Carbon performance evaluation method based on data envelope comprehensive model

Abstract

The invention provides a carbon performance evaluation method based on a data envelope comprehensive model, and relates to the technical field of carbon performance evaluation, and the method comprises the steps: obtaining carbon performance influence data; analyzing the carbon performance influence data by using a carbon performance evaluation system to obtain a system output result; analyzing a system output result by using the data envelope comprehensive model to obtain a carbon performance comprehensive evaluation parameter; and dividing the carbon performance level of each enterprise by using the carbon performance comprehensive evaluation parameters to obtain a carbon performance evaluation result, and completing the carbon performance evaluation based on the data envelope comprehensive model. According to the method, the problems that existing carbon performance evaluation indexes are conflicted in attribute, high in subjectivity and unreasonable in evaluation result are solved.

Description

Technical Field

[0001] This specification relates to the technical field of carbon performance evaluation, and particularly to a carbon performance evaluation method based on a data envelopment analysis comprehensive model. Background Art

[0002] Carbon performance evaluation is a process of comprehensively measuring the efforts and output effects of an enterprise's carbon activities, and is particularly important for achieving low-carbon transformation in the field of engineering construction. The carbon performance evaluation of engineering construction enterprises is a complex decision-making system, involving multiple factors such as energy consumption, environmental protection, resource utilization, economic development, and social responsibility, and there are conflicting and complex relationships among these factors. However, the current carbon performance evaluation system for construction enterprises is not yet mature, fails to consider the characteristics and requirements of the engineering construction industry, and lacks a scientific and reasonable index system and a matching evaluation method.

[0003] In addition, the existing indicators only consider from a single level, do not reflect the differences in indicator weights, and have problems such as strong subjectivity and reduced applicability of evaluation results. Therefore, how to design a reasonable enterprise carbon performance evaluation index system, identify the key factors affecting engineering construction carbon performance, construct an enterprise carbon performance evaluation model, and quantitatively evaluate the low-carbon development level of enterprises has become an urgent problem to be solved. Summary of the Invention

[0004] In view of the above deficiencies in the prior art, a carbon performance evaluation method based on a data envelopment analysis comprehensive model provided by the present invention solves the problems of conflicting attributes, strong subjectivity, and unreasonable evaluation results of existing carbon performance evaluation indicators.

[0005] To achieve the above invention objective, the technical solution adopted by the present invention is: a carbon performance evaluation method based on a data envelopment analysis comprehensive model, including: S1: Obtain carbon performance impact data; S2: Analyze the carbon performance impact data using a carbon performance evaluation system to obtain a system output result; S3: Analyze the system output result using a data envelopment analysis comprehensive model to obtain a carbon performance comprehensive evaluation parameter; S4: Use the carbon performance comprehensive evaluation parameter to divide the carbon performance levels of each enterprise to obtain a carbon performance evaluation result, and complete the carbon performance evaluation based on the data envelopment analysis comprehensive model.

[0006] Further, the S2 includes: Analyze the carbon performance impact data using a carbon performance evaluation system to obtain a system original output result; Perform standardization processing on the system original output result to obtain a system output result: ; Among them, represents the system output result, represents the th evaluation object's original system output result of the th evaluation index, represents the minimum value function, represents the maximum value function.

[0007] Furthermore, the S3 includes: Using the entropy weight method, analyze each evaluation object in the system output result to obtain the evaluation object weights; Using the relative information degree judgment matrix and constraint conditions, construct the initial structure of the data envelopment comprehensive model; Input the system output result and the evaluation object weights into the initial structure of the data envelopment comprehensive model, and through analysis, obtain the comprehensive carbon performance evaluation parameters.

[0008] Furthermore, the expression of the evaluation object weight is: ; ; ; Among them, represents the weight of the th evaluation object, represents the entropy value of the evaluation index, represents the number of evaluation objects, represents the dimensionless system output result, represents the system output result, represents the number of evaluation objects, represents the number of evaluation indexes.

[0009] Furthermore, the expression of the relative information degree judgment matrix is: ; ; ; ; Among them, represents the input index matrix, represents the output index matrix, represents the relative information amount between different input indexes, represents the weight of the input index , represents the weight of the input index , represents the number of input indexes, Indicates the relative information content between different output indicators, Indicates the input indicators The weights corresponding to the output indicators, Indicates the input indicators The weights corresponding to the output indicators, Indicates the number of output indicators; among them, and is a positive reciprocal matrix.

[0010] Furthermore, the expression of the constraint condition is: ; ; ; Among them, Indicates the maximum value function, Indicates the weight vector of the output indicators, Indicates the vector of output indicator values of the enterprise to be evaluated currently, Indicates the comprehensive carbon performance score of the enterprise to be evaluated currently, Indicates the weight vector of the input indicators, Indicates the th enterprise's input indicator value vector, Indicates the th enterprise's output indicator value vector, Indicates the input indicator value vector of the enterprise to be evaluated currently, Indicates the input entropy weight constraint cone, Indicates the output entropy weight constraint cone, Indicates the input indicator matrix, Indicates the maximum eigenvalue of the input indicator matrix, Indicates the input indicator identity matrix, Indicates the weight vector of input indicator m, Indicates the output indicator matrix, Indicates the maximum eigenvalue of the output indicator matrix, Indicates the output indicator identity matrix, Indicates the weight vector of output indicator s.

[0011] The beneficial effects of the present invention are as follows: to provide a carbon performance evaluation method based on a data envelopment analysis (DEA) comprehensive model. Through a scientific and reasonable carbon performance index system and an objective evaluation method, clear and accurate low-carbon decision-making can be carried out for the carbon performance of engineering construction enterprises. (1) Combining the characteristics of carbon emissions in the engineering construction industry, a corporate carbon performance evaluation index system is constructed from the perspective of "input-output". The information entropy method is introduced to determine the index weights, and the DEA technology in objective decision-making is integrated to evaluate the corporate carbon performance, overcoming the subjectivity of evaluation based on historical experience and improving the accuracy and effectiveness of decision-making; (2) Using the DEA comprehensive model, the carbon performance level of engineering construction enterprises is comprehensively and deeply analyzed, providing a new management tool for enterprises to carry out carbon management activities, reducing the conflict and subjectivity of carbon performance evaluation index attributes, and making the evaluation results more reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] This specification will be further described by way of exemplary embodiments, which will be described in detail through the accompanying drawings. These embodiments are not restrictive. In these embodiments, the same numbers represent the same structures, where: Figure 1 FIG. is an exemplary flowchart of a carbon performance evaluation method based on a data envelopment analysis (DEA) comprehensive model according to some embodiments of this specification. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0013] The following describes the specific embodiments of the present invention to facilitate those skilled in the art of this technology to understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art of this technology, as long as various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are within the scope of protection.

[0014] Embodiment Figure 1 FIG. is an exemplary flowchart of a carbon performance evaluation method based on a data envelopment analysis (DEA) comprehensive model according to some embodiments of this specification. As Figure 1 shown, the process includes the following steps. In some embodiments, the process can be executed by a processor.

[0015] S1: Obtain carbon performance impact data.

[0016] The carbon performance impact data is the relevant data that affects the carbon performance evaluation. For example, the carbon performance impact data may include the environmental impact assessment documents of construction projects, project budget and final accounts statements, corporate annual audit reports, annual responsibility reports, pollutant emissions, energy consumption, social risks, and carbon emissions, etc.

[0017] In some embodiments, the processor may analyze the enterprise's annual business basic data to obtain carbon performance impact data.

[0018] In some embodiments, the processor may use multiple capacity metrics to analyze the carbon performance impact data to obtain the input metrics of the carbon performance evaluation system.

[0019] In some embodiments, the expression of the multiple capacity metric may be: ; ; ; where represents the multiple capacity metric of each type of carbon performance impact data, represents the adjustment factor of the upper capacity metric, represents the adjustment factor of the lower capacity metric, represents the multiple upper capacity metric, represents the multiple lower capacity metric, represents the cumulative multiplication operation, represents the th type of carbon performance impact data, represents the total type of carbon performance impact data, represents the th upper capacity metric of the carbon performance impact data, represents the th lower capacity metric of the carbon performance impact data.

[0020] S2: Use the carbon performance evaluation system to analyze the carbon performance impact data to obtain the system output result.

[0021] The carbon performance evaluation system is a system for evaluating carbon performance through carbon performance impact data.

[0022] In some embodiments, as shown in Table 1, the processor may construct a carbon performance evaluation system based on the input metrics and output metrics.

[0023] Table 1 Carbon Performance Evaluation System

[0024] The system output result is a comprehensive metric for evaluating carbon performance. For example, the system output result may include metrics such as resource utilization, energy conservation and emission reduction, enterprise reputation, and financial performance.

[0025] In some embodiments, the processor may implement S2 based on the following steps: Analyze the carbon performance impact data using the carbon performance evaluation system to obtain the original system output result; perform standardization processing on the original system output result to obtain the system output result.

[0026] In some embodiments, the expression of the system output result may be: ; where represents the system output result, represents the original system output result of the th evaluation object for the th evaluation index, represents the minimum value function, represents the maximum value function.

[0027] S3: Analyze the system output result using the data envelopment comprehensive model to obtain the carbon performance comprehensive evaluation parameter.

[0028] The data envelopment comprehensive model is a mathematical calculation model that combines DEA and the entropy weight method.

[0029] The carbon performance comprehensive evaluation parameter is a parameter that reflects the order of the value performance of each enterprise. For example, as shown in Table 2, the carbon performance comprehensive evaluation parameter may include the decision-making unit, the value performance dimension (Vp value), and the ranking situation, etc.

[0030] Table 2 Carbon performance comprehensive evaluation parameter

[0031] In some embodiments, the processor may implement S3 based on the following steps: Analyze each evaluation object in the system output result using the entropy weight method to obtain the evaluation object weight; construct the initial structure of the data envelopment comprehensive model using the relative information degree judgment matrix and the constraint conditions; input the system output result and the evaluation object weight into the initial structure of the data envelopment comprehensive model, and through analysis, obtain the carbon performance comprehensive evaluation parameter.

[0032] The evaluation object weight is a parameter that reflects the importance degree of the evaluation object.

[0033] In some embodiments, the expression of the evaluation object weight may be: ; ; ; where represents the th evaluation object weight, represents the entropy value of the evaluation index, represents the number of evaluation objects, represents the output result of the dimensionless system, represents the system output result, represents the number of evaluation objects, represents the number of evaluation indicators.

[0034] The initial structure of the data envelopment comprehensive model is the initial structure of a mathematical model used to analyze the system output result and the weights of evaluation objects. For example, the initial structure of the data envelopment comprehensive model may include a relative information degree judgment matrix and constraint conditions.

[0035] The relative information degree judgment matrix is a matrix used to judge the relative information degree of the target enterprise.

[0036] In some embodiments, the expression of the relative information degree judgment matrix can be: ; ; ; ; where, represents the input index matrix, represents the output index matrix, represents the relative information amount between different input indexes, represents the input index weight, represents the input index weight, represents the number of input indexes, represents the relative information amount between different output indexes, represents the input index weight corresponding to the output index, represents the input index weight corresponding to the output index, represents the number of output indexes; where, and are positive reciprocal matrices.

[0037] The constraint condition is the constraint condition of the relative information degree judgment matrix.

[0038] In some embodiments, the processor can construct an entropy weight constraint cone as the constraint condition of the relative information degree judgment matrix.

[0039] In some embodiments, the expression of the constraint condition can be: ; ; ; Among them, represents the maximum value function, represents the weight vector of the output indicators, represents the vector of output indicator values of the enterprise to be evaluated currently, represents the comprehensive carbon performance score of the enterprise to be evaluated currently, represents the weight vector of the input indicators, represents the th vector of input indicator values of the enterprise, represents the th vector of output indicator values of the enterprise, represents the vector of input indicator values of the enterprise to be evaluated currently, represents the input entropy weight constraint cone, represents the output entropy weight constraint cone, represents the input indicator matrix, represents the maximum eigenvalue of the input indicator matrix, represents the input indicator identity matrix, represents the weight vector of input indicator m, represents the output indicator matrix, represents the maximum eigenvalue of the output indicator matrix, represents the output indicator identity matrix, represents the weight vector of output indicator s.

[0040] In some embodiments, the weight vector of the input indicators and the weight vector of the output indicators meet the consistency requirements of the corresponding input indicator matrix and output indicator matrix.

[0041] In some embodiments, represents that the adjusted weight vector needs to be in the same direction as the eigenvector corresponding to the maximum eigenvalue, which can be used to avoid contradictions in weight allocation; can be used to ensure that the input-output efficiency of all enterprises does not exceed 1; can be used to normalize the input weights of the current enterprise; represents non-negativity of weights; represents that the weights need to meet the conditions of the entropy weight constraint cone to ensure the objectivity and consistency of weight allocation.

[0042] In some embodiments, the processor can use the relative information degree judgment matrix, construct the weight relationship through the ratio of indicator weights, define the feasible region of weights through the maximum eigenvalue and the identity matrix to construct the entropy weight constraint cone, and combine the DEA model to achieve an objective evaluation of the enterprise's carbon performance. All parameters work together to ensure the scientificity and rationality of the evaluation process.

[0043] S4: Use the comprehensive carbon performance evaluation parameters to classify the carbon performance levels of each enterprise, obtain the carbon performance evaluation results, and complete the carbon performance evaluation based on the data envelopment comprehensive model.

[0044] The carbon performance evaluation results are the results of the comprehensive carbon performance scores of each enterprise. For example, as shown in Table 3, the carbon performance evaluation results may include grades, classification bases, descriptions, and identification colors.

[0045] Table 3 Carbon Performance Evaluation Results

[0046] In some embodiments, the processor can be represented by five grades, namely, the first grade, the second grade, the third grade, the fourth grade, and the fifth grade, reflecting the level grades of carbon performance management of different enterprises.

[0047] In some embodiments of this specification, a carbon performance evaluation method based on the data envelopment comprehensive model is provided. Through a scientific and reasonable carbon performance index system and an objective evaluation method, the carbon performance of engineering construction enterprises can be clearly and accurately evaluated for low-carbon decision-making. (1) Combining the characteristics of carbon emissions in the engineering construction industry, a carbon performance evaluation index system for enterprises is constructed from the perspective of "input-output". The information entropy method is introduced to determine the index weights, and the DEA technology in objective decision-making is integrated to evaluate the carbon performance of enterprises, overcoming the subjectivity of evaluation based on historical experience and improving the accuracy and effectiveness of decision-making; (2) Using the data envelopment comprehensive model, comprehensively and deeply analyze the carbon performance levels of engineering construction enterprises, provide a new management tool for enterprises to carry out carbon management activities, reduce the conflicts and subjectivity of carbon performance evaluation index attributes, and make the evaluation results more reasonable.

Claims

1. A carbon performance evaluation method based on a data envelopment synthesis model, characterized in that: include: S1: Obtain carbon performance impact data; S2: Analyze the carbon performance impact data using the carbon performance evaluation system to obtain the system output result; S3: Analyze the output results of the system using a data envelopment synthesis model to obtain comprehensive carbon performance evaluation parameters; S4: Using the carbon performance comprehensive evaluation parameters, the carbon performance level of each enterprise is divided to obtain the carbon performance evaluation results, and the carbon performance evaluation based on the data envelopment comprehensive model is completed.

2. The carbon performance evaluation method based on the data envelopment comprehensive model according to claim 1 is characterized in that: The S2 includes: Utilizing the carbon performance evaluation system, analyzing the carbon performance impact data to obtain the original output results of the system; The original output result of the system is standardized to obtain the system output result: ； in, Indicates the system output results. Indicates Evaluation object The original output results of the system of evaluation indicators, represents the minimum value function, Represents the maximum value function.

3. The carbon performance evaluation method based on the data envelopment comprehensive model according to claim 1 is characterized in that: The S3 includes: Using the entropy weight method, each evaluation object in the output result of the system is analyzed to obtain the evaluation object weight; Using the relative information judgment matrix and constraint conditions, the initial structure of the data envelopment synthesis model is constructed; The system output results and the evaluation object weights are input into the initial structure of the data envelopment comprehensive model, and carbon performance comprehensive evaluation parameters are obtained through analysis.

4. The carbon performance evaluation method based on the data envelopment comprehensive model according to claim 3 is characterized in that: The expression of the evaluation object weight is: ； ； ； in, Indicates The weight of the evaluation object, represents the entropy value of the evaluation index, Indicates the number of evaluation objects. represents the output result of dimensionless system, Indicates the system output results. Indicates the number of evaluation objects. Indicates the number of evaluation indicators.

5. The carbon performance evaluation method based on data envelopment comprehensive model according to claim 3 is characterized in that: The expression of the relative information judgment matrix is: ； ； ； ； in, represents the input indicator matrix, represents the output indicator matrix, Represents the relative amount of information between different input indicators, Indicates input index The weight of Indicates input index The weight of Indicates the number of input indicators, Represents the relative amount of information between different output indicators, Indicates input index The weight of the corresponding output indicator, Indicates input index The weight of the corresponding output indicator, Represents the number of output indicators; where, and is a positive reciprocal matrix.

6. The carbon performance evaluation method based on the data envelopment comprehensive model according to claim 3 is characterized in that: The constraint condition is expressed as: ； ； ； in, represents the maximum value function, represents the weight vector of the output indicator, Represents the output index value vector of the current enterprise to be evaluated, It indicates the comprehensive carbon performance score of the enterprise to be evaluated. represents the weight vector of the input indicators, Indicates The input indicator value vector of each enterprise, Indicates The output index value vector of each enterprise, Represents the input indicator value vector of the current enterprise to be evaluated, represents the input entropy weight constraint cone, represents the output entropy weight constraint cone, represents the input indicator matrix, represents the maximum eigenvalue of the input indicator matrix, represents the input index identity matrix, represents the weight vector of the input index m, represents the output indicator matrix, represents the maximum eigenvalue of the output indicator matrix, represents the output indicator unit matrix, Represents the weight vector of the output indicator s.

Images