ESG Evaluation Method, Electronic Device and Readable Storage Medium for Building Materials Industry Enterprises

Abstract

The present invention discloses an ESG evaluation method, an electronic device and a readable storage medium for enterprises in the building materials industry. By obtaining the parameter information of the target enterprise to be evaluated, determining the first evaluation data and the second evaluation data of the target enterprise to be evaluated according to the parameter information, and adjusting the first evaluation data according to the second evaluation data to obtain the final evaluation result of the target enterprise to be evaluated; The present application establishes an ESG evaluation model for enterprises in the building materials industry, conducts evaluations according to the evaluation indicators of the industry and the relevant parameters of the enterprise itself, comprehensively evaluates by fitting the enterprise's own evaluation factors and the evaluation factors in the entire industry during the evaluation process, and can quickly rate all applicant enterprises through a unified evaluation model during the evaluation process, improving the rating efficiency and shortening the rating time and labor costs.

Description

Technical Field

[0001] This application belongs to the technical field of data analysis, and in particular, relates to an ESG evaluation method for enterprises in the building materials industry, an electronic device, and a readable storage medium. Background Art

[0002] Environmental, Social and Governance (ESG) generally refers to the assessment of the sustainability of an enterprise's operation and its impact on social values from three dimensions: environment, society, and corporate governance. On November 1, 2023, the China National Building Materials Federation organized a working seminar on ESG (Environmental, Social and Governance) in the building materials industry. The meeting systematically introduced the research background and work progress of two documents, namely "Research Report on the Development of ESG in the Chinese Building Materials Industry (2023)" and "Guidelines for Information Disclosure of Environmental, Social and Corporate Governance (ESG) of Enterprises in the Building Materials Industry", and required the building materials industry to strengthen the disclosure of ESG information and promote the market transformation towards "sustainable development".

[0003] At present, in the building materials industry, during the ESG rating, awards, and related certificate review processes, most information is rated through the active declarations of each enterprise and manual investigations by the review units. In the rating process, since there are many indicators and manufacturers involved in the building materials industry, in most cases, the review institutions need to classify and rate the various parameter indicators declared by the enterprises one by one in combination with industry indicators. The rating completely relies on manual work, and there is no effective solution for quickly rating a large number of enterprises. Patent CN116664016B discloses a method, device, electronic device, and readable storage medium for screening ESG sub-topics, and its main technology lies in simplifying the rating process; Patent CN117634997B discloses a deep neural network method for positioning and mapping the value chain assets of an enterprise organization, and discloses a method for evaluating an enterprise through a neural network. However, none of the above technical solutions provide a technical solution for rating a large number of enterprises from the review perspective. Summary of the Invention

[0004] To make up for the above technical deficiencies, this application proposes an ESG evaluation method for enterprises in the building materials industry, an electronic device, and a readable storage medium. The technical solution of the method includes:

[0005] An ESG evaluation method for enterprises in the building materials industry, which obtains the parameter information of the target enterprise to be evaluated, determines the first evaluation data and the second evaluation data of the target enterprise to be evaluated according to the parameter information, and adjusts the first evaluation data according to the second evaluation data to obtain the final evaluation result of the target enterprise to be evaluated; wherein, the acquisition method of the first evaluation data includes: constructing an industry evaluation database based on evaluation indicators; mapping the parameter information of the target enterprise to be evaluated to the evaluation database, obtaining the standardized evaluation information of the target enterprise to be evaluated, and obtaining the first evaluation data according to the evaluation information; the acquisition method of the second evaluation data includes: clustering and sorting the parameter information of all enterprises to be evaluated according to clustering characteristics, and obtaining the normal distribution results of all enterprises to be evaluated under each cluster; establishing a clustering database of all enterprises to be evaluated according to the clustering characteristics and the normal distribution results, and assigning corresponding weights to each enterprise according to the normal distribution results of each enterprise under each cluster; substituting the target enterprise to be evaluated into the clustering database, obtaining the corresponding weight of the enterprise, and obtaining the second evaluation data according to the corresponding weight.

[0006] Further, the clustering characteristics meet the ESG requirements of the building materials industry, and at least one-fifth of the enterprises to be evaluated have this characteristic.

[0007] Further, the method of assigning corresponding weights to each enterprise includes: assigning a weight of 1.2 to the top 10% before sorting, a weight of 1.0 to the middle 80% of the sorting, and a weight of 0.8 to the bottom 10% of the sorting.

[0008] Further, the process of obtaining the first evaluation data also includes: judging the mapping ratio of the parameter information of the target enterprise to be evaluated to the evaluation database, using this mapping ratio as an evaluation factor, and using the evaluation information × the evaluation factor as the first evaluation data.

[0009] Further, the process of adjusting the first evaluation factor according to the second evaluation factor includes: converting the value of the second evaluation factor into a percentage and multiplying it by the first evaluation factor.

[0010] Further, the evaluation information includes the number of evaluation indicators corresponding to the target enterprise to be evaluated and the evaluation results of each evaluation indicator; the second evaluation factor includes the clustering type of the target enterprise to be evaluated, the number of evaluation indicators under each cluster, and the weight score under each cluster.

[0011] Further, in the process of adjusting the first evaluation data according to the second evaluation data to obtain the final evaluation result of the target enterprise to be evaluated, there is also a process of adjusting the second evaluation data through a compensation factor. The acquisition process of the compensation parameter includes: performing weight compensation for the top 5% of the enterprises with the largest number of evaluation indicators and clustering types.

[0012] Further, the weight compensation X range includes 1.2 < X ≤ 1.5.

[0013] An electronic device, comprising a processor and a memory, where the memory stores programs or instructions that can run on the processor, and when the programs or instructions are executed by the processor, the steps of the method described in any one of the above are implemented.

[0014] A readable storage medium, storing programs or instructions thereon, and when the programs or instructions are executed by a processor, the steps of the method described in any one of the above are implemented.

[0015] This application establishes an ESG evaluation model for enterprises in the building materials industry, conducts evaluations based on industry review indicators and the enterprise's own relevant parameters. During the evaluation process, it comprehensively evaluates by fitting the enterprise's own evaluation factors and its evaluation factors in the entire industry. During the evaluation process, all applying enterprises can be quickly rated through a unified evaluation model, improving the rating efficiency and shortening the rating time and labor costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic flowchart of the method of an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] Next, the technical solutions of this application will be clearly and completely described in conjunction with the accompanying drawings. Obviously, the described embodiments are some, but not all, of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts shall fall within the protection scope of this application.

[0018] In the description of this application, it should be noted that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. is based on the orientation or positional relationship shown in the accompanying drawings. It is only for the convenience of describing this application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of this application. In addition, the terms "first", "second", "third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0019] In the description of the present application, it should be noted that unless otherwise clearly specified and defined, the terms "installation", "connection", and "coupling" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific circumstances.

[0020] The present invention will be further described in detail below with reference to the accompanying drawings.

[0021] The present application provides an ESG evaluation method, an electronic device, and a readable storage medium for enterprises in the building materials industry. The evaluation is carried out according to the evaluation indicators of the industry and the relevant parameters of the enterprise itself. During the evaluation process, the evaluation is comprehensively carried out by fitting the evaluation factors of the enterprise itself and the evaluation factors of the enterprise in the entire industry. During the evaluation process, all applying enterprises can be quickly rated through a unified evaluation model, improving the rating efficiency and shortening the rating time and labor cost.

[0022] Referring to Figure 1 , an ESG evaluation method for enterprises in the building materials industry, obtains the parameter information of the target enterprise to be evaluated, determines the first evaluation data and the second evaluation data of the target enterprise to be evaluated according to the parameter information, and adjusts the first evaluation data according to the second evaluation data to obtain the final evaluation result of the target enterprise to be evaluated; wherein, the obtaining method of the first evaluation data includes: constructing an industry evaluation database based on the evaluation indicators; mapping the parameter information of the target enterprise to be evaluated to the evaluation database, obtaining the standardized evaluation information of the target enterprise to be evaluated, and obtaining the first evaluation data according to the evaluation information; the obtaining method of the second evaluation data includes: clustering and sorting the parameter information of all enterprises to be evaluated according to the clustering characteristics, obtaining the normal distribution results of all enterprises to be evaluated under each cluster; establishing a clustering database of all enterprises to be evaluated according to the clustering characteristics and the normal distribution results, and assigning corresponding weights to each enterprise according to the normal distribution results of each enterprise under each cluster; substituting the target enterprise to be evaluated into the clustering database, obtaining the corresponding weight of the enterprise, and obtaining the second evaluation data according to the corresponding weight. In this embodiment, in order to improve the evaluation rate in the ESG evaluation process of enterprises and reduce the manual review cost, this embodiment adopts the method of establishing a corresponding evaluation model for rating. During the modeling process, a corresponding industry evaluation database is established according to the characteristics of the building materials industry. Generally, the industry evaluation indicators refer to national standards, industry standards, or enterprise standards in this field. Generally speaking, the main key evaluation indicator framework in the building materials industry rating contains 3 themes, 13 issues, and 33 topics, as shown in Table 1.

[0023] Table 1 Hierarchical Structure and Weights of Key ESG Rating Issues in the Building Materials Industry

[0024]

[0025] On the basis of the above framework, further refine each enterprise's indicators and conduct classified reviews according to the actual situation of each enterprise. Specifically, relevant standard documents such as "T / CBMF 268.2—2024 Guidelines for Enterprise Environment, Society and Corporate Governance (ESG) in the Building Materials Industry" can be referred to. In the process of obtaining the first evaluation data, there are two methods: actively collecting by the evaluation unit or declaring by the enterprise submission. If actively collecting by the evaluation unit, artificial intelligence can be used for auxiliary collection. For example, establish a special evaluation model, set up corresponding model libraries according to enterprise types, establish matching relationships for relevant words in the model libraries, map based on the frequency of the subject words in the publicly available information collected and the important industry issues to form effective information, and then extract the first evaluation data according to the effective information. There are many artificial intelligence-related models in this process, which will not be elaborated here. In the process from effective information to the first evaluation data, it can be automatically extracted by training a neural network or manually extracted by the method of manual noise reduction, depending on the actual situation.

[0026] The evaluation indicators of this application serve as the basis for the industry evaluation database in this field. On the basis of the previous manual evaluation and scoring, a database model is further established. According to the model indicators and evaluation criteria, the evaluation results of the enterprise to be evaluated are obtained, and the parameter information of the target enterprise to be evaluated is mapped to the evaluation database to obtain the standardized evaluation information of the target enterprise to be evaluated. However, this application is not a search model, and it does not conduct a table lookup evaluation after the enterprise submits relevant parameter forms. Since there are differences in the geographical location, scale, number of employees, business volume, R & D investment, environmental protection investment, etc. of the enterprises to be evaluated in the industry, although the simple table lookup and scoring method can reflect the ESG standards of the enterprises to be evaluated to a certain extent, it cannot exclude the situation where some indicators of individual enterprises are missing and only the advantageous indicators are declared but a better evaluation is obtained. However, it is not practical to require all enterprises to meet all indicators at the present stage, and blind deduction of points will reduce the accuracy of the entire ESG evaluation. Therefore, this application further introduces invisible evaluation data, that is, the second evaluation data, on the basis of the current index evaluation of the first evaluation data. The second evaluation data clusters, classifies, and ranks enterprises, extracts clustering features according to industry characteristics, and then ranks them under each feature. The enterprises are ranked according to their scores under each cluster, and the normal distribution of enterprises under the clustering feature index is obtained according to the score range of the enterprises. A clustering database of all enterprises to be evaluated is established according to the clustering features and the normal distribution results, and corresponding weights are assigned to each enterprise according to the normal distribution results of each enterprise under each cluster. On the basis of the above embodiments, the clustering feature meets the ESG requirements of the building materials industry, and no less than one-fifth of the enterprises to be evaluated have this feature. In this embodiment, the distribution of each enterprise under each clustering feature is obtained through multiple clusterings, and each enterprise is preferably provided with a suitable classification and score range to facilitate the evaluation of the overall strength of the enterprise. This application changes the original subjective judgment evaluation method to an evaluation based on objective indicators such as the enterprise's own indicators and the specific position of the enterprise in the industry, excluding subjective influences and improving the objectivity of the evaluation.

[0027] On the basis of the above one or more embodiments, the method for assigning corresponding weights to each enterprise includes: assigning a weight of 1.2 to the top 10% before ranking, assigning a weight of 1.0 to the middle 80% during ranking, and assigning a weight of 0.8 to the bottom 10% after ranking. In this embodiment, according to the clustering results, the corresponding industry ranking status of each enterprise under the clustering feature, that is, the normal distribution interval, is obtained, and weight assignment is performed for the enterprise according to the distribution interval of the industry.

[0028] On the basis of one or more of the above embodiments, the first evaluation data acquisition process further includes: determining the mapping ratio of the parameter information of the target enterprise to be reviewed and the review database, using the mapping ratio as the review factor, and using the review information × the review factor as the first evaluation data. In this implementation, in order to further reflect the implementation strength and coverage of the ESG standards by the enterprise to be reviewed, this application further uses the proportion of the enterprise's satisfaction rate for the review indicators as the review factor to further improve the accuracy of the review.

[0029] Based on one or more of the above embodiments, the process of adjusting the first evaluation factor according to the second evaluation factor includes: converting the value of the second evaluation factor into a percentage and then multiplying the percentage by the first evaluation factor.

[0030] Based on one or more of the above embodiments, the review information includes the number of review indicators corresponding to the target enterprise to be reviewed and the review results of each review indicator; the second evaluation factor includes the cluster type of the target enterprise to be reviewed, the number of review indicators under each cluster and the weight score under each cluster.

[0031] On the basis of one or more of the above embodiments, in the process of adjusting the first evaluation data according to the second evaluation data to obtain the final evaluation result of the target enterprise to be reviewed, the process of adjusting the second evaluation data by a compensation factor is also included, and the compensation parameter acquisition process includes: weight compensation for the 5% of enterprises with the largest number of review indicators and cluster types. On the basis of the above review, in order to further encourage enterprises in this industry to develop comprehensively, balanced but not outstanding, this application further adopts the method of compensation weights to make overall adjustments to enterprises with relatively comprehensive industry indicators, and use review factors to comprehensively compensate enterprise scores. As an evaluation factor that reflects the degree of fit between enterprises and industry indicators, the review factor can comprehensively compensate for the weight of relatively comprehensive enterprises to improve the comprehensiveness of the review dimension.

[0032] Based on one or more of the above embodiments, the range of the weight compensation X includes 1.2<X≤1.5.

[0033] The present application also proposes an electronic device, which includes a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the program or instructions are executed by the processor, the steps of the method described in any of the above embodiments are implemented.

[0034] The present application also proposes a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method described in any of the above embodiments are implemented.

[0035] The protection scope of the present invention is not limited thereto. Any change or substitution of technical solutions that can be conceived without creative labor should be covered within the protection scope of the present invention. The protection scope of the present invention shall be subject to the protection scope defined by the claims.

Claims

1. An ESG evaluation method for building materials industry enterprises, characterized by: Acquire parameter information of the target enterprise to be reviewed, determine first evaluation data and second evaluation data of the target enterprise to be reviewed according to the parameter information, and adjust the first evaluation data according to the second evaluation data to obtain a final evaluation result of the target enterprise to be reviewed; Wherein, the first evaluation data acquisition method includes: Build an industry review database based on review indicators; Mapping the parameter information of the target enterprise to be reviewed to the review database, obtaining standardized review information of the target enterprise to be reviewed, and obtaining first evaluation data according to the review information; The second evaluation data acquisition method includes: The parameter information of all the enterprises to be reviewed is clustered and sorted according to the clustering characteristics, and the normal distribution results of all the enterprises to be reviewed under each cluster are obtained; A clustering database of all enterprises to be reviewed is established based on clustering characteristics and normal distribution results, and corresponding weights are assigned to each enterprise based on the normal distribution results of each enterprise under each cluster; Substituting the target enterprise to be reviewed into the clustering database, obtaining the corresponding weight of the enterprise, and obtaining the second evaluation data according to the corresponding weight; The method of allocating corresponding weights to each enterprise includes: the top 10% is allocated a weight of 1.2, the middle 80% is allocated a weight of 1.0, and the bottom 10% is allocated a weight of 0.8; The process of adjusting the first evaluation factor according to the second evaluation factor includes: converting the value of the second evaluation factor into a percentage and then multiplying the percentage by the first evaluation factor; The review information includes the number of review indicators corresponding to the target enterprise to be reviewed and the review result of each review indicator; the second evaluation factor includes the cluster type of the target enterprise to be reviewed, the number of review indicators under each cluster and the weight score under each cluster.

2. The method according to claim 1, characterized in that The clustering characteristic is meeting the ESG requirements of the building materials industry, and no less than one-fifth of the companies to be reviewed have this characteristic.

3. The method according to claim 1, characterized in that The first evaluation data acquisition process also includes: determining the mapping ratio between the target enterprise parameter information to be evaluated and the evaluation database, using the mapping ratio as the evaluation factor, and using the evaluation information×the evaluation factor as the first evaluation data.

4. The method according to claim 1, characterized in that: The process of adjusting the first evaluation data according to the second evaluation data to obtain the final evaluation result of the target enterprise to be evaluated also includes a process of adjusting the second evaluation data through a compensation factor. The compensation parameter acquisition process includes: performing weight compensation for 5% of enterprises with the largest number of evaluation indicators and cluster types.

5. The method according to claim 4, characterized in that The weight compensation X range includes 1.2<X ≤1.

5.

6. An electronic device, characterized in that: The electronic device includes a processor and a memory, wherein the memory stores a program or instruction that can be run on the processor, and when the program or instruction is executed by the processor, the steps of the method according to any one of claims 1 to 5 are implemented.

7. A readable storage medium, characterized in that: The readable storage medium stores a program or an instruction, and when the program or the instruction is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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