Enterprise health assessment system based on fsQCA analysis

Abstract

The invention belongs to the technical field of enterprise management, and particularly relates to an fsQCA analysis-based enterprise health assessment system, which realizes comprehensive and deep assessment of enterprise health conditions through organic combination of a data acquisition module, a data analysis module and an assessment module. The data acquisition module can collect multi-dimensional data including personal characteristics of employees, organization environment, digital transformation characteristics and the like. And the data analysis module constructs a relation model of condition variables and result variables by applying a fuzzy set qualitative comparative analysis method, and accurately identifies factors influencing enterprise health and configuration paths thereof. And the evaluation module further automatically generates a detailed evaluation report containing the excitation path, the inhibition path and the improvement suggestion according to the analysis result. The system not only can provide an accurate and objective evaluation result for an enterprise, but also can timely and effectively guide the enterprise to carry out strategic planning and operation management adjustment, and promotes the enterprise to realize healthy and sustainable development.

Description

Technical Field

[0001] The present invention belongs to the technical field of enterprise management, and in particular relates to an enterprise health assessment system based on fsQCA analysis. Background Art

[0002] In the current practice of enterprise management, enterprise health assessment has become an important tool to measure the operation status of enterprises and guide their strategic planning. Traditional enterprise health assessment methods often rely on subjective judgment or simple financial indicators, which are difficult to fully and deeply reflect the true health status of enterprises. With the deepening of digital transformation, enterprise health assessment is also facing new challenges and opportunities.

[0003] In recent years, fuzzy set qualitative comparative analysis (fsQCA), as an emerging research method, has gradually been applied to the field of corporate health assessment. By constructing a relationship model between conditional variables and outcome variables, fsQCA can systematically analyze the factors and configuration paths that lead to changes in corporate health status. However, there is currently no corporate health assessment system based on fsQCA analysis on the market, which has brought certain obstacles to the digital transformation of corporate health assessment. Although fsQCA has shown great potential in the field of corporate health assessment, existing technologies still have many shortcomings in practical applications. First, traditional assessment methods lack scientific data collection and analysis methods, making it difficult to ensure the accuracy and objectivity of assessment results. Second, existing assessment systems often only focus on single-dimensional assessment indicators, ignoring the complexity and diversity of corporate health status, and are difficult to effectively apply to corporate strategic planning and operational management. Summary of the invention

[0004] The purpose of the present invention is to provide an enterprise health assessment system based on fsQCA analysis to solve the problems raised in the background technology.

[0005] The present invention achieves the above-mentioned purpose through the following technical solutions:

[0006] The present invention proposes an enterprise health assessment system based on fsQCA analysis, including a data acquisition module, a data analysis module and an assessment module:

[0007] The data collection module is used to collect a multidimensional data set including employee personal characteristic data, organizational environment, digital transformation characteristics and employee innovation level according to a preset data collection framework; wherein the employee innovation level is based on the set project information and the innovation evaluation standards of each stage, and the innovation evaluation value is calculated by a preset evaluation model;

[0008] The data analysis module is used to construct conditional variables and result variables based on the multidimensional data set, and identify the configuration path that leads to the enhancement or weakening of employee innovation through fuzzy set operations and truth table analysis;

[0009] The evaluation module is used to draw an evaluation chart of the enhancement or weakening of the innovation ability of the digital transformation units and employees based on the configuration path, and to perform an enterprise health assessment in combination with the evaluation chart.

[0010] Further, the data acquisition module includes a first acquisition unit and a second acquisition unit;

[0011] The first collection unit is used to collect employee personal characteristic data, organizational environment and digital transformation characteristics;

[0012] The second collection unit is preset with an innovation evaluation benchmark library and an evaluation subunit, the innovation evaluation benchmark library contains innovation evaluation standards and benchmark data set according to different projects and project stages, and the evaluation subunit is built-in with an evaluation model based on the innovation evaluation benchmark library, and the evaluation model includes the following formula: innovation evaluation value = Σ(X*(Z / Y));

[0013] Among them, X is the weight of the i-th evaluation index, Z is the data collected in real time by the first collection unit, and Y is the benchmark data of the corresponding stage.

[0014] Furthermore, the personal characteristic data includes the employee's age, gender, educational background and work experience information; the organizational environment includes the company's organizational structure, cultural atmosphere and management system information; and the digital transformation characteristics include the company's digital transformation level.

[0015] Further, the data analysis module includes a variable construction unit and a fuzzy set operation unit;

[0016] The variable construction unit is used to construct the employee personal characteristic data, organizational environment and digital transformation characteristics in the multidimensional data set as conditional variables, and construct the innovation assessment value as a result variable;

[0017] The fuzzy set operation unit is used to construct a relationship model between condition variables and result variables through fuzzy set operations, and its expression is defined as: R = f (Condition_1, Condition_2, ..., Condition_i), wherein R represents the result variable, Condition_i represents the i-th condition variable, and f is the membership function set in the fsQCA analysis; then, according to the result variable value under each condition combination, the configuration path is determined through the truth table, in which the configuration path with enhanced innovation is set as the stimulation path, and the path with weakened innovation is set as the inhibition path.

[0018] Further, the evaluation module includes a chart drawing unit and a graded evaluation unit;

[0019] The chart drawing unit is used to draw a radar chart to show the performance of employee innovation under different combinations of conditions, each dimension represents an evaluation indicator, and the radius or area of ​​the chart represents the strength of innovation;

[0020] The grading assessment unit is used to perform a comprehensive assessment based on a preset grading assessment system and the data in the chart to determine the enterprise health level.

[0021] Furthermore, the preset grading evaluation system includes:

[0022] A-level health: corresponding to the chart results showing that there are 60% or more excitation paths, and the average impact strength of the excitation paths exceeds 0.7;

[0023] B-level health: corresponds to 50%-60% of the excitation paths in the chart results, and the average impact strength of the excitation paths is between 0.5 and 0.7; at the same time, the inhibition paths do not exceed 20%, and the average impact strength is less than 0.3;

[0024] C-level health: corresponding to the coexistence of excitation pathway and inhibition pathway, the excitation pathway accounts for 40%-50%, and the average impact strength is less than 0.5; the inhibition pathway accounts for 10%-20%, and the average impact strength is higher than 0.4;

[0025] D-level health: corresponds to more than 60% of the inhibition paths in the chart results, the average impact strength of the inhibition paths exceeds 0.5, and less than 10% of the excitation paths, the average impact strength of the excitation paths is less than 0.2.

[0026] Furthermore, the evaluation system also includes a report generation module for automatically generating an enterprise health evaluation report including an excitation path, an inhibition path and improvement suggestions according to the fsQCA analysis results.

[0027] The beneficial effects of the present invention are:

[0028] 1. The data collection module in the present invention can comprehensively collect multidimensional data sets including employee personal characteristic data, organizational environment, digital transformation characteristics and employee innovation level according to the preset data collection framework. The data analysis module builds a relationship model between conditional variables and outcome variables based on these data sets, and identifies the factors and configuration paths that lead to changes in the health status of the enterprise through fuzzy set operations and truth table analysis. This method ensures the accuracy and objectivity of the evaluation results.

[0029] 2. This invention not only focuses on the evaluation indicators of a single dimension, but also comprehensively considers the influence of multiple aspects such as employee personal characteristics, organizational environment, digital transformation characteristics, etc. This makes the evaluation results more comprehensive and in-depth reflection of the real health status of the enterprise.

[0030] 3. The evaluation module in the present invention can automatically generate an enterprise health evaluation report containing excitation paths, inhibition paths and improvement suggestions based on the analysis results. This automated report generation function greatly improves the efficiency and quality of the evaluation work, so that the evaluation results can be applied to the strategic planning and operation management of the enterprise in a timely and effective manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a system architecture diagram of the evaluation system in the present invention.

[0032] Figure 2 This is another system architecture diagram of the evaluation system in the present invention.

[0033] Figure 3 It is a structural diagram of the data acquisition module in the present invention.

[0034] Figure 4 It is a structural diagram of the data analysis module in the present invention.

[0035] Figure 5 It is a structural diagram of the evaluation module in the present invention. DETAILED DESCRIPTION

[0036] The present application is further described in detail below in conjunction with the accompanying drawings. It is necessary to point out here that the following specific implementation methods are only used to further illustrate the present application and cannot be understood as limiting the scope of protection of the present application. Technical personnel in this field can make some non-essential improvements and adjustments to the present application based on the above application content.

[0037] Example 1

[0038] like Figure 1-2 As shown, this embodiment proposes an enterprise health assessment system based on fsQCA analysis, including a data acquisition module, a data analysis module and an assessment module:

[0039] The data collection module is used to collect multidimensional data sets including employee personal characteristic data, organizational environment, digital transformation characteristics and employee innovation level according to the preset data collection framework (preset data collection framework: defines the scope, format, frequency, etc. of data collection to ensure the comprehensiveness and consistency of data); among which, the employee innovation level is based on the set project information and the innovation evaluation standards of each stage, and the innovation evaluation value is calculated through the preset evaluation model.

[0040] Further preferably, the personal characteristic data include the employee's age, gender, educational background and work experience information; the organizational environment includes the company's organizational structure, cultural atmosphere and management system information; the digital transformation characteristics include the company's digital transformation level (the company's digital transformation level can be achieved by collecting relevant reports, data analysis or expert evaluation of the company. Based on this information, the set level standards are used to determine the company's digital transformation level).

[0041] The data analysis module is used to construct conditional variables and outcome variables based on multidimensional data sets, and to identify the configuration paths that lead to enhanced or weakened employee innovation through fuzzy set operations and truth table analysis;

[0042] The evaluation module is used to draw evaluation charts of the increase or decrease in innovation of digital transformation units and employees based on the configuration path, and to conduct enterprise health assessment in combination with the evaluation charts.

[0043] like Figure 3 As shown, further preferably, the data acquisition module includes a first acquisition unit and a second acquisition unit;

[0044] The first collection unit is used to collect employee personal characteristic data, organizational environment and digital transformation characteristics;

[0045] The second collection unit is preset with an innovation evaluation benchmark library and an evaluation sub-unit. The innovation evaluation benchmark library contains innovation evaluation standards and benchmark data set according to different projects and project stages. The evaluation sub-unit is built-in with an evaluation model based on the innovation evaluation benchmark library. The evaluation model includes the following formula: innovation evaluation value = Σ(X*(Z / Y));

[0046] Among them, X is the weight of the i-th evaluation index, Z is the data collected in real time by the first collection unit, and Y is the benchmark data of the corresponding stage.

[0047] like Figure 4 As shown, further preferably, the data analysis module includes a variable construction unit and a fuzzy set operation unit;

[0048] The variable construction unit is used to construct the employee personal characteristic data, organizational environment and digital transformation characteristics in the multidimensional data set as conditional variables, and the innovation assessment value as the result variable;

[0049] The fuzzy set operation unit is used to construct a relationship model between condition variables and result variables through fuzzy set operations. Its expression is defined as: R = f(Condition_1, Condition_2, ..., Condition_i), where R represents the result variable, Condition_i represents the i-th condition variable, and f is the membership function set in the fsQCA analysis; then, according to the result variable value under each condition combination, the configuration path is determined through the truth table. In the configuration path, the path that enhances innovation is set as the stimulation path, and the path that weakens innovation is set as the inhibition path.

[0050] It can be understood that in the data analysis module, the method of determining whether it is an excitation pathway or an inhibition pathway according to the analysis results of the fsQCA analysis is as follows:

[0051] Fuzzy set operation: Through fuzzy set operation, the relationship model between conditional variables and result variables is constructed. According to the membership function (f) in the relationship model, the value of the result variable under each condition combination is calculated.

[0052] Truth table analysis: Based on the results of fuzzy set operations, a truth table is constructed to list all combinations of conditions and their corresponding innovation assessment values.

[0053] Path identification:

[0054] Stimulation path: In the truth table, find the combination of conditions that leads to a significant increase in the innovation assessment value (that is, exceeding the preset threshold or significantly better than other combinations). These combinations are the stimulation paths.

[0055] Inhibition path: On the contrary, find out the combination of conditions that leads to a significant decrease in the innovation assessment value (that is, lower than the preset threshold or significantly worse than other combinations). These combinations are inhibition paths.

[0056] More specifically, the data analysis module includes variable construction: constructing each data in the multidimensional data set into conditional variables and result variables. Fuzzy set operation: constructing a relationship model between conditional variables and result variables through fuzzy logic processing, and calculating the result variable value under each condition combination. Truth table analysis: constructing a truth table based on the results of fuzzy set operations to identify the configuration path that leads to increased or decreased employee innovation.

[0057] like Figure 5 As shown, further preferably, the evaluation module includes a chart drawing unit and a graded evaluation unit;

[0058] The chart drawing unit is used to draw a radar chart to show the performance of employees' innovation under different combinations of conditions. Each dimension represents an evaluation indicator, and the radius or area of ​​the chart indicates the strength of innovation.

[0059] The grading assessment unit is used to conduct a comprehensive assessment based on the preset grading assessment system and the data in the chart to determine the enterprise health level.

[0060] Further preferably, the preset grading evaluation system includes:

[0061] A-level health: The corresponding chart results show that there are 60% or more excitation paths, and the average impact strength of the excitation paths exceeds 0.7;

[0062] B-level health: corresponds to 50%-60% of the excitation paths in the chart results, and the average impact strength of the excitation paths is between 0.5 and 0.7; at the same time, the inhibition paths do not exceed 20%, and the average impact strength is less than 0.3;

[0063] C-level health: corresponding to the coexistence of excitation pathway and inhibition pathway, the excitation pathway accounts for 40%-50%, and the average impact strength is less than 0.5; the inhibition pathway accounts for 10%-20%, and the average impact strength is higher than 0.4;

[0064] D-level health: more than 60% of the inhibition paths in the corresponding chart results have an average impact strength of more than 0.5, and less than 10% of the excitation paths have an average impact strength of less than 0.2.

[0065] More specifically, the evaluation module includes chart drawing: using radar charts and other visual tools to show the performance of employee innovation under different combinations of conditions. Grading evaluation: Based on the preset grading evaluation system, a comprehensive evaluation is conducted in combination with chart data to determine the level of corporate health.

[0066] Correspondingly, in the evaluation module, when it is implemented, a radar chart is first drawn to intuitively display the innovation performance under each evaluation indicator. Then, according to the hierarchical evaluation system, the ratio of the excitation path and the inhibition path and the average impact strength are calculated. Finally, the health of the enterprise is comprehensively evaluated and the corresponding grade judgment is given.

[0067] Further preferably, the evaluation system also includes a report generation module for automatically generating an enterprise health evaluation report including an excitation path, an inhibition path and improvement suggestions according to the fsQCA analysis results.

[0068] According to the above-mentioned embodiment of the present invention, the evaluation system realizes a comprehensive evaluation of employee innovation and the overall health of the enterprise by integrating multiple modules such as data collection, data analysis, evaluation and report generation. The system presets a data collection framework to ensure the comprehensiveness and consistency of the data, and accurately identifies the configuration paths that stimulate and inhibit employee innovation through fuzzy set operations and truth table analysis. The evaluation module uses visualization tools to display the evaluation results, combined with a hierarchical evaluation system, to provide enterprises with intuitive and accurate health judgments. The report generation module automatically summarizes the analysis results and outputs an evaluation report containing improvement suggestions to help enterprises optimize management and promote innovation. The system has smooth interaction, a friendly interface, supports regular data updates, ensures the timeliness and accuracy of the evaluation, and is an important tool for enterprises to enhance their competitiveness and achieve sustainable development.

[0069] It is obvious to those skilled in the art that the embodiments of the present invention are not limited to the details of the above exemplary embodiments, and that the embodiments of the present invention can be implemented in other specific forms without departing from the spirit or basic features of the embodiments of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the embodiments of the present invention is limited by the attached claims rather than the above description, so it is intended to include all changes that fall within the meaning and scope of the equivalent elements of the claims in the embodiments of the present invention. Any figure mark in the claims should not be regarded as limiting the claims involved. In addition, it is obvious that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units, modules or devices stated in the system, device or terminal claims can also be implemented by the same unit, module or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.

[0070] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments can still be modified, or some of the technical features can be replaced by equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. An enterprise health assessment system based on fsQCA analysis, characterized in that: Including data acquisition module, data analysis module and evaluation module: The data collection module is used to collect a multidimensional data set including employee personal characteristic data, organizational environment, digital transformation characteristics and employee innovation level according to a preset data collection framework; wherein the employee innovation level is based on the set project information and the innovation evaluation standards of each stage, and the innovation evaluation value is calculated by a preset evaluation model; The data analysis module is used to construct conditional variables and result variables based on the multidimensional data set, and identify the configuration path that leads to the enhancement or weakening of employee innovation through fuzzy set operations and truth table analysis; The evaluation module is used to draw an evaluation chart of the enhancement or weakening of the innovation ability of the digital transformation units and employees based on the configuration path, and to perform an enterprise health assessment in combination with the evaluation chart.

2. According to claim 1, the enterprise health assessment system based on fsQCA analysis is characterized by: The data acquisition module includes a first acquisition unit and a second acquisition unit; The first collection unit is used to collect employee personal characteristic data, organizational environment and digital transformation characteristics; The second collection unit is preset with an innovation evaluation benchmark library and an evaluation subunit, the innovation evaluation benchmark library contains innovation evaluation standards and benchmark data set according to different projects and project stages, and the evaluation subunit is built-in with an evaluation model based on the innovation evaluation benchmark library, and the evaluation model includes the following formula: innovation evaluation value = Σ(X*(Z / Y)); Among them, X is the weight of the i-th evaluation index, Z is the data collected in real time by the first collection unit, and Y is the benchmark data of the corresponding stage.

3. The enterprise health assessment system based on fsQCA analysis according to claim 2 is characterized by: The personal characteristic data includes the employee's age, gender, educational background and work experience information; the organizational environment includes the company's organizational structure, cultural atmosphere and management system information; the digital transformation characteristics include the company's digital transformation level.

4. The enterprise health assessment system based on fsQCA analysis according to claim 1 is characterized by: The data analysis module includes a variable construction unit and a fuzzy set operation unit; The variable construction unit is used to construct the employee personal characteristic data, organizational environment and digital transformation characteristics in the multidimensional data set as conditional variables, and construct the innovation assessment value as a result variable; The fuzzy set operation unit is used to construct a relationship model between condition variables and result variables through fuzzy set operations, and its expression is defined as: R = f (Condition_1, Condition_2, ..., Condition_i), wherein R represents the result variable, Condition_i represents the i-th condition variable, and f is the membership function set in the fsQCA analysis; then, according to the result variable value under each condition combination, the configuration path is determined through the truth table, in which the configuration path with enhanced innovation is set as the stimulation path, and the path with weakened innovation is set as the inhibition path.

5. The enterprise health assessment system based on fsQCA analysis according to claim 4 is characterized by: The evaluation module includes a chart drawing unit and a graded evaluation unit; The chart drawing unit is used to draw a radar chart to show the performance of employee innovation under different combinations of conditions, each dimension represents an evaluation indicator, and the radius or area of ​​the chart represents the strength of innovation; The grading assessment unit is used to perform a comprehensive assessment based on a preset grading assessment system and the data in the chart to determine the enterprise health level.

6. The enterprise health assessment system based on fsQCA analysis according to claim 5 is characterized by: The preset grading evaluation system includes: A-level health: corresponding to the chart results showing that there are 60% or more excitation paths, and the average impact strength of the excitation paths exceeds 0.7; B-level health: corresponds to 50%-60% of the excitation paths in the chart results, and the average impact strength of the excitation paths is between 0.5 and 0.7; at the same time, the inhibition paths do not exceed 20%, and the average impact strength is less than 0.3; C-level health: corresponding to the coexistence of excitation pathway and inhibition pathway, the excitation pathway accounts for 40%-50%, and the average impact strength is less than 0.5; the inhibition pathway accounts for 10%-20%, and the average impact strength is higher than 0.4; D-level health: corresponds to more than 60% of the inhibition paths in the chart results, the average impact strength of the inhibition paths exceeds 0.5, and less than 10% of the excitation paths, the average impact strength of the excitation paths is less than 0.

2.

7. The enterprise health assessment system based on fsQCA analysis according to claim 6 is characterized by: The evaluation system also includes a report generation module, which is used to automatically generate an enterprise health evaluation report including an excitation path, an inhibition path and improvement suggestions according to the fsQCA analysis results.

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