CN110705840A - Method for evaluating correlation between intellectual capital and enterprise profitability - Google Patents

Method for evaluating correlation between intellectual capital and enterprise profitability Download PDF

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CN110705840A
CN110705840A CN201910862446.8A CN201910862446A CN110705840A CN 110705840 A CN110705840 A CN 110705840A CN 201910862446 A CN201910862446 A CN 201910862446A CN 110705840 A CN110705840 A CN 110705840A
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王乐
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State Grid Shanghai Electric Power Co Ltd
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Abstract

The invention relates to an assessment method of correlation between intellectual capital and profitability of an enterprise, which is used for assessing the correlation between the intellectual capital and the profitability of electric power, thermal power production and supply industries, and comprises the following steps: s1, constructing a VAIC model; s2, collecting financial data of each enterprise in the area needing to be evaluated, and inputting the financial data into a VAIC model to obtain quantified intellectual capital IC; s3, constructing a correlation evaluation model, selecting an owner angle profit ability ROE and a manager angle profit ability ROA as explained variables, selecting an intellectual capital IC as an explained variable, and selecting a control variable; s4, inputting the explanation variable, the explained variable and the control variable into the correlation evaluation model respectively to obtain correlation coefficients between the explained variable, the explanation variable and the control variable, and outputting correlation relations and sizes reflecting the intelligent capital IC and the angle profitability ROE of the owner and the angle profitability ROA of the manager.

Description

Method for evaluating correlation between intellectual capital and enterprise profitability
Technical Field
The invention relates to development planning of enterprises in the power and heat production and supply industries, in particular to an assessment method for correlation between intellectual capital and profitability of the enterprises.
Background
The intellectual capital injects new power for the improvement of the profitability of the enterprise, and the practical influence of the intellectual capital on the performance of the enterprise also becomes the key problem of the enterprise operation and management. The relatively common knowledge of intellectual capital by the academic community is: owned by the organization, promoting the performance of the organization, intangible assets. In addition to the business world, intellectual capital is attracting the interests of both the scientific world and the trainees, leading to intense research on intellectual capital management.
Intellectual capital efficiency is important to the power, thermal production and supply industries, and the relationship between intellectual capital and profitability of the power, thermal production and supply industries is worth discussing. From the resource dimension and the competitiveness dimension, intellectual capital has a significant promoting effect on profitability of electricity, heat production and supply industries. From the competitive dimension, the resources of the power and heat production and supply industry have the characteristics of value, scarcity, uniqueness, organization and the like, so the resource of intellectual capital forms the core competitiveness of the power and heat production and supply industry, and therefore the intellectual capital plays an important role in improving the profitability of the power and heat production and supply industry.
From these two dimensions, it can be seen that intellectual capital can significantly contribute to profitability of the power, thermal production and supply industries. However, the research on intellectual capital and profitability of enterprises is mainly focused on businesses at present, the research on the correlation between the intellectual capital and the profitability of the electric power, thermal power production and supply industry is less, and because the businesses and the electric power, thermal power production and supply industry have many differences, no suitable method for evaluating the correlation between the intellectual capital and the profitability of the electric power, thermal power production and supply industry exists in the prior art, so that the related enterprises of the electric power, thermal power production and supply industry cannot reasonably utilize the intellectual capital to improve the profitability of the related enterprises.
Meanwhile, the development characteristics and the development conditions of the power and heat production and supply industries in different areas are different, so that a reliable assessment method for the correlation between the intellectual capital and the profitability of enterprises, which is suitable for the power and heat production and supply industries, is needed to be designed, and the assessment method is suitable for different areas.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide an assessment method for correlation between intellectual capital and profitability of an enterprise.
The purpose of the invention can be realized by the following technical scheme:
an assessment method of correlation between intellectual capital and profitability of an enterprise for assessing correlation between intellectual capital and profitability of electric power, thermal power production and supply industry, comprising the steps of:
s1, constructing a VAIC model;
s2, collecting financial data of each enterprise, inputting the financial data into a VAIC model, and obtaining quantified intellectual capital IC;
s3, constructing a correlation evaluation model, selecting an owner angle profit ability ROE and a manager angle profit ability ROA as explained variables, selecting an intellectual capital IC as an explained variable, and selecting a control variable;
and S4, inputting the explanation variable, the explained variable and the control variable into the correlation evaluation model respectively, and outputting correlation coefficients between the intellectual capital IC and the angle profit capability ROE of the owner and the angle profit capability ROA of the manager respectively.
Further, the VAIC model is used for quantifying intellectual capital IC, the quantified intellectual capital IC comprises human capital efficiency HCE, structural capital efficiency SCE and material capital efficiency CEE, the human capital efficiency HCE is used for measuring the appreciation efficiency of human capital, the material capital efficiency CEE is used for measuring the appreciation efficiency of material capital, and the structural capital efficiency SCE is used for measuring the appreciation efficiency of structural capital.
Further, the expression of intellectual capital IC is:
IC＝HCE+SCE+CEE
HCE＝VA/HC
VA＝I+R+T+D+HC
SCE＝(VA-HC)/VA
CEE＝VA/CE
wherein VA is enterprise increment, HC is worker pay, I is interest expenditure, R is increase of income reserved in the year, T is income tax fee, and D is dividend.
Further, the manager angular profitability ROA is expressed by an asset profitability, the asset profitability is obtained by a ratio of a net profit to a total asset, the owner angular profitability ROE is expressed by a net asset profitability, and the net asset profitability is obtained by a ratio of a net profit to an owner equity.
Further, the control variables in the correlation evaluation model include a macro-economic GDP G, an enterprise-scale ES, a material capital MC and a financing lever FL, wherein the macro-economic GDP G is represented by national production total value increase, the enterprise-scale ES is represented by a natural logarithm of business income, the material capital MC is represented by a fixed asset-to-total asset ratio, and the financing lever FL is represented by a liability-to-owner equity ratio.
Further, the correlation evaluation model performs correlation analysis between each two of the explained variable, the explained variable and the control variable to obtain a corresponding correlation coefficient, and the calculation formula of the correlation coefficient r is as follows:
Figure BDA0002200215490000032
Figure BDA0002200215490000033
wherein X and Y are two variables for correlation analysis respectively,
Figure BDA0002200215490000035
and
Figure BDA0002200215490000036
mean, l, of two variables which are each subjected to correlation analysisXXIs the sum of the squared deviations from the mean of the X,/YYIs the sum of the squares of the mean deviations of Y, lXYIs X and YSum of the mean squared differences between them.
Further, the evaluation method further comprises the steps of:
and S5, obtaining the correlation and significance level between each component of the intellectual capital IC and the manager angle profitability ROA and the owner angle profitability ROE respectively through variance testing and regression analysis.
Further, the step S5 specifically includes:
51) carrying out regression analysis on the intellectual capital IC and the manager angle profit ability ROA, the intellectual capital IC components and the manager angle profit ability ROA, the intellectual capital IC and the owner angle profit ability ROE and the intellectual capital IC components and the owner angle profit ability ROE respectively to obtain a regression result;
52) performing variance test according to the regression result, judging whether the corresponding regression analysis model has variance, if so, correcting the standard error by the white variance, taking the standard error as the regression result and executing the step 53), and if not, directly executing the step 53);
53) and obtaining the correlation and significance level among the variables according to the T value in the regression result.
Further, when the absolute value of the T value is greater than 2.50, the two variables are correlated at a significance level of 1%; when the absolute value of the value of T is greater than 2.00 and equal to or less than 2.50, the two variables are correlated at a significance level of 5%; when the value of T is greater than 1.60 absolute and equal to or less than 2.00, the two variables are related at a significance level of 10%.
Compared with the prior art, the invention has the following advantages:
1) through statistical analysis of a large number of samples, the data distribution of the owner angle profit ability ROE and the manager angle profit ability ROA in the power and heat production and supply industries is found to have large difference, so the invention provides the evaluation method of the intellectual capital and the profit ability of the power and heat production and supply industries, and the correlation between the intellectual capital and the profit ability can be evaluated more comprehensively and credibly by selecting the owner angle profit ability ROE and the manager angle profit ability ROA as the interpreted variables of the evaluation model;
2) through statistical analysis of a large number of samples, the minimum value of the material capital efficiency CEE is-0.937, the minimum value of the human capital efficiency HCE is-49.263, and the minimum value of the structural capital efficiency SCE is-59.652, which all present negative numbers in the electric power and thermal power production and supply industries show that the effect of utilizing the material capital, the human capital and the structural capital for the increment of the profitability of the enterprises in China is poor and needs to be further improved, so that the invention selects the human capital efficiency HCE, the structural capital efficiency SCE and the material capital efficiency CEE to quantify the intellectual capital IC so as to evaluate the correlation between the intellectual capital IC and the profitability of the electric power and thermal power production and supply industries and provide effective reference for utilizing the material capital, the human power and the structural capital for the increment of the profitability of the enterprises, the practicability is high;
3) according to the method, the financial data of the same type of enterprises in the area where the enterprises are located is used as a data basis to carry out corresponding evaluation, and after the correlation evaluation is finished, the correlation level between each component of the intellectual capital IC and the profitability of the enterprises is further evaluated through regression analysis.
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FIG. 1 is a schematic flow chart of the evaluation method of the present invention;
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. It is to be understood that the embodiments described are only a few embodiments of the present invention, and not all embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.
Examples
As shown in FIG. 1, the invention provides a method for evaluating the correlation between intellectual capital and profitability of an enterprise, which is used for evaluating the correlation between the intellectual capital and the profitability of electric power, thermal power production and supply industries, and comprises the following steps:
s1, constructing a VAIC model;
s2, collecting financial data of each enterprise, inputting the financial data into a VAIC model, and obtaining quantified intellectual capital IC;
s3, constructing a correlation evaluation model, selecting an owner angle profit ability ROE and a manager angle profit ability ROA as explained variables, selecting an intellectual capital IC as an explained variable, and selecting a control variable;
and S4, inputting the explanation variable, the explained variable and the control variable into the correlation evaluation model respectively, and outputting correlation coefficients between the intellectual capital IC and the angle profit capability ROE of the owner and the angle profit capability ROA of the manager respectively.
The variables of the correlation evaluation model are designed as follows:
(1) interpreting variables: intellectual capital IC.
The intellectual capital IC includes human capital efficiency HCE for measuring the appreciation efficiency of human capital, structural capital efficiency SCE for measuring the appreciation efficiency of utilizing physical capital, and physical capital efficiency CEE for measuring the appreciation efficiency of structural capital.
The expression intellectual capital IC is:
IC＝HCE+SCE+CEE
the expression of human capital efficiency HCE is:
HCE＝VA/HC
VA＝I+R+T+D+HC
wherein VA is enterprise increment, HC is worker pay, I is interest expenditure, R is increase of retained income of the year, T is income tax expense, and D is dividend;
the expression for structural capital efficiency SCE is:
SCE＝(VA-HC)/VA
the expression for the material capital efficiency CEE is:
CEE＝VA/CE
(2) the explained variables are: owner angle profitability ROE and manager angle profitability ROA.
The manager angular profitability ROA is represented by the asset profitability, which is obtained by the ratio of net profits to the total assets, the owner angular profitability ROE is represented by the net asset profitability, which is obtained by the ratio of net profits to the owner equity.
(3) Control variables: macroeconomy GDP G, business size ES, material capital MC, and financing leverage FL.
The macroeconomy GDP G is represented by national production gross value augmentation, the enterprise size ES by the natural logarithm of revenue, the material capital MC by the ratio of fixed assets to total assets, and the financing lever FL by the ratio of liability to owner equity.
In this example, an analytic statistical analysis of the interpretation variables, the interpreted variables, and the control variables was performed on 193 samples of power, heat production, and supply financial data, as shown in table 1:
TABLE 1 descriptive statistics of model variables
Figure BDA0002200215490000061
The minimum value of the material capital efficiency CEE is-0.937, the minimum value of the human capital efficiency HCE is-49.263, the minimum value of the structural capital efficiency SCE is-59.652, and negative numbers are presented, which indicates that the effect of utilizing material capital, human capital and structural capital for the profitability increment of enterprises in electric power, thermal power production and supply enterprises in China is poor and needs to be further improved, so the invention selects the human capital efficiency HCE, the structural capital efficiency SCE and the material capital efficiency CEE to quantify the intellectual capital IC so as to evaluate the correlation between the intellectual capital IC and the profitability of electric power, thermal power production and supply enterprises, and can provide effective reference for utilizing the material capital, the human capital and the structural capital for the profitability increment of the enterprises;
meanwhile, it can be seen that there is a large difference between the data distribution of the owner angle profitability ROE and the manager angle profitability ROA, and therefore it is necessary to select the owner angle profitability ROE and the manager angle profitability ROA as the interpreted variables of the evaluation model.
The correlation evaluation model carries out Pearson correlation analysis on the explained variable, the explained variable and the control variable pairwise to obtain a corresponding Pearson correlation coefficient, and the calculation formula of the Pearson correlation coefficient r is as follows:
Figure BDA0002200215490000071
Figure BDA0002200215490000072
Figure BDA0002200215490000074
wherein X and Y are two variables for correlation analysis respectively,
Figure BDA0002200215490000075
andmean, l, of two variables which are each subjected to correlation analysisXXIs the sum of the squared deviations from the mean of the X,/YYIs the sum of the squares of the mean deviations of Y, lXYIs the sum of the mean deviations between X and Y.
After obtaining the correlation coefficient between the intellectual capital IC and the owner angular profit capacity ROE and the manager angular profit capacity ROA, in order to further evaluate the correlation magnitude of the components constituting the intellectual capital IC to the owner angular profit capacity ROE and the manager angular profit capacity ROA, the embodiment further adds step S5, and the specific steps of step S5 include:
51) carrying out regression analysis on the intellectual capital IC and the manager angle profit ability ROA, the intellectual capital IC components and the manager angle profit ability ROA, the intellectual capital IC and the owner angle profit ability ROE and the intellectual capital IC components and the owner angle profit ability ROE respectively to obtain a regression result;
52) performing variance test according to the regression result, judging whether the corresponding regression analysis model has variance, if so, correcting the standard error by the white variance, taking the standard error as the regression result and executing the step 53), and if not, directly executing the step 53);
53) and obtaining the correlation and significance level among the variables according to the T value in the regression result.
When the absolute value of the T value is greater than 2.50, the two variables are related at a significance level of 1%; when the absolute value of the value of T is greater than 2.00 and equal to or less than 2.50, the two variables are correlated at a significance level of 5%; when the value of T is greater than 1.60 absolute and equal to or less than 2.00, the two variables are related at a significance level of 10%.
The embodiment processes the financial data of 97 enterprises related to the power and heat production and supply industries in a certain area, and evaluates the correlation between intellectual capital and the profitability of the enterprises by using the evaluation method provided by the invention, wherein the data processing tool is Stata 10.
The correlation coefficients between the explained variables, the explained variables and the controlled variables are obtained as shown in table 2:
TABLE 2 Pearson correlation coefficients for model variables
Figure BDA0002200215490000081
From table 2, it can be seen that the manager's angle profitability ROA and the owner's angle profitability ROE are positively correlated with intellectual capital IC for 97 enterprises in the selected area of this embodiment.
After the Pearson correlation coefficients between the variables are obtained, the regression analysis is performed again in this example, and the results are as follows:
(1) intellectual capital IC and manager angular profitability ROA
On the basis of the regression results, an heteroscedastic test was performed to yield Prob > chi2 ═ 0.0000. Therefore, there is heteroscedasticity in the model. The robust option is selected from the options of regression, and the regression results are shown in table 3:
TABLE 3 regression results of intellectual capital IC and manager Angle profitability ROA
Figure BDA0002200215490000082
Wherein, indicates a significant level of 1%, 5%, 10%, respectively.
And (3) combining the F value and the P value to judge the significance of the linear relation, wherein the Prob > F is 0.0000<0.0001, so that the confidence coefficient reaches more than 99.99%.
Regression results indicate that intellectual capital IC is positively correlated to manager angular profitability ROA at a significant level of 5%, i.e. intellectual capital has a significant positive promoting effect on manager angular profitability ROA for the electricity, heat production and supply industries. The manager-oriented profitability ROA is negatively correlated with the financing lever FL, the macro-economic GDP G at a significant level of 1%, and positively correlated with the enterprise-scale ES at a significant level of 1%.
(2) Human capital efficiency HCE, structural capital efficiency SCE and material capital efficiency CEE and manager angle profitability ROA
On the basis of the regression results, heteroscedastic tests were performed to yield Prob > chi2 ═ 0.7390, and therefore the model was free of heteroscedasticity. The regression results are shown in table 4:
TABLE 4 regression results of intellectual capital components and manager Angle profitability (ROA)
Figure BDA0002200215490000091
Wherein, indicates a significant level of 1%, 5%, 10%, respectively.
And (3) combining the F value and the P value to judge the significance of the linear relation, wherein the Prob > F is 0.0000<0.0001, so that the confidence coefficient reaches more than 99.99%.
From the regression results of the intellectual capital components and the manager-oriented profitability ROA, the human capital efficiency HCE is positively correlated with the manager-oriented profitability ROA at a significant level of 5%, the structural capital efficiency SCE is not significantly correlated with the manager-oriented profitability ROA, and the material capital efficiency CEE is positively correlated with the manager-oriented profitability ROA at a significant level of 1%. That is, it can be concluded from the evaluation results that, for the electric power, thermal power production and supply industries, the significant promoting effect of intellectual capital on the manager's angle profitability ROA mainly derives from material capital and human capital, and the influence of structural capital on the manager's angle profitability ROA is insignificant.
(3) Intellectual capital IC and owner angle profitability ROE
On the basis of the regression results, an heteroscedastic test was performed to find Prob > chi2 ═ 0.0000, and therefore heteroscedasticity existed in the model. The robust option is selected from the options for regression, and the regression results are shown in table 5:
TABLE 5 regression results of intellectual capital IC and owner's angular profitability ROE
Wherein, indicates a significant level of 1%, 5%, 10%, respectively.
And (3) combining the F value and the P value to judge the significance of the linear relation, wherein the Prob > F is 0.0000<0.0001, so that the confidence coefficient reaches more than 99.99%.
According to regression results, the intellectual capital IC is positively correlated with the owner's angular profitability ROE at a significant level of 1%, i.e. for the electricity, heat production and supply industry, the intellectual capital IC has a significant positive promoting effect on the owner's angular profitability ROE, and the owner's angular profitability ROE is negatively correlated with the financing lever FL, the macroscopic economy GDP G at a significant level of 1%, and is positively correlated with the enterprise-scale ES at a significant level of 1%.
(4) Human capital efficiency HCE, structural capital efficiency SCE, and material capital efficiency CEE vs. owner angle profitability ROE
On the basis of the regression results, an heteroscedastic test was performed to find Prob > chi2 ═ 0.0000, and therefore heteroscedasticity existed in the model. The robust option is selected from the options for regression, and the regression results are shown in table 6:
TABLE 6 regression results of intellectual capital components and owner Angle profitability ROE
Figure BDA0002200215490000102
Figure BDA0002200215490000111
Wherein, indicates a significant level of 1%, 5%, 10%, respectively.
And (3) combining the F value and the P value to judge the significance of the linear relation, wherein the Prob > F is 0.0000<0.0001, so that the confidence coefficient reaches more than 99.99%.
From the regression results of intellectual capital components and owner angle profitability ROE, it can be obtained that human capital efficiency HCE is positively correlated with owner angle profitability ROE at a significant level of 5%, and structural capital efficiency SCE, material capital efficiency CEE is positively correlated with owner angle profitability ROE at a significant level of 1%. That is, for the electricity, heat production and supply industries, the material capital, human capital and structural capital in intellectual capital all contribute significantly to the profitability ROE of the owner.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and those skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (9)

1. An assessment method of correlation between intellectual capital and profitability of an enterprise for assessing correlation between intellectual capital and profitability of electric power, thermal power production and supply industry, comprising the steps of:
s1, constructing a VAIC model;
s2, collecting financial data of each enterprise, inputting the financial data into a VAIC model, and obtaining quantified intellectual capital IC;
s3, constructing a correlation evaluation model, selecting an owner angle profit ability ROE and a manager angle profit ability ROA as explained variables, selecting an intellectual capital IC as an explained variable, and selecting a control variable;
and S4, inputting the explanation variable, the explained variable and the control variable into the correlation evaluation model respectively, and outputting correlation coefficients between the intellectual capital IC and the angle profit capability ROE of the owner and the angle profit capability ROA of the manager respectively.
2. The method according to claim 1, wherein the VAIC model is used for quantifying intellectual capital IC, the quantified intellectual capital IC comprises human capital efficiency HCE, structural capital efficiency SCE and material capital efficiency CEE, the human capital efficiency HCE is used for measuring the appreciation efficiency of human capital, the material capital efficiency CEE is used for measuring the appreciation efficiency of material capital, and the structural capital efficiency SCE is used for measuring the appreciation efficiency of structural capital.
3. The method for assessing the correlation between intellectual capital and profitability of an enterprise as claimed in claim 2, wherein the expression of intellectual capital IC is:
IC＝HCE+SCE+CEE
HCE＝VA/HC
VA＝I+R+T+D+HC
SCE＝(VA-HC)/VA
CEE＝VA/CE
wherein VA is enterprise increment, HC is worker pay, I is interest expenditure, R is increase of income reserved in the year, T is income tax fee, and D is dividend.
4. The method of claim 1, wherein the manager angular profitability ROA is expressed by an asset profitability, the asset profitability is expressed by a net profit to gross asset ratio, the owner angular profitability ROE is expressed by a net asset profitability, and the net asset profitability is expressed by a net profit to owner equity ratio.
5. The method of claim 4, wherein the control variables in the correlation model include a macro-economic GDP G, an enterprise size ES, a material capital MC and a financing lever FL, the macro-economic GDP G is represented by national production gross value increase, the enterprise size ES is represented by natural logarithm of business income, the material capital MC is represented by a fixed asset-to-gross asset ratio, and the financing lever FL is represented by a liability-to-owner equity ratio.
6. The method according to claim 5, wherein the correlation evaluation model performs correlation analysis between each of the explained variables, the explained variables and the controlled variables to obtain corresponding correlation coefficients, and the correlation coefficient r is calculated as:
Figure FDA0002200215480000021
Figure FDA0002200215480000022
wherein X and Y are two variables for correlation analysis respectively,
Figure FDA0002200215480000025
and
Figure FDA0002200215480000026
mean, l, of two variables which are each subjected to correlation analysisXXIs the sum of the squared deviations from the mean of the X,/YYIs the sum of the squares of the mean deviations of Y, lXYIs the sum of the mean deviations between X and Y.
7. The method for assessing the correlation between intellectual capital and profitability of an enterprise as claimed in claim 1, further comprising the steps of:
and S5, obtaining the correlation and significance level between each component of the intellectual capital IC and the manager angle profitability ROA and the owner angle profitability ROE respectively through variance testing and regression analysis.
8. The method for assessing the correlation between intellectual capital and profitability of an enterprise as claimed in claim 7, wherein said step S5 comprises:
51) carrying out regression analysis on the intellectual capital IC and the manager angle profit ability ROA, the intellectual capital IC components and the manager angle profit ability ROA, the intellectual capital IC and the owner angle profit ability ROE and the intellectual capital IC components and the owner angle profit ability ROE respectively to obtain a regression result;
52) performing variance test according to the regression result, judging whether the corresponding regression analysis model has variance, if so, correcting the standard error by the white variance, taking the standard error as the regression result and executing the step 53), and if not, directly executing the step 53);
53) and obtaining the correlation and significance level among the variables according to the T value in the regression result.
9. The method for assessing the correlation between intellectual capital and profitability of an enterprise of claim 8 wherein when the absolute value of T is greater than 2.50, the two variables are correlated at a significance level of 1%; when the absolute value of the value of T is greater than 2.00 and equal to or less than 2.50, the two variables are correlated at a significance level of 5%; when the value of T is greater than 1.60 absolute and equal to or less than 2.00, the two variables are related at a significance level of 10%.
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