. When the subsidy coefficient is less than 0.65, under the same subsidy coefficient, the product subsidy policy is more effective than the green investment subsidy policy in terms of emission reduction and profit increase. Under the product subsidy policy, manufacturers can also make more profits than under the green investment policy.

[0254] In addition to subsidy policies, the development of carbon trading markets and green product markets also has a significant impact on industrial enterprises' carbon emission reduction decisions. Figure 4 The total carbon emissions of the supply chain under different carbon market prices and consumer green awareness coefficients are shown. The increase in carbon market prices and consumer green awareness will lead to a reduction in total carbon emissions, and the increase in consumer green awareness is more effective in promoting carbon emission reduction. Therefore, in order to better achieve the goal of controlling industrial carbon emissions, the government should cooperate with industrial enterprises to improve consumers' green awareness and establish a greener market environment.

[0255] The application of subsidy policies requires financial support from the government, and how to use funds more efficiently is an important issue that the government management is concerned about. Therefore, this paper compares and analyzes the impact of four mixed low-carbon policies on supply chain performance under the same subsidy budget.

[0256] Figure 5 The results show that the emission reduction decisions of suppliers and manufacturers under the same subsidy budget are affected by grandfather-based carbon trading and two subsidy policies (e S1 、e M1 and e S2 、e M2), the profits of suppliers, manufacturers and retailers (SP1, MP1, RP1 and SP2, MP2, RP2), and the total emissions (E1 and E2) and total profits (SCP1 and SCP2) of the supply chain. Under the same subsidy budget, the green investment subsidy policy can motivate manufacturers to achieve a higher level of emission reduction. The pressure on suppliers to reduce emissions is reduced, so they choose a lower level of emission reduction. Under the same subsidy budget, the green investment subsidy policy can help the supply chain achieve less total carbon emissions than under the product subsidy policy. When the subsidy budget is increased, the green investment subsidy can more effectively reduce total emissions. Suppliers and retailers can obtain higher profits under the green investment subsidy policy, while manufacturers can obtain higher profits under the product subsidy policy. When the total subsidy budget is less than 4000, the supply chain profit under the product subsidy will be higher than the supply chain profit under the green investment subsidy. When the subsidy budget exceeds 4000, the supply chain will obtain higher profits under the green investment subsidy.

[0257] Figure 6 The emission reduction decisions of suppliers and manufacturers under the baseline C&T and two subsidy models are shown (e S3 、e M3 and e S4 、e M4 ), the profits of suppliers, manufacturers and retailers (SP3, MP3, RP3 and SP4, MP4, RP4), and the total emissions (E3 and E4) and total profits (SCP3 and SCP4) of the supply chain. Under the same subsidy budget, green investment subsidies are more effective in carbon emission reduction. Providing more subsidies can help all parties in the supply chain obtain higher profits. Similar to the situation under the grandfather rule, green investment subsidies are more conducive to the profitability of suppliers and retailers, while product subsidies are more beneficial to manufacturers. When the subsidy budget is less than 4,500, the product subsidy policy can bring more profits to the entire supply chain. But when the total subsidy exceeds 4,500, the supply chain profit under the green investment subsidy begins to rise.

[0258] Figure 7 The total emissions and profits of the supply chain under four mixed policy scenarios are shown, where Ei (i = 1, .., 4) is the total carbon emissions under the four supply chain scenarios, and SCPi (i = 1, .., 4) represents the four supply chain scenarios. Figure 7It can be seen that the combination of grandfather-based C&T and green investment subsidy policies can help the supply chain achieve the lowest total emissions. Under the four mixed policy scenarios, the increase in subsidy budget can improve the sustainability and profitability of the supply chain. The supply chain profit under the baseline rule is greater than the supply chain profit under the grandfather rule. When the subsidy budget is less than 4500, the supply chain profit is the highest under the mixed policy of C&T based on the baseline rule and product subsidies. When the subsidy budget is greater than 4500, the supply chain can obtain the highest profit under the mixed policy of C&T based on the baseline rule and green investment subsidies.

[0259] appendix

[0260] (1) When 2gc P -2(1-s)k<0,π M is a concave function.

[0261] make The best emission reduction can be obtained M ,Right now:

[0262]

[0263] The supplier's profit function becomes:

[0264]

[0265] By differentiating the supplier profit function, we can obtain:

[0266]

[0267]

[0268] where con=F -1 (r)+ag(E S +E M +E R )

[0269] (A3)

[0270] Therefore, π S About e s A concave function of . Let The optimal emission reduction level of suppliers can be obtained, namely:

[0271]

[0272] By substituting equation (A4) into equations (A1) and (7), the optimal emission reduction level of the manufacturer and the order quantity of the retailer can be calculated, respectively:

[0273]

[0274]

[0275]

[0276]

[0277] (2) When 2gc P -2(1-s)k>0,π M is a convex function.

[0278] Given e M =0, the supplier's profit function expression becomes:

[0279]

[0280] In this case, the supplier's reduction level is:

[0281]

[0282] The corresponding order quantity should be:

[0283]

[0284] Given e M =E M , the supplier's profit function expression becomes:

[0285]

[0286] In this case, the corresponding emission reduction levels of suppliers and the order volumes of retailers are:

[0287]

[0288] The proofs of the supply chain model under the remaining three carbon policy scenarios are similar to the proofs of the model under the grandfather rule of green investment subsidies.

[0289] Therefore, the present invention adopts the above-mentioned multi-party supply chain carbon emission management method based on subsidies and carbon rights trading, and studies the impact of a mixed low-carbon policy consisting of carbonization technologies with different subsidies and different subsidy allocation rules on supply chain carbon emission reduction and profit realization. The results show that suppliers' green efforts can help the supply chain achieve better emission reduction and profitability. In addition, the application of mixed low-carbon policies can also promote higher levels of emission reduction; technology combined with grandfathering rules and green investment subsidies is more suitable for developed and high-emission industries. The combination of measurement and control technology with benchmarking rules and subsidy policies is more suitable for developing industries; under the same budget, the measurement and control mechanism and the mixed policy of grandfathering rules and green investment subsidies can help the supply chain achieve the lowest total emissions.

[0290] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A multi-party supply chain carbon emission management method based on subsidies and carbon rights trading, characterized by: It includes the following steps: S1. Based on the carbon trading mechanism and low-carbon subsidies, a hybrid carbon emission policy is formed, a supply chain model is established, and model settings are carried out; S2. Conduct a mode analysis on the supply chain model in step S1; S3. Conduct a performance analysis on the supply chain models with different modes in step S2, and formulate supply chain decisions under the same subsidy budget.

2. The multi-party supply chain carbon emission management method based on subsidy and carbon rights trading according to claim 1 is characterized in that: In step S1, the carbon trading mechanism considers two quota allocation rules, namely the grandfathering rule and the baseline rule. Under the grandfathering rule, a total carbon emission quota for a certain period, i.e., the carbon cap C, is set for the manufacturer; Under the baseline rule, the allocated limit is not fixed, but is proportional to the manufacturer's production capacity, i.e., the emission intensity e multiplied by the product of the wholesale price and the output wQ; The newsvendor model is used to simulate the market uncertainty, considering the impact of consumers' green awareness g on product demand. The product demand function D in the green market is defined as: D = y + ε (1) Where y = ag(E S +E M +E R -e S -e M ), a is the product demand in the original market, Es, E M , E R are the unit carbon emissions of suppliers, manufacturers and retailers, es and e M are the unit carbon emission reduction of suppliers and manufacturers, g(E S +E M +E R -e S -e M ) represents the impact of consumers’ green awareness on product demand, and ε is a random variable showing market uncertainty, where ε∈[A, B], a≥-a+g(E S +E M +E R ), E(ε)=μ, the product price p is set as a constant in the newsboy model; the Steinberg game model is used to simulate the coordination between the parties in the supply chain.

3. The multi-party supply chain carbon emission management method based on subsidy and carbon rights trading according to claim 2 is characterized in that: Step S2 specifically includes: S21. The total carbon emission control and trading rule based on the grandfathering rule, i.e., analyze the supply chain mode under the carbon trading mechanism based on the grandfathering quota allocation rule; S22. The total carbon emission control and trading rule based on the baseline method management rule, i.e., analyze the supply chain mode under the carbon trading mechanism based on the baseline method quota allocation rule.

4. The multi-party supply chain carbon emission management method based on subsidy and carbon rights trading according to claim 3 is characterized in that: Step S21 specifically includes: S211. The supply chain mode under green investment subsidies; For the supply chain under the grandfathered carbon trading and green investment subsidy policy, the retailer’s profit π R The function expression is: π R =E[pmin(Q,D)+v(Q-D) + -t(D-Q) + -wQ] (2) The function expression consists of four parts, among which (QD) + Indicates unsold products, (DQ) + represents unmet demand; the first part is the revenue, i.e. pmin(Q,D), and the second part is the residual value of unsold products v(QD) + , where v is the residual value of the product, the third part is the penalty cost of product shortage, t is the penalty price of a single product, the fourth part is the cost of purchasing the product from the manufacturer, and w is the wholesale price of the product; Taking into account the impact of mixed low-carbon policies, the manufacturer's profit π M The function expression is: The manufacturer's profit includes wholesale revenue, the green investment cost after subsidy, and the emissions trading cost. The wholesale revenue is the profit per unit product multiplied by the product order quantity Q. The government green investment subsidy coefficient is s (0 < s < 1), k is the manufacturer's green investment cost coefficient, and the carbon credit trading volume is the actual emissions after green investment minus the allocated quota, which is (E M -e M )Q - C. A positive value means that the manufacturer must purchase quotas from the carbon market, while a negative value means that the manufacturer sells the unused quotas to other companies in the carbon market; The supplier's profit function π S The expression includes the wholesale revenue of parts, production cost and the cost of using green materials or energy, that is: π S =(u-c1-he S )Q (4) Among them, u is the component price, c1 is the unit production cost of the supplier, and h is the green investment cost coefficient of the supplier; The total carbon emissions of the entire supply chain, E, include suppliers (E s -e S )Q、Manufacturer(E M -e M )Q and the retailer’s carbon emissions E R Q, that is: And=(And S -And S )Q+(E M -And M )Q+E R Q (5) The backward induction method is used to analyze the decisions of the three supply chain parties, and the inventory factor r = Q - y is used to simplify the calculation: r > ε means that the product is greater than the demand, resulting in product surplus; r < ε means that the product is lower than the demand, resulting in product shortage; Therefore, the profit function of the retailer becomes: p R =E[p min(y+ε,y+r)+v(r-ε) + -t(e-r) + -w(y+r)] (6) Through the derivation of the retailer's profit function, the results are as follows: The optimal order quantity Q is: Q=F -1 (r)+a-g(E S +E M +E R )+g(e S +e M ) (8) in, By substituting equation (8) into manufacturer π M The profit function becomes: Where con = F -1 (r)+ag(E S +E M +E R ), through the derivation of the manufacturer's profit function, the following conclusions are drawn: S212. The supply chain mode under product subsidies; According to the product subsidy policy, the government will provide a subsidy of mw for each green product produced by the manufacturer, where m is the subsidy coefficient (0 < m < 1) and w is the manufacturer's wholesale price; The expression of the retailer's profit function is: π R =E[pmin(Q,D)+v(Q-D) + -t(D-Q) + -wQ] (11) The expression of the manufacturer's profit function is: The expression of the supplier's profit function is: π S =(u-c1-he S )Q (13) The total carbon emission of the entire supply chain is: And=(And S -And S )Q+(E M -And M )Q+E R Q (14)。 5. The multi-party supply chain carbon emission management method based on subsidy and carbon rights trading allocation rules according to claim 4 is characterized in that: Step S22 specifically includes: S221. The supply chain mode under green investment subsidies; The expression of the retailer's profit function is: π R =E[pmin(Q,D)+v(Q-D) + -t(D-Q) + -wQ] (15) The expression of the manufacturer's profit function is: Under the baseline rule, the manufacturer's emission allowance is the baseline emission intensity multiplied by the output value, that is, ewQ. Therefore, the trading volume of emission allowances is (E M -e M )Q-ewQ; The expression of the supplier's profit function is: π S =(u-c1-he S )Q (17) The total carbon emission of the entire supply chain is: And=(And S -And S )Q+(E M -And M )Q+E R Q (18); S222. The supply chain mode under product subsidies; The expression of the retailer's profit function is: π R =E[pmin(Q,D)+v(Q-D) + -t(D-Q) + -wQ] (19) The expression of the manufacturer's profit function is: The expression of the supplier's profit function is: π S =(c1−he1)Q (21) The total carbon emission of the entire supply chain is: E=(e S -e1)Q+(e M -e2)Q+e R Q (22)。 6. The multi-party supply chain carbon emission management method based on subsidy and carbon rights trading according to claim 5 is characterized in that: In step S3, the performance analysis of the supply chain model is carried out from the aspects of supply chain performance and total carbon emissions.

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