Hierarchical optimization evaluation method based on ESG index hierarchical data

Abstract

The invention relates to the technical field of ESG index analysis, and discloses a hierarchical optimization evaluation method based on ESG index hierarchical data, which solves the technical problem that the effect of hierarchical data in the evaluation process is not fully considered in the prior art, and comprises the following steps: determining evaluation indexes and a hierarchical system of an enterprise in three aspects of environment (E), society (S) and governance (G); obtaining numerical values of all the bottommost evaluation indexes; determining the current levels of the bottommost layer evaluation indexes and non-bottommost layer evaluation indexes; determining an optimization target of the ESG evaluation result; according to a preset index upgrading scheme, different upgrading schemes meeting the optimization target of the ESG evaluation result are calculated, and the treatment cost generated in the upgrading scheme determining process is calculated; performing quantitative evaluation on the difficulty level of the enterprise optimization process according to a preset enterprise optimization evaluation model; and generating a total ESG optimization evaluation result. According to the technical scheme, the method aims at providing a finer basis for enterprise investors and decision makers.

Description

Technical Field

[0001] The present invention relates to the technical field of ESG indicator analysis, and more specifically, to a hierarchical optimization evaluation method based on ESG indicator stratified data. Background Art

[0002] ESG refers to the three aspects of environment, society and governance. The ESG evaluation system is based on these three dimensions to comprehensively evaluate the performance of enterprises in sustainable development. The evaluation method focuses on environment, society and governance, systematically evaluates the risks and opportunities faced by enterprises in sustainable development, and comprehensively reveals the performance of enterprises in environmental adaptability, social influence and governance compliance by quantifying ESG key performance indicators and analyzing external influencing factors, thereby providing scientific basis for investors and decision makers.

[0003] With the development of ESG technology, the increasing attention of society to ESG and the widening of the scope of ESG, the amount of hierarchical data used in the corporate ESG evaluation system is increasing. In view of the huge data base, the evaluation scheme of the ESG evaluation system in the existing technology adopts the scheme of building a corporate evaluation model, and the corporate evaluation model usually adopts a weighted method to construct an evaluation formula. For example, Figure 1 The enterprise evaluation model shown has multiple evaluation index data of 1, 2, 3, 4, 5, 6, etc. in the three aspects of environment (E), society (S) and governance (G). The evaluation index data of 1, 2, 3, 4, 5, 6, etc. may also have multiple evaluation index data at the bottom. The evaluation formula constructed by weighted method in the prior art is mainly based on the influence of evaluation indexes 1, 2, 3, 4, 5, 6 on environment (E) or society (S) or governance (G), and a weighted ratio is determined for each evaluation index, and weighted calculation is performed to obtain the final ESG evaluation result.

[0004] However, existing assessment methods have not fully considered the role of classification data in the assessment process. This limitation constitutes a key issue that needs to be addressed. Summary of the invention

[0005] In view of the technical problem that the evaluation methods in the prior art mentioned in the background technology have not fully considered the role of graded data in the evaluation process, the graded optimization evaluation method of the present invention is calculated in layers according to the layered system of ESG evaluation indicators, and at the same time incorporates the influencing factors of graded data in the layered data. On the basis of being able to independently calculate all evaluation indicators, different upgrade plans can be refined to provide more refined basis for corporate investors and decision makers.

[0006] To achieve the above-mentioned invention purpose, the present invention provides the following technical solutions: A hierarchical optimization evaluation method based on ESG indicator hierarchical data, comprising the following steps: Determine the evaluation indicators and hierarchical system of an enterprise in three aspects: environment (E), society (S), and governance (G); Obtain the values of all the lowest-level evaluation indicators; Derive the current level of the lowest-level evaluation indicators: According to the obtained values of the lowest-level evaluation indicators and the preset indicator grading scheme, grade each of the lowest-level evaluation indicators; Derive the current level of the non-lowest-level evaluation indicators: According to the grading results of the rated lowest-level evaluation indicators and the preset indicator grading scheme, determine the levels of the upper-level evaluation indicators; Select the optimization objective of the ESG evaluation result; According to the preset indicator upgrade scheme, calculate different upgrade schemes that meet the optimization objective of the ESG evaluation result; According to the preset indicator upgrade scheme, determine the governance costs incurred during different upgrade schemes; Based on the preset enterprise optimization evaluation model, conduct a relatively accurate quantitative evaluation of the difficulty level of the enterprise optimization process in terms of the governance cost dimension; Generate the total ESG optimization evaluation result, and screen out the optimal upgrade scheme that meets the optimization objective of the ESG evaluation result.

[0007] Through the above technical solutions, the hierarchical optimization evaluation method of the present invention calculates layer by layer according to the hierarchical system of ESG evaluation indicators, and at the same time incorporates the influencing factors of hierarchical data in the hierarchical data. On the basis of being able to independently account for all evaluation indicators, different upgrade schemes can be refined, so as to provide more refined basis for enterprise investors and decision-makers.

[0008] The present invention further provides: The preset indicator grading scheme refers to an indicator grading scheme predefined according to the characteristics of the lowest-level evaluation indicators and comprehensive factors of enterprise types, in accordance with the magnitudes of the values of the lowest-level evaluation indicators; at the same time, the total number of grading levels of each evaluation indicator is the same; at the same time, the level of the upper-level evaluation indicator is jointly determined by the levels of all its lower-level evaluation indicators, and the level of the upper-level evaluation indicator is given the lowest level of all its lower-level evaluation indicators.

[0009] The present invention further provides: The preset indicator upgrade scheme refers to the amount of governance costs predefined according to the characteristics of the lowest-level evaluation indicators and comprehensive factors of enterprise types, for the process of upgrading the lowest-level evaluation indicators from the low-level stage to the high-level stage.

[0010] Further, the present invention provides: The preset enterprise optimization evaluation model refers to a model for evaluating the difficulty level of the enterprise optimization process based on the amount of governance costs; the formula of the preset enterprise optimization evaluation model is: A = C1 + ((X - T1) / T) * C; Wherein, A represents the evaluation result; X represents the amount required for upgraded governance, T1 represents the lowest price in the price range where X is located, T represents the price difference in a certain price range, C represents the score difference in a certain score range, and C1 represents the lowest score in the score range where X is located.

[0011] Further, the present invention provides: The content of the total ESG optimization evaluation result includes the summary of different upgrade plans and the corresponding different ESG hierarchical optimization score reports for different upgrade plans; that is, firstly, the ESG hierarchical optimization objectives and specific hierarchical optimization plans; secondly, the ESG hierarchical optimization score, which represents the difficulty level of the optimization work process from the perspective of governance costs.

[0012] In summary, the present invention has the following beneficial effects: (1) The hierarchical optimization evaluation method of the present invention quantitatively evaluates the difficulty level of the enterprise ESG optimization work based on the governance amount dimension, providing a scientific basis for enterprise investors and decision-makers; (2) The governance amount value in the hierarchical optimization evaluation method of the present invention is calculated layer by layer according to the hierarchical system of ESG evaluation indicators, so as to be able to independently calculate all evaluation indicators and the governance amount required when formulating different upgrade plans, providing a more refined basis for enterprise investors and decision-makers; (3) In the hierarchical optimization evaluation method of the present invention, the total ESG optimization evaluation result mainly includes two parts. The first part is the grading situation of the enterprise ESG according to the preset index grading plan; the second part is the different ESG hierarchical optimization score reports corresponding to different upgrade plans formulated for each bottom-level evaluation indicator and the combination of different upgrade plans; therefore, when the top-level ESG grading level remains unchanged, it is still possible to select to formulate upgrade plans within the hierarchical data to refine and optimize the hierarchical data. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a schematic reference diagram of the background art of the present invention; Figure 2 It is a block diagram of the process flow of the hierarchical optimization evaluation based on the ESG index hierarchical data of the present invention; Figure 3 It is a schematic diagram of the hierarchical structure of the ESG index hierarchical data of the present invention; Figure 4 It is a schematic diagram of the summation structure of the governance costs in the hierarchical optimization process based on the ESG index hierarchical data of the present invention. Detailed implementation manners

[0014] The present invention will be further described in detail below in conjunction with embodiments and the accompanying drawings, but the implementation manners of the present invention are not limited thereto.

[0015] A hierarchical optimization evaluation method based on ESG index hierarchical data, combined with Figures 2 - 4 As shown in the figure, the working steps of the hierarchical evaluation method are as follows: The first step: Determine the evaluation indicators and hierarchical system of the enterprise in three aspects: environment (E), society (S), and governance (G); The second step: Obtain the values of all the bottom-level evaluation indicators; The third step: Derive the current level of the bottom-level evaluation indicators: According to the obtained values of the bottom-level evaluation indicators and the preset index grading scheme, rate each bottom-level evaluation indicator; The fourth step: Derive the current level of the non-bottom-level evaluation indicators: According to the rating results of the rated bottom-level evaluation indicators and the preset index grading scheme, grade the upper-level evaluation indicators; The fifth step: Select the optimization objective of the ESG evaluation result; The sixth step: According to the preset index upgrade scheme, calculate different upgrade schemes that meet the optimization objective of the ESG evaluation result; The seventh step: According to the preset index upgrade scheme, determine the governance costs incurred during different upgrade schemes; The eighth step: Based on the preset enterprise optimization evaluation model, conduct a relatively accurate quantitative evaluation of the difficulty level of the enterprise optimization process in terms of the governance cost dimension; The ninth step: Generate the total ESG optimization evaluation result and screen out the optimal upgrade scheme that meets the optimization objective of the ESG evaluation result.

[0016] Wherein: The preset index grading scheme refers to an index grading scheme predefined according to the characteristics of the bottom-level evaluation indicators and comprehensive factors such as the enterprise type, etc., according to the magnitude of the values of the bottom-level evaluation indicators; at the same time, the total number of grading levels of each evaluation indicator is the same; at the same time, the level of the upper-level evaluation indicator is jointly determined by the levels of all its lower-level evaluation indicators, and the level of the upper-level evaluation indicator is given the lowest level of all its lower-level evaluation indicators.

[0017] The preset index upgrade scheme refers to the amount of governance costs predefined according to the characteristics of the bottom-level evaluation indicators and comprehensive factors such as the enterprise type, etc., required for the bottom-level evaluation indicators to upgrade from the lowest level stage to the highest level.

[0018] The preset enterprise optimization evaluation model refers to a model for evaluating the difficulty level of the enterprise optimization process based on the amount of governance costs. The preset enterprise optimization evaluation model is: A = C1 + ((X - T1) / T) * C; Among them, A represents the evaluation result; X represents the amount required for upgrading governance, T1 represents the lowest price in the price range where X is located, T represents the price difference in a certain price range (T2 - T1), C represents the score difference in a certain score range (C2 - C1), and C1 represents the lowest score in the score range where X is located.

[0019] The total ESG optimization evaluation result refers to the summary of different upgrading plans formulated for each lowest-level evaluation indicator and the corresponding different ESG hierarchical optimization score reports. The ESG hierarchical optimization score report mainly includes two aspects. First, the ESG hierarchical optimization goals and specific optimization plans. Second, the ESG hierarchical optimization score, and the ESG hierarchical optimization score indicates the difficulty level of the optimization work process from the perspective of governance costs.

[0020] The following takes a specific implementation case as a specific example.

[0021] In this specific example, taking a domestic private automobile manufacturing enterprise (hereinafter referred to as "the enterprise") as an example, combined with Figure 1 As shown in the hierarchical division of the enterprise's ESG indicators, the first-level evaluation indicators of the enterprise's ESG are three evaluation indicators: Environment (E), Society (S), and Governance (G).

[0022] The second-level evaluation indicators of the enterprise's ESG are the underlying indicators corresponding to Environment (E), Society (S), and Governance (G). Among them, Environment (E) focuses on the impact of the enterprise on the natural environment. The underlying evaluation indicators of Environment (E) in this example include: 1. Greenhouse gas emissions: Whether the carbon emissions of the enterprise in production and operation meet international or regional standards.

[0023] 2. Energy use: Whether clean energy is adopted and whether there is room for improving energy efficiency.

[0024] 3. Water resource management: Whether water is conserved and wastewater is treated.

[0025] 4. Pollution and waste treatment: The control situation of the enterprise over air pollution, soil pollution, and waste emissions.

[0026] 5. Biodiversity protection: Whether the destruction of the natural ecosystem is avoided.

[0027] Society (S) focuses on the enterprise's responsibilities to social stakeholders (employees, customers, communities, etc.). The underlying evaluation indicators of Society (S) usually include: 1. Employee rights and interests: Whether fair compensation and good working conditions are provided.

[0028] 2. Occupational Health and Safety: Whether measures are taken to ensure the health and safety of employees.

[0029] 3. Diversity and Inclusion: Whether gender equality and diversity are promoted.

[0030] 4. Supply Chain Responsibility: Whether social and environmental risks in the supply chain are managed.

[0031] 5. Community Impact: Whether the enterprise makes positive contributions to the economy, education, health, etc. of the community where it is located.

[0032] 6. Customer Privacy Protection: Whether privacy protection and data security regulations are complied with.

[0033] Governance (G) focuses on the performance of the enterprise in terms of governance structure and compliance. The underlying evaluation indicators of Governance (G) usually include: 1. Board Structure: Whether the board of directors is independent, diverse, and professional.

[0034] 2. Business Ethics and Compliance: Whether laws and regulations are complied with.

[0035] 3. Shareholder Rights Protection: Whether all shareholders are treated fairly, especially minority shareholders.

[0036] 4. Information Disclosure: Whether financial and non-financial information is disclosed transparently and in a timely manner.

[0037] 5. Risk Management: Whether there are effective internal control and risk management mechanisms.

[0038] The third-layer evaluation indicators of enterprise ESG are the underlying indicators of the second-layer evaluation indicators (the underlying indicators of Environment (E), Society (S), and Governance (G)). Since the evaluation systems of different enterprises are formulated differently, they are not listed one by one in this embodiment. Taking the second-layer evaluation indicator "Greenhouse Gas Emissions" as an example, the underlying indicators of "Greenhouse Gas Emissions", that is, the third-layer evaluation indicators are: 1. The greening situation in the geographical area where the carbon emissions monitored by the enterprise are located; 2. The practice of the enterprise's measures for digesting and treating greenhouse gases; 3. Whether the enterprise's carbon emission methods comply with international or regional standards.

[0039] Taking the second-layer evaluation indicator "Energy Usage" as another example, the underlying indicators of "Energy Usage", that is, the third-layer evaluation indicators are: 1. The proportion of clean energy used by the enterprise; 2. The energy utilization efficiency of the enterprise, etc.

[0040] As can be seen from the above examples, the second-level evaluation indicators have third-level evaluation indicators, and the third-level evaluation indicators may also have fourth-level evaluation indicators, and so on. Therefore, the first-level evaluation indicators, second-level evaluation indicators, third-level evaluation indicators, etc. of enterprise ESG together constitute the hierarchical data of ESG indicators. The present invention conducts hierarchical optimization evaluation based on the hierarchical data of ESG indicators, providing a more refined basis for enterprise investors and decision-makers.

[0041] Before elaborating on the specific hierarchical optimization evaluation method, this embodiment predefines the content of the preset index grading scheme, the preset index upgrade scheme, the preset enterprise optimization evaluation model, and the total result of ESG optimization evaluation here.

[0042] The preset index grading scheme is predefined in this embodiment as follows: Through the predefined preset index grading scheme, all the bottom-level evaluation indicators in the ESG system are divided into six levels according to the magnitude of the index values, namely Level I, Level II, Level III, Level IV, Level V, and Level VI. Level I indicates that the evaluation indicator is in the optimal state and no further index optimization is required, which can be understood as having no room for optimization; Level VI indicates that the evaluation indicator is in the worst state and further index optimization is required, which can be understood as having the largest room for optimization.

[0043] When a certain bottom-level evaluation indicator is in the Level VI state, then this bottom-level evaluation indicator has five upgrade schemes, namely: the upgrade scheme from Level VI to Level V, or the upgrade scheme from Level VI to Level IV, or the upgrade scheme from Level VI to Level III, or the upgrade scheme from Level VI to Level II, or the upgrade scheme from Level VI to Level I.

[0044] When a certain bottom-level evaluation indicator is in the Level V state, then this bottom-level evaluation indicator has four upgrade schemes, namely: the upgrade scheme from Level V to Level IV, or the upgrade scheme from Level V to Level III, or the upgrade scheme from Level V to Level II, or the upgrade scheme from Level V to Level I.

[0045] When a certain bottom-level evaluation indicator is in the Level IV state, then this bottom-level evaluation indicator has three upgrade schemes, namely: the upgrade scheme from Level IV to Level III, or the upgrade scheme from Level IV to Level II, or the upgrade scheme from Level IV to Level I.

[0046] When a certain bottom-level evaluation indicator is in the Level III state, then this bottom-level evaluation indicator has two upgrade schemes, namely: the upgrade scheme from Level III to Level II, or the upgrade scheme from Level III to Level I.

[0047] When a certain bottom-level evaluation indicator is in the Level II state, then this bottom-level evaluation indicator has one upgrade scheme, which is: the upgrade scheme from Level II to Level I.

[0048] Meanwhile, in the preset index grading scheme, the predefined content also includes the predefined grading of non-bottom-level evaluation indicators. In the present invention, the level of an upper-level evaluation indicator is determined by the lowest level of all its lower-level evaluation indicators, and the level of the upper-level evaluation indicator is given by the lowest level of all lower-level evaluation indicators. For example, if the third-level evaluation indicator is the bottom-level evaluation indicator, and there are five lower-level evaluation indicators corresponding to the second-level evaluation indicator, and the levels of the five lower-level evaluation indicators are level I, level II, level III, level IV, and level V respectively, then the level of the second-level evaluation indicator is level V.

[0049] The preset index upgrade scheme is essentially a predefined model that stipulates the amount of governance costs incurred during the index upgrade process. In this model, first, the governance cost values incurred during each upgrade process of each bottom-level evaluation indicator from level VI to level I, level II, level III, level IV, and level V are determined in advance, and then the governance cost values incurred during the possible upgrade schemes of each non-bottom-level evaluation indicator are determined in advance; the governance cost values of the possible upgrade schemes of the latter non-bottom-level evaluation indicators are actually determined by summing the governance cost values of the bottom-level evaluation indicators. Based on this idea, an upgrade model of the preset index upgrade scheme can be established using the summation algorithm in the prior art, so as to quickly determine the governance cost value incurred during any upgrade scheme.

[0050] The preset enterprise optimization evaluation model refers to a refined algorithm model that evaluates the difficulty level of the enterprise optimization process based on the amount of governance costs. The preset enterprise optimization evaluation model includes two parts. The first part predefines the scoring range corresponding to the amount of a certain governance cost and the difficulty level of the enterprise optimization process. For example, when the governance cost is zero, the optimization difficulty score is 100 points (full marks), when the governance cost is between 10,000 and 100,000, the difficulty level score is between 90 and 99 points, and when the governance cost is between 100,000 and 1,000,000, the difficulty level score is between 80 and 90 points; the second part is the predefined formula of the preset enterprise optimization evaluation model, and the model formula is: A = C1 + ((X - T1) / T) * C; Wherein, A represents the evaluation result; X represents the amount required for the upgrade governance, T1 represents the lowest price of the price range where X is located, T represents the price difference of a certain price range (T2 - T1), C represents the score difference of a certain scoring range (C2 - C1), and C1 represents the lowest score of the scoring range where X is located.

[0051] For example, when an enterprise needs to optimize the ESG evaluation results, it first determines the optimization goal of the ESG evaluation results. For example, the optimization goal is to improve the ESG evaluation results by one level. After determining the optimization goal, the optimization plan (usually with multiple optimization plans) is determined according to the preset index grading scheme. At the same time, the governance cost amount corresponding to multiple optimization plans is calculated through the preset index upgrade plan. At this time, the calculated governance cost amount is used to calculate the quantified difficulty level of the optimization process through the preset enterprise optimization evaluation model, and then an optimal optimization plan can be selected, and the difficulty level of the optimization process of the optimal optimization plan can be known.

[0052] For example, the governance cost amount corresponding to an optimization plan is 560,000. According to the model formula, it can be known that: A = 80 + ((56 - 10) / 90) * 10 = 85.1, then the score for the difficulty level of the optimization is 85.1 points.

[0053] The content of the total ESG optimization evaluation results includes the summary of different upgrade plans and the different ESG grading optimization score reports corresponding to different upgrade plans, that is, first, the ESG grading optimization goals and specific grading optimization plans; second, the ESG grading optimization scores, and the ESG grading optimization scores represent the difficulty level of the optimization work process from the perspective of governance costs.

[0054] Based on the above predefined content, the working steps of the hierarchical optimization evaluation method based on ESG index hierarchical data of the present invention are as follows: The first step: Determine the evaluation indicators and hierarchical system of the enterprise in three aspects of environment (E), society (S), and governance (G) according to national standards, industry standards, or enterprise standards; The second step: According to the hierarchical system of the evaluation indicators, and use sensors to measure, or obtain data such as third-party public information data, etc. to obtain the values of all the bottom-layer evaluation indicators; The third step: Determine the current level of the bottom-layer evaluation indicators: According to the obtained values of the bottom-layer evaluation indicators and the preset index grading scheme, rate each bottom-layer evaluation indicator; The fourth step: Determine the current level of the non-bottom-layer evaluation indicators: According to the rating results of the rated bottom-layer evaluation indicators and the preset index grading scheme, grade the upper-layer evaluation indicators; The fifth step: Determine the optimization goal of the ESG evaluation results; The sixth step: According to the preset index upgrade plan, calculate different upgrade plans that meet the optimization goal of the ESG evaluation results; The seventh step: According to the preset index upgrade plan, determine the governance costs incurred during different upgrade plans; in this step, the governance costs required during different upgrade plans are equal to the sum of the governance cost amounts required for the upgrade of the bottom-layer evaluation indicators; Step 8: Based on the preset enterprise optimization evaluation model, conduct a relatively accurate quantitative evaluation on the difficulty level of the enterprise optimization process based on the governance cost; Step 9: Generate the total ESG optimization evaluation result, and screen out the optimal upgrade plan that meets the optimization objectives of the ESG evaluation result.

[0055] The above are only the preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions within the idea of the present invention belong to the protection scope of the present invention. It should be noted that for those of ordinary skill in the art, several improvements and refinements made without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A hierarchical optimization evaluation method based on ESG index hierarchical data, characterized in that: The following steps are involved: Determine the evaluation indicators and tiering system for enterprises in the three aspects of environment (E), society (S) and governance (G); Get the values ​​of all the lowest-level evaluation indicators; Export the current level of the lowest level evaluation indicators: rate each lowest level evaluation indicator according to the obtained value of the lowest level evaluation indicator and the preset indicator grading scheme; Export the current level of non-bottom-level evaluation indicators: grade the upper-level evaluation indicators based on the rating results of the bottom-level evaluation indicators and the preset indicator grading scheme; Select optimization targets for ESG evaluation results; Based on the preset indicator upgrade plan, calculate different upgrade plans that meet the optimization goals of the ESG evaluation results; According to the preset indicator upgrade plan, determine the governance costs incurred during the different upgrade plans; According to the preset enterprise optimization evaluation model, a relatively accurate quantitative evaluation of the difficulty of the enterprise optimization process is carried out based on the governance cost dimension; Generate the overall results of ESG optimization evaluation and screen out the optimal upgrade plan that meets the optimization goals of the ESG evaluation results.

2. A hierarchical optimization evaluation method based on ESG index hierarchical data according to claim 1, characterized in that: The preset indicator grading scheme refers to an indicator grading scheme pre-defined according to the characteristics of the lowest-level evaluation indicators and comprehensive factors of the enterprise type, according to the size of the lowest-level evaluation indicators; at the same time, the total number of grading levels of each evaluation indicator is the same; at the same time, the level of the upper-level evaluation indicator is jointly determined by the levels of all its lower-level evaluation indicators, and the level of the upper-level evaluation indicator is given the lowest level of all lower-level evaluation indicators.

3. The hierarchical optimization evaluation method based on ESG index hierarchical data according to claim 1 is characterized by: The preset indicator upgrade plan refers to the pre-definition of the amount of governance costs required to upgrade the lowest-level evaluation indicators from a low-level stage to a high-level stage based on the characteristics of the lowest-level evaluation indicators and comprehensive factors of the enterprise type.

4. The hierarchical optimization evaluation method based on ESG index hierarchical data according to claim 1 is characterized by: The preset enterprise optimization evaluation model refers to a model that evaluates the difficulty of the enterprise optimization process based on the amount of governance costs; the formula of the preset enterprise optimization evaluation model is: A=C1+((X-T1) / T)*C; Among them, A represents the evaluation result; X represents the amount required for upgrading governance, T1 represents the lowest price in the price range where X is located, T represents the price difference in a certain price range, C represents the score difference in a certain score range, and C1 represents the lowest score in the score range where X is located.

5. The hierarchical optimization evaluation method based on ESG index hierarchical data according to claim 1 is characterized by: The content of the overall results of the ESG optimization evaluation includes different upgrade plans and a summary of different ESG grading optimization scoring reports corresponding to different upgrade plans; first, the ESG grading optimization goals and specific grading optimization plans; second, the ESG grading optimization scoring score. The ESG grading optimization scoring score indicates the difficulty of carrying out the optimization work process from the perspective of governance costs.

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