CN115222448A - Manufacturing industry enterprise market capacity quantitative analysis method and analysis model based on big data analysis - Google Patents
Manufacturing industry enterprise market capacity quantitative analysis method and analysis model based on big data analysis Download PDFInfo
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Abstract
The invention discloses a manufacturing industry enterprise market capacity quantitative analysis method and an analysis model based on big data analysis. The analysis method comprises the following steps: according to annual financial statement data of the company on the market of the stock A in the past years, carrying out industry subdivision on the industry of the company on the market of the stock A in the past years; determining the total market sales of the subdivided industries according to industry data published by the State statistics bureau and data published by the industry Association; the data of the manufacturing industry are integrated, the dimensionality reduction calculation is carried out through a factor analysis method, the market capacity quantitative analysis indexes of enterprises of the manufacturing industry are determined to be market share, sales growth rate, variation coefficient, market expansion index and customer management capacity, and a quantitative analysis model is established; further determining the weight coefficient of the quantitative analysis index, determining the influence factor of the quantitative analysis index, and obtaining the quantitative analysis index factor with the value range between 0 and 1 after normalization processing. The quantitative analysis model can well measure and evaluate the development status and the prospect of the enterprise.
Description
Technical Field
The application belongs to the technical field of data processing, particularly belongs to the technical field of enterprise financial management big data processing, and particularly relates to a manufacturing industry enterprise market capacity quantitative analysis method and an analysis model based on big data analysis.
Background
At present, most of domestic scholars carry out market capacity research and analysis of enterprise operation capacity by substituting financial data of domestic enterprises into foreign existing models for direct analysis, and neglects the difference between the application environment of the foreign models and the domestic market environment. Moreover, the financial accounting standards at home and abroad have larger difference, so that the analysis result of the market capacity of the domestic enterprises by utilizing the existing model is not reasonable, does not conform to the actual situation and has to be proved about the accuracy.
In the aspect of empirical analysis, the empirical research of China always tries to find uniform parameters to solve the problems of all enterprises, and the strain capacity of processing different enterprises and flexibly selecting respective parameters is lacked.
At present, the research on the market ability of the enterprise operation ability lacks theoretical guidance, most of the research variables are selected by a qualitative method, and the practical guidance significance of the research result on the enterprise development is seriously insufficient.
At present, the analysis methods of the market capacity of the enterprise operation capacity are different from each other, the selected financial indexes are not comprehensive enough, and each method has certain one-sidedness.
The market capacity of the enterprise operation capacity refers to the strategic position of an enterprise in the market segment, and whether the strategic resources and the unique capacity of the enterprise can meet the customer requirements of the market segment is analyzed and determined, so that the market capacity of the enterprise has important practical significance, and the problem to be solved urgently in the enterprise operation at present is also solved.
Disclosure of Invention
In view of the above, in one aspect, some embodiments disclose a manufacturing industry enterprise market capacity quantitative analysis method based on big data analysis, including:
s101, conducting industry subdivision on the industry of the company on the stock market in the past year according to annual financial statement data disclosed by the company on the stock market in the past year;
s102, determining the total market sales of the subdivided industries according to industry data published by the State statistics bureau and data published by the industry association;
s103, integrating enterprise customer management capacity data, sales data and related data obtained based on the sales data in the manufacturing industry, performing dimensionality reduction calculation through a factor analysis method, and determining the market capacity quantitative analysis indexes of the enterprise in the manufacturing industry as market share, sales growth rate, variation coefficient, market expansion index and customer management capacity;
s104, determining a weight coefficient of the quantitative analysis index;
s105, determining an influence factor of the quantitative analysis index, and obtaining the quantitative analysis index factor with a value range between [0 and 1] after normalization processing;
s106, establishing a quantitative analysis model, wherein the quantitative analysis model is expressed as follows:
wherein, X i Expressing quantitative analysis indexes, wherein i takes values of 1-5, and respectively expressing the market share, the sales growth rate, the variation coefficient, the market expansion index and the customer management capacity of the five quantitative analysis indexes; omega i Representing a quantitative analysis index X i A corresponding weight coefficient; f (X) i ) Quantitative analysis index X i The quantitative analysis index factor of (4); score represents the total index of quantitative analysis.
Some embodiments disclose a manufacturing industry enterprise market capacity quantitative analysis method based on big data analysis, wherein the market share is a proportion of sales of an enterprise in total sales of like products in the market, and the market share is expressed as:
in some embodiments, the manufacturing industry enterprise market capacity quantitative analysis method based on big data analysis has a sales increase rate that is a proportion of the current sales increase of the enterprise main business in the total market sales of the current market, expressed as:
in some embodiments of the method for quantitatively analyzing enterprise market capacity in the manufacturing industry based on big data analysis, the variation coefficient is the dispersion of enterprise income data, and is expressed as:
wherein S represents the business income standard deviation,
representing the average amount of revenue for the business.
Some embodiments disclose a manufacturing industry enterprise market capacity quantitative analysis method based on big data analysis, wherein the market expansion index is a ratio of the enterprise multi-stage sales growth rate to the enterprise multi-stage growth rate, and is expressed as:
in some embodiments, the customer management ability is a proportion of the number of high-quality users counted by the RFM model to the total number of users, and is expressed as:
some embodiments disclose a manufacturing industry enterprise market capacity quantitative analysis method based on big data analysis, which determines a weight coefficient of each quantitative analysis index in the manufacturing industry according to a field method, and a weight coefficient omega of market share 1 0.5, a weight coefficient ω of sales growth rate 2 0.3, coefficient of variation weight coefficient omega 3 0.1, a weight coefficient ω of the market expansion coefficient 4 0.05, weight coefficient ω of customer management ability 5 Is 0.05.
Some embodiments disclose a manufacturing industry enterprise market capacity quantitative analysis method based on big data analysis, wherein a normalization processing formula is as follows:
wherein z represents a quantitative analysis index, z min ，z max Respectively representing the minimum value and the maximum value of the quantitative analysis indexes of all listed companies in the industry of the enterprise, g (z) representing the normalization processing of the quantitative analysis indexes, and the value range being [0,1]]。
On the other hand, some embodiments disclose a manufacturing industry enterprise market capacity quantitative analysis model based on big data analysis, which is characterized in that the quantitative analysis model is expressed as:
wherein, X i Expressing quantitative analysis indexes, wherein i takes values of 1-5, and respectively expressing market share, sales growth rate, variation coefficient, market expansion index and customer management capacity of the five quantitative analysis indexes; omega i Representing a quantitative analysis index X i A corresponding weight coefficient; f (X) i ) Quantitative analysis index X i The quantitative analysis index factor of (4); score represents the total index of quantitative analysis.
Some embodiments disclose a manufacturing industry enterprise market capacity quantitative analysis model based on big data analysis, a weight coefficient omega of market share 1 0.5, a weight coefficient ω for sales growth rate 2 0.3, coefficient of variation weight coefficient omega 3 0.1, a weight coefficient ω of the market expansion coefficient 4 0.05, weight coefficient ω of customer management ability 5 And was 0.05.
The manufacturing industry enterprise market capacity quantitative analysis method based on big data analysis disclosed by the embodiment of the application combines annual financial statement data disclosed by an A stock market company, industry data published by the national statistical bureau and data published by an industry association to segment the industry and analyze financial data of the segment industry, performs dimension reduction calculation by a factor analysis method, determines manufacturing industry enterprise market capacity quantitative analysis indexes such as market share, sales growth rate, variation coefficient, market expansion index and customer management capacity, determines weight coefficients of the quantitative analysis indexes, and establishes a quantitative analysis model; the quantitative analysis model can well measure and evaluate the development status and the prospect of enterprises.
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FIG. 1 is a flow chart of a method for quantitatively analyzing the market capacity of enterprises in the manufacturing industry
Detailed Description
The word "embodiment" as used herein, is not necessarily to be construed as preferred or advantageous over other embodiments, including any embodiment illustrated as "exemplary". Unless otherwise indicated, the performance indicators tested in the examples herein were tested using methods routine in the art. It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure.
Unless defined otherwise, technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; other test methods and techniques not specifically mentioned in the present application are those commonly employed by those of ordinary skill in the art.
The terms "substantially" and "about" are used herein to describe small fluctuations. For example, they may refer to less than or equal to ± 5%, such as less than or equal to ± 2%, such as less than or equal to ± 1%, such as less than or equal to ± 0.5%, such as less than or equal to ± 0.2%, such as less than or equal to ± 0.1%, such as less than or equal to ± 0.05%. Numerical data represented or presented herein in a range format is used merely for convenience and brevity and thus should be interpreted flexibly to include not only the numerical values explicitly recited as the limits of the range, but also to include all the individual numerical values or sub-ranges encompassed within that range. For example, a numerical range of "1 to 5%" should be interpreted to include not only the explicitly recited values of 1% to 5%, but also include individual values and sub-ranges within the indicated range. Thus, included in this numerical range are individual values, such as 2%, 3.5%, and 4%, and sub-ranges, such as 1% to 3%, 2% to 4%, and 3% to 5%, etc. This principle applies equally to ranges reciting only one numerical value. Moreover, such an interpretation applies regardless of the breadth of the range or the characteristics being described.
In this document, including the claims, conjunctions such as "comprising," including, "" carrying, "" having, "" containing, "" involving, "" containing, "and the like are understood to be open-ended, i.e., to mean" including but not limited to. Only the connection words of 'composed of' 8230; '8230'; 'composed of' 8230 ';' are closed connection words.
In the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present disclosure. It will be understood by those skilled in the art that the present application may be practiced without some of these specific details. In the examples, some methods, means, instruments, apparatuses, etc. known to those skilled in the art are not described in detail in order to highlight the subject matter of the present application.
On the premise of no conflict, the technical features disclosed in the embodiments of the present application may be combined at will, and the obtained technical solution belongs to the content disclosed in the embodiments of the present application.
In some embodiments, as shown in fig. 1, the method for quantitative analysis of market capacity of manufacturing industry enterprise based on big data analysis comprises:
s101, conducting industry subdivision on the industry of the company on the stock market in the past year according to annual financial statement data disclosed by the company on the stock market in the past year; generally, companies on the market in stock A cover various industries of national economy, the characteristics of the industries are different, the industries are subdivided, and the financial statement data of the companies in the subdivided industries are classified, summarized and analyzed, so that the subdivided industries are conveniently and accurately researched; the industry subdivision is generally carried out according to the classification basis of the national institute of statistics and industry association, so that the enterprise information data issued by the national institute of statistics and industry association can be kept consistent, and reasonable data analysis is carried out; while subdividing the industry, screening the enterprises to which the subdivided industry belongs, so that the enterprises are reasonably affiliated to the subdivided industry category, each enterprise in the subdivided industry has reasonable contribution to the overall condition of the industry, and the industry information and the enterprise information reasonably reflect the actual condition of the stock market A;
s102, determining the total market sales of the subdivided industries according to industry data issued by the State statistics office and data issued by industry associations; based on the industry subdivision result and the enterprise classification result of the company listed in the stock A market and in combination with data issued by the national statistical agency and the industry association, the total market sales of the subdivision industry can be determined, the market sales data of each enterprise in the subdivision industry can also be obtained, and the industry status of each enterprise in the subdivision industry and the market status of products in the past year;
s103, integrating enterprise customer management capacity data, sales data and related data obtained based on the sales data in the manufacturing industry, performing dimensionality reduction calculation by a factor analysis method, determining the market capacity quantitative analysis indexes of the enterprise in the manufacturing industry as market share, sales growth rate, variation coefficient, market expansion index and customer management capacity, and establishing a quantitative analysis model; generally, enterprise management capacity data, business turnover, sales growth rate, market share, variation coefficient, market expansion coefficient, net profit, profit growth rate, receivable accounts, receivable bills, business income-sales cost ratio and the like of enterprises in the manufacturing industry are important financial data, but the importance degree of each data is different from the association degree of other data, and considering that the quantitative analysis of all financial data on the enterprise market capacity can cause the influence factors to have overhigh dimension and increased analysis difficulty, and the influence factors are associated with each other, so that the influence factors are not convenient to reasonably control, and the quantitative analysis result loses the actual reference value and the prediction significance; the applicant performs dimensionality reduction calculation on the multi-dimensional data, and finally determines quantitative analysis indexes of five dimensionalities, namely market share, sales growth rate, variation coefficient, market expansion index and customer management capacity through a factor analysis method;
s104, determining a weight coefficient of the quantitative analysis index; establishing a weight coefficient of the quantitative analysis index by adopting a Delphi method based on the determined five-dimensional quantitative analysis index, generally, randomly inviting hundreds of related industry experts and entrepreneurs to participate in investigation questionnaires, scoring the influence of the five-dimensional quantitative analysis index on the aspect of enterprise market capacity, and then calculating by adopting an analytic hierarchy process according to the investigation result of the questionnaires to obtain the weight coefficient corresponding to the five-dimensional quantitative analysis index of each questionnaire; further, the weight coefficients of the five-dimensional quantitative analysis indexes of all questionnaires are subjected to arithmetic mean respectively, and finally the respective weight coefficients of the five-dimensional quantitative analysis indexes are obtained;
s105, determining the influence factors of the quantitative analysis indexes, and obtaining the influence factors with the value range between 0 and 1 after normalization processing;
s106, carrying out quantitative analysis on the enterprise market capacity, and establishing a quantitative analysis model according to the generalized additive model based on five-dimensional quantitative analysis indexes, wherein the quantitative analysis model is expressed as follows:
wherein, X i Expressing quantitative analysis indexes, wherein i takes values of 1-5, and respectively expressing the market share, the sales growth rate, the variation coefficient, the market expansion index and the customer management capacity of the five quantitative analysis indexes; omega i Indicating quantitative analysis index X i A corresponding weight coefficient; f (X) i ) Quantitative analysis index X i The quantitative analysis index factor of (4); score represents the total index of quantitative analysis.
Specifically, the quantitative analysis indexes of the market capacity of enterprises in the manufacturing industry are determined to be five dimensions of market share, sales growth rate, variation coefficient, market expansion index and customer management capacity, and the total quantitative analysis indexes are expressed as follows:
Score＝ω 1 f (market share)) + ω 2 f (sales growth rate) + ω 3 f (coefficient of variation) + ω 4 f (market expansion index) + omega 5 f (customer management ability)
Some embodiments disclose a manufacturing industry enterprise market capacity quantitative analysis method based on big data analysis, and a weight coefficient omega of market share 1 0.5, sales growth rateWeight coefficient ω of (c) 2 0.3, coefficient of variation weight coefficient omega 3 0.1, a weight coefficient ω of the market expansion coefficient 4 0.05, weight coefficient ω of customer management ability 5 And was 0.05.
Quantitative analysis index
The market share is the proportion of the sales of the enterprise in the total sales of the same products in the market, the market share is the share of the products of the enterprise in the market, namely the control capacity of the enterprise on the market, and the enterprise can obtain a certain form of monopoly in the process of not much expanding the market share of the enterprise, so that monopoly profit can be brought, and a certain competitive advantage can be kept. Generally, market share is expressed as:
the sales increase rate is the proportion of the current sales increase of the business of the enterprise in the total sales of the market in the upper period. The sales growth rate indicates the increase and decrease of business income of the enterprise compared with the current period, and is an important index for evaluating the growth status and development ability of the enterprise. The sales growth rate is expressed as:
the variation coefficient is the dispersion of the income data of the enterprise, and is a statistic for measuring the variation degree or deviation degree of each observation value in the data, and the smaller the variation coefficient is, the smaller the deviation degree is, the smaller the risk is; conversely, the greater the coefficient of variation, the greater the degree of deviation and the greater the risk. The coefficient of variation is expressed as:
wherein S represents the business income standard deviation,
representing the average amount of revenue for the business. Generally, a coefficient of variation of less than 15% is a small variation, a coefficient of variation of 15-35% is a medium variation, a coefficient of variation of 35-100% is a strong variation, and a coefficient of variation of more than 1 is an ultra-strong variation.
The market expansion index is a risk index, is used for measuring the expansion condition of the enterprise market capacity relative to the whole subdivided industry, and can be expressed by the ratio of the multi-stage sales growth rate of the enterprise to the multi-stage growth rate of the industry, and the specific calculation formula is as follows:
generally, the market expansion index measures the expansion condition of the market capacity of the enterprise relative to the whole segment industry or the expansion condition of the benchmarking company in the segment industry, and if the market expansion index is greater than 1, the market expansion speed of the enterprise can be considered to be higher than that of the whole segment industry or the benchmarking company; if the market expansion index is less than 1, the market expansion speed of the enterprise is lower than that of the whole segment industry or the benchmarking company; if the market expansion index is equal to 1, the market expansion speed of the enterprise can be considered to be the same as that of the whole segment industry or the benchmarking company.
The customer management capacity is the proportion of the high-quality user number counted by the RFM model in the total user number, and is expressed as:
the RFM model is a model widely used in a plurality of analysis modes in the field of customer relationship management, is an important tool and means for measuring customer value and customer profit creating capability, and comprehensively describes the value condition of a customer through three indexes of time of last consumption of Recency, the height of customer consumption Frequency and the size of customer consumption money Monetary. Based on the three indexes, the customers can be classified; for example, a client with a recent consumption time, a high consumption frequency and a high consumption amount can be attributed as an important value client; the customers who have long consumption time recently but high consumption frequency and high consumption amount can belong to the customers to be kept, possibly the loyal customers who do not exist for a period of time, and the enterprise needs to actively keep contact; recently, customers who consume in a relatively short time and have high consumption amount but low consumption frequency can belong to important development customers, and the customers have low loyalty, but have potential and need to be developed in a key way; recently, customers who consume for a long time and a low frequency but consume money for a long time can be attributed to important saving customers, and such customers may be customers who will be lost or are lost by the enterprise, and should take saving measures. In general, the customer management ability factor is obtained through simulation calculation of three indexes, and can objectively reflect the customer management ability of an enterprise in the segment industry to which the enterprise belongs.
Normalization of quantitative analysis indicators
The market capacity quantitative analysis indexes of enterprises in the manufacturing industry have different index dimensions of market share, sales growth rate, variation coefficient, market expansion index and customer management capacity, so that in order to facilitate calculation and expression by using the same analysis model, normalization processing can be carried out on each quantitative analysis index, the data of the quantitative analysis indexes are subjected to linear transformation and mapped into an interval [0,1], and dimensionless factors uniformly positioned in the interval are obtained.
As an alternative embodiment, the formula for performing normalization processing on the quantitative analysis index is expressed as:
wherein z represents a quantitative analysis index of a business, z min ，z max Respectively representing the minimum value and the maximum value of the quantitative analysis indexes of all listed companies in the industry of the enterprise, g (z) representing normalization processing, and the value range being [0,1]]。
Market share normalization process
Wherein z1 represents the market share of the enterprise to be evaluated, and z1 min Represents the minimum value of market share in the manufacturing industry, z1 max The maximum value of the market share of the manufacturing industry is represented; if the market share z1 of the evaluated enterprise is not more than the minimum value z1 min If the f (z 1) is 0, if the market share z1 of the evaluated enterprise is larger than the maximum value z1 max If f (z 1) is 1; if the market share z1 of the evaluated enterprise is at the minimum value z1 min And maximum value z1 max The value of the market share factor f (z 1) is between 0 and 1; the market share is a positive index, and the larger the value of the general market share factor index is, the higher the enterprise score is.
Sales growth rate normalization process
Wherein z2 represents the sales growth rate of the enterprise being evaluated, z2 min Represents the minimum value of sales growth rate in the manufacturing industry, z2 max Represents the maximum value of the sales growth rate of the manufacturing industry; if the sales growth rate z2 of the evaluated enterprise is not more than the minimum value z2 min If the value of f (z 2) is 0, if the sales growth rate z2 of the evaluated enterprise is greater than the maximum value z2 max If f (z 2) is 1; if the sales growth rate z2 of the evaluated enterprise is at the minimum value z2 min And maximum value z2 max In between, the value of the sales growth rate factor f (z 2) is between 0 and 1; the sales growth rate is a positive index, and the higher the value of the general sales growth rate factor is, the higher the enterprise score is.
Coefficient of variation normalization
The variation coefficient is a negative index, the larger the value of the variation coefficient is, the smaller the index of an enterprise in the subdivision industry is, for the convenience of use, the variation coefficient is converted into a positive index in a modeling and is consistent with other indexes, and therefore, the variation coefficient is subtracted by 1 and is converted into the positive index; the normalization process of the coefficient of variation converted into the forward direction index is expressed as:
Wherein z3 represents the coefficient of variation of the enterprise to be evaluated, the coefficient of variation factor f (z 3) is a forward index, and generally, the larger the value of f (z 3), the higher the enterprise score is.
Market expansion index normalization process
Wherein z4 represents the market expansion index of the enterprise being evaluated, z4 min Denotes the minimum value of the market spread index in the manufacturing industry, z4 max The maximum value of the market expansion index of the manufacturing industry is represented; if the market expansion index z4 of the evaluated enterprise is not more than the minimum value z4 min If f (z 4) is 0, if the market expansion index z4 of the evaluated enterprise is larger than the maximum value z4 max If f (z 4) is 1; if the market expansion index z4 of the evaluated enterprise is at the minimum value z4 min And maximum value z4 max F (z 4) is between 0 and 1; the market expansion index is a forward index, and the larger the value of the general market expansion index is, the higher the enterprise score is.
Customer management capability normalization process
Wherein z5 represents the customer management capacity of the enterprise to be evaluated, and the value of a customer management capacity factor f (z 5) is between 0 and 1; the customer management ability is a forward index, and the larger the value of the general customer management ability factor index is, the higher the enterprise score is.
As an alternative embodiment, the manufacturing industry enterprise market capacity quantitative analysis model based on big data analysis is expressed as follows:
score =0.5f (market share) +0.3f (sales growth) +0.1f (coefficient of variation) +0.05f (market expansion index) +0.05f (customer management capacity).
The technical details are further illustrated in the following examples.
Example 1
2020-year market capacity quantitative analysis of white household appliance enterprise American electrical appliances
The financial data of the electric appliance in 2020 based on the America is subjected to quantitative analysis, and the financial data of each listed company in the white appliance industry in 2020 is subjected to statistical analysis to obtain:
maximum value of market share z1 in white goods industry max Is 0.31, minimum value z1 min Is 0, the market share z1 of the american appliance is:
the market share factor f (z 1) of the beautiful electric appliance obtained by the normalization processing is 1.
Maximum value of sales growth rate z2 in the white goods industry max Is 0.5172, minimum value z2 min Is-0.9798, and the sales growth rate z2 of the American electrical appliance is:
the sales growth rate factor f (z 2) of the beautiful electric appliance obtained by the normalization processing is 0.67;
in the white household appliance industry, the coefficient of variation factor f (z 3) of the American electrical appliance is as follows:
maximum value of market expansion index z4 in white appliance industry max 30.04, minimum value of market expansion index z4 min Is-0.53, and the market spread index z4 of the American appliance is:
the market expansion index factor f (z 4) of the beautiful electric appliance obtained by normalization treatment is 0.1;
in the white household appliance industry, a customer management ability index z5 is subjected to analog calculation to obtain a customer management ability index factor f (z 5) as follows:
the final market capacity quantitative analysis total index of the 2020 American household appliance is 0.8145, and the calculation formula is as follows:
S core ＝0.5×1+0.3×0.67+0.1×0.75+0.05×0.1+0.05×x0.67＝0.8145
example 2
2020-year market capacity quantitative analysis of white household appliance enterprise and Hisense household appliances
Quantitative analysis is carried out on financial data of the maritime home appliance in 2020, statistical analysis is carried out on financial data of various listed companies in the white home appliance industry in 2020, and the statistical analysis result is obtained by referring to embodiment 1:
the market share z1 of the household appliance for the WeChat is as follows:
the market share factor f (z 1) of the household appliance for hyacinths obtained by the normalization processing is 0.17.
The sales growth rate z2 of the maritime home appliances is as follows:
the sales growth rate factor f (z 2) of the hyacinths household electrical appliance is 0.69 after normalization processing;
the coefficient of variation influence factor f (z 3) of the household appliance for the WeChat is as follows:
the market expansion index z4 of the household appliance for the WeChat is as follows:
the market expansion index factor f (z 4) of the Hessian household appliance is obtained through normalization treatment and is 0.04;
the customer management ability index z5 is subjected to analog calculation, and the customer management ability index factor f (z 5) of the maritime home appliance is obtained as follows:
finally, the total market capacity quantitative analysis index of the maritime communication household appliance in 2020 is 0.4, and the calculation formula is as follows:
S core ＝0.5×0.17+0.3×0.69+0.1×0.77+0.05×0.04+0.05×0.67＝0.4
example 3
2020-year market capacity quantitative analysis of white household appliance enterprise grapple appliances
Based on 2020 financial data of the Gelier electrical appliance, quantitative analysis is carried out, 2020 financial report data of various listed companies in the white appliance industry are statistically analyzed, and the statistical result is obtained by referring to embodiment 1:
the market share z1 of the lattice force electric appliance is as follows:
the market share factor f (z 1) of the grignard appliance obtained by the normalization processing is 0.58.
The sales growth rate z2 of the Grignard appliance is:
the sales growth rate factor f (z 2) of the grid power electric appliance is 0.56 through normalization processing;
the coefficient of variation influence factor f (z 3) of the lattice force electric apparatus is as follows:
the market expansion index z4 of the grignard appliance is:
the market expansion index factor f (z 4) of the grid power electrical appliance obtained by normalization processing is 0.09;
the client management ability index z5 is subjected to simulation calculation, and the grid power electric appliance client management ability index factor f (z 5) is obtained as follows:
finally, the total market capacity quantitative analysis index of the Geli electric appliance in 2020 is 0.57, and the calculation formula is as follows:
S core ＝0.5×0.58+0.3×0.56+0.1×0.74+0.05×0.09+0.05×0.67＝0.57
example 4
2020-year market capacity quantitative analysis of boss electrical appliances of white household electrical appliance enterprises
Based on 2020 financial data of boss electrical appliances, quantitative analysis is carried out, 2020 financial report data of various listed companies in the white appliance industry is statistically analyzed, and the statistical result is obtained by referring to embodiment 1:
the market share z1 of the boss electrical appliance is as follows:
and the market share factor f (z 1) of the boss electrical appliance is obtained to be 0.03 through normalization processing.
The sales growth rate z2 of the boss electrical appliance is:
the sales growth rate factor f (z 2) of the boss electrical appliance is 0.69 after normalization processing;
the coefficient of variation influence factor f (z 3) of the boss electrical appliance is as follows:
the market expansion index z4 of the boss electrical appliance is as follows:
the market expansion index factor f (z 4) of the boss electrical appliance obtained by normalization processing is 0.05;
the client management ability index z5 is subjected to simulation calculation, and the client management ability index factor f (z 5) of the boss electrical appliance is obtained as follows:
finally, the total market capacity quantitative analysis index of the 2020 boss electrical appliance is 0.34, and the calculation formula is as follows:
S core ＝0.5×0.03+0.3×0.69+0.1×0.82+0.05×0.05+0.05×0.67＝0.34
the quantitative analysis total indexes and company actual data statistical results of electric appliances, weChat electric appliances and electric appliances of the American society in 2020 are listed in the following table 1:
TABLE 1 Total index of quantitative analysis of enterprise market ability, company actual data statistics
As can be seen from table 1, in comparison with sales of enterprises, the four home appliances are ranked in order as beautiful electric appliances, lattice electric appliances, hyacing electric appliances and boss electric appliances, the sales of the four home appliances are greatly different, and the turnover of the beautiful electric appliance ranked first is 35 times of the turnover of the boss electric appliance ranked fourth; comparing the growth rates of business income and business income ratios of enterprises, ranking the four household electrical appliances of the enterprise sequentially as a Hitachi household electrical appliance, a boss electrical appliance, a beautiful electrical appliance and a Grignard electrical appliance, and ranking the fourth Grignard electrical appliance as a negative growth, wherein the growth rate of the first Hitachi household electrical appliance and the fourth Grignard electrical appliance is different by 44%; comparing by using the coefficient of variation factors, and ranking sequentially by the boss electrical appliance, the glad electrical appliance, the beautiful electrical appliance and the Haixin electrical appliance, wherein the four electrical appliances are not very different in enterprises; comparing with market expansion index factors, ranking sequentially as American household appliances, hisense appliances, boss appliances and Grignard appliances, wherein the first American appliance is 2.5 times of the fourth Grignard appliance; from the results, although the sales can reflect the market status of the enterprise as a whole, influence of other indexes is ignored, the overall evaluation of the enterprise market capacity is unreasonable, the weaknesses of the enterprise in some aspects cannot be reflected, the overall development evaluation of the enterprise is unfavorable, the points of the contemporaneous business income growth rate, the coefficient of variation factor, the market expansion index factor and the like are different, and the overall market capacity of the enterprise cannot be reflected reasonably and completely;
compared with the total index score of quantitative analysis, the ranks of the four household electrical enterprises are sequentially beautiful electrical appliances, strong electrical appliances, haixin electrical appliances and boss electrical appliances, and the total index of quantitative analysis between the four household electrical enterprises has smaller difference amplitude. The overall development situation of the beautiful electric appliance with the highest total index score is analyzed quantitatively; the differences between the second-ranked powerful electrical appliances and the Haixin electrical appliances and the boss electrical appliances are not big, but the differences of the three electrical enterprises in other indexes are big, and the three electrical enterprises respectively have advantages and obvious weaknesses. Therefore, the total quantitative analysis index obtained based on the quantitative analysis index factor and the weight coefficient of the quantitative analysis index reasonably and scientifically reflects the market capacity of four household electrical enterprises.
From the above table 1, it can be further found that the total index score of the relative quantitative analysis is higher for the enterprises with high sales and fast business income increase. In contrast, when the sales amount is low but the business acceleration is fast, the total index of quantitative analysis can obtain a higher score. Therefore, the quantitative analysis model obtained by the manufacturing industry enterprise market capacity quantitative analysis method disclosed by the embodiment can well measure and evaluate the development status and the prospect of the enterprise. Meanwhile, the enterprise can be reasonably evaluated by combining the dominant factors and the weak indexes of enterprise development, so that the enterprise can make good use of the advantages and avoid the disadvantages, the investment is increased in the weak indexes, the enterprise shows a good overall development situation in the market capacity, the market capacity of the enterprise is improved, and the enterprise has guiding significance for the overall situation and the development prospect of the enterprise.
The manufacturing industry enterprise market capacity quantitative analysis method based on big data analysis disclosed by the embodiment of the application is used for subdividing the industry by combining annual financial statement data disclosed by a stock market marketing company A, industry data published by the national statistical bureau and data published by an industry association, analyzing financial data of the subdivided industry, performing dimensionality reduction calculation by a factor analysis method, determining manufacturing industry enterprise market capacity quantitative analysis indexes as market share, sales growth rate, variation coefficient, market expansion index and customer management capacity, determining weight coefficient of the quantitative analysis indexes, and establishing a quantitative analysis model; the quantitative analysis model can well measure and evaluate the development status and the prospect of enterprises.
The technical solutions and the technical details disclosed in the embodiments of the present application are only examples to illustrate the inventive concept of the present application, and do not limit the technical solutions of the present application, and all the conventional changes, substitutions, or combinations made on the technical details disclosed in the present application have the same inventive concept as the present application, and are within the protection scope of the claims of the present application.
Claims (10)
1. The manufacturing industry enterprise market capacity quantitative analysis method based on big data analysis is characterized by comprising the following steps:
s101, conducting industry subdivision on the industry of the company on the stock market in the past year according to annual financial statement data disclosed by the company on the stock market in the past year;
s102, determining the total market sales of the subdivided industries according to industry data issued by the State statistics office and data issued by industry associations;
s103, integrating enterprise customer management capacity data, sales data and related data obtained based on the sales data in the manufacturing industry, performing dimensionality reduction calculation by a factor analysis method, and determining market capacity quantitative analysis indexes of the enterprise in the manufacturing industry as market share, sales growth rate, variation coefficient, market expansion index and customer management capacity;
s104, determining a weight coefficient of the quantitative analysis index;
s105, determining the influence factors of the quantitative analysis indexes, and obtaining the quantitative analysis index factors with the value range between [0,1] after normalization processing;
s106, establishing a quantitative analysis model, wherein the expression is as follows:
wherein X i Expressing quantitative analysis indexes, wherein i takes values of 1-5, and respectively expressing the market share, the sales growth rate, the variation coefficient, the market expansion index and the customer management capacity of the five quantitative analysis indexes; omega i Representing quantitative analysisIndex X i A corresponding weight coefficient; f (X) i ) Quantitative analysis index X i The quantitative analysis index factor of (4); score represents the total index of quantitative analysis.
2. The manufacturing industry enterprise market capacity quantitative analysis method based on big data analysis according to claim 1, wherein the market share is a proportion of sales of an enterprise in total sales of like products in the market, and is expressed as:
3. the manufacturing industry enterprise market capacity quantitative analysis method based on big data analysis according to claim 1, wherein the sales growth rate is a proportion of the current sales growth of the enterprise main business in the total sales promotion of the market, and is expressed as follows:
4. the method as claimed in claim 1, wherein the variation coefficient is a dispersion of business income data expressed as:
wherein, S represents the standard deviation of business income,
representing the average amount of revenue for the business.
5. The method for quantitatively analyzing the market capacity of manufacturing industry enterprises based on big data analysis as claimed in claim 1, wherein the market expansion index is the ratio of the multi-stage sales growth rate of an enterprise to the multi-stage growth rate of the industry, expressed as:
6. the method for quantitatively analyzing the market capacity of the manufacturing industry enterprise based on big data analysis according to claim 1, wherein the customer management capacity is a proportion of the total number of users of high quality users counted by the RFM model, and is expressed as:
7. the method for quantitatively analyzing the market capacity of the manufacturing industry enterprises based on big data analysis as claimed in claim 1, wherein the weighting factor of each quantitative analysis index in the manufacturing industry, specifically, the weighting factor ω of the market share ratio is determined according to the field method 1 Is 0.5, the weight coefficient omega of the sales growth rate 2 Is 0.3, and the weight coefficient omega of the coefficient of variation 3 Is 0.1, the weight coefficient omega of the market expansion coefficient 4 0.05, weight coefficient omega of the customer management ability 5 Is 0.05.
8. The manufacturing industry enterprise market capacity quantitative analysis method based on big data analysis as claimed in claim 1, wherein the normalization processing formula is:
wherein z represents an amountIndex of chemical analysis, z min ，z max Respectively representing the minimum value and the maximum value of the quantitative analysis indexes of all listed companies in the industry of the enterprise, g (z) representing the normalization processing of the quantitative analysis indexes, and the value range being [0,1]]。
9. The manufacturing industry enterprise market capacity quantitative analysis model based on big data analysis is characterized in that the quantitative analysis model is expressed as follows:
wherein, X i Expressing quantitative analysis indexes, wherein i takes values of 1-5, and respectively expressing market share, sales growth rate, variation coefficient, market expansion index and customer management capacity of the five quantitative analysis indexes; omega i Representing a quantitative analysis index X i A corresponding weight coefficient; f (X) i ) Quantitative analysis index X i The quantitative analysis index factor of (2); score represents the total index of quantitative analysis.
10. The manufacturing industry enterprise market capability quantitative analysis model based on big data analysis of claim 9, wherein: a weight coefficient ω of the market share 1 Is 0.5, the sales growth rate has a weight coefficient omega 2 Is 0.3, and the weight coefficient omega of the coefficient of variation 3 Is 0.1, the weight coefficient omega of the market expansion coefficient 4 0.05, weight coefficient omega of the customer management ability 5 Is 0.05.
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| CN116822754B (en) * | 2023-08-30 | 2023-12-15 | 亿家商业科创产业管理(湖北)有限公司 | Data specification analysis system based on modularized classification of enterprise service items |
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