Enterprise operation decision optimization method and system based on carbon dependent loan interest rate

Abstract

The invention relates to the cross technical field of low-carbon supply chain management and enterprise financial operation, in particular to a supply chain enterprise operation decision optimization method and system based on a carbon dependent loan interest rate, and the method comprises the following steps: collecting enterprise carbon quota quantity and carbon emission information; a financial institution provides two loan schemes for manufacturers confronting capital constraints: fixed interest rate loan: the loan interest rate is not changed once the loan interest rate is determined; carbon dependent floating interest rate loan: the loan is linked with the carbon emission reduction of the manufacturer, and the higher the carbon emission reduction is, the lower the loan interest rate is; a manufacturer selects a loan mode suitable for himself and decides the carbon emission reduction amount and the wholesale price of the product. According to different loan schemes, a loan strategy capable of maximizing the profit of a manufacturer or realizing higher carbon emission reduction is found, and meanwhile, a profit optimization strategy is provided for a bank and a quantitative basis is provided for the government to formulate a carbon policy.

Description

Technical Field

[0001] This invention relates to the interdisciplinary field of low-carbon supply chain management and corporate financial operations, specifically to a method and system for optimizing corporate operational decisions based on carbon-dependent loan interest rates. It is specifically applied to how manufacturers with limited funds can optimize their financing and operational decisions under the background of carbon quotas and carbon trading policies, while also providing policymakers with some reasonable policy suggestions. Background Technology

[0002] With the deepening of the global low-carbon development concept and the continuous improvement of consumers' environmental awareness, manufacturers need to invest in green technologies to reduce the carbon emissions of their products to meet market demands. However, the research and development and application of green technologies require substantial financial investment, and most manufacturers face a shortage of funds, making it difficult to smoothly carry out emission reduction activities such as energy structure transformation, industrial upgrading and transformation, and green technology innovation. This indicates that existing funds alone are insufficient to meet the demand, and there is an urgent need to guide social capital investment through green finance tools to help achieve the "dual carbon" goals. To guide more funds into the field of carbon emission reduction, the People's Bank of China has launched a carbon emission reduction support tool, which operates with a direct "loan first, then borrow" mechanism to support the development of key areas such as clean energy, energy conservation and environmental protection, and carbon emission reduction technologies. Therefore, in-depth research on the impact of financing policies under the carbon emission reduction support tool on the carbon reduction operation mechanism of enterprises has important theoretical and practical significance for promoting the sustainable development of my country's economy and society and helping to achieve the "dual carbon" goals.

[0003] With the support of carbon emission reduction support tools, financial institutions' financing policies can be divided into two categories based on whether they are linked to corporate carbon emissions. The first category is fixed-rate financing unrelated to corporate carbon emissions; its interest rate is usually linked to the project's risk and return, and is not significantly different from traditional credit financing methods. The second category is carbon-dependent loans: financing methods where the interest rate is linked to corporate carbon emissions. Specifically, the greater the carbon reduction, the lower the financing rate; conversely, the lower the carbon reduction, the higher the financing rate. This indicates that under financing methods linked to carbon emissions mechanisms, a company's carbon reduction effectiveness directly affects its financing interest rate.

[0004] Furthermore, under carbon quota and carbon trading policies, manufacturers whose carbon emissions exceed their quotas can sell them on the carbon market to generate revenue; if their emissions exceed their quotas, they must purchase additional carbon quotas to offset the difference. Therefore, under carbon-dependent loan interest rates, high carbon reductions can lead to lower loan interest rates and potentially generate revenue from selling surplus carbon quotas. Existing business operation decisions have not fully incorporated this policy characteristic: manufacturers struggle to balance the costs of emission reduction investments, loan repayments, and carbon quota trading revenue, often resulting in either excessive emission reduction investments squeezing profits or insufficient emission reductions leading to carbon quota penalties. Therefore, whether carbon-dependent loan interest rates, compared to fixed loan interest rates, can change companies' carbon reduction decisions, encourage them to reduce emissions further, and lower financing costs is a scientific question worthy of in-depth research.

[0005] While existing research focuses on supply chain financing and low-carbon operations, it largely concentrates on fixed-interest-rate scenarios, lacking a systematic decision-making approach for "carbon-dependent loan interest rates." Furthermore, it fails to provide an integrated solution from the manufacturer's perspective, demonstrating how financing decisions (front-end) influence product production decisions (back-end), thus failing to meet manufacturers' decision-making needs under current financing policies, carbon trading policies, and consumers' green preferences. Therefore, there is an urgent need for a method that integrates carbon-dependent loan interest rates, carbon quota trading policies, and collaborative decision-making among supply chain enterprises to address the core issues currently faced by manufacturers, while also providing relevant management insights for policymakers. Summary of the Invention

[0006] This invention aims to provide a method and system for optimizing enterprise operation decisions based on carbon-dependent loan interest rates. It addresses the problems of insufficient emission reduction funds for manufacturers, blind selection of loan strategies, poor coordination between operation and financial decisions, and difficulty in balancing profits and emission reduction in the existing technology. It helps manufacturers select the optimal loan method and production and operation plan based on market dynamics, while promoting the improvement of overall social welfare and providing scientific theoretical support for achieving the "dual carbon" goal as soon as possible.

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] A method for optimizing corporate operational decisions based on carbon-dependent loan interest rates includes the following steps:

[0009] Step S1: Data Collection: Collect data on manufacturers' carbon emissions, financial data, and market demand data;

[0010] Step S2: Through historical data collection and market research, retailers can analyze consumer preferences and predict sensitive parameters for carbon reduction coefficients. By combining utility theory from economics, we can predict consumers' valuation of a product's utility. And by using information related to the carbon emissions of a manufacturer's products, it is possible to estimate the carbon reductions that its green technologies can achieve. ;

[0011] Step S3: Financial institutions set up two different loan plans based on different interest rates;

[0012] Step S4: Based on the company's carbon quota and the carbon reduction cost of the product, the manufacturer constructs a profit function under two different loan interest rate schemes. Under the goal of maximizing profits, the manufacturer solves for the optimal carbon reduction and wholesale price of the product. The manufacturer and retailer's profits and carbon reduction under the equilibrium decision results of the two loan schemes are compared. Based on the manufacturer's phased goals, the optimal loan strategy is selected.

[0013] In a further optimization of this technical solution, step S1 specifically includes:

[0014] (1) Manufacturer carbon emission data: initial carbon emissions Annual carbon allowances issued by the government Emission reductions achievable through green technologies Emission reduction cost coefficient ;

[0015] (2) Financial data: Fixed loan interest rates provided by financial institutions Sensitive parameters of carbon-dependent loan interest rates Unit price in the carbon trading market ;

[0016] (3) Market demand data: Historical consumer purchase data to estimate consumer sensitivity to product carbon emission reduction. and consumers' valuation of the product. ;

[0017] Data collection was achieved through a combination of internal statistics and external collaboration: manufacturers compiled initial carbon emissions statistics. Carbon emission reduction Data; collaborating with banks to obtain sensitive parameters regarding the difference between carbon reduction and benchmark amounts in loan interest rates. ; Obtain consumer sensitivity through market research institutions and consumers' valuation of the product Unit price in the carbon trading market This ensures that the data is authentic and traceable.

[0018] A further optimization of this technical solution is that step S2 includes: the carbon emission reduction of the product will increase the utility of the product, and the price of the product is... Consumers purchase products based on the principle that their utility is non-negative, thus establishing the consumer's utility function. and consumer surplus function Predict the quantity of products purchased by retailers And construct the retailer's revenue function given a fixed wholesale price. , This is the wholesale price.

[0019] This technical solution is further optimized in step 3 regarding the loan scheme:

[0020] (3) Fixed-rate loan scheme: loan interest rate Fixed loan interest rate It was determined before the loan was issued and it will not change with the manufacturer's final carbon emission reductions;

[0021] (4) Carbon-dependent loan scheme: loan interest rate Related to carbon emission reductions, after a loan is issued, the interest rate varies depending on the manufacturer's final carbon emission reductions. Specifically, the interest rate is negatively correlated with the manufacturer's product carbon emission reductions. The higher the rate, the higher the loan interest rate. The lower;

[0022] Based on the initial carbon emissions collected from manufacturers The annual carbon allowance issued by the government Carbon emission reductions achievable through green technologies and sensitive parameters of carbon-dependent loan interest rates It can be seen that carbon-dependent loans are .

[0023] In a further optimization of this technical solution, step S4 specifically includes:

[0024] Under the carbon cap and carbon trading system, if a company's carbon emissions exceed its carbon quota, it needs to purchase the corresponding carbon quota. ,in, This represents the manufacturer's initial carbon emissions. For manufacturers' carbon allowances. This refers to the carbon emission reductions of manufacturers; if a company's carbon emissions are lower than its carbon allowances, the company can obtain additional profits by selling carbon allowances.

[0025] If the manufacturer's carbon emission reduction is By estimating the manufacturer's emission reduction parameters, the cost of carbon emission reduction can be determined. According to market research on carbon prices, the total amount of loans for manufacturers with limited funds is the cost of carbon emission reduction plus the cost of selling or buying carbon allowances. ;

[0026] The manufacturer's profit function is ,in, This is the wholesale price, specifically...

[0027] (1) In the fixed-rate model, the manufacturer's profit is: ;

[0028] (2) In the carbon-dependent interest rate model, the manufacturer's profit is: ;

[0029] Retailers first optimize product prices To obtain the optimal retail price of a product; given a fixed retail price, the manufacturer decides on the wholesale price of the product. and carbon emission reduction ; and thus obtain the financial institution's revenue under this scheme. and social welfare ,in, It reflects financial institutions' sensitivity to the carbon reduction resulting from loans. The harm caused by carbon emissions to manufacturers.

[0030] A corporate operational decision optimization system based on carbon-dependent loan interest rates, the system comprising:

[0031] (1) Data collection and analysis module: used to collect manufacturers' initial carbon emissions, carbon quotas, emission reduction cost coefficients, financial institutions' benchmark interest rates and the sensitivity parameters of interest rates to carbon reduction, carbon trading prices, consumers' sensitivity to the carbon reduction of emission reduction products, and retailers' demand parameters based on consumers' historical purchase data, to verify the validity of the data, and to predict the emission reduction potential of manufacturers and market demand characteristics after preprocessing. (2) Retailer behavior prediction module: Based on the sensitivity coefficient of carbon emission reduction collected from historical consumer purchase data, the module predicts consumer purchase behavior for carbon-reduced products. Based on the assessment of consumer behavior, the retailer predicts the retail price of the product.

[0032] (3) Manufacturer Behavior Prediction Module: Based on the manufacturer's initial carbon emissions, carbon quotas, benchmark interest rates of financial institutions, the sensitivity parameters of interest rates to carbon reduction, and carbon trading prices, the module predicts the manufacturer's total loan amount and emission reduction effort coefficient.

[0033] (4) Loan scheme optimization module: Combine consumers’ historical purchase data and retailers’ retail prices, and input the manufacturer’s profit function under two loan interest rate scenarios: fixed and carbon-dependent; solve for the optimal product wholesale price and carbon emission reduction, and then obtain the profits of manufacturers and retailers, financial institutions and social welfare under the two loan interest rate scenarios. By comparing the core indicators under the two scenarios and combining the manufacturer’s phased goals, the optimal combination of loan strategy and operation strategy is output.

[0034] The retailer behavior prediction module and the manufacturer behavior prediction module analyze and process the data and behavior of retailers and manufacturers using economic utility theory, consumer behavior, and Stackelberg's game theory methods. They belong to the data analysis and processing unit. Finally, the optimal loan plan is output by comparing the manufacturer's profits and social welfare.

[0035] This technical solution is further optimized by including a data input unit in the data collection and analysis module. The data input unit is used to input the consumer's sensitivity coefficient to the carbon reduction of the product and to receive external and internal data.

[0036] Further optimizations to this technical solution include a data analysis and processing unit, used to analyze and process consumers' historical purchase data, manufacturers' carbon emission data, and data on financial institutions' benchmark interest rates and their sensitivity to carbon reduction. Based on consumers' utility functions and retailers' profit functions, it analyzes and predicts consumers' purchasing behavior and retailers' product retail prices.

[0037] Further optimization of this technical solution includes a loan scheme optimization module comprising: a fixed interest rate scheme and a carbon-dependent loan interest rate scheme. First, consumer purchasing behavior and retailer wholesale prices are imported into the manufacturer's profit function model to solve for the optimal product wholesale price and carbon reduction amount under different loan schemes, thereby obtaining the profits and social welfare of manufacturers and financial institutions. Then, the profits and social welfare are compared and analyzed to derive the optimal loan scheme.

[0038] The above-mentioned technical solution, which differs from existing technologies, has the following beneficial effects:

[0039] (1) Alleviating capital constraints: By linking the interest rate of carbon-dependent loans to carbon emission reductions, the loan costs for manufacturers to reduce emissions can be reduced, solving the problem of insufficient funds for emission reductions, and at the same time incentivizing manufacturers to increase carbon emission reductions;

[0040] (2) Optimize decision-making coordination: The Stackelberg game model led by manufacturers achieves coordination between "manufacturer carbon emission reduction - wholesale price" and "retailer retail price - demand", avoiding internal decision-making conflicts in the supply chain and improving the overall profitability of the supply chain;

[0041] (3) Flexible strategy adaptation: It provides a comparison and selection of two loan interest rate scenarios, and manufacturers can dynamically adjust according to phased goals (short-term profits, long-term emission reduction) and market parameters to adapt to different business scenarios;

[0042] (4) Balancing multiple objectives: While increasing manufacturers' profits and carbon emission reductions, social welfare is also considered, which is in line with the low-carbon policy orientation and helps manufacturers achieve sustainable development;

[0043] (5) Strong applicability: The system module design fits the actual business process of the manufacturer, the data collection relies on the existing interface, and the decision output provides specific and executable parameters. No additional complex development is required, and it is easy to promote and apply. Attached Figure Description

[0044] Figure 1 Flowchart of an optimization method for corporate operational decisions based on carbon-dependent loan interest rates;

[0045] Figure 2 A system architecture diagram for an enterprise operational decision optimization method based on carbon-dependent loan interest rates;

[0046] Figure 3 A schematic diagram of the optimal loan scheme selection module provided for the implementation of this invention. Detailed Implementation

[0047] To explain in detail the technical content, structural features, objectives, and effects of the technical solution, the following description is provided in conjunction with specific embodiments and accompanying drawings.

[0048] See Figure 1 The diagram shown is a flowchart of a method for optimizing enterprise operational decisions based on carbon-dependent loan interest rates. A preferred embodiment of this invention provides a method for optimizing enterprise operational decisions based on carbon-dependent loan interest rates, comprising the following steps:

[0049] Step S1: Data Collection: Collect relevant data from manufacturers, including carbon emission data, financial data, market demand data, etc., specifically including:

[0050] (1) Manufacturer carbon emission data: initial carbon emissions (Carbon emissions per unit of product without the adoption of green technologies), annual carbon allowances issued by the government (In line with policy emission reduction guidelines, with quotas not exceeding the initial carbon emissions), carbon emission reductions achievable through green technologies. (Determined by the manufacturer's level of green technology, not exceeding the initial carbon emissions), emission reduction cost coefficient (This reflects the cost efficiency of green technology investment; the smaller the coefficient, the lower the cost.)

[0051] (2) Financial data: Fixed loan interest rates provided by financial institutions Sensitive parameters of carbon-dependent loan interest rates (The larger the parameter, the more significant the reduction in loan interest rates due to increased carbon emission reductions), the unit price in the carbon trading market. (A uniform unit price for purchasing or selling carbon allowances);

[0052] (3) Market demand data: Historical consumer purchase data to estimate consumer sensitivity to product carbon emission reduction. (The higher the sensitivity, the stronger the consumer's willingness to purchase due to the product's increased carbon emission reduction, and the higher the consumer's valuation of the product.) (Generally follows a uniform distribution of 0-1);

[0053] Data collection was achieved through a combination of internal statistics and external collaboration: manufacturers internally calculated initial carbon emissions. Carbon emission reduction Data; collaborating with banks to obtain sensitive parameters regarding the difference between carbon reduction and benchmark amounts in loan interest rates. ; Obtain consumer sensitivity through market research institutions and consumers' valuation of the product Carbon trading price data This ensures that the data is authentic and traceable.

[0054] Step S2: Carbon-reducing products differ from general products in that their utility valuation approximates both the consumer's valuation of the product's functionality and its environmental utility valuation based on carbon emission reduction. Due to this consistency among consumers, retailers can analyze consumer preferences and predict sensitive parameters for carbon emission reduction coefficients through historical data collection and market research. By combining utility theory from economics, we can predict consumers' valuation of a product's utility. And by using information related to the carbon emissions of a manufacturer's products, it is possible to estimate the carbon reductions that its green technologies can achieve. .

[0055] The carbon emission reduction of a product will increase its utility, and the price of the product will be... Consumers purchase products based on the principle that their utility is non-negative, thus establishing the consumer's utility function. and consumer surplus function Predict the quantity of products purchased by retailers And construct the retailer's revenue function given a fixed wholesale price. , This is the wholesale price.

[0056] Step S3: Two loan options based on different interest rate settings:

[0057] (5) Fixed-rate loan scheme (loan interest rate) Fixed loan interest rate It was determined before the loan was issued that it would not change with the manufacturer's final carbon emission reductions.

[0058] (6) Carbon-dependent loan scheme: loan interest rate Related to carbon emission reductions. After a loan is issued, the interest rate varies depending on the manufacturer's final carbon emission reduction. Specifically, the loan interest rate is negatively correlated with the manufacturer's product carbon emission reduction; the amount of carbon reduction corresponds to the amount of carbon emissions reduced. The higher the rate, the higher the loan interest rate. The lower.

[0059] Based on the initial carbon emissions collected from manufacturers The annual carbon allowance issued by the government Carbon emission reductions achievable through green technologies and sensitive parameters of carbon-dependent loan interest rates It can be seen that carbon-dependent loans are ( )

[0060] Step S4: Manufacturers construct profit functions under two different loan interest rate schemes based on their carbon allowances and product carbon reduction costs. Under the objective of profit maximization, they solve for the optimal carbon reduction and wholesale price for their products. By comparing the profits and carbon reductions of manufacturers and retailers under the equilibrium decisions of the two loan schemes, and based on the manufacturer's phased objective (profit maximization or carbon reduction maximization), they select the optimal loan strategy (fixed-rate loan or carbon-dependent rate loan). By writing the profit and social welfare functions of financial institutions based on their utility, and then conducting comparative analysis, they can provide some rational suggestions for policy-making agencies.

[0061] Under the carbon cap and carbon trading system, if a company's carbon emissions exceed its carbon quota, it needs to purchase the corresponding carbon quota. ,in, For the manufacturer's initial carbon emissions, For manufacturers' carbon allowances. This refers to the carbon emission reductions of manufacturers; if a company's carbon emissions are lower than its carbon allowances, the company can obtain additional profits by selling carbon allowances.

[0062] If the manufacturer's carbon emission reduction is By estimating the manufacturer's emission reduction parameters, the cost of carbon emission reduction can be determined. According to market research on carbon prices, the total amount of loans for manufacturers with limited funds is the cost of carbon emission reduction plus the cost of selling or buying carbon allowances. ).

[0063] The manufacturer's profit function is .in, These are wholesale prices. Specifically,

[0064] (1) In the fixed-rate model, the manufacturer's profit is:

[0065] (2) In the carbon-dependent interest rate model, the manufacturer's profit is:

[0066]

[0067] Retailers first optimize product prices To obtain the optimal retail price of a product; given a fixed retail price, the manufacturer determines the optimal wholesale price of the product. and carbon emission reduction ; and thus obtain the financial institution's revenue under this scheme. and social welfare ,in, It reflects financial institutions' sensitivity to the carbon reduction resulting from loans. The harm caused by carbon emissions to manufacturers.

[0068] Under two different loan interest rate schemes, retailers use historical consumer purchase data to analyze consumer purchasing behavior, while manufacturers decide on wholesale prices and carbon reductions based on profit maximization. By comparing the differences in profits and social welfare under the equilibrium results of these two loan interest rate schemes, financial institutions and governments can be guided to set and select the optimal loan interest rate scheme.

[0069] Based on the design and comparison of two different loan interest rate schemes, financial institutions guide manufacturers to increase carbon reduction by setting appropriate benchmark interest rates and interest rate incentive coefficients; predict consumers' acceptance of carbon-reducing products by using historical consumer purchase data and environmental consumption preferences, and set the retail price of products with the goal of maximizing profits; and combine the manufacturer's phased goals, such as maximizing profits, achieving the highest carbon reduction, or maximizing total social welfare, to determine the optimal loan scheme and carbon reduction amount for the manufacturer.

[0070] See Figure 2 The diagram shown illustrates the structure for optimizing enterprise operational decisions based on carbon-dependent loan interest rates. The enterprise operational decision optimization system based on carbon-dependent loan interest rates comprises four main functional modules:

[0071] (1) Data collection and analysis module: used to collect manufacturers' initial carbon emissions, carbon quotas, emission reduction cost coefficients, financial institutions' benchmark interest rates and the sensitivity parameters of interest rates to carbon reduction, carbon trading prices, consumers' sensitivity to the carbon reduction of emission reduction products, and retailers' demand parameters based on consumers' historical purchase data, to verify the validity of the data, and to predict the emission reduction potential of manufacturers and market demand characteristics after preprocessing.

[0072] (2) Retailer behavior prediction module: Based on the sensitivity coefficient of carbon emission reduction collected from historical consumer purchase data, the module predicts consumer purchase behavior for carbon-reduced products. Based on the assessment of consumer behavior, the retailer predicts the retail price of the product.

[0073] (3) Manufacturer Behavior Prediction Module: Based on the manufacturer's initial carbon emissions, carbon quotas, benchmark interest rates of financial institutions, the sensitivity parameters of interest rates to carbon reduction, and carbon trading prices, the module predicts the manufacturer's total loan amount and emission reduction effort coefficient.

[0074] (4) Loan Scheme Optimization Module: This module combines historical consumer purchase data and retailer prices, inputting the manufacturer's profit function under both fixed and carbon-dependent loan interest rate scenarios. It then solves for the optimal product wholesale price and carbon emission reduction, thereby deriving the profits of manufacturers and retailers, financial institutions, and social welfare under the two loan interest rate scenarios. By comparing the core indicators under the two scenarios and combining them with the manufacturer's phased goals, it outputs the optimal combination of loan strategy (loan scheme) and operational strategy (carbon reduction, wholesale price).

[0075] The data collection and analysis module includes a data input unit for manufacturers, consumers, financial institutions and market information, a data analysis and processing unit for retailers and manufacturers, and an optimal loan solution output unit.

[0076] The data input unit is used to input data such as manufacturers, consumers, financial institutions, and market information under different loan interest rate schemes, and to store them in a categorized manner; for example... Figure 3 As shown, the relevant data mainly includes: manufacturers' initial carbon emission information, carbon quota information, manufacturers' carbon emission reduction costs and market carbon trading prices, the sensitivity coefficient of financial institutions' interest rates to the difference between the manufacturer's final carbon reduction and the benchmark carbon reduction, the sensitivity coefficient of consumers to the carbon reduction of products and their historical purchase data.

[0077] The data analysis and processing unit is used to analyze and process consumers' historical purchase data, manufacturers' carbon emission data, and financial institutions' benchmark interest rates and their sensitivity to carbon reduction. Based on consumers' utility functions and retailers' profit functions, it analyzes and predicts consumers' purchasing behavior, retailers' product retail prices, and manufacturers' carbon reduction and total loan amount.

[0078] The output units of the optimal loan scheme include: a fixed interest rate scheme and a carbon-dependent loan interest rate scheme. First, the consumer purchasing behavior and retailer wholesale prices obtained from the consumer and retailer analysis and processing units are imported into the manufacturer's profit function model to solve for the manufacturer's optimal product wholesale price and carbon reduction under different loan schemes. This yields the profits and social welfare of the manufacturer and financial institutions. Subsequently, the profits and social welfare are compared and analyzed to derive the optimal loan scheme.

[0079] The data collection and analysis module is a data input unit that includes data input from consumers, manufacturers, financial institutions, and market information. The retailer behavior prediction module and the manufacturer behavior prediction module analyze and process the data and behavior of retailers and manufacturers using relevant knowledge of economic utility theory, consumer behavior, and Stackelberg's game theory methods. They belong to the data analysis and processing unit. Finally, the output unit derives the optimal loan plan by comparing manufacturer profits and social welfare.

[0080] This invention provides capital-constrained manufacturers with an integrated "financial-operational" decision-making solution in a low-carbon supply chain through a systematic approach and system design. It addresses the core issue of balancing emissions reduction and profits while adapting to dynamic market changes, providing strong support for manufacturers' low-carbon transformation. This invention effectively solves the problem that traditional green credit cannot accurately incentivize corporate emissions reduction, achieving a dual optimization of supply chain economic and environmental benefits.

[0081] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

[0082] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Unless otherwise specified, an element defined by the phrase "comprising..." or "including..." does not exclude the presence of additional elements in the process, method, article, or terminal device that includes said element. Additionally, in this document, "greater than," "less than," "exceeding," etc., are understood to exclude the stated number; "above," "below," "within," etc., are understood to include the stated number.

[0083] Although the above embodiments have been described, those skilled in the art, once they understand the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the above descriptions are merely embodiments of the present invention and do not limit the scope of patent protection of the present invention. Any equivalent structural or procedural transformations made using the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for optimizing enterprise operational decisions based on carbon-dependent loan interest rates, characterized in that, Includes the following steps: Step S1: Data Collection: Collect data on manufacturers' carbon emissions, financial data, and market demand data; Step S2: Through historical data collection and market research, retailers can analyze consumer preferences and predict sensitive parameters for carbon reduction coefficients. By combining utility theory from economics, we can predict consumers' valuation of a product's utility. And by using information related to the carbon emissions of a manufacturer's products, it is possible to estimate the carbon reductions that its green technologies can achieve. ; Step S3: Financial institutions set up two different loan plans based on different interest rates; Step S4: Based on the company's carbon quota and the carbon reduction cost of the product, the manufacturer constructs a profit function under two different loan interest rate schemes. Under the goal of maximizing profits, the manufacturer solves for the optimal carbon reduction and wholesale price of the product. The manufacturer and retailer's profits and carbon reduction under the equilibrium decision results of the two loan schemes are compared. Based on the manufacturer's phased goals, the optimal loan strategy is selected.

2. The enterprise operation decision optimization method based on carbon-dependent loan interest rates as described in claim 1, characterized in that, Step S1 specifically includes: (1) Manufacturer carbon emission data: initial carbon emissions Annual carbon allowances issued by the government Emission reductions achievable through green technologies Emission reduction cost coefficient ; (2) Financial data: Fixed loan interest rates provided by financial institutions Sensitive parameters of carbon-dependent loan interest rates Unit price in the carbon trading market ; (3) Market demand data: Historical consumer purchase data to estimate consumer sensitivity to product carbon emission reduction. and consumers' valuation of the product. ; Data collection was achieved through a combination of internal statistics and external collaboration: manufacturers compiled initial carbon emissions statistics. Carbon emission reduction Data; collaborating with banks to obtain sensitive parameters regarding the difference between carbon reduction and benchmark amounts in loan interest rates. ; Obtain consumer sensitivity through market research institutions and consumers' valuation of the product Unit price in the carbon trading market This ensures that the data is authentic and traceable.

3. The enterprise operation decision optimization method based on carbon-dependent loan interest rates as described in claim 2, characterized in that, Step S2 includes: the carbon emission reduction of the product will increase the utility of the product, and the price of the product is... Consumers purchase products based on the principle that their utility is non-negative, thus establishing the consumer's utility function. and consumer surplus function Predict the quantity of products purchased by retailers And construct the retailer's revenue function given a fixed wholesale price. , This is the wholesale price.

4. The enterprise operation decision optimization method based on carbon-dependent loan interest rates as described in claim 1, characterized in that, The loan plan in step 3: (1) Fixed-rate loan scheme: loan interest rate Fixed loan interest rate It was determined before the loan was issued and it will not change with the manufacturer's final carbon emission reductions; (2) Carbon-dependent loan scheme: loan interest rate Related to carbon emission reductions, after a loan is issued, the interest rate varies depending on the manufacturer's final carbon emission reductions. Specifically, the interest rate is negatively correlated with the manufacturer's product carbon emission reductions. The higher the rate, the higher the loan interest rate. The lower; Based on the initial carbon emissions collected from manufacturers The annual carbon allowance issued by the government Carbon emission reductions achievable through green technologies and sensitive parameters of carbon-dependent loan interest rates It can be seen that carbon-dependent loans are .

5. The supply chain enterprise operation decision optimization method based on carbon-dependent loan interest rates as described in claim 1, characterized in that, Step S4 specifically includes: Under the carbon cap and carbon trading system, if a company's carbon emissions exceed its carbon quota, it needs to purchase the corresponding carbon quota. ,in, This represents the manufacturer's initial carbon emissions. For manufacturers' carbon allowances. This refers to the carbon emission reductions of manufacturers; if a company's carbon emissions are lower than its carbon allowances, the company can obtain additional profits by selling carbon allowances. If the manufacturer's carbon emission reduction is By estimating the manufacturer's emission reduction parameters, the cost of carbon emission reduction can be determined. According to market research on carbon prices, the total amount of loans for manufacturers with limited funds is the cost of carbon emission reduction plus the cost of selling or buying carbon allowances. ; The manufacturer's profit function is ,in, This is the wholesale price, specifically... (1) In the fixed-rate model, the manufacturer's profit is: ; (2) In the carbon-dependent interest rate model, the manufacturer's profit is: ; Retailers first optimize product prices To obtain the optimal retail price of a product; given a fixed retail price, the manufacturer decides on the wholesale price of the product. and carbon emission reduction ; and thus obtain the financial institution's revenue under this scheme. and social welfare ,in, It reflects financial institutions' sensitivity to the carbon reduction resulting from loans. The harm caused by carbon emissions to manufacturers.

6. A corporate operational decision optimization system based on carbon-dependent loan interest rates, characterized in that, The system includes: (1) Data collection and analysis module: used to collect manufacturers' initial carbon emissions, carbon quotas, emission reduction cost coefficients, financial institutions' benchmark interest rates and the sensitivity parameters of interest rates to carbon reduction, carbon trading prices, consumers' sensitivity to the carbon reduction of emission reduction products, and retailers' demand parameters based on consumers' historical purchase data, to verify the validity of the data, and to predict the emission reduction potential of manufacturers and market demand characteristics after preprocessing. (2) Retailer behavior prediction module: Based on the sensitivity coefficient of carbon emission reduction collected from historical consumer purchase data, the module predicts consumer purchase behavior for carbon-reduced products. Based on the assessment of consumer behavior, the retailer predicts the retail price of the product. (3) Manufacturer Behavior Prediction Module: Based on the manufacturer's initial carbon emissions, carbon quotas, benchmark interest rates of financial institutions, the sensitivity parameters of interest rates to carbon reduction, and carbon trading prices, the module predicts the manufacturer's total loan amount and emission reduction effort coefficient. (4) Loan scheme optimization module: Combine consumers’ historical purchase data and retailers’ retail prices, and input the manufacturer’s profit function under two loan interest rate scenarios: fixed and carbon-dependent; solve for the optimal product wholesale price and carbon emission reduction, and then obtain the profits of manufacturers and retailers, financial institutions and social welfare under the two loan interest rate scenarios. By comparing the core indicators under the two scenarios and combining the manufacturer’s phased goals, the optimal combination of loan strategy and operation strategy is output. The retailer behavior prediction module and the manufacturer behavior prediction module analyze and process the data and behavior of retailers and manufacturers using economic utility theory, consumer behavior, and Stackelberg's game theory methods. They belong to the data analysis and processing unit. Finally, the optimal loan plan is output by comparing the manufacturer's profits and social welfare.

7. The enterprise operation decision optimization system based on carbon-dependent loan interest rates as described in claim 6, characterized in that, The data collection and analysis module includes a data input unit, which is used to input consumers' sensitivity coefficients to the carbon reduction of products and to receive external and internal data.

8. The enterprise operation decision optimization system based on carbon-dependent loan interest rates as described in claim 6, characterized in that, It also includes a data analysis and processing unit for analyzing and processing consumers’ historical purchase data, manufacturers’ carbon emission data, and data on financial institutions’ benchmark interest rates and their sensitivity to carbon reduction. Based on consumers’ utility functions and retailers’ profit functions, it analyzes and predicts consumers’ purchasing behavior, retailers’ product retail prices, and then predicts manufacturers’ carbon reduction and loan amounts.

9. The enterprise operation decision optimization system based on carbon-dependent loan interest rates as described in claim 6, characterized in that, The loan scheme optimization module includes: a fixed interest rate scheme and a carbon-dependent loan interest rate scheme. First, consumer purchasing behavior and retailer wholesale prices are imported into the manufacturer's profit function model to solve for the manufacturer's optimal product wholesale price and carbon reduction under different loan schemes, thereby obtaining the profits and social welfare of the manufacturer and financial institutions. Then, the profits and social welfare are compared and analyzed to derive the optimal loan scheme.

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