Carbon reduction evaluation method and device, and computer readable storage medium

Abstract

The invention relates to a carbon reduction evaluation method and device and a computer readable storage medium, and relates to the technical field of energy. The carbon reduction evaluation method comprises the steps of determining a subjective weight of each carbon reduction index of a plurality of carbon reduction indexes of a supplier based on an analytic hierarchy process; determining an objective weight of each carbon reduction index based on an entropy method; determining a comprehensive weight of each carbon reduction index according to the subjective weight and the objective weight of each carbon reduction index; and based on an approximate ideal solution sorting method, according to the comprehensive weight of each carbon reduction index, determining a carbon reduction score of the supplier.

Description

Technical Field

[0001] The present disclosure relates to the field of energy technology, and in particular to a carbon reduction assessment method and device, and a computer-readable storage medium. Background Art

[0002] As the global climate change problem becomes increasingly serious, low-carbon, environmental protection and sustainable development have become the consensus of all walks of life. As one of the important pillars of the global economy, the construction machinery industry is imperative to transform into a low-carbon one, and the implementation of low-carbon procurement is an important aspect of the industry's low-carbon transformation.

[0003] Large enterprises have a large number of suppliers, covering a wide range and with great differences in scale, making it difficult to evaluate their carbon reduction capabilities. Summary of the invention

[0004] According to the first aspect of the present disclosure, a carbon reduction assessment method is provided, including: determining the subjective weight of each of the supplier's multiple carbon reduction indicators based on the analytic hierarchy process; determining the objective weight of each of the carbon reduction indicators based on the entropy method; determining the comprehensive weight of each of the carbon reduction indicators based on the subjective weight and objective weight of each of the carbon reduction indicators; determining the supplier's carbon reduction score based on the comprehensive weight of each of the carbon reduction indicators based on the approximate ideal solution sorting method.

[0005] In some embodiments, determining the comprehensive weight of each carbon reduction indicator based on the subjective weight and objective weight of each carbon reduction indicator includes: determining the comprehensive weight of each carbon reduction indicator based on the geometric mean of the subjective weight and the objective weight of each carbon reduction indicator.

[0006] In some embodiments, the approach-to-ideal solution sorting method determines the supplier's carbon reduction score according to the comprehensive weight of each carbon reduction indicator, including: weighting the distance score in the approach-to-ideal solution sorting method according to the comprehensive weight of each carbon reduction indicator; and determining the comprehensive weight of each carbon reduction indicator according to the weighted distance score.

[0007] In some embodiments, the carbon reduction assessment method further includes: classifying suppliers; and determining carbon reduction indicators for different categories of suppliers before determining the subjective weight and objective weight of each carbon reduction indicator.

[0008] In some embodiments, the carbon reduction assessment method also includes: determining the same carbon reduction indicators for suppliers of different categories; determining the subjective weight of the same carbon reduction indicator based on the hierarchical analysis method; determining the objective weight of the same carbon reduction indicator based on the entropy method; determining the comprehensive weight of the same carbon reduction indicator based on the subjective weight and objective weight of the same carbon reduction indicator; determining the overall carbon reduction score for each category based on the comprehensive weight of each of the same carbon reduction indicators based on the approximate ideal solution sorting method.

[0009] In some embodiments, the carbon reduction index includes at least one of the following: comprehensive energy consumption per unit of output value; carbon emissions per unit of output value; the proportion of annual green electricity consumption to total electricity consumption; the proportion of environmental protection investment to the total operating costs of the enterprise; the proportion of the number of employees in low-carbon related positions to the total number of employees in the enterprise; the proportion of the number of low-carbon R&D projects to the total number of R&D projects of the enterprise; the comprehensiveness of the low-carbon system; the operability of the low-carbon system; and the effectiveness of the low-carbon system.

[0010] According to a second aspect of the present disclosure, a carbon reduction assessment device is provided, including: a subjective weight determination module, configured to determine the subjective weight of each of a plurality of carbon reduction indicators of a supplier based on an analytic hierarchy process; an objective weight determination module, configured to determine the objective weight of each of the carbon reduction indicators based on an entropy method; a comprehensive weight determination module, configured to determine the comprehensive weight of each of the carbon reduction indicators based on the subjective weight and objective weight of each of the carbon reduction indicators; and a scoring module, configured to determine the carbon reduction score of the supplier based on the comprehensive weight of each of the carbon reduction indicators based on an approximate ideal solution sorting method.

[0011] According to a third aspect of the present disclosure, a carbon reduction assessment device is provided, comprising: a memory; and a processor coupled to the memory, wherein the processor is configured to execute a carbon reduction assessment method according to any of some embodiments of the present disclosure based on instructions stored in the memory.

[0012] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which computer program instructions are stored. When the instructions are executed by a processor, the carbon reduction assessment method described in any embodiment of the present disclosure is implemented.

[0013] According to a fifth aspect of the present disclosure, a computer program product is provided, comprising computer program instructions, which, when executed by a processor, implement the carbon reduction assessment method according to any of the embodiments of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The accompanying drawings, which constitute a part of the specification, illustrate embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0015] The present disclosure may be more clearly understood from the following detailed description with reference to the accompanying drawings, in which:

[0016] Figure 1 A flow chart showing a carbon reduction assessment method according to some embodiments of the present disclosure;

[0017] Figure 2 shows an importance scale table according to some embodiments of the present disclosure;

[0018] Figure 3 Showing a random consistency carbon reduction index according to some embodiments of the present disclosure;

[0019] Figure 4 Showing supplier data according to some embodiments of the present disclosure;

[0020] Figure 5 A block diagram showing a carbon reduction assessment device according to some embodiments of the present disclosure;

[0021] Figure 6 A block diagram showing a carbon reduction assessment device according to other embodiments of the present disclosure;

[0022] Figure 7 A block diagram showing a computer system for implementing some embodiments of the present disclosure; DETAILED DESCRIPTION

[0023] Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present disclosure unless otherwise specifically stated.

[0024] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0025] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the present disclosure, its application, or uses.

[0026] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0027] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0028] It should be noted that like reference numerals and letters refer to similar items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0029] Due to the large number of suppliers of large enterprises, wide coverage, and large differences in scale, it is difficult to make horizontal comparisons of suppliers in terms of low carbon. Related technologies use the method of directly weighted summation of carbon reduction indicators to evaluate suppliers. This method has poor accuracy and low credibility.

[0030] Figure 1A flow chart showing a carbon reduction assessment method according to some embodiments of the present disclosure.

[0031] like Figure 1 As shown, the carbon reduction assessment method includes steps S1 to S4. In some embodiments, the carbon reduction assessment method is performed by a carbon reduction assessment device.

[0032] In step S1, based on the hierarchical analysis method, the subjective weight of each of the supplier's multiple carbon reduction indicators is determined; in step S2, based on the entropy method, the objective weight of each carbon reduction indicator is determined; in step S3, according to the subjective weight and objective weight of each carbon reduction indicator, the comprehensive weight of each carbon reduction indicator is determined; in step S4, based on the approximate ideal solution sorting method, the supplier's carbon reduction score is determined according to the comprehensive weight of each carbon reduction indicator.

[0033] Regarding the analytic hierarchy process, the importance of carbon reduction indicators is first scaled through expert scoring, and the subjective weights of carbon reduction indicators are calculated based on the importance.

[0034] In the evaluation process of the AHP, decision makers (such as experts) make judgments and choices on the importance of different carbon reduction indicators based on their own experience, values, strategic goals and other subjective factors. This preference will affect the weight distribution of carbon reduction indicators and thus affect the final evaluation results.

[0035] The decision maker's preference is usually reflected through the method of paired comparison, that is, the decision maker compares each pair of carbon reduction indicators to determine which carbon reduction indicator is more important and to what extent. This subjective judgment will form a judgment matrix, and then the weight of each carbon reduction indicator will be calculated through mathematical methods.

[0036] Therefore, the decision maker's preferences play a guiding and adjusting role in the evaluation system, so that the evaluation results can meet the strategic needs of the enterprise and the expectations of the decision maker.

[0037] The entropy law evaluates the weight of carbon reduction indicators based on the objective laws of data such as information entropy.

[0038] The Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), also known as the superior and inferior solution distance method, calculates the similarity (or distance) between each evaluation object and the ideal solution and the negative ideal solution to obtain the ranking results of each evaluation object. This method can make full use of the information of the original data, and its results can more accurately reflect the gap between the evaluation schemes.

[0039] By establishing a reasonable, comprehensive, accurate and efficient method for evaluating the low-carbon performance of suppliers, we can improve the efficiency of the implementation of low-carbon procurement strategies and the accuracy of the evaluation of the low-carbon performance of the supply chain.

[0040] The present disclosure combines subjective (hierarchical analysis method) and objective (entropy weight method) weight calculation methods. That is to say, subjective factors such as expert experience and decision maker preferences are taken into account, while objective data laws such as data variation and information entropy are taken into account, making the weight determination more reasonable and comprehensive. In addition, the present disclosure adopts the TOPSIS method to calculate the evaluation results based on the subjective and objective comprehensive weights, taking into account the weights and interrelationships between various carbon reduction indicators, and can more intuitively and comprehensively evaluate the pros and cons of the supplier's low-carbon performance level.

[0041] Figure 2 An importance scale table according to some embodiments of the present disclosure is shown.

[0042] Let's combine Figure 2 , introducing the analytic hierarchy process.

[0043] The importance is scaled by expert scoring method, and a nine-level importance scale is established, such as Figure 2 The expert scoring method is adopted, and no less than three experts are hired to compare and score the importance of carbon reduction indicators at the same level in the assessment system, and the arithmetic mean of the scoring results is calculated.

[0044] Based on the calculation results of the arithmetic mean, a judgment matrix is ​​constructed. The arithmetic mean result is constructed into a judgment matrix A. Each element a in the judgment matrix A ij It represents the relative importance of the i-th carbon reduction indicator to the j-th carbon reduction indicator. Conversely, the relative importance of the j-th carbon reduction indicator to the i-th carbon reduction indicator is recorded as 1 / a ij . Where i and j are positive integers.

[0045] Based on the eigenvalue method, solve the maximum eigenvalue λ of the judgment matrix max and its corresponding eigenvector.

[0046] The consistency test of the consistency carbon reduction index CI is introduced, and the formula is as follows:

[0047]

[0048] Among them, m is the carbon reduction index number of this layer.

[0049] Figure 3 A random consistency carbon reduction index according to some embodiments of the present disclosure is shown.

[0050] Random Index (RI) is such as Figure 3As shown, the consistency ratio CR is obtained through the following formula to perform consistency test. Figure 3 In the equation, n represents the nth carbon reduction indicator.

[0051] CR=CI / RI (2)

[0052] If the test fails, the experts will need to re-score and form a new judgment matrix until the test passes.

[0053] If the test passes, its maximum eigenvalue λ max The corresponding eigenvector is normalized to obtain the weight α of the carbon reduction index at this level. For the jth carbon reduction index at this level, the weight calculated by the hierarchical analysis method is recorded as α j , a total of m carbon reduction indicators.

[0054] The following describes a method for determining objective assignment weights using the entropy method according to some embodiments of the present disclosure.

[0055] Obtain the carbon reduction index data of the evaluated party, with a total of m carbon reduction indexes and n evaluated suppliers. The data of the ith supplier under the jth carbon reduction index is recorded as x ij .

[0056] Carbon reduction indicators are classified into positive carbon reduction indicators (the larger the value, the better) and negative carbon reduction indicators (the smaller the value, the better). Positive and negative carbon reduction indicators are standardized separately.

[0057] The standardized formula for the positive carbon reduction indicator is as follows.

[0058]

[0059] The standardized formula for the negative carbon reduction indicator is as follows.

[0060]

[0061] Calculate the proportion of the data of the i-th supplier under different carbon reduction indicators to the sum of all data of the carbon reduction indicator. The formula is as follows

[0062]

[0063] The information entropy of the j-th carbon reduction indicator is calculated using the following formula.

[0064]

[0065] Where 0≤e j ≤1, p ij >0, the value of k is, for example, m.

[0066] In order to make p ij >0, used to calculate pij x′ ij It cannot be 0, so we need to ij The value of 0 is translated into a smaller value like 0.000001.

[0067] The information entropy redundancy is calculated using the following formula.

[0068] d j =1-e j (7)

[0069] Where 0≤d j ≤1;

[0070] The weight of carbon reduction indicators is determined by information entropy redundancy, and the weight of each carbon reduction indicator is calculated as follows.

[0071] Weight = information entropy redundancy / sum of information entropy redundancy of all carbon reduction indicators

[0072] The greater the information entropy redundancy, the greater the weight of the carbon reduction indicator. The sum of the weights of carbon reduction indicators is 1.

[0073] The objective weight β of the carbon reduction index is calculated by the following formula: j .

[0074]

[0075] In some embodiments, the comprehensive weight of each carbon reduction indicator is determined based on the subjective weight and objective weight of each carbon reduction indicator, including: determining the comprehensive weight of each carbon reduction indicator based on the geometric mean of the subjective weight and the objective weight of each carbon reduction indicator.

[0076] For example, the weight of each carbon reduction indicator at each level is obtained by analytic hierarchy process: j (j=1,2,…,m); The weight of each carbon reduction index at each level is obtained by entropy method as β j (j=1,2,…,m), and the comprehensive weight is calculated by the following formula.

[0077]

[0078] By combining subjective and objective weights, the comprehensive weight can more comprehensively reflect the importance of carbon reduction indicators, reduce the deviation that may be caused by a single method, obtain a more comprehensive and reasonable carbon reduction indicator weight, and improve the accuracy and reliability of the evaluation results. Enterprises can more accurately evaluate the low-carbon performance level of suppliers and make more reasonable decisions.

[0079] At the same time, the integration of subjective and objective weights can adapt to different subjective and objective evaluation scenarios and needs, and provide a more flexible weight allocation solution.

[0080] The following introduces an evaluation process based on the approach-to-ideal solution sorting method according to some embodiments of the present disclosure.

[0081] First, all carbon reduction indicator data must be made positive. That is, the larger the data, the better the carbon reduction indicator.

[0082] The positive data of the i-th supplier under the j-th carbon reduction indicator is recorded as y ij , there are m carbon reduction indicators and n evaluated suppliers.

[0083] The forward matrix is ​​constructed as follows.

[0084]

[0085] The matrix is ​​normalized and the normalized matrix is ​​recorded as Z. The expressions of the elements in Z are as follows.

[0086]

[0087] Determine the optimal solution and the worst solution. The vector of the optimal solution is recorded as Z 1 , which is composed of the maximum value of each column element in the matrix Z, and the expression is as follows.

[0088]

[0089] The vector of the worst solution is denoted by Z - , which is composed of the minimum value of each column element in the matrix Z, and the expression is as follows.

[0090]

[0091] In some embodiments, based on the approximate ideal solution sorting method, the carbon reduction score of the supplier is determined according to the comprehensive weight of each carbon reduction indicator, including: weighting the distance score in the approximate ideal solution sorting method according to the comprehensive weight of each carbon reduction indicator; determining the comprehensive weight of each carbon reduction indicator based on the weighted distance score.

[0092] For example, the distance between the evaluated supplier's solution and the optimal solution and the worst solution is calculated to quantify the degree of closeness of the evaluated supplier to the ideal state. The calculation formula is as follows.

[0093]

[0094] and Respectively reflect the gap between the evaluated supplier and the best and worst solutions, where ω j is the comprehensive weight of the jth carbon reduction indicator, It represents the distance score of the evaluated supplier relative to the optimal solution on the jth carbon reduction indicator. It represents the distance score of the evaluated supplier relative to the worst solution on the jth carbon reduction indicator.

[0095] Calculate the closeness between the evaluated supplier and the optimal solution. Through the gap between the evaluated supplier and the optimal and worst solutions, we can get a value C that can reflect the relative closeness between the evaluated supplier and the optimal solution. i (i.e., closeness coefficient), the calculation formula is as follows.

[0096]

[0097] C i The larger the value, the closer the evaluated supplier is to the optimal solution, which indicates that the evaluated supplier has a stronger low-carbon performance. For example, the low-carbon performance of suppliers is divided into the following levels:

[0098] 0.8≤C i ≤1.0 indicates very strong low-carbon performance;

[0099] 0.6≤C i ≤0.8 indicates strong low-carbon efficiency;

[0100] 0.4≤C i ≤0.6 indicates average low-carbon performance;

[0101] 0.2≤C i ≤0.4 indicates weak low-carbon performance;

[0102] 0≤C i ≤0.2 indicates very weak low carbon performance.

[0103] In some embodiments, carbon reduction indicators include at least one of the following: comprehensive energy consumption per unit of output value; carbon emissions per unit of output value; the proportion of annual green electricity consumption to total electricity consumption; the proportion of environmental protection investment to the total operating costs of the enterprise; the proportion of the number of employees in low-carbon related positions to the total number of employees in the enterprise; the proportion of the number of low-carbon R&D projects to the total number of R&D projects of the enterprise; the comprehensiveness of the low-carbon system; the operability of the low-carbon system and the effectiveness of the low-carbon system.

[0104] For example, starting from the production situation, management system, operation and investment of enterprises, a scientific, comprehensive and operational carbon reduction indicator system can be constructed. For complex carbon reduction indicator systems, a hierarchical structure can be adopted, namely, the target layer, the criterion layer and the carbon reduction indicator layer;

[0105] For example, the target layer of the carbon reduction indicator system includes supplier low-carbon performance evaluation, and the criterion layer includes low-carbon level, low-carbon investment and low-carbon system, which are recorded as P1, P2 and P3 respectively.

[0106] The three carbon reduction indicators of energy intensity, carbon emission intensity and green electricity ratio are linked to the low-carbon level, which are recorded as C11, C12 and C13 respectively. Energy intensity refers to the comprehensive energy consumption per unit of output value (the ratio of the comprehensive energy consumption of the enterprise to the total output value, in tons of standard coal per 10,000 yuan); carbon emission intensity refers to the carbon emissions per unit of output value (the ratio of the carbon emissions of the enterprise to the total output value, in tons of carbon dioxide equivalent per 10,000 yuan); the green electricity ratio refers to the proportion of green electricity in electricity consumption in that year (%).

[0107] The low-carbon investment includes three carbon reduction indicators: the proportion of environmental protection investment, the proportion of low-carbon personnel and the proportion of low-carbon R&D, which are recorded as C21, C22 and C23 respectively. The proportion of environmental protection investment refers to the proportion of environmental protection investment to the total operating cost of the enterprise (%); the proportion of low-carbon personnel refers to the proportion of employees in low-carbon related positions to the total number of employees in the enterprise (%); the proportion of low-carbon R&D refers to the proportion of low-carbon R&D projects to the total R&D projects of the enterprise (%).

[0108] The low-carbon system is equipped with three carbon reduction indicators: system comprehensiveness, system operability and system effectiveness, which are denoted as C31, C32 and C33 respectively. The carbon reduction indicator of system comprehensiveness is used to evaluate whether the construction of low-carbon system covers all aspects of enterprise operation; the carbon reduction indicator of system operability is used to evaluate whether the low-carbon system can be effectively understood, followed and implemented in the actual implementation process; the carbon reduction indicator of system effectiveness is used to evaluate whether the enterprise has truly implemented the low-carbon system in actual operation, whether it has formulated specific implementation plans and timetables, and ensured that all employees understand and abide by these systems.

[0109] First, we need to determine the value-selecting rules for each carbon reduction indicator. For example, we need to formulate value-selecting rules for each carbon reduction indicator, and for qualitative carbon reduction indicators, we need to explain the specific values ​​corresponding to the specific situation. The value-selecting rules can be determined through literature research, policy documents, and expert consultation.

[0110] Taking the above-mentioned carbon reduction indicators as an example, the following introduces the value-selecting rules of the carbon reduction indicators and the specific scoring process of suppliers.

[0111] The value-setting rules for the system's comprehensive carbon reduction index are as follows: if the system covers all aspects of the enterprise's operations, it is scored as 10 points; if the system covers all important links, it is scored as 8 points; if the system covers some important links, it is scored as 6 points; if the system basically does not cover important links, it is scored as 3 points; if there is no relevant system, it is scored as 0 points.

[0112] The value-setting rules for the institutional operability carbon reduction index are as follows: if the system is clear and unambiguous, its measures and processes can be smoothly implemented in actual operations, which is scored as 10 points; if the system is clear and unambiguous, but its measures and processes are difficult to implement in actual operations, which is scored as 7 points; if the system is relatively clear and unambiguous, but its measures and processes cannot be implemented in actual operations, which is scored as 4 points; if the system is unclear and unambiguous, its measures and processes cannot be implemented in actual operations, which is scored as 0 points.

[0113] The value-setting rules for the carbon reduction index of system effectiveness are as follows: if all employees are ensured to comply with these systems and specific implementation plans and timetables are formulated, it will be scored as 10 points; if all employees are ensured to comply with these systems but no specific implementation plans and timetables are formulated, it will be scored as 7 points; if all employees are ensured to understand these systems, it will be scored as 4 points; if not all employees understand these systems, it will be scored as 0 points.

[0114] The subjective value assignment weights are determined by using the hierarchical analysis method, and the carbon reduction index weights at the criterion level are obtained as follows.

[0115] α P ={0.61,0.22,0.17} (16)

[0116] The weights of carbon reduction indicators at low carbon levels are as follows.

[0117] α S1 ={0.37,0.45,0.18} (17)

[0118] The weights of carbon reduction indicators under low-carbon investment are as follows:

[0119] α S2 ={0.33,0.25,0.42} (18)

[0120] The weights of carbon reduction indicators under the low-carbon system are as follows.

[0121] α S3 ={0.29,0.50,0.21} (19)

[0122] The subjective weight α of all carbon reduction indicators in the carbon reduction indicator layer j as follows.

[0123] α j

[0124] ={0.23,0.27,0.11,0.07,0.06,0.09,0.05,0.08,0.04}

[0125] =C11,C12,…C33 (21)

[0126] The entropy method is used to determine the objective assignment weights, and the objective weights of all carbon reduction indicators in the carbon reduction indicator layer are obtained as follows.

[0127] β j ={0.11,0.17,0.11,0.12,0.11,0.10,0.08,0.10,0.10} (22)

[0128] Among them, j = C11, C12,…C33.

[0129] Then, the comprehensive weight is determined, and the comprehensive weight of all carbon reduction indicators in the carbon reduction indicator layer is obtained as follows.

[0130]

[0131] Among them, j = C11, C12,…C33.

[0132] It is also necessary to collect, clean and process the data from suppliers. Data can be collected from suppliers in various ways, such as sensors, questionnaires, website logs, etc., and the data provided by suppliers can be converted into specific values ​​that meet the carbon reduction index value rules.

[0133] Figure 4 1 shows supplier data according to some embodiments of the present disclosure. Figure 4 The carbon reduction indicator system and data are only examples and can be determined based on actual conditions.

[0134] Based on formula (23) j The value and Figure 4 The data shown in the figure are ranked by TOPSIS method. The low-carbon efficiency scores of the five suppliers evaluated are 0.4639, 0.4408, 0.7911, 0.3685 and 0.4967 respectively.

[0135] The higher the score, the stronger the supplier's low-carbon efficiency, that is, the evaluated suppliers are ranked from high to low: Supplier 3, Supplier 5, Supplier 1, Supplier 2, Supplier 4.

[0136] In some embodiments, the carbon reduction assessment method further includes: classifying suppliers; and determining carbon reduction indicators for different categories of suppliers before determining the subjective weight and objective weight of each carbon reduction indicator.

[0137] Suppliers can be classified according to certain standards, such as: classification according to the importance of suppliers, classification according to business and project requirements, classification according to the products supplied by suppliers and classification according to the size of suppliers.

[0138] After classification, a carbon reduction index system is built for each category to evaluate the low-carbon efficiency level of suppliers in that category. After the carbon reduction index system is built, the value-selecting rules for carbon reduction indicators in all carbon reduction index systems are established. The value-selecting rules include quantitative rules, semi-quantitative rules, and qualitative rules.

[0139] Obtain the data requirements of different categories of carbon reduction indicator systems, and import, clean and process the relevant data of its target suppliers. For each category of suppliers, a weight calculation method combining subjective and objective is used to obtain the comprehensive weight of carbon reduction indicators at all levels. The subjective value assignment calculation method is the hierarchical analysis method, and the objective value assignment weight calculation method is the entropy method. The TOPSIS method is used to calculate the low-carbon performance evaluation results of each category of suppliers separately.

[0140] For example, suppliers can be divided into electronic components, metal raw materials and mechanical parts (respectively recorded as Class A, Class B and Class C) according to the products they supply. In view of the different industry characteristics and low-carbon development conditions of the three types of suppliers, a carbon reduction indicator system is established respectively, and the value-taking rules for all carbon reduction indicators are established.

[0141] The carbon reduction indicator systems for Class A, Class B and Class C suppliers are respectively used to determine the weights of carbon reduction indicators, and a weight calculation method combining subjective and objective methods is adopted. Among them, the subjective value assignment calculation method is the hierarchical analysis method, and the objective value assignment weight calculation method is the entropy method.

[0142] Taking Class A as an example, according to the carbon reduction indicator system of Class A, the data requirements are communicated to Class A suppliers, and Class A suppliers upload and import relevant data. The data is cleaned and processed and converted into specific values ​​that meet the requirements.

[0143] According to the weight of the carbon reduction index in the carbon reduction index system of Class A suppliers and the data of Class A suppliers, the TOPSIS method is used to calculate the low-carbon score of each Class A supplier. The calculation method of the low-carbon score of Class B and Class C suppliers is similar and will not be repeated here.

[0144] In some embodiments, the carbon reduction assessment method also includes: determining the same carbon reduction indicators for suppliers of different categories; determining the subjective weights of the same carbon reduction indicators based on the hierarchical analysis method; determining the objective weights of the same carbon reduction indicators based on the entropy method; determining the comprehensive weights of the same carbon reduction indicators based on the subjective weights and objective weights of the same carbon reduction indicators; determining the overall carbon reduction score for each category based on the comprehensive weights of each same carbon reduction indicator based on the approximate ideal solution sorting method.

[0145] For example, analyze the commonality of the low-carbon performance evaluation and carbon reduction index system of Class A, Class B and Class C suppliers, select the carbon reduction index or characteristics that Class A, Class B and Class C suppliers have in the low-carbon performance evaluation, and build a general evaluation system applicable to all categories of suppliers. For example, all categories of suppliers may need to consider the same carbon reduction indicators such as energy consumption, carbon emissions, energy efficiency, carbon emission intensity, environmental protection investment ratio, renewable energy utilization rate, and number of environmental protection certifications.

[0146] Based on these same carbon reduction indicators, a comprehensive evaluation system is constructed to evaluate the overall low-carbon performance of each category of suppliers (A, B, and C).

[0147] According to the data requirements for the overall assessment of the carbon reduction index system, representative data is obtained. Representative data is, for example, data that can reflect the low-carbon performance of suppliers in the entire category, such as obtained by calling the average value, calling the highest value, calling the lowest value, calling the mode, etc. The average value is, for example, the average carbon emissions of suppliers in a certain category. The highest value is, for example, the highest energy efficiency in a certain category. The lowest value is, for example, the lowest carbon emission intensity in a certain category.

[0148] Then, the overall low-carbon performance of each type of supplier is evaluated, and the comprehensive weights of carbon reduction indicators at all levels are obtained by using a combination of subjective and objective weight calculation methods. The subjective weight calculation method is the hierarchical analysis method, and the objective weight calculation method is the entropy method.

[0149] Based on the carbon reduction indicator weights and overall data of the overall carbon reduction indicator system, the TOPSIS method is also used to evaluate the overall low-carbon performance of different categories of suppliers.

[0150] For example, it is calculated that the overall carbon reduction score of Class A suppliers is 0.6, the overall carbon reduction score of Class B suppliers is 0.4, and the overall carbon reduction score of Class C suppliers is 0.2.

[0151] These scores reflect the overall performance of suppliers in each category in terms of low-carbon efficiency. A higher score indicates that the supplier in that category is more environmentally friendly and has a lower carbon footprint overall. This evaluation method allows companies to quickly understand the low-carbon performance of suppliers in different categories, which helps to develop more targeted supply chain management strategies and improvement plans.

[0152] It is important to note that these scores are relative and are used to compare performance between different categories. The specific score range and interpretation can be determined based on the design of the evaluation system. For example, 0.6 may represent "good", 0.4 represents "average", 0.2 represents "needs improvement", etc.

[0153] At the same time, the carbon reduction score can be calculated for individual suppliers under the overall carbon reduction index system and compared with the overall carbon reduction score of the category to which it belongs, so that the carbon reduction level of an individual supplier can be intuitively compared with the overall level of suppliers of this category.

[0154] The above calculation results can be displayed in the user interface. For example, the user interface displays the low-carbon efficiency evaluation results and rankings of all suppliers under category A, the low-carbon efficiency evaluation results and rankings of all suppliers under category B, and the low-carbon efficiency evaluation results and rankings of all suppliers under category C. The proportion of suppliers in each score range under category A, the proportion of suppliers in each score range under category B, and the proportion of suppliers in each score range under category C can also be displayed separately. For the overall part, the low-carbon efficiency evaluation results and rankings of categories A, B, and C, as well as the proportion of different categories in each score range can be displayed.

[0155] The evaluation method can include both individual evaluation of suppliers under each category and overall evaluation of each category. That is, it can evaluate the overall low-carbon performance level of suppliers in different categories to help enterprises identify key industries, and it can also evaluate the low-carbon performance level of different suppliers under the same category to assist enterprises in selecting more environmentally friendly suppliers.

[0156] In some embodiments, the subjective weight calculation method may also use an empirical method or a multi-factor statistical method, and the objective weight calculation method may also use a factor analysis method or an information weight method.

[0157] Figure 5 A block diagram of a carbon reduction assessment device according to some embodiments of the present disclosure is shown.

[0158] like Figure 5 As shown, the carbon reduction assessment device 5 includes a subjective weight determination module 51 , an objective weight determination module 52 , a comprehensive weight determination module 53 , and a scoring module 54 .

[0159] The subjective weight determination module 51 is configured to determine the subjective weight of each of the multiple carbon reduction indicators of the supplier based on the hierarchical analysis method, for example, by performing the following steps: Figure 1 Step S1 is shown.

[0160] The objective weight determination module 52 is configured to determine the objective weight of each carbon reduction indicator based on the entropy method, for example, by performing the following steps: Figure 1 Step S2 is shown.

[0161] The comprehensive weight determination module 53 is configured to determine the comprehensive weight of each carbon reduction indicator according to the subjective weight and objective weight of each carbon reduction indicator, for example, by performing the following steps: Figure 1 Step S3 shown.

[0162] The scoring module 54 is configured to determine the carbon reduction score of the supplier based on the comprehensive weight of each carbon reduction indicator based on the approximate ideal solution sorting method, for example, Figure 1 Step S4 is shown.

[0163] In some embodiments, the carbon reduction assessment device also includes a classification module and a classification assessment module. The classification module is configured to: classify suppliers. For example, suppliers are classified according to certain standards, and the classification standards include: classification according to the importance of suppliers, classification according to business and project requirements, classification according to the products supplied by suppliers, and classification according to the scale of suppliers. After classification, a carbon reduction indicator system is built for each category to evaluate the low-carbon efficiency level of suppliers under this category; after the carbon reduction indicator system is built, value rules for all carbon reduction indicators are established, and the value rules may include quantitative rules, semi-quantitative rules, and qualitative rules. The classification assessment module is configured to determine carbon reduction indicators for different categories of suppliers before determining the subjective weight and objective weight of each carbon reduction indicator.

[0164] In some embodiments, the carbon reduction assessment device also includes a data acquisition module, which is configured to obtain data requirements for different categories of carbon reduction indicator systems, and import, clean and process relevant data of its target suppliers.

[0165] In some embodiments, the carbon reduction assessment device also includes an overall assessment module, which is configured to: determine the same carbon reduction indicators for suppliers of different categories; determine the subjective weights of the same carbon reduction indicators based on the hierarchical analysis method; determine the objective weights of the same carbon reduction indicators based on the entropy method; determine the comprehensive weights of the same carbon reduction indicators based on the subjective weights and objective weights of the same carbon reduction indicators; determine the overall carbon reduction score for each category based on the comprehensive weights of each same carbon reduction indicator based on the approximate ideal solution sorting method.

[0166] For example, analyze the commonalities of all categories of low-carbon performance evaluation and carbon reduction indicator systems, take the supplier categories as the evaluation objects, construct the overall low-carbon performance evaluation and carbon reduction indicator system and carbon reduction indicator content, and formulate carbon reduction indicator value rules. Obtain the data requirements of the overall evaluation and carbon reduction indicator system, obtain the required data from the data acquisition module, and process the supplier-related data according to the data requirements of the overall evaluation and carbon reduction indicator system. Conduct an overall low-carbon performance evaluation of the supplier categories, and also use a weight calculation method that combines subjective and objective methods to obtain the comprehensive weights of the carbon reduction indicators at the next level. Based on the acquired data, use the TOPSIS method to calculate the overall low-carbon performance evaluation results of the supplier categories.

[0167] The carbon reduction assessment device can include both a classification assessment module and an overall assessment module: the classification assessment module assesses the pros and cons of the individual low-carbon performance levels of different suppliers in the same category, helping enterprises identify key industries for supply chain emission reduction and carbon reduction, and optimizing resource allocation in a targeted manner. The overall assessment module can assess the overall low-carbon performance level of different categories, making it more suitable for the assessment of complex suppliers of large enterprises, helping enterprises select lower-carbon and environmentally friendly suppliers, thereby enhancing the green and low-carbon competitiveness of products.

[0168] In some embodiments, the carbon reduction assessment device also includes a display module, which is configured to do at least one of the following: display the low-carbon efficiency assessment results and rankings of suppliers under different product categories, and the proportion of suppliers in each score range under different categories; display the low-carbon efficiency assessment results and rankings of different categories, and the proportion of different categories in each score range.

[0169] According to some embodiments of the present disclosure, the carbon reduction assessment device integrates the analytic hierarchy process, entropy method and weighted TOPSIS, which can better balance subjective judgment and objective data, provide more comprehensive and accurate assessment results, and is suitable for evaluating the low-carbon performance of a large number of complex suppliers, providing an effective tool for the low-carbon management of the enterprise's supply chain.

[0170] The above modules can be interconnected as needed.

[0171] Figure 6 A block diagram of a carbon reduction assessment device according to other embodiments of the present disclosure is shown.

[0172] like Figure 6 As shown, the carbon reduction assessment device 6 includes a memory 61; and a processor 62 coupled to the memory 61, and the memory 61 is used to store instructions for executing the carbon reduction assessment method. The processor 62 is configured to execute the carbon reduction assessment method in any of the embodiments of the present disclosure based on the instructions stored in the memory 61.

[0173] Figure 7 A block diagram of a computer system for implementing some embodiments of the present disclosure is shown.

[0174] like Figure 7 As shown, the computer system 70 may be embodied in the form of a general purpose computing device. The computer system 70 includes a memory 710, a processor 720, and a bus 700 that connects the various system components.

[0175] The memory 710 may include, for example, a system memory, a non-volatile storage medium, etc. The system memory may store, for example, an operating system, an application program, a boot loader, and other programs. The system memory may include a volatile storage medium, such as a random access memory (RAM) and / or a cache memory. The non-volatile storage medium may store, for example, instructions for executing the carbon reduction assessment method in any of the embodiments of the present disclosure. The non-volatile storage medium includes, but is not limited to, a disk memory, an optical memory, a flash memory, and the like.

[0176] The processor 720 can be implemented by a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistors, etc. Discrete hardware components. Accordingly, each module such as the judgment module and the determination module can be implemented by a central processing unit (CPU) running instructions in a memory that execute corresponding steps, or can be implemented by a dedicated circuit that executes corresponding steps.

[0177] The bus 700 may use any of a variety of bus architectures, including, but not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, and a Peripheral Component Interconnect (PCI) bus.

[0178] The computer system 70 may also include an input / output interface 730, a network interface 740, a storage interface 750, etc. These interfaces 730, 740, 750, the memory 710, and the processor 720 may be connected via a bus 700. The input / output interface 730 may provide a connection interface for input / output devices such as a display, a mouse, and a keyboard. The network interface 740 may provide a connection interface for various networked devices. The storage interface 750 may provide a connection interface for external storage devices such as a floppy disk, a USB flash drive, and an SD card.

[0179] Here, various aspects of the present disclosure are described with reference to flowcharts and / or block diagrams of methods, devices, and computer program products according to embodiments of the present disclosure. It should be understood that each frame of the flowchart and / or block diagram and the combination of frames can be implemented by computer-readable program instructions.

[0180] These computer-readable program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable device to produce a machine, so that the processor executes the instructions to produce means for implementing the functions specified in one or more blocks in the flowchart and / or block diagram.

[0181] These computer-readable program instructions can also be readable and stored in a computer-readable memory, which cause the computer to work in a specific manner to produce a product, including instructions for implementing the functions specified in one or more blocks in the flowchart and / or block diagram.

[0182] The present disclosure can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects.

[0183] The carbon reduction assessment method and device, and computer-readable storage medium in the above-mentioned embodiments can more accurately assess the low-carbon performance of suppliers.

[0184] So far, the carbon reduction assessment method and device, and computer-readable storage medium according to the present disclosure have been described in detail. In order to avoid obscuring the concept of the present disclosure, some details known in the art are not described. Based on the above description, those skilled in the art can fully understand how to implement the technical solution disclosed herein.

Claims

1. A carbon reduction assessment method, comprising: Based on the analytic hierarchy process, the subjective weight of each carbon reduction indicator of the supplier's multiple carbon reduction indicators is determined; Determine the objective weight of each carbon reduction indicator based on the entropy method; Determine the comprehensive weight of each carbon reduction indicator according to the subjective weight and objective weight of each carbon reduction indicator; Based on the approximate ideal solution ranking method, the supplier's carbon reduction score is determined according to the comprehensive weight of each carbon reduction indicator.

2. The carbon reduction assessment method according to claim 1, wherein: Determining the comprehensive weight of each carbon reduction indicator according to the subjective weight and the objective weight of each carbon reduction indicator includes: The comprehensive weight of each carbon reduction indicator is determined according to the geometric mean of the subjective weight and the objective weight of each carbon reduction indicator.

3. The carbon reduction assessment method according to claim 1, wherein: The method based on the approach to ideal solution ranking determines the carbon reduction score of the supplier according to the comprehensive weight of each carbon reduction indicator, including: According to the comprehensive weight of each carbon reduction indicator, the distance score in the approaching ideal solution ranking method is weighted; Based on the weighted distance score, the comprehensive weight of each carbon reduction indicator is determined.

4. The carbon reduction assessment method according to claim 1, further comprising: Categorize suppliers; Before determining the subjective weight and objective weight of each carbon reduction indicator, carbon reduction indicators are determined separately for different categories of suppliers.

5. The carbon reduction assessment method according to claim 4, further comprising: Determine the same carbon reduction targets for different categories of suppliers; Based on the analytic hierarchy process, the subjective weights of the same carbon reduction indicators are determined; Determine the objective weight of the same carbon reduction indicator based on the entropy method; Determining the comprehensive weight of the same carbon reduction indicator according to the subjective weight and the objective weight of the same carbon reduction indicator; Based on the approximate ideal solution ranking method, the overall carbon reduction score of each category is determined according to the comprehensive weight of each of the same carbon reduction indicators.

6. The carbon reduction assessment method according to claim 1, wherein: The carbon reduction index includes at least one of the following: Comprehensive energy consumption per unit of output value; Carbon emissions per unit of output value; The proportion of green electricity consumption to total electricity consumption each year; The proportion of environmental protection investment to the total operating costs of the enterprise; The proportion of employees in low-carbon related positions to the total number of employees in the enterprise; The proportion of low-carbon R&D projects to the total number of R&D projects of the enterprise; The comprehensiveness of the low-carbon system; The operability of low-carbon systems; The effectiveness of low-carbon systems.

7. A carbon reduction assessment device, comprising: A subjective weight determination module is configured to determine a subjective weight of each of a plurality of carbon reduction indicators of a supplier based on an analytic hierarchy process; An objective weight determination module is configured to determine the objective weight of each carbon reduction indicator based on an entropy method; A comprehensive weight determination module, configured to determine the comprehensive weight of each carbon reduction indicator according to the subjective weight and the objective weight of each carbon reduction indicator; The scoring module is configured to determine the carbon reduction score of the supplier based on the comprehensive weight of each carbon reduction indicator based on the approximate ideal solution sorting method.

8. A carbon reduction assessment device, comprising: Memory; as well as A processor coupled to the memory, wherein the processor is configured to execute the carbon reduction assessment method according to any one of claims 1 to 6 based on instructions stored in the memory.

9. A computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, implements the carbon reduction assessment method according to any one of claims 1 to 6.

10. A computer program product, comprising computer program instructions, which, when executed by a processor, implement the carbon reduction assessment method according to any one of claims 1 to 6.

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