Industrial chain node development evaluation method and system based on new quality productivity index

Abstract

The invention discloses an industrial chain node development evaluation method and system based on a new quality productivity index, and the method comprises the steps: obtaining industrial chain power data and social data, and building a basic database; constructing an industrial upstream and downstream network relation graph based on the basic database; new quality production evaluation indexes are constructed from different dimensions, and a new quality productivity index evaluation system is formed; screening indexes in the new quality productivity index evaluation system, and calculating a new quality productivity index of each node of the industrial chain; and evaluating the high-quality development condition of each node of the industry chain based on the new-quality productivity index and by considering the influence of upstream and downstream fluctuation transmission. The method can evaluate the high-quality development condition of each node of the industrial chain in combination with the upstream fluctuation influence of the industrial chain, analyzes the advantage nodes and weak links of the industrial chain, and facilitates the dynamic monitoring of the full-chain development of the industrial chain.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing and industrial analysis, and relates to a method and system for evaluating the development of industrial chain nodes based on a new quality productivity index. Background Art

[0002] The threat of decoupling and the risk of chain breakage in the industrial chain are increasing. Industrial safety issues have become a major problem facing social development, and building a safer and more controllable industrial system has become a consensus. The production index analysis method for industrial chain development evaluation and the construction of new quality production indexes for each node of the industrial chain can assist relevant departments in carrying out industrial planning, industrial analysis, industrial investment promotion, industrial support and other related work more accurately and scientifically, and prevent possible risks in the industrial chain.

[0003] At present, the prior art document 1 (CN108287867B) proposes a method for generating an industry prosperity index, which comprehensively reflects the industry change trend through the industry prosperity index, analyzes the industry development trend, and guides the production, operation and investment of enterprises. However, this method does not take into account that the industry is in a dynamic industrial chain and is deeply affected by its upstream and downstream industries. Moreover, the data used in this method is only based on logistics data, which can only reflect the industry dynamics that are strongly related to logistics. Prior art document 2 (CN118428813A) proposes a business prosperity index calculation model based on electric energy data, and provides enterprises with a set of comprehensive economic status assessment tools through characteristic analysis of the business prosperity index. Prior art document 3 (CN116629683A) proposes a method for constructing an industry prosperity index based on an industrial Internet platform, and constructs an industry prosperity index through historical transaction data of the entire platform.

[0004] In general, the current measurement of industry prosperity is only from the perspective of a specific industry or enterprise, without considering the development dynamics of the enterprise or industry in the entire industrial chain. Enterprises make up the industry, and the mutual influence between the upstream and downstream of the industrial chain is inevitable. Therefore, considering the prospects of industry or enterprise development from the perspective of the entire link is more objective and can better reflect the real situation. In addition, the current construction of industry prosperity index is mostly based on a single data source. The above-mentioned existing technical documents use logistics data, power data and industrial Internet platform data respectively. The single data shows the development status of the industry is also single, and the problems reflected are not comprehensive enough. Summary of the invention

[0005] In order to solve the deficiencies in the prior art, the present invention provides an industrial chain node development evaluation method and system based on the new quality productivity index. By selecting and constructing data indicators and considering the impact of upstream and downstream fluctuations on the entire industrial chain, the new quality productivity is evaluated. It can accurately and scientifically assist related work such as industrial planning, industrial analysis, industrial investment promotion and industrial support, and reduce the threat of decoupling and the risk of chain breakage in the industrial chain.

[0006] The present invention adopts the following technical solution.

[0007] A first aspect of the present invention provides an industrial chain node development evaluation method based on a new quality productivity index, comprising:

[0008] Acquire power data and social data from the industry chain and establish a basic database;

[0009] Based on the basic database, construct an industry upstream and downstream network relationship diagram;

[0010] Construct new quality production evaluation indicators from different dimensions to form a new quality productivity index evaluation system;

[0011] Based on the basic database, the index value in the new quality productivity index evaluation system is calculated for each node in the industrial chain, and the important index value is obtained according to the calculation result analysis, and the new quality productivity index of the corresponding node is calculated using the important index value;

[0012] Based on the upstream and downstream network relationship diagram of the industry and the above-mentioned important indicator values, considering the impact of upstream and downstream fluctuations, the new quality productivity index of each node in the middle and downstream is adjusted, and then the high-quality development of each node in the industrial chain is evaluated.

[0013] Preferably, the acquisition of industrial chain power data and social data and establishment of a basic database includes:

[0014] Obtain the relevant industries involved in the upstream, midstream and downstream of the industrial chain nodes, and based on the data in the basic database, obtain the production-supply-sales relationship, clarify the industry to which the enterprise belongs through its products, determine the industry subordinate enterprise information of each industrial chain node in the network, and complete the construction of the upstream and downstream network relationship diagram of the industry.

[0015] Preferably, the new quality production evaluation index is constructed from different dimensions to form a new quality productivity index evaluation system, including:

[0016] Construct new quality production evaluation indicators from the dimensions of technological innovation, new productivity factors, high-quality development and industrial development drive to form a new quality productivity index evaluation system;

[0017] The new quality production evaluation indicators constructed from the dimension of technological innovation include the average number of invention patents / standards owned by each enterprise, the core patent ratio, the innovative power manufacturing index, the proportion of enterprises with advanced process / material patents, and the proportion of enterprises with national patent awards;

[0018] The new quality production evaluation indicators constructed from the dimension of new productive factors include: the proportion of high-growth enterprises, the year-on-year electricity consumption of high-growth enterprises, the average electricity consumption of high-growth enterprises, the proportion of listed companies, the historical ratio of electricity consumption of listed companies and the average electricity consumption of listed companies;

[0019] The new quality production evaluation indicators constructed from the dimension of high-quality development include: production service level, population talent concentration, proportion of new workers, degree of digitization, green energy level, enterprise electricity consumption trend indicators, factor productivity, production guarantee indicators, per capita electricity consumption index, number of invention patents per billion kw.h and enterprise capacity utilization evaluation indicators;

[0020] The new quality production evaluation indicators constructed from the dimension of industrial development drive include: core product price index, year-on-year domestic sales of downstream consumer products, year-on-year exports of downstream consumer products, scale and degree of industrial upgrading.

[0021] Preferably, based on the basic database, the index value in the new quality productivity index evaluation system is calculated for each node in the industrial chain, and the important index value is obtained according to the calculation result analysis, and the new quality productivity index of the corresponding node is calculated using the important index value, which specifically includes:

[0022] Taking each node as the evaluation object, based on the basic database, the new quality production evaluation index values ​​of different dimensions are calculated for each node in the industrial chain to form an industrial chain node development evaluation matrix;

[0023] Filter out important indicator values ​​based on the industry chain node development evaluation matrix;

[0024] The important index values ​​are used to calculate the new quality productivity index F of the corresponding node.

[0025] Preferably, the important indicator values ​​are screened out according to the industrial chain node development evaluation matrix, including:

[0026] The indicator values ​​in the industrial chain node development evaluation matrix are standardized, and the formula is as follows:

[0027]

[0028] in, is the value of the jth indicator of the i-th evaluation object after standardization;

[0029] n is the number of nodes in the industrial chain, and m is the number of new quality productivity indexes;

[0030] x ij is the value of the jth indicator of the i-th evaluation object; and j are the mean and standard deviation of the jth indicator respectively;

[0031] Calculate the correlation coefficient matrix R, the formula is as follows:

[0032] R=(r pq ) m×m

[0033]

[0034] where r pq is the correlation coefficient between the pth indicator and the qth indicator, r pp =1, r pq =r pq ;

[0035] Calculate the eigenvalues ​​and eigenvectors of the correlation coefficient matrix R, and obtain m new indicator variables based on the eigenvectors, as follows:

[0036] 1) Calculate the eigenvalues ​​λ1≥λ2≥...≥λm≥0 of the correlation coefficient matrix R and the corresponding eigenvector u j =(u 1j ,u 2j ,...u nj ) T , j = 1...m;

[0037] 2) Obtain m new indicator variables based on the eigenvector:

[0038]

[0039] where y 1 ,y 2 ,y m They are the 1st, 2nd, and mth new indicator variables respectively; is the value of the mth indicator of the nth evaluation object after standardization;

[0040] Based on the characteristic values, N new indicator variables are selected from the m new indicator variables as important indicator values, including:

[0041] 1) Calculate the information contribution rate b of the eigenvalue λj j , the formula is as follows:

[0042]

[0043] 2) Sort the m new indicator variables according to the information contribution rate of their corresponding eigenvalues ​​from large to small, and select N new indicator variables to obtain N important indicator values.

[0044] Preferably, the calculation formula of the new quality productivity index F is as follows:

[0045]

[0046] where y j is the value of the jth important indicator.

[0047] Preferably, in step 5, based on the upstream and downstream network relationship diagram of the industry and the important indicator values, the new quality productivity index of each node in the middle and downstream is adjusted considering the impact of upstream and downstream fluctuation transmission, so as to evaluate the high-quality development of each node in the industrial chain, including:

[0048] Obtain each node of the industrial chain in the industrial upstream and downstream network relationship diagram, which is divided into upstream nodes, midstream nodes and downstream nodes; among them, the upstream nodes are not affected by the nodes further upstream, the midstream nodes are affected by the upstream nodes, the downstream nodes are affected by the midstream nodes, and the impact of the upstream nodes on the downstream nodes is transmitted through the midstream node links; for the midstream and downstream nodes, firstly, calculate layer by layer to obtain the new quality productivity index of the midstream nodes under the influence of the upstream, and then calculate the new quality productivity index of the downstream nodes under the influence of the midstream nodes;

[0049] By comparing the new quality productivity index of upstream nodes, the new quality productivity index of midstream nodes considering the influence of upstream nodes, and the new quality productivity index of downstream nodes considering the influence of midstream nodes, we can screen out the weak nodes in high-quality development of each node in the industrial chain.

[0050] Preferably, the calculation method of the new quality productivity index of the midstream node considering the upstream influence is:

[0051] 1) According to the important index value of each node, calculate the correlation between the midstream node x and its upstream nodes;

[0052] 2) Based on the new quality productivity index of the node, calculate the fluctuation degree of each upstream node:

[0053]

[0054] Among them, Δy is the fluctuation degree of upstream node y;

[0055] F t is the new quality productivity index of the upstream node y in the current period;

[0056] F t-1 is the new quality productivity index of the upstream node y in the previous period;

[0057] 3) Multiplying the correlation by the fluctuation degree of the corresponding upstream node to obtain the coefficient of the corresponding midstream node affected by the upstream, forming a P-dimensional Y vector;

[0058] 4) Standardize the coefficient of the midstream node affected by the upstream in the P-dimensional Y vector to obtain the standardized coefficient vector Y', sum the elements in the vector to obtain the fluctuation impact value of the upstream node, and multiply it with the new quality productivity index of the corresponding midstream node to obtain the new quality productivity index of the midstream node considering the upstream influence.

[0059] Preferably, the correlation between the midstream node x and each of its upstream nodes is calculated according to the important index value of each node, as follows:

[0060] Each node has N important index values, which form the node's feature vector value. The correlation between node x and each upstream node is calculated based on the node's feature vector value:

[0061]

[0062] Where Cy is the correlation between node x and upstream node y, y ranges from 1 to P, and P is the total number of upstream nodes;

[0063] a is the feature vector value of the upstream node y;

[0064] b is the eigenvector value of the midstream node x.

[0065] The second aspect of the present invention provides an industrial chain node development evaluation system based on the new quality productivity index, comprising:

[0066] Data acquisition module, used to obtain industrial chain power data and social data and establish a basic database;

[0067] A relationship diagram construction module, used to construct an industry upstream and downstream network relationship diagram based on the basic database;

[0068] Evaluation index construction module, used to construct new quality production evaluation indicators from different dimensions and form a new quality productivity index evaluation system;

[0069] A new quality productivity index calculation module, which is used to calculate the index value in the new quality productivity index evaluation system for each node in the industrial chain based on the basic database, obtain important index values ​​according to the calculation results, and use the important index values ​​to calculate the new quality productivity index of the corresponding node;

[0070] The development status assessment module is used to adjust the new quality productivity index of each node in the middle and downstream based on the upstream and downstream network relationship diagram of the industry and the above-mentioned important indicator values, taking into account the impact of upstream and downstream fluctuations, and then assess the high-quality development of each node in the industrial chain.

[0071] A third aspect of the present invention provides a terminal, comprising a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method.

[0072] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0073] Compared with the prior art, the beneficial effects of the present invention include at least:

[0074] The present invention integrates enterprise electricity consumption data with social data such as products, intellectual property rights, and industries to build a basic database for the industrial chain. The database is based on social data and power data, and combines static and dynamic data. The introduced power data has a wide coverage, high real-time performance, and high accuracy, and can better reflect the development of various industries. According to the production-supply-sales relationship of the industrial structure, an industry upstream and downstream network relationship diagram is formed, which is convenient for dynamic monitoring of the development of the entire industrial chain;

[0075] The present invention takes into account the development characteristics of the entire industrial chain and the supply and demand relationship and operating situation of the entire industry from upstream to mid- and downstream, explores the relationship between industrial production and electricity consumption quantification, and constructs new quality production evaluation indicators from the dimensions of technological innovation, productivity factors, industrial drive, and high-quality development to form a new quality productivity index evaluation system. This indicator system focuses on measuring the innovation, digitalization, and intelligence of enterprises, which is consistent with the goal of building a modern industrial system in the country. It can more effectively evaluate the development status of the industry and provide a practical basis for identifying weaknesses in the process of modernization and digitalization.

[0076] The present invention not only takes into account static data such as the number of enterprise patents and enterprise production capacity, but also combines it with power data that has a strong correlation with industrial development. It can respond to industrial trends in a timely manner with high real-time performance, and constructs an industrial evaluation system from multiple dimensions.

[0077] The present invention constructs an evaluation system from the perspective of new quality productivity, which can better reflect the scientific and technological innovation of modern industries and meet the requirements of industrial development in the new era. Compared with other evaluation systems, it can better discover the limitations of high-quality development in the industrial chain, thereby improving the overall development of the industrial chain. It is an important assessment at this stage of development.

[0078] The present invention combines the new quality productivity index evaluation system to calculate the new quality productivity index of each industrial node in the upstream and downstream industrial network relationship diagram, combines the upstream fluctuation impact of the industrial chain to evaluate the high-quality development of each node in the industrial chain, analyzes the advantageous nodes and weak links of the industrial chain, and facilitates the formulation of corresponding industrial planning and development strategies.

[0079] After obtaining the new quality productivity index of each node in the industrial chain, the present invention is not limited to directly evaluating the nodes of the industrial chain based on it. At this time, the new quality productivity index of each node only considers the development and construction of the node itself, and does not consider that each node is in a different stage of the industrial chain and is affected by upstream and downstream fluctuations. The present invention adjusts the new quality productivity index of the original node through the influence of upstream and downstream fluctuations, and constructs the new quality productivity index of each node under the influence of upstream and downstream transmission. It is closer to the actual situation, the evaluation is more real and effective, and the weak nodes and links in the industrial chain can be discovered in time.

[0080] The present invention is different from the traditional industrial chain evaluation method that directly evaluates based on the static indicators of the nodes. The traditional industrial chain evaluation method does not take into account that the nodes are in different positions (upstream, midstream and downstream) in the industrial chain, are affected by the upstream, and the impact is continuously transmitted to the downstream. The evaluation of the impact of upstream and downstream fluctuations considered in the present invention is closer to the real state, can reflect the real state of each node, and obtain a practical node development state. And the fluctuation transmission considered is not a simple superposition of the upstream impact to the downstream, but based on the correlation between each upstream node and its adjacent nodes, the node with a larger correlation has a greater impact on the adjacent nodes when it fluctuates. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 This is a flow chart of the industrial chain node development evaluation method based on the new quality productivity index of the present invention;

[0082] Figure 2 This is the calculation principle diagram of the new quality productivity index of the midstream node considering the influence of the upstream. DETAILED DESCRIPTION

[0083] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only embodiments of a part of the present invention, rather than all embodiments. Based on the spirit of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the protection scope of the present invention.

[0084] like Figure 1 As shown, Embodiment 1 of the present invention provides an industrial chain node development evaluation method based on the new quality productivity index, which mainly includes the following steps:

[0085] Step 1: Obtain power data and social data from the industrial chain and establish a basic database;

[0086] Further optimization is to construct an industrial chain node evaluation system from multiple dimensions. The first step is data collection, and establishing a comprehensive basic database is the prerequisite for everything.

[0087] Table 1 shows the data types and data sources involved, among which industrial and commercial data and patent data are used to establish the upstream and downstream relationship of the industrial chain, see step 2 for details. The data from 1 to 9 in Table 1 are all used to evaluate the development status of the industrial chain, with a wide range of data, a large scope, and a complete evaluation system.

[0088] In terms of power data, we obtained marketing 2.0 data and new power consumption collection system data from the data center, including customer profiles, behaviors, and power consumption data;

[0089] In terms of social data, development indicator data of social development individuals were collected from multiple platforms in three dimensions: government, institutions, and enterprises.

[0090] Table 1 Data sources and types

[0091]

[0092]

[0093] The above-mentioned power data and social data can be used to calculate the values ​​of various indicators in the subsequent new quality productivity index evaluation system. The corresponding correlation between data and indicators is: power data: customer information-A3, B2, C4), accounts receivable-C6, invoice details-C12, historical capacity-C9, business expansion information-C9, daily frozen electricity-A3, B1, B2, B3, B5, B6, C1, C2, C4, C7, C8, C10, C11, C12, D4, D5, power generation data-C5; social data: enterprise production release information-C1, C8, industry report-A4, product information-A4, D1, D2, D3, D5, operating profit-A2, D2, D3, enterprise registration information-A4, B5, industrial enterprise directory-A4, enterprise production and sales-A4, D2, D3, questionnaire-C3, C10 and patent data-A1, A5, C11.

[0094] Step 2: Based on the basic database, construct an industry upstream and downstream network relationship diagram:

[0095] It is further preferred to establish an industry upstream and downstream network relationship diagram, including obtaining the relevant industries involved in the upstream, midstream and downstream of the industrial chain nodes, and based on the data in the basic database, obtaining the production-supply-sales relationship, clarifying the industry to which the enterprise belongs through its products, determining the industry subordinate enterprise information of each industrial chain node in the network, and completing the construction of the industry upstream and downstream network relationship diagram.

[0096] Specifically, the information of industrial chain nodes is obtained according to the predefined classification rules, and then the relevant industries involved in the upstream, midstream and downstream of the industrial chain are obtained (taking the photovoltaic industry as an example, the node information includes the relevant industries involved in the photovoltaic industry, such as the upstream silver powder, glass, monocrystalline silicon wafer and other industries, the midstream inverter, junction box, solar cell and other industries, the downstream photovoltaic system, photovoltaic power generation system, etc.), and the information of subordinate enterprises in the node industry is further constructed based on the upstream, midstream and downstream relationships of the industrial chain nodes. It is mainly based on the patent data (relevant product patents) and industrial and commercial information (product information, enterprise production and sales) in the basic database to obtain the production-supply-sales relationship, clarify the industry to which the enterprise belongs through its main products, determine the industry subordinate enterprise information of each industrial chain node in the network, and complete the construction of the upstream and downstream network relationship diagram of the industry.

[0097] The theoretical method of constructing the industrial chain is completed by decomposing it according to the product life cycle and the importance of the correlation between industrial nodes, with reference to the classification rules of domestic key industrial research institutions such as "Foresight Industry Research Institute" and "New Materials Online".

[0098] The sources of industrial chain enterprises include two parts. First, the present invention determines the ownership of enterprises through the industrial chain node products involved in the patent layout of enterprises based on the patent database of the State Intellectual Property Office. Secondly, the present invention uses the industrial and commercial information database of the national enterprise credit information disclosure system to process the enterprises that have opened businesses with industrial chain node products in their business scope.

[0099] After obtaining the industrial chain network information, the new quality productivity index of each node, that is, each link in the upstream and downstream of the industrial chain, can be evaluated, and the evaluation object is all the enterprises involved in the node.

[0100] Step 3: Construct new quality production evaluation indicators from different dimensions to form a new quality productivity index evaluation system;

[0101] Further optimization, the new quality productivity evaluation system specifically includes four dimensions, namely, technological innovation indicators, new productivity factor indicators, high-quality development indicators, and industrial development driving indicators. It covers all dimensions of industry development, comprehensive capabilities, and comprehensively evaluates the status of the industry, as shown in Table 2.

[0102] Table 2 Evaluation system of new quality productivity index

[0103]

[0104]

[0105] The details are as follows:

[0106] (1) Construct indicators for technological innovation. Science and technology are key factors in promoting the development of productivity, so the evaluation system should include indicators of technological innovation capabilities.

[0107] The preferred dimension of technological innovation evaluates the performance of enterprises in terms of technology R&D investment, patent applications and innovative achievements, reflecting the technological leadership and innovation capabilities of the industrial chain. The specific indicators and calculation methods are as follows:

[0108] 1) The average number of invention patents / standards owned by each enterprise is A1;

[0109]

[0110] The number of patents is full data, which comes from the State Intellectual Property Office. The standard data is full data, which is collected from the National Standard Information Public Service Platform.

[0111] 2) The core patent ratio A2 reflects the quality of innovation and the focus of innovation activities;

[0112]

[0113] Key products refer to products whose turnover accounts for more than 50% of the enterprise.

[0114] 3) Innovative Power Manufacturing Index A3: i.e., R&D investment A3, which measures the degree of actual work on technological innovation;

[0115]

[0116] The attributes of a research enterprise can be judged by the industry reported by the enterprise when it registers with the power company.

[0117] 4) The proportion of enterprises with advanced process / material patents is A4, which reflects the attention and pre-research degree of enterprises in the industry to cutting-edge technologies, which represents the important technological trend of the industry;

[0118]

[0119] The total number of upstream, midstream and downstream enterprises has been obtained when the industrial chain is constructed. Advanced patents: refers to patents classified in the fields of next-generation technology or related to research and development technology mentioned in the corresponding industry association report.

[0120] All indicators here are for nodes, and the corresponding enterprises under each node (in the upstream, midstream and downstream of the industrial chain) are determined according to the industrial chain network relationship diagram in step 2.

[0121] Patent data is full data from the State Intellectual Property Office. This type of patent is collected and classified using patent search formulas.

[0122] 5) The proportion of enterprises winning the National Patent Award is A5. This is an important award for measuring the importance of patents. Winning this award can reflect the importance of the technology to a certain extent.

[0123]

[0124] The national patent award data comes from the list of winners published annually by the State Intellectual Property Office.

[0125] (2) Construct indicators of high-quality development dimensions, analyze the industrial growth rate, market competitiveness and profitability of enterprises, and reflect the production development level and sustainability of the industrial chain.

[0126] The high-quality development dimension includes 6 indicators, the specific meanings and calculation methods are as follows:

[0127] 1) The number of high-growth enterprises accounts for B1;

[0128]

[0129] High-growth enterprises include user enterprises with enterprise labels such as "gazelle", "specialized, sophisticated and innovative", "unicorn" and "potential unicorn". These enterprises often represent the innovation frontier and high growth of the industry. Enterprise label data is collected from the list of gazelle, specialized, sophisticated and innovative enterprises announced by national ministries and commissions.

[0130] 2) The year-on-year electricity consumption of high-growth enterprises B2 reflects the changes and fluctuations of high-growth enterprises. The enterprise label data is collected from the list of gazelle, specialized and new enterprises announced by national ministries and commissions, and the electricity consumption data comes from power companies; B2, the calculation formula is:

[0131]

[0132] Each period can be defined as monthly, quarterly or annual.

[0133] 3) The average electricity consumption of high-growth enterprises is B3, which reflects the development vitality of high-growth enterprises in the industry. The data source is the same as above.

[0134] 4) The number of listed companies accounts for B4, which reflects the market recognition and financing capabilities of technology-innovative companies and is an important indicator for measuring the vitality and maturity of industrial innovation;

[0135]

[0136] 5) The electricity consumption of listed companies over the years B5 is used to measure the fluctuation of listed companies; B5, the calculation formula is as follows;

[0137]

[0138] 6) The average electricity consumption of listed companies is B6, which reflects the development vitality of listed companies in the industry;

[0139] (3) Construct new dimensional indicators of productive factors, which cover green energy, population and talent, degree of digitalization, degree of production services, factor productivity, and production security.

[0140] The new productivity factor dimension is based on the three factors of labor, labor materials and labor objects. The first factor of new productivity: higher-quality labor; the second factor of new productivity: higher-end labor materials; the third factor of new productivity: wider labor objects. The specific indicators and calculation methods are as follows:

[0141] (3.1) The first factor: higher-quality workers, including the following indicators:

[0142] 1) Innovative Manufacturing Index: Production Service Degree C1. The production service degree measures the ability of new workers to improve production efficiency and service quality, and is of great significance for evaluating their direct contribution to industrial development.

[0143] This indicator is measured by comparing the electricity consumption of regional research and experimental development, science and technology promotion and application services, research-based production enterprises, and higher education over the years. The C1 calculation formula is as follows:

[0144]

[0145] By regional research and experimental development, technology promotion and application services, research-based production enterprises, and higher education capacity share. The enterprise label of this type (production service type) is searched in the power system.

[0146] 2) Innovation Manufacturing Index: Population Talent Concentration C2. The population talent concentration reflects the density of talents and the quality of the innovation environment in the region, and plays a fundamental role in attracting and cultivating new workers.

[0147] This indicator is measured by the year-on-year electricity consumption for science, education, culture, health and sports. The formula is as follows;

[0148]

[0149] Among them, the Education, Science, Culture, Health and Sports Bureau queries the power system user tags, and the current period can be monthly, quarterly or annual data.

[0150] 3) The proportion of new workers C3. This indicator directly reflects the innovation ability of new workers and their contribution to technological progress. It is an important indicator to measure the output of innovative results of workers in actual work.

[0151] This indicator is measured by the number of inventors and the number of employees. This number is not the full number. The data comes from the list of companies compiled by the association every year, and the number of inventors is compiled, while the number of employees is reported by the companies themselves.

[0152] The calculation formula is as follows:

[0153]

[0154] The number of inventors is collected from the list of enterprises compiled by the industry association each year, while the number of employees is reported by the enterprises themselves.

[0155] (3.2) The second factor: higher-end labor materials, including the following indicators:

[0156] 1) Digital Manufacturing Capability Index: Digitalization level C4. The digitalization level reflects the industry's ability to adapt to new technologies and new models.

[0157] This indicator is measured by the proportion of electricity consumption in the digital industry to the service industry. The installed capacity is reported by the Photovoltaic Association and is not complete data.

[0158] 2) Green Energy Power Index: Green Energy Degree C5, Green Energy Degree reflects the application and development of distributed photovoltaic power generation by industry enterprises, and is an important indicator for measuring the sustainable energy utilization of labor objects. Green energy is of great significance to achieving sustainable development.

[0159] This indicator is measured by the historical ratio of distributed photovoltaic power generation of industry enterprises.

[0160]

[0161] It refers to the total amount of photovoltaic power generation involved in all enterprises under this node. The current period can be monthly, quarterly or annual.

[0162] 3) Business operating conditions: Enterprise electricity payment index C6. This indicator of electricity payment reflects the financial health and operational efficiency of the enterprise, and has reference value for evaluating the stability and credit status of the enterprise.

[0163] This indicator is measured by the average remittance cycle and the data comes from power companies.

[0164] 4) Business operation status: Enterprise electricity consumption trend index C7. As an auxiliary indicator, electricity consumption trend can reflect the production activity level and business status of the enterprise, and has a certain reference significance for the comprehensive assessment of industrial development.

[0165] This indicator is measured by the year-on-year electricity consumption of related enterprises in the node.

[0166]

[0167] It refers to the total electricity consumption of all enterprises under this node, and the current period can be monthly, quarterly or annual.

[0168] (3.3) The third factor: a wider range of labor objects, including the following indicators:

[0169] 1) Power consumption output index: Factor productivity C8, measured by the manufacturing output value per kilowatt-hour, directly reflects the production efficiency and resource utilization efficiency of the labor object. High productivity is crucial to improving the overall industrial competitiveness.

[0170] This indicator is measured by the manufacturing output value per kilowatt-hour, where the output value data comes from the companies themselves and the electricity quantity comes from the power companies.

[0171]

[0172] 2) Power consumption output index: Production guarantee index C9 reflects the performance of labor objects in production stability and guarantee capabilities. Stable production guarantee plays an important role in maintaining long-term production activities and avoiding risks.

[0173] This indicator is measured by the ratio of average household capacity over the years. Source: power companies.

[0174] 3) Per capita electricity consumption index C10, which measures the energy efficiency and labor productivity of an industry through the ratio of energy consumption to the number of employees, is a key factor in evaluating the sustainability of industrial development.

[0175]

[0176] The electricity consumption data comes from the power company, and the personnel data is reported by the enterprise organization.

[0177] 4) Number of invention patents per 100 million kw.h C11. This indicator directly reflects the output of technological innovation and is an important indicator for measuring the activity and output efficiency of technological innovation.

[0178]

[0179] The full data and patent data come from the State Intellectual Property Office, and the electricity consumption comes from the power company.

[0180] 5) Enterprise capacity utilization evaluation index C12 reflects the effect of electricity cost control. Electricity cost directly affects the production efficiency of the enterprise and can indirectly reflect the overall capacity utilization of the industry.

[0181]

[0182] The indicator is measured by the average corporate electricity price, with data coming from power companies.

[0183] (4) Construct indicators of the driving dimension of industrial development, examine the driving effect of market demand on the industrial chain and the fulfillment of corporate social responsibilities, and evaluate the market adaptability and sustainable development potential of the industrial chain.

[0184] In the dimension of driving industrial development, the market and sustainable development of enterprises are the internal driving force for the sustainable development of the industry. They are also indispensable factors in evaluating industrial development. This dimension includes 6 indicators. The specific meanings and calculation methods are as follows:

[0185] 1) Core product price index D1: Product price trends reflect the market supply and demand relationship and product competitiveness, and have an important impact on corporate profitability and market positioning;

[0186]

[0187] The prices of core products are collected by industry associations.

[0188] 2) Market demand: Domestic sales of downstream consumer goods increased by D2 year-on-year. Product sales are of great significance for assessing the long-term growth potential of the industry.

[0189]

[0190] The current period can be monthly, quarterly or annual.

[0191] 3) Market demand: The export of downstream consumer goods increased by D3 year-on-year. The growth trend of export scale shows the international market competitiveness and external demand of the products, which is crucial for the global layout of industrial development.

[0192]

[0193] The current period can be monthly, quarterly or annual.

[0194] 4) Scale degree D4: Scale degree measures the scale change and expansion capacity of the industry by comparing the average electricity consumption per household in the manufacturing industry over the years, which is of great significance for understanding the macro trend of industrial development;

[0195] 6) Degree of industrial upgrading D5. The degree of industrial upgrading measures the optimization and upgrading of industrial structure by comparing the proportion of electricity consumption of high-end finished product enterprises over the years, reflecting the ability of the industry to transform into high value-added fields.

[0196]

[0197] The current period can be monthly, quarterly or annual.

[0198] Step 4: Based on the basic database, the index value in the new quality productivity index evaluation system is calculated for each node in the industrial chain, and the important index value is obtained according to the calculation result analysis, and the new quality productivity index of the corresponding node is calculated using the important index value;

[0199] Further optimization, the new quality productivity evaluation system established specifically includes four dimensions and a total of 28 indicators. However, the large number of indicators can comprehensively measure the state of industrial development on the one hand, and on the other hand, the repeated appearance of redundant indicators will have a biased impact on the final industrial chain development evaluation, which is mainly reflected in the emphasis on the proportion of redundant indicators. Therefore, before the final calculation of the new quality productivity index of the industrial chain node, it is necessary to calculate the indicator value of the established indicator system and obtain the important indicator value based on the calculation results to remove the influence of redundant indicators. Specifically including:

[0200] Step 4.1, according to the above-mentioned index system and basic database, calculate the indicators of each dimension of the industrial chain node. Each node in the upstream and downstream of the industrial chain contains 28 new quality productivity index systems. Form an industrial chain node development evaluation matrix for each node.

[0201] Step 4.2, feature screening of the new quality productivity index of each node. Feature screening is very important for subsequent evaluation. It involves an unsupervised feature selection method, including but not limited to distance-based methods, such as principal component analysis, linear discriminant analysis, etc.; cluster-based methods, including K-means clustering, etc.

[0202] Taking principal component analysis as an example, the features are screened. The specific steps are as follows:

[0203] Step 4.2.1, standardize the raw data:

[0204] Assume that there are m indicator variables for principal component analysis, x1, x2, ... xm, and n evaluation objects in total, where n is the number of nodes in the industrial chain, and the value of the jth indicator of the ith evaluation object is xij. Standardize each indicator, and the formula is as follows:

[0205]

[0206] in is the value of the jth indicator of the ith evaluation object after standardization; n is the number of nodes in the industrial chain, and m is the number of new quality productivity indexes; in this embodiment, m is 28, indicating that there are 28 new quality productivity indexes.

[0207] and j are the sample mean and standard deviation of the j-th indicator respectively.

[0208] Step 4.2.2, calculate the correlation coefficient matrix R, the specific formula is as follows:

[0209] R=(r pq ) m×m

[0210]

[0211] where r pq is the correlation coefficient between the pth indicator and the qth indicator, r pp =1, r pq =r qp ;

[0212] Step 4.2.3, calculate eigenvalues ​​and eigenvectors

[0213] Calculate the eigenvalues ​​λ1≥λ2≥...≥λm≥0 of the correlation coefficient matrix R and the corresponding eigenvector u 1 ,u 2 ,...u m , where u j =(u 1j ,u 2j ,...u nj ) T , composed of m new indicator variables composed of feature vectors

[0214]

[0215] where y 1 is the first principal component, y 2 is the second principal component, y m It is the mth principal component, that is, the mth new indicator variable.

[0216] Step 4.2.4, based on the characteristic values, select N new indicator variables from the m new indicator variables as important indicator values. For example, select N important indicator values ​​from the 28 new indicator variables y1-y28, such as: y1-yN, including:

[0217] 1) Calculate the information contribution rate b of the eigenvalue λj j , the formula is as follows:

[0218]

[0219] 2) Sort the m new indicator variables from large to small according to the information contribution rate of their corresponding eigenvalues, and select the N principal component features to obtain N important indicator values;

[0220] The feature information with large contribution rate is screened out in turn, and the cumulative contribution rate is calculated. The cumulative contribution rate is the proportion of the contribution rate of the screened feature information to the sum of all feature information contribution rates. When the proportion is close to 1, generally 0.85, 0.9, 0.95, the screening is stopped. At this time, the N features selected are N principal component features.

[0221] Step 4.3, use the important index value to calculate the new quality productivity index of the corresponding node, the formula is as follows:

[0222]

[0223] where y j is the value of the jth important indicator.

[0224] bj is the information contribution rate of the jth principal component.

[0225] This new quality productivity index plays a leading role in innovation, breaking away from the traditional industrial production growth mode and productivity development path. It has the characteristics of high technology, high efficiency and high quality, and is in line with the advanced productivity quality of the new development concept.

[0226] Step 5: Based on the upstream and downstream network relationship diagram of the industry and the above-mentioned important indicator values, considering the impact of upstream and downstream fluctuations, adjust the new quality productivity index of each node in the middle and downstream, and then evaluate the high-quality development of each node in the industrial chain.

[0227] Further preferably, step 4 obtains the new quality productivity index, but the industrial chain is a dynamic link, and the development of the upstream will affect the development of the downstream to a certain extent. It is not comprehensive to evaluate the nodes in the middle and downstream without considering the impact of upstream fluctuations. Therefore, the evaluation of the nodes in the industrial chain is specifically divided into nodes with upstream influence and nodes without upstream influence, which specifically includes the following steps:

[0228] The new quality productivity index of the nodes at the upstream of the industrial chain. The upstream nodes are not affected by any nodes further upstream, so their new quality productivity index is the one obtained in step 4.

[0229] The new quality productivity index of nodes in the middle and downstream of the industrial chain, among which the midstream nodes are affected by the upstream nodes, and the downstream nodes are affected by the midstream nodes, and the influence of the upstream nodes on the downstream nodes is transmitted through the midstream node links. Therefore, the measurement method of the new quality productivity index of the midstream and downstream nodes is consistent, and needs to be calculated layer by layer, that is, first calculate the new quality productivity index of the midstream nodes under the influence of the upstream, and then calculate the new quality productivity index of the downstream nodes under the influence of the midstream nodes.

[0230] Assuming that there are Q midstream nodes and P upstream nodes, the calculation method of the new quality productivity index of the midstream nodes under the influence of the upstream is:

[0231] 1) According to the important index values ​​of each node, calculate the correlation between each node x in the middle reaches and each node in its upstream, as follows:

[0232] Each node has N important index values, which form the node's feature vector value. The correlation between node x and each upstream node is calculated based on the node's feature vector value:

[0233]

[0234] Where Cy is the correlation between node x and upstream node y;

[0235] a is the feature vector value of the upstream node y;

[0236] b is the eigenvector value of the midstream node x;

[0237] 2) Based on the new quality productivity index of the node, calculate the fluctuation degree of each upstream node:

[0238] Considering the development and changes of each upstream node, the changes of upstream nodes are measured by the changes in the node's new quality productivity index over a period of time, as follows:

[0239]

[0240] Among them, Δy is the fluctuation degree of upstream node y;

[0241] F t is the new quality productivity index of the upstream node y in the current period;

[0242] F t-1 is the new quality productivity index of the upstream node y in the previous period;

[0243] Each period can be defined as monthly, quarterly, annual, etc.

[0244] 3) Multiplying the correlation by the fluctuation degree of the corresponding upstream node to obtain the coefficient of the corresponding midstream node affected by the upstream, forming a P-dimensional Y vector;

[0245] 4) Standardize the coefficient of the midstream node affected by the upstream in the P-dimensional Y vector to obtain the standardized coefficient vector Y', sum the elements in the vector to obtain the fluctuation impact value of the upstream node, and multiply it with the new quality productivity index of the corresponding midstream node to obtain the new quality productivity index of the midstream node considering the upstream influence;

[0246] The standardized formula is as follows:

[0247]

[0248] where x i is the coefficient value of the midstream node affected by the upstream before normalization;

[0249] x i′ is the coefficient value of the midstream node affected by the upstream after standardization;

[0250] x min is the minimum coefficient value in the Y vector, x max is the maximum coefficient value in the Y vector.

[0251] Similarly, the updated new quality productivity index of the midstream node is used to calculate the new quality productivity index of the downstream nodes in turn. Please refer to the above for details. First, calculate the correlation between the downstream node and each midstream node in the previous layer, and the degree of fluctuation of each midstream node in the previous layer. Then multiply the correlation and the degree of fluctuation to obtain the coefficient of the corresponding downstream node affected by the midstream. After standardization, multiply it with the new quality productivity index of the corresponding downstream node to obtain the new quality productivity index of the downstream node considering the influence of the midstream node.

[0252] Based on the new quality productivity index of each node in the industrial chain obtained above, the weak links in the industrial chain are analyzed to provide guidance for the overall development of the industrial chain.

[0253] Here is an example:

[0254] Given P nodes in the upstream and Q nodes in the midstream, each node has N important index values ​​and a new quality productivity index F. Now calculate the new quality productivity index of the midstream node considering the influence of the upstream, as Figure 2 As shown, taking the first node in the middle as an example, the calculation process is as follows:

[0255] 1) Calculate the correlation C1...Cp between the midstream node 1 and the upstream P nodes,

[0256]

[0257] Among them, a corresponds to the N important index values ​​(y1..yN) of the upstream P nodes, and b corresponds to the N important index values ​​of the midstream node 1.

[0258] 2) Calculate the fluctuation of P upstream nodes, Δ1...Δp,

[0259]

[0260] where F t is the new quality productivity index of the node, F t-1 It is the new quality productivity index of the previous period of the node. The definition of each period can be monthly, quarterly, annual, etc.

[0261] 3) Calculate the influence vector Y of the upstream on the midstream node 1,

[0262]

[0263] 4) Standardize the influence vector and sum it to get the influence value of the upstream P nodes on the midstream node 1, multiply it by the new quality productivity index of the midstream node 1 to get the corrected new quality productivity index (i.e. considering the impact of upstream and downstream fluctuations).

[0264] 5) By analogy, the revised new quality productivity index of all nodes in the midstream can be obtained.

[0265] Embodiment 2 of the present invention provides an industrial chain node development evaluation system based on a new quality productivity index, including:

[0266] Data acquisition module, used to obtain industrial chain power data and social data and establish a basic database;

[0267] A relationship diagram construction module, used to construct an industry upstream and downstream network relationship diagram based on the basic database;

[0268] Evaluation index construction module, used to construct new quality production evaluation indicators from different dimensions and form a new quality productivity index evaluation system;

[0269] A new quality productivity index calculation module, which is used to calculate the index value in the new quality productivity index evaluation system for each node in the industrial chain based on the basic database, obtain important index values ​​according to the calculation results, and use the important index values ​​to calculate the new quality productivity index of the corresponding node;

[0270] The development status assessment module is used to adjust the new quality productivity index of each node in the middle and downstream based on the upstream and downstream network relationship diagram of the industry and the above-mentioned important indicator values, taking into account the impact of upstream and downstream fluctuations, and then assess the high-quality development of each node in the industrial chain.

[0271] Embodiment 3 of the present invention provides a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method.

[0272] Embodiment 4 of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0273] Compared with the prior art, the beneficial effects of the present invention include at least:

[0274] 1. The present invention integrates enterprise electricity consumption data with social data such as products, intellectual property rights, and industries to build a basic database for the industrial chain. According to the production-supply-sales relationship of the industrial structure, an upstream and downstream network relationship diagram of the industry is formed, which is convenient for dynamic monitoring of the development of the entire industrial chain;

[0275] 2. The present invention takes into account the development characteristics of the entire industrial chain and the supply and demand relationship and business situation of the entire industry from upstream to mid- and downstream, explores the relationship between industrial production and electricity consumption quantification, and constructs new quality production evaluation indicators from the dimensions of technological innovation, productivity factors, industrial drive, and high-quality development to form a new quality productivity index evaluation system. This index system focuses on measuring the innovation, digitization, and intelligence of enterprises, which is consistent with the goal of building a modern industrial system in the country. It more effectively evaluates the development status of the industry and provides a practical basis for identifying weaknesses in the modernization and digitization process. While considering static data on the number of enterprise patents and enterprise production capacity, the present invention combines power data that has a strong correlation with industrial development, can respond to development trends in a timely manner, and has high real-time performance, and constructs an industrial evaluation system from multiple dimensions.

[0276] 3. The present invention combines the new quality productivity index evaluation system to calculate the new quality productivity index of each industrial node in the upstream and downstream network relationship diagram of the industry, combines the impact of upstream fluctuations in the industrial chain to evaluate the high-quality development of each node in the industrial chain, analyzes the advantageous nodes and weak links in the industrial chain, and facilitates the formulation of corresponding industrial planning and development strategies. After obtaining the new quality productivity index of each node in the industrial chain, the present invention is not limited to directly evaluating the nodes of the industrial chain based on it. At this time, the new quality productivity index of each node only considers the development and construction of the node itself, and does not consider that each node is in a different stage of the industrial chain and is affected by upstream and downstream fluctuations. The present invention corrects the new quality productivity index of the original node through the influence of upstream and downstream fluctuations, and constructs the new quality productivity index of each node under the influence of upstream and downstream transmission. It is closer to the actual situation, the evaluation is more real and effective, and the weak nodes and links of the industrial chain can be discovered in time.

[0277] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0278] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0279] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0280] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0281] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for evaluating the development of industrial chain nodes based on the new quality productivity index, characterized in that: include: Acquire power data and social data from the industry chain and establish a basic database; Based on the basic database, construct an industry upstream and downstream network relationship diagram; Construct new quality production evaluation indicators from different dimensions to form a new quality productivity index evaluation system; Based on the basic database, the index value in the new quality productivity index evaluation system is calculated for each node in the industrial chain, and the important index value is obtained according to the calculation result analysis, and the new quality productivity index of the corresponding node is calculated using the important index value; Based on the upstream and downstream network relationship diagram of the industry and the above-mentioned important indicator values, considering the impact of upstream and downstream fluctuations, the new quality productivity index of each node in the middle and downstream is adjusted, and then the high-quality development of each node in the industrial chain is evaluated.

2. According to claim 1, a method for evaluating the development of industrial chain nodes based on the new quality productivity index is characterized by: The acquisition of industrial chain power data and social data and establishment of a basic database include: Obtain the relevant industries involved in the upstream, midstream and downstream of the industrial chain nodes, and based on the data in the basic database, obtain the production-supply-sales relationship, clarify the industry to which the enterprise belongs through its products, determine the industry subordinate enterprise information of each industrial chain node in the network, and complete the construction of the upstream and downstream network relationship diagram of the industry.

3. The method for evaluating the development of industrial chain nodes based on the new quality productivity index according to claim 1 is characterized by: The new quality production evaluation indicators are constructed from different dimensions to form a new quality productivity index evaluation system, including: Construct new quality production evaluation indicators from the dimensions of technological innovation, new productivity factors, high-quality development and industrial development drive to form a new quality productivity index evaluation system; The new quality production evaluation indicators constructed from the dimension of technological innovation include the average number of invention patents / standards owned by each enterprise, the core patent ratio, the innovative power manufacturing index, the proportion of enterprises with advanced process / material patents, and the proportion of enterprises with national patent awards; The new quality production evaluation indicators constructed from the dimension of new productive factors include: the proportion of high-growth enterprises, the year-on-year electricity consumption of high-growth enterprises, the average electricity consumption of high-growth enterprises, the proportion of listed companies, the historical ratio of electricity consumption of listed companies and the average electricity consumption of listed companies; The new quality production evaluation indicators constructed from the dimension of high-quality development include: production service level, population talent concentration, proportion of new workers, degree of digitization, green energy level, enterprise electricity consumption trend indicators, factor productivity, production guarantee indicators, per capita electricity consumption index, number of invention patents per billion kw.h and enterprise capacity utilization evaluation indicators; The new quality production evaluation indicators constructed from the dimension of industrial development drive include: core product price index, year-on-year domestic sales of downstream consumer products, year-on-year exports of downstream consumer products, scale and degree of industrial upgrading.

4. According to claim 1, a method for evaluating the development of industrial chain nodes based on the new quality productivity index is characterized by: Based on the basic database, the index value in the new quality productivity index evaluation system is calculated for each node in the industrial chain, and the important index value is obtained according to the calculation result analysis, and the new quality productivity index of the corresponding node is calculated using the important index value, which specifically includes: Taking each node as the evaluation object, based on the basic database, the new quality production evaluation index values ​​of different dimensions are calculated for each node in the industrial chain to form an industrial chain node development evaluation matrix; Filter out important indicator values ​​based on the industry chain node development evaluation matrix; The important index values ​​are used to calculate the new quality productivity index F of the corresponding node.

5. The method for evaluating the development of industrial chain nodes based on the new quality productivity index according to claim 4 is characterized by: The important indicator values ​​are screened out according to the industrial chain node development evaluation matrix, including: The indicator values ​​in the industrial chain node development evaluation matrix are standardized, and the formula is as follows: in, is the value of the jth indicator of the i-th evaluation object after standardization; n is the number of nodes in the industrial chain, and m is the number of new quality productivity indexes; x ij is the value of the jth indicator of the i-th evaluation object; and j are the mean and standard deviation of the jth indicator respectively; Calculate the correlation coefficient matrix R, the formula is as follows: R＝(r pq ) m×m Where rpq is the correlation coefficient between the pth indicator and the qth indicator, rpp = 1, rpq = rqp; Calculate the eigenvalues ​​and eigenvectors of the correlation coefficient matrix R, and obtain m new indicator variables based on the eigenvectors, as follows: 1) Calculate the eigenvalues ​​λ1≥λ2≥...≥λm≥0 of the correlation coefficient matrix R and the corresponding eigenvector uj=(u 1j ,u 2j ,...unj) T , j = 1...m; 2) Obtain m new indicator variables based on the eigenvector: ... Among them, y1, y2, and ym are the 1st, 2nd, and mth new indicator variables respectively; is the value of the mth indicator of the nth evaluation object after standardization; Based on the characteristic values, N new indicator variables are selected from the m new indicator variables as important indicator values, including: 1) Calculate the information contribution rate nk of the eigenvalue λj, the formula is as follows: 2) Sort the m new indicator variables according to the information contribution rate of their corresponding eigenvalues ​​from large to small, and select N new indicator variables to obtain N important indicator values.

6. The method for evaluating the development of industrial chain nodes based on the new quality productivity index according to claim 5 is characterized by: The calculation formula of the new quality productivity index F is as follows: where y j is the value of the jth important indicator.

7. According to claim 1, a method for evaluating the development of industrial chain nodes based on the new quality productivity index is characterized by: In step 5, based on the upstream and downstream network relationship diagram of the industry and the important indicator values, the new quality productivity index of each node in the middle and downstream is adjusted considering the impact of upstream and downstream fluctuations, and then the high-quality development of each node in the industrial chain is evaluated, including: Obtain each node of the industrial chain in the industrial upstream and downstream network relationship diagram, which is divided into upstream nodes, midstream nodes and downstream nodes; among them, the upstream nodes are not affected by the nodes further upstream, the midstream nodes are affected by the upstream nodes, the downstream nodes are affected by the midstream nodes, and the influence of the upstream nodes on the downstream nodes is transmitted through the midstream node links; for the midstream and downstream nodes, firstly, calculate layer by layer to obtain the new quality productivity index of the midstream nodes under the influence of the upstream, and then calculate the new quality productivity index of the downstream nodes under the influence of the midstream nodes; By comparing the new quality productivity index of upstream nodes, the new quality productivity index of midstream nodes considering the influence of upstream nodes, and the new quality productivity index of downstream nodes considering the influence of midstream nodes, we can screen out the weak nodes in high-quality development of each node in the industrial chain.

8. The method for evaluating the development of industrial chain nodes based on the new quality productivity index according to claim 7 is characterized by: The calculation method of the new quality productivity index of the midstream node considering the upstream influence is: 1) According to the important index value of each node, calculate the correlation between the midstream node x and its upstream nodes; 2) Based on the new quality productivity index of the node, calculate the fluctuation degree of each upstream node: Among them, Δy is the fluctuation degree of upstream node y; F t is the new quality productivity index of the upstream node y in the current period; F t-1 is the new quality productivity index of the upstream node y in the previous period; 3) Multiplying the correlation by the fluctuation degree of the corresponding upstream node to obtain the coefficient of the corresponding midstream node affected by the upstream, forming a P-dimensional Y vector; 4) Standardize the coefficient of the midstream node affected by the upstream in the P-dimensional Y vector to obtain the standardized coefficient vector Y', sum the elements in the vector to obtain the fluctuation impact value of the upstream node, and multiply it with the new quality productivity index of the corresponding midstream node to obtain the new quality productivity index of the midstream node considering the upstream influence.

9. The method for evaluating the development of industrial chain nodes based on the new quality productivity index according to claim 8 is characterized by: According to the important index value of each node, the correlation between the midstream node x and its upstream nodes is calculated as follows: Each node has N important index values, which form the node's feature vector value. The correlation between node x and each upstream node is calculated based on the node's feature vector value: Where Cy is the correlation between node x and upstream node y, y ranges from 1 to P, and P is the total number of upstream nodes; a is the feature vector value of the upstream node y; b is the eigenvector value of the midstream node x.

10. An industrial chain node development evaluation system based on the new quality productivity index, using the method described in any one of claims 1 to 9, characterized in that: The system comprises: Data acquisition module, used to obtain industrial chain power data and social data and establish a basic database; A relationship diagram construction module, used to construct an industry upstream and downstream network relationship diagram based on the basic database; Evaluation index construction module, used to construct new quality production evaluation indicators from different dimensions and form a new quality productivity index evaluation system; A new quality productivity index calculation module, which is used to calculate the index value in the new quality productivity index evaluation system for each node in the industrial chain based on the basic database, obtain important index values ​​according to the calculation results, and use the important index values ​​to calculate the new quality productivity index of the corresponding node; The development status assessment module is used to adjust the new quality productivity index of each node in the middle and downstream based on the upstream and downstream network relationship diagram of the industry and the above-mentioned important indicator values, taking into account the impact of upstream and downstream fluctuations, and then assess the high-quality development of each node in the industrial chain.

11. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1-9.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 9 are implemented.

Images