Enterprise department and wound ability data management method and device, equipment and storage medium

Abstract

The invention discloses an enterprise department and wound ability data management method and device, equipment and a storage medium, and the method comprises the steps: obtaining the original data of the enterprise department and wound ability; inputting the original data into an enterprise department and wound ability analysis model to enable the enterprise department and wound ability analysis model to output an analysis result about the enterprise department and wound ability; wherein the original data comprises enterprise research and development expenditure, a business income growth rate, logarithmic total assets, a capital and credit rate, cash flow, establishment time and intellectual property quantity. The computer model-based enterprise department and wound ability data management method, device and equipment and the storage medium have the beneficial effects that the enterprise department and wound ability can be comprehensively evaluated, and the computer model-based enterprise department and wound ability data management method and device and the storage medium are provided.

Description

Technical Field

[0001] The present application relates to the technical field of enterprise evaluation data management, and more specifically, to a method, device, equipment and storage medium for enterprise scientific and technological innovation capability data management. Background Art

[0002] As an important force for economic growth, small and medium-sized enterprises are playing an increasingly important role in all walks of life, especially in high-tech emerging industries. my country's newly emerging regional equity markets play an important role in nurturing small and medium-sized enterprises. However, in regional equity markets, although some companies have achieved remarkable results in product innovation, technological research and development, and service upgrades, these achievements are often not fully recognized and utilized.

[0003] For example, for enterprises in the regional equity market, it is urgent to build a systematic and comprehensive science and technology innovation capability evaluation system to measure the science and technology innovation capabilities and potential of enterprises. Summary of the invention

[0004] The content of this application is used to introduce concepts in a brief form, which will be described in detail in the detailed implementation section below. The content of this application is not intended to identify the key features or essential features of the technical solution claimed for protection, nor is it intended to limit the scope of the technical solution claimed for protection.

[0005] Some embodiments of the present application propose a method, device, electronic device and computer-readable medium for managing enterprise scientific and technological innovation capability data to solve the technical problems mentioned in the above background technology section.

[0006] As a first aspect of the present application, some embodiments of the present application provide a method for managing enterprise scientific and technological innovation capability data, including: obtaining original data of the enterprise's scientific and technological innovation capability; inputting the original data into an enterprise's scientific and technological innovation capability analysis model so that the enterprise's scientific and technological innovation capability analysis model outputs analysis results about the enterprise's scientific and technological innovation capability; wherein the original data includes: enterprise R&D expenditure, operating income growth rate, logarithmic total assets, debt-to-asset ratio, cash flow, establishment time and number of intellectual property rights.

[0007] Optionally, in some embodiments of the present application, the enterprise scientific and technological innovation capability data management method further includes: constructing the enterprise scientific and technological innovation capability analysis model.

[0008] Optionally, in some embodiments of the present application, constructing the enterprise's scientific and technological innovation capability analysis model includes: constructing an indicator system; supplementing characteristic indicators based on the indicator system; collecting and preprocessing multi-source heterogeneous data; establishing the enterprise's scientific and technological innovation capability analysis model based on data analysis and mining; and verifying the effectiveness of the enterprise's scientific and technological innovation capability analysis model.

[0009] Optionally, in some embodiments of the present application, the supplementing of characteristic indicators based on the indicator system includes:

[0010] Characteristic indicators that constitute inefficient R&D investment;

[0011] Among them, the inefficient R&D investment lnRD is constructed through enterprise R&D expenditure, operating income growth rate, logarithmic total assets, debt-to-asset ratio, cash flow, establishment time and number of invention patents.

[0012] Optionally, in some embodiments of the present application, the inefficient R&D investment lnRD is calculated by the formula:

[0013] lnRD=Growth+Size+Lev+Cash+FirmAge+Pat+ε

[0014] Among them, RD, Growth, Size, Lev, Cash, FirmAge and Pat represent the enterprise's R&D expenditure, operating income growth rate, logarithmic total assets, debt-to-asset ratio, cash flow, establishment time and number of invention patents respectively. By performing multivariate linear regression on the above model and grouping enterprises from different industries, the residual ε is used to measure the level of "inefficient R&D investment" of the enterprise. When ε is greater than 0, it means that the enterprise has an over-investment problem, otherwise the enterprise has an under-investment problem.

[0015] Optionally, in some embodiments of the present application, the collection and preprocessing of multi-source heterogeneous data includes: acquiring corresponding data from multiple data sources; and preprocessing the collected data to unify and normalize the dimensions.

[0016] Optionally, in some embodiments of the present application, the enterprise's scientific and technological innovation capability analysis model is established based on data analysis and mining, including: converting the three-level subdivided indicators of the indicator system into secondary indicators through principal component analysis, and then using the entropy weight method to calculate the weights of these secondary indicators, and combining the weight calculation to obtain a comprehensive scientific and technological innovation index as the analysis result.

[0017] As a second aspect of the present application, some embodiments of the present application provide a kind of enterprise scientific and technological innovation capability data management, including: an acquisition module, used to acquire the original data of the enterprise's scientific and technological innovation capability; an analysis module, used to input the original data into the enterprise's scientific and technological innovation capability analysis model so that the enterprise's scientific and technological innovation capability analysis model outputs analysis results about the enterprise's scientific and technological innovation capability.

[0018] As the third aspect of the present application, some embodiments of the present application provide an electronic device, comprising: one or more processors; a storage device on which one or more programs are stored, and when the one or more programs are executed by one or more processors, the one or more processors implement the method described in any implementation manner of the above-mentioned first aspect.

[0019] As a fourth aspect of the present application, some embodiments of the present application provide a computer-readable medium on which a computer program is stored, wherein when the program is executed by a processor, the method described in any implementation of the above-mentioned first aspect is implemented.

[0020] The beneficial effect of the present application is that it provides a method, device, equipment and storage medium for managing enterprise scientific and technological innovation capability data based on a computer model, which can comprehensively evaluate the scientific and technological innovation capability of an enterprise. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The drawings constituting a part of this application are used to provide a further understanding of this application, so that other features, purposes and advantages of this application become more obvious. The drawings and descriptions of the exemplary embodiments of this application are used to explain this application and do not constitute an improper limitation on this application.

[0022] In addition, throughout the drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that the components and elements are not necessarily drawn to scale.

[0023] In the attached picture:

[0024] Figure 1 It is a structural diagram of the main steps of the enterprise scientific and technological innovation capability data management method according to an embodiment of the present application;

[0025] Figure 2 It is a structural schematic diagram of an enterprise scientific and technological innovation capability data management device according to an embodiment of the present application;

[0026] Figure 3 It is a schematic diagram of a process for constructing an enterprise scientific and technological innovation capability analysis model according to an embodiment of the present application;

[0027] Figure 4 is a schematic diagram of an indicator system structure according to an embodiment of the present application;

[0028] Figure 5 It is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0029] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments set forth herein. On the contrary, these embodiments are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0030] It should also be noted that, for ease of description, only the parts related to the invention are shown in the drawings. In the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0031] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0032] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0033] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0034] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0035] Reference Figures 1 to 4 As shown, as the first aspect of the present application, some embodiments of the present application provide a method for managing enterprise scientific and technological innovation capability data, including: obtaining original data of the enterprise's scientific and technological innovation capability; inputting the original data into an enterprise's scientific and technological innovation capability analysis model so that the enterprise's scientific and technological innovation capability analysis model outputs analysis results about the enterprise's scientific and technological innovation capability; wherein the original data includes: enterprise R&D expenditure, operating income growth rate, logarithmic total assets, debt-to-asset ratio, cash flow, establishment time and number of intellectual property rights.

[0036] Specifically, the enterprise scientific and technological innovation capability data management method also includes: constructing the enterprise scientific and technological innovation capability analysis model.

[0037] Specifically, the construction of the enterprise's scientific and technological innovation capability analysis model includes: constructing an indicator system; supplementing characteristic indicators based on the indicator system; collecting and preprocessing multi-source heterogeneous data; establishing the enterprise's scientific and technological innovation capability analysis model based on data analysis and mining; and verifying the effectiveness of the enterprise's scientific and technological innovation capability analysis model.

[0038] Specifically, the supplement of characteristic indicators based on the indicator system includes:

[0039] Characteristic indicators that constitute inefficient R&D investment;

[0040] Among them, the inefficient R&D investment lnRD is constructed through enterprise R&D expenditure, operating income growth rate, logarithmic total assets, debt-to-asset ratio, cash flow, establishment time and number of invention patents.

[0041] Specifically, the inefficient R&D investment lnRD is calculated by the formula:

[0042] lnRD=Growth+Size+Lev+Cash+FirmAge+Pat+ε

[0043] Among them, RD, Growth, Size, Lev, Cash, FirmAge and Pat represent the enterprise's R&D expenditure, operating income growth rate, logarithmic total assets, debt-to-asset ratio, cash flow, establishment time and number of invention patents respectively. By performing multivariate linear regression on the above model and grouping enterprises from different industries, the residual ε is used to measure the level of "inefficient R&D investment" of the enterprise. When ε is greater than 0, it means that the enterprise has an over-investment problem, otherwise the enterprise has an under-investment problem.

[0044] Specifically, the collection and preprocessing of multi-source heterogeneous data includes: acquiring corresponding data from multiple data sources; and preprocessing the collected data to unify and normalize the dimensions.

[0045] Specifically, the enterprise's scientific and technological innovation capability analysis model is established based on data analysis and mining, including: reducing the three-level subdivided indicators of the indicator system into secondary indicators through principal component analysis, and then using the entropy weight method to calculate the weights of these secondary indicators, and combining the weight calculation to obtain a comprehensive scientific and technological innovation index as the analysis result.

[0046] As a second aspect of the present application, some embodiments of the present application provide an enterprise scientific and technological innovation capability data management device, including: an acquisition module for acquiring original data of the enterprise's scientific and technological innovation capability; an analysis module for inputting the original data into an enterprise's scientific and technological innovation capability analysis model so that the enterprise's scientific and technological innovation capability analysis model outputs analysis results about the enterprise's scientific and technological innovation capability.

[0047] As a specific application of this application, in order to rely on computer equipment and computer programs to evaluate the technological innovation capabilities of regional equity market enterprises, refer to Figure 2 and Figure 3 As shown, a specific implementation of the present application is expanded.

[0048] When applying the solution of this application to the current specific application scenario, the specific solution of this application includes:

[0049] The technical solution of the present invention mainly includes the following steps:

[0050] 1. Sorting out documents and building an evaluation system: By sorting out various documents related to the evaluation of scientific and technological innovation capabilities, including the "Evaluation Index System for Chinese Enterprises' Innovation Capabilities", "Guidelines for the Evaluation of Scientific and Technological Innovation Attributes", "Management Measures for the Recognition of High-tech Enterprises", "National Key High-tech Fields Supported by the State", etc., as well as relevant literature on the evaluation of scientific and technological innovation capabilities of existing enterprises and industries at home and abroad, and considering the feasibility of data acquisition, we sorted out evaluation indicators commonly used in the industry that are in line with the characteristics of enterprises in the regional equity market, including traditional indicators such as "the proportion of R&D expenditure to main business income", "the proportion of R&D personnel to total employees", "the number of invention patents", and "the proportion of valid patents to the number of patent authorizations".

[0051] 2. Definition of additional characteristic indicators: On this basis, based on the scientific and technological innovation characteristics of enterprises in the regional equity market, using financial econometric methods and machine learning models, we calculated characteristic indicators including inefficient R&D investment, disruptive innovation and knowledge breadth, and constructed a three-level indicator system including 3 dimensions, 7 major categories and 30 sub-indicators, forming a comprehensive index that can scientifically evaluate the scientific and technological innovation capabilities of enterprises.

[0052] "Inefficient R&D investment" refers to the insufficient R&D investment, repeated R&D investment and low-end blind R&D investment behaviors that occur in the process of achieving scientific and technological innovation. Objectively, it will hinder the company from forming a business model that makes profits through intellectual property rights, resulting in the inability to fully form innovative R&D processes and R&D industry chains. Based on the existing literature on the quantitative methods of "inefficient R&D investment", and considering the feasibility of data acquisition, this paper proposes the following characteristic indicator construction method:

[0053] lnRD=Growth+Size+Lev+Cash+FirmAge+Pat+ε

[0054] Among them, RD, Growth, Size, Lev, Cash, FirmAge and Pat represent the enterprise's R&D expenditure, operating income growth rate, logarithmic total assets, debt-to-asset ratio, cash flow, establishment time and number of invention patents respectively. By performing multivariate linear regression on the above model and grouping enterprises from different industries, the residual ε is used to measure the level of "inefficient R&D investment" of the enterprise. When ε is greater than 0, it means that the enterprise has an over-investment problem, otherwise the enterprise has an under-investment problem.

[0055] "Disruptive innovation" is based on traditional innovation, disruptive innovation and micro-innovation, and leads to qualitative change from quantitative change, from gradual change to disruptive change, including a new technology or a new cross-disciplinary and cross-field application based on existing technology. The present invention uses the PageRank algorithm to calculate the influence of technology and construct a directed weighted citation network, where the node V is a paper or invention patent, and the directed edge E is the citation relationship between nodes, and the weight of each node is obtained. The definition indicators are as follows:

[0056]

[0057] Where N F is the sum of the weights of all nodes that reference this node but do not reference the forward node, N B N is the sum of the weights of all nodes that reference the node’s forward node and reference the node. R It is the sum of the weights of all nodes that do not reference this node but reference the forward node.

[0058] "Knowledge breadth" measures patent quality from the perspective of the coverage and complexity of the knowledge contained in the patent. The present invention uses the following formula to calculate the knowledge breadth of enterprise patents:

[0059] PatKnow i =1-∑(Pat_num i,m / Pat_num i ) 2

[0060] Where Pat_num i,m Pat_num represents the number of patent applications filed by enterprise i under group m. i It represents the total number of patent applications of enterprise i under all major classification groups.

[0061] Collection and preprocessing of multi-source heterogeneous data: Since regional equity market data has the problems of short sedimentation time and limited data volume, the present invention selects as many data sources as possible when collecting data, including the CSRC's supervision chain big data warehouse, third-party data platform, etc. However, the data structures of different data sources are different, and there are problems of complex data structure and high data dimension after combination. Therefore, the present invention first merges different data sources, and then preprocesses the integrated data: For numerical data, due to the difference in dimensions between different indicators, normalization is first performed, using the maximum-minimum normalization method. In addition, for reverse indicators (indicators with a negative correlation with the company's technological innovation capabilities), a normalization process of taking the opposite number is performed; for text data, such as "executive technical resume", word segmentation is first performed. Based on the preset dictionary of the present invention, the word set after word segmentation is compared with the dictionary, and whether the company's executives have technical resumes is judged based on whether the two have intersections.

[0062] Data analysis and mining: In order to objectively customize the weights of indicators so that the obtained weighted index can effectively reflect the technological innovation capabilities of enterprises, the present invention converts the three-level subdivision indicators in the above indicator system into secondary indicators through principal component analysis (PCA) dimensionality reduction, and then uses the entropy weight method to calculate the weights of these secondary indicators. Finally, a comprehensive technological innovation index is calculated by combining these weights.

[0063] First, principal component analysis (PCA) is used to reduce the dimensionality of the indicator data. This method converts potentially correlated variables into a set of linearly uncorrelated variables through orthogonal transformation, which helps to extract the main information that best represents the variability of the data, namely the secondary indicators, from the numerous tertiary indicators. While reducing the complexity of the data, it also ensures that the focus of the analysis is on the most influential factors, which is conducive to evaluating the efficiency and accuracy of the model.

[0064] Secondly, the entropy weight method is used to determine the weight of each secondary indicator. The entropy weight method is an objective weighting method based on the principle of information entropy, which can quantify the usefulness and diversity of indicator information. In this process, the smaller the entropy value of each indicator, the greater the variability of the indicator, so it should be given a higher weight in the overall evaluation. Compared with the common hierarchical analysis method, this method can effectively reduce the impact of subjective judgment on weight allocation. Specifically, assuming that there are m sub-samples in a sample, each sub-sample has n indicators, and the indicator set X = {x 11 ,x 12 ,…,x mn}. Each indicator needs to be standardized first, and the positive indicator x' ij As follows, the inverse index is normalized to -x' ij .

[0065]

[0066] Then for x' ij Add a small constant to perform the translation operation to get y ij , so that all the results are positive. Calculate its weight p under the jth index ij .

[0067]

[0068] Calculate the entropy value of the jth indicator:

[0069] Introduce constant k to ensure that the p of the jth index ij are equal, satisfying H j =1, then the indicator does not provide any information. ij = 0, let p ij ×(lnpij )=0, thus ensuring E j The value range is [0, 1].

[0070]

[0071] Calculate the weight of the jth indicator

[30]

[0072]

[0073] Finally, the final science and technology innovation index will be calculated by weighted summation. The weighted summation of the secondary indicator values ​​and their corresponding weights determined in the previous steps will be used to comprehensively reflect the scientific and technological innovation capabilities of the enterprise, providing a quantitative evaluation tool for enterprise management and policy makers in terms of the scientific and technological innovation capabilities of the enterprise.

[0074] Visualization and verification of the effectiveness of the evaluation system: After obtaining the weights of the indicator system and the corresponding scientific and technological innovation scores, the present invention uses the t-SNE method to reduce the original three-level indicator data to two dimensions, and visualize the relationship between the scientific and technological innovation ability scores and the data. The core idea of ​​t-SNE is to maintain the similarity between data points in high-dimensional and low-dimensional spaces, and minimize the KL divergence between the two conditional probability distributions in high-dimensional and low-dimensional spaces to make them as similar as possible. In addition, the present invention also counts the number of enterprises in different score intervals and draws a histogram to observe whether the enterprise's scientific and technological innovation scores are basically normally distributed, so as to judge the effectiveness of the evaluation system.

[0075] like Figure 5 As shown, the electronic device 800 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage device 808 into a random access memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the electronic device 800 are also stored. The processing device 801, the ROM 802, and the RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0076] Typically, the following devices may be connected to the I / O interface 805: input devices 806 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 807 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 808 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 809. The communication device 809 may allow the electronic device 800 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 5The electronic device 800 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 5 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0077] In particular, according to some embodiments of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In some such embodiments, the computer program can be downloaded and installed from the network through the communication device 809, or installed from the storage device 808, or installed from the ROM 802. When the computer program is executed by the processing device 801, the above-mentioned functions defined in the method of some embodiments of the present disclosure are executed.

[0078] It should be noted that the computer-readable medium described above in some embodiments of the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more wires, 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), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0079] In some embodiments of the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device, or device. In some embodiments of the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in combination with an instruction execution system, device, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0080] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperTextTransferProtocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an adhoc peer-to-peer network), as well as any currently known or future developed network.

[0081] The computer-readable medium may be included in the electronic device or may exist independently without being installed in the electronic device. The computer-readable medium carries one or more programs.

[0082] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer may be connected to the user's computer through 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., through the Internet using an Internet service provider).

[0083] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, which contains one or more executable instructions for implementing a specified logical function.

[0084] It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures.

[0085] For example, two boxes shown in succession may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of boxes in the block diagram and / or flow chart, can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0086] The units described in some embodiments of the present disclosure may be implemented in software or hardware, and the units described may also be arranged in a processor.

[0087] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0088] The above descriptions are only some preferred embodiments of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by a specific combination of the above-mentioned technical features, but should also cover other technical solutions formed by any combination of the above-mentioned technical features or their equivalent features without departing from the above-mentioned inventive concept. For example, the above-mentioned features are replaced with the technical features with similar functions disclosed in the embodiments of the present disclosure (but not limited to) and the technical solutions formed.

Claims

1. A method for managing enterprise scientific and technological innovation capability data, comprising: Obtaining original data on the scientific and technological innovation capabilities of enterprises; Inputting the original data into the enterprise scientific and technological innovation capability analysis model so that the enterprise scientific and technological innovation capability analysis model outputs analysis results on the enterprise scientific and technological innovation capability; Among them, the original data include: enterprise R&D expenditure, operating income growth rate, logarithmic total assets, debt-to-asset ratio, cash flow, establishment time and number of intellectual property rights.

2. The enterprise scientific and technological innovation capability data management method according to claim 1 is characterized by: The enterprise scientific and technological innovation capability data management method further includes: Construct the enterprise's scientific and technological innovation capability analysis model.

3. The enterprise scientific and technological innovation capability data management method according to claim 2, Features: Wherein, the construction of the enterprise scientific and technological innovation capability analysis model includes: Build an indicator system; Supplementing characteristic indicators based on the indicator system; Collection and preprocessing of multi-source heterogeneous data; Establishing the enterprise's scientific and technological innovation capability analysis model based on data analysis and mining; Verify the effectiveness of the enterprise's scientific and technological innovation capability analysis model.

4. The enterprise scientific and technological innovation capability data management method according to claim 3 is characterized by: in, The supplement of characteristic indicators based on the indicator system includes: Characteristic indicators that constitute inefficient R&D investment; Among them, the inefficient R&D investment lnRD is constructed through enterprise R&D expenditure, operating income growth rate, logarithmic total assets, debt-to-asset ratio, cash flow, establishment time and number of invention patents.

5. The enterprise scientific and technological innovation capability data management method according to claim 4 is characterized by: in, The inefficient R&D investment lnRD is calculated by the formula lnRD=Growth+Size+Lev+Cash+FirmAge+Pat+ε Among them, RD, Growth, Size, Lev, Cash, FirmAge and Pat represent the enterprise's R&D expenditure, operating income growth rate, logarithmic total assets, debt-to-asset ratio, cash flow, founding time and number of invention patents respectively. By performing multivariate linear regression on the above model and grouping enterprises in different industries, the residual ε is used to measure the level of "inefficient R&D investment" of the enterprise. When ε is greater than 0, it means that the enterprise has an over-investment problem, otherwise the enterprise has an under-investment phenomenon.

6. The enterprise scientific and technological innovation capability data management method according to claim 5, Features: The collection and preprocessing of multi-source heterogeneous data includes: Obtain relevant data from multiple data sources; The collected data are preprocessed to unify and normalize the dimensions.

7. The enterprise scientific and technological innovation capability data management method according to claim 6 is characterized by: in, The establishment of the enterprise scientific and technological innovation capability analysis model based on data analysis and mining includes: The three-level subdivision indicators of the indicator system are converted into secondary indicators through principal component analysis, and then the entropy weight method is used to calculate the weights of these secondary indicators. Combined with the weight calculation, a comprehensive science and technology innovation index is obtained as the analysis result.

8. An enterprise scientific and technological innovation capability data management device, comprising: The acquisition module is used to obtain the original data of the enterprise's scientific and technological innovation capabilities; The analysis module is used to input the original data into the enterprise's scientific and technological innovation capability analysis model so that the enterprise's scientific and technological innovation capability analysis model outputs analysis results on the enterprise's scientific and technological innovation capability.

9. An electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the processors implement the method according to any one of claims 1 to 7.

10. A computer readable medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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