Research on the core competitiveness of pharmaceutical listed companies based on fuzzy comprehensive evaluation

Abstract

The pharmaceutical industry is an important part of our national economy, which is the combination of traditional industry and modern industry. Medicine is an industry with high technology, high risk, high investment and high return, and has always been the focus of competition in developed countries. If Chinese pharmaceutical enterprises want to stand out in such fierce competition, they must find out the core competitiveness that fits their own development path. Based on the construction of the evaluation index system of the core competitiveness of the pharmaceutical industry, this study makes an empirical analysis of Hengrui pharmaceutical based on the fuzzy comprehensive evaluation method, discusses the reasons for the formation of its core competitiveness, and puts forward effective ways for listed companies in the pharmaceutical industry to enhance their core competitiveness.

Keywords

Core competitiveness pharmaceutical listed companies fuzzy comprehensive evaluation Hengrui pharmaceutical

1 Introduction

The pharmaceutical industry is closely related to national health, and is an important part of our national economy, is the combination of traditional industry and modern industry, and plays a huge role in promoting economic development and social progress. With the development of economy, the growth of world population, the acceleration of social aging, and the increasing awareness of health care, the global pharmaceutical market is expanding rapidly. In the face of its attractive good situation and high profits, large-scale multinational enterprises carry out a series of M&A and restructuring with strong capital and technical capabilities, and the products of major global pharmaceutical enterprises have also entered China. After China’s accession to WTO, many pharmaceutical enterprises in various countries have successively established production, R&D and sales bases in China, and the market control power has been continuously enhanced. Chinese pharmaceutical enterprises are facing internal and external problems, not only facing external mixed competition, but also facing internal competition challenges. Entering the 2019, the “The Belt and Road” strategy was comprehensively promoted. “The Plan of Health China 2030” was fully implemented, the demand in the international market was picking up, and the upgrading of domestic health consumption accelerated.

The core competitiveness of an enterprise is formed over a long period of time. It is unique and not easy to be imitated by competitors, and is the unique ability to realize customer value as well as self-worth. Once the pharmaceutical enterprises have the core competitiveness, they will develop towards stable, sustainable and long-term competitive advantage. The research on Hengrui pharmaceutical, a representative enterprise in China’s pharmaceutical industry, is conducive to the analysis of the reasons for the formation of the core competitiveness of pharmaceutical enterprises and a reasonable grasp of the development direction of Chinese pharmaceutical enterprises.

2 Literature review

Patel proposed patent measurement method, which uses patent data combined with PS-RTA two-dimensional distribution map to identify. Henderson constructed the index of architecture capability and component capability, and graded the competitiveness of the enterprise through interviews and data search.

Wei et al. [1] constructed a hierarchical grey evaluation model, using the grey theory to process the evaluator’s decentralized information into a weight vector describing different levels of grey, and then on this basis, the single value processing was carried out to get the comprehensive evaluation value of the core competitiveness level of the evaluated enterprise, and then the ranking of the core competitiveness level was compared. Zhu and Zhang [2] established the competitiveness evaluation index system that conforms to the characteristics of traditional Chinese medicine enterprises by using Delphi expert consultation method, obtained the competitiveness index system that conforms to the characteristics of traditional Chinese medicine enterprises by analyzing the opinion coordination coefficient of experts, and pointed out the key to the development of traditional Chinese medicine enterprises in China: improve the quality of traditional Chinese medicine products and protect and develop the existing traditional Chinese medicine secret recipe. Yi, et al. [3] Based on the performance scale of the balanced scorecard, from seven aspects of total operating revenue, market share, return on assets, net profit, products and services, employee satisfaction, customer satisfaction, etc., it can be divided into financial and non-financial advantages to comprehensively reflect the core competitiveness of enterprises. Lou [4] used the data envelopment method to evaluate Sinopec’s competitiveness in 2002-2015 by selecting indicators such as operating capacity and solvency. Qin [5] used AHP to give weight to the evaluation index system of core competitiveness of taxi software enterprises. Cao, et al. divided the core competitiveness of agricultural logistics enterprises into five levels: logistics service ability, innovation ability, logistics marketing ability, organization management ability and enterprise culture, and adopted the secondary evaluation to build the core of agricultural logistics enterprises Fuzzy comprehensive evaluation model of competitiveness. Through the fuzzy comprehensive evaluation model, the importance and advantages and disadvantages of each element of the core competitiveness of agricultural products logistics enterprises are well reflected, which points out the direction for the promotion of the core competitiveness of agricultural products logistics enterprises.

3 Establishing evaluation system

3.1 Evaluation index system of core competitiveness of the pharmaceutical industry

Referring to the research results on the evaluation of the core competitiveness of the pharmaceutical industry at home and abroad, the final evaluation index system of the core competitiveness of pharmaceutical enterprises is formed from four aspects of the functional scale, operation, innovation and growth of pharmaceutical enterprises. The specific indexes are shown in Table 1.

Table 1
Evaluation index system of core competitiveness of pharmaceutical enterprises

First level index Second level index Third level index

Index name Index interpretation

Evaluation index system of core competitiveness of pharmaceutical enterprises (U) Scale (U₁) Total assets (U₁₁) –

Main business income (U₁₂) –

Number of employees (U₁₃) –

Product line type (U₁₄) –

Management nature (U₂) Operating profit margin (U₂₁) Operating profit/total business income×100%

Return on equity (U₂₂) Net profit/average net assets* 100%

Cost profit margin (U₂₃) Total profit/total cost×100%

Earnings per share (U₂₄) Current net profit attributable to common shareholders/weighted average number of common shares outstanding in the current period

Turnover rate of total assets (U₂₅) Sales revenue/total assets

Annual net cash flow (U₂₆) Cash inflow –cash outflow

Turnover rate of accounts receivable (U₂₇) Net sales revenue of the current period/[(balance of accounts receivable at the beginning of the period + balance of accounts receivable at the end of the period)/2]

Quick ratio (U₂₈) Quick assets/current liabilities

Innovativeness (U₃) Book value of intangible assets (U₃₁) –

R &D investment proportion (U₃₂) –

Number of domestic invention patents (U₃₃) –

Core technology products (U₃₄) –

Growth (U₄) Profit growth rate of main business (U₄₁) [(profit of main business in the current period –profit of main business in the previous period)/profit of main business in the previous period]×100%

Net profit growth rate (U₄₂) (current net profit –previous net profit)/previous net profit* 100%

Growth rate of total assets (U₄₃) Total assets growth of the year/total assets at the beginning of the year×100%

Growth rate of net assets (U₄₄) [(closing net assets –opening net assets)/opening net assets]×100%

Net cash flow growth from operating activities (U₄₅) –

First level index	Second level index	Third level index
Evaluation index system of core competitiveness of pharmaceutical enterprises (U)	Scale (U₁)	Total assets (U₁₁)	–
		Main business income (U₁₂)	–
		Number of employees (U₁₃)	–
		Product line type (U₁₄)	–
	Management nature (U₂)	Operating profit margin (U₂₁)	Operating profit/total business income×100%
		Return on equity (U₂₂)	Net profit/average net assets* 100%
		Cost profit margin (U₂₃)	Total profit/total cost×100%
		Earnings per share (U₂₄)	Current net profit attributable to common shareholders/weighted average number of common shares outstanding in the current period
		Turnover rate of total assets (U₂₅)	Sales revenue/total assets
		Annual net cash flow (U₂₆)	Cash inflow –cash outflow
		Turnover rate of accounts receivable (U₂₇)	Net sales revenue of the current period/[(balance of accounts receivable at the beginning of the period + balance of accounts receivable at the end of the period)/2]
		Quick ratio (U₂₈)	Quick assets/current liabilities
	Innovativeness (U₃)	Book value of intangible assets (U₃₁)	–
		R &D investment proportion (U₃₂)	–
		Number of domestic invention patents (U₃₃)	–
		Core technology products (U₃₄)	–
	Growth (U₄)	Profit growth rate of main business (U₄₁)	[(profit of main business in the current period –profit of main business in the previous period)/profit of main business in the previous period]×100%
		Net profit growth rate (U₄₂)	(current net profit –previous net profit)/previous net profit* 100%
		Growth rate of total assets (U₄₃)	Total assets growth of the year/total assets at the beginning of the year×100%
		Growth rate of net assets (U₄₄)	[(closing net assets –opening net assets)/opening net assets]×100%
		Net cash flow growth from operating activities (U₄₅)	–

3.2 Establishing evaluation model

(1) Analytic hierarchy process

Using the analytic hierarchy process to analyze the evaluation index system, we can get the following pairwise comparison judgment matrix, and calculate the weight and eigenvalue of each pairwise comparison judgment matrix with Matlab software, the specific content is as following in Table 2.

Table 2
Pairwise comparison judgment matrix under scale indexes

Index U₁₁ U₁₂ U₁₃ U₁₄

U₁₁ 1 4 6 5

U₁₂ 1/4 1 2 3

U₁₃ 1/6 1/2 1 2

U₁₄ 1/5 1/3 1/2 1

Index	U₁₁	U₁₂	U₁₃	U₁₄
U₁₁	1	4	6	5
U₁₂	1/4	1	2	3
U₁₃	1/6	1/2	1	2
U₁₄	1/5	1/3	1/2	1

Let the comparison matrix in Table 2 be A₁. Then $A_{1} = [\begin{matrix} 1 & 4 & 6 & 5 \\ 1 / 4 & 1 & 2 & 3 \\ 1 / 6 & 1 / 2 & 1 & 2 \\ 1 / 5 & 1 / 3 & 1 / 2 & 1 \end{matrix}]$ . It solves A₁ in this paper, using the Matlab ATLAB software. The result shows that the maximum eigenvalue of matrix λ_max = 4.1077, the corresponding eigenvectors are (0.9082, 0.3050, 0.1766, 0.1209). Check the consistency, $CI = \frac{λ_{max} - 4}{4 - 1} = 0.0339$ , $CR = \frac{CI}{RI} = \frac{0.0339}{0.90} = 0.0377 < 0.1$ . Through the consistency test, the weight of the feature vector is w₁=(0.601, 0.202, 0.117, 0.080).

It can be seen from the above Table 3, A₂ is shown as following:

Table 3

Pairwise comparison judgment matrix under operational indexes

Index	U₂₁	U₂₂	U₂₃	U₂₄	U₂₅	U₂₆	U₂₇	U₂₈
U₂₁	1	1/2	4	1/2	6	4	5	7
U₂₂	2	1	4	6	8	5	7	8
U₂₃	1/4	1/4	1	2	4	1/2	4	6
U₂₄	1/5	1/6	1/2	1	2	1/3	4	5
U₂₅	1/6	1/8	1/4	1/2	1	1/3	3	4
U₂₆	1/4	1/5	2	3	3	1	4	5
U₂₇	1/5	1/7	1/4	1/4	1/3	1/4	1	1
U₂₈	1/7	1/8	1/6	1/5	1/4	1/5	1	1

$A_{2} = [\begin{matrix} 1 & 1 / 2 & 4 & 1 / 2 & 6 & 4 & 5 & 7 \\ 2 & 1 & 4 & 6 & 8 & 5 & 7 & 8 \\ 1 / 4 & 1 / 4 & 1 & 2 & 4 & 1 / 2 & 4 & 6 \\ 1 / 5 & 1 / 6 & 1 / 2 & 1 & 2 & 1 / 3 & 4 & 5 \\ 1 / 6 & 1 / 8 & 1 / 4 & 1 / 2 & 1 & 1 / 3 & 3 & 4 \\ 1 / 4 & 1 / 5 & 2 & 3 & 3 & 1 & 4 & 5 \\ 1 / 5 & 1 / 7 & 1 / 4 & 1 / 4 & 1 / 3 & 1 / 4 & 1 & 1 \\ 1 / 7 & 1 / 8 & 1 / 6 & 1 / 5 & 1 / 4 & 1 / 5 & 1 & 1 \end{matrix}]$ (1)

Using Matlab software to A₂, the result shows that the maximum eigenvalue of the matrix λ_max = 8.4648, the corresponding eigenvectors are (0.5047, 0.7595, 0.2322, 0.1535, 0.1061, 0.2708, 0.0616, 0.0507). Check the consistency, $CI = \frac{λ_{max} - 8}{8 - 1} = 0.0664$ , $CR = \frac{CI}{RI} = \frac{0.1757}{1.41} = 0.04579 < 0.1$ . Through the consistency test, the weight of the feature vector is W₂ = (0.236, 0.355, 0.109, 0.072, 0.049, 0.127, 0.029, 0.023).

It can be seen from the above Table 4, $A_{3} = [\begin{matrix} 1 & 1 / 6 & 1 / 5 & 1 / 8 \\ 6 & 1 & 2 & 1 / 5 \\ 5 & 1 / 2 & 1 & 1 / 6 \\ 8 & 5 & 6 & 1 \end{matrix}]$ . Using Matlab software to A₃, the result shows that the maximum eigenvalue of the matrix λ_max = 4.2588, the corresponding eigenvectors are (0.0621; 0.2868; 0.1873; 0.9374). Check the consistency, $CI = \frac{λ_{max} - 4}{4 - 1} = 0.0863$ , $CR = \frac{CI}{RI} = \frac{0.0863}{0.90} = 0.09585 < 0.1$ . Through the consistency test, the weight of the feature vector is W₃ = (0.042; 0.195; 0.127; 0.636).

Table 4

Pairwise comparison judgment matrix under innovation indexes

Index	U₃₁	U₃₂	U₃₃	U₃₄
U₃₁	1	1/6	1/5	1/8
U₃₂	6	1	2	1/5
U₃₃	5	1/2	1	1/6
U₃₄	8	5	6	1

It can be seen from the above Table 5, $A_{4} = [\begin{matrix} 1 & 4 & 1 / 2 & 5 & 6 \\ 1 / 4 & 1 & 1 / 4 & 2 & 3 \\ 2 & 5 & 1 & 5 & 6 \\ 1 / 5 & 1 / 2 & 1 / 5 & 1 & 2 \\ 1 / 6 & 1 / 3 & 1 / 6 & 1 / 2 & 1 \end{matrix}]$ . Using Matlab software to A₄, the result shows that the maximum eigenvalue of the matrix λ_max = 5.1395, the corresponding eigenvectors are (0.5818, 0.2090, 0.7698, 0.1327, 0.0873). Check the consistency, $CI = \frac{λ_{max} - 5}{5 - 1} = 0.0329$ , $CR = \frac{CI}{RI} = \frac{0.0329}{1.12} = 0.0294 < 0.1$ . Through the consistency test, the weight of the feature vector is W₄ = (0.327, 0.117, 0.432, 0.075, 0.049).

Table 5

Pairwise comparison judgment matrix under growth indexes

Index	U₄₁	U₄₂	U₄₃	U₄₄	U₄₅
U₄₁	1	4	1/2	5	6
U₄₂	1/4	1	1/4	2	3
U₄₃	2	4	1	5	6
U₄₄	1/5	1/2	1/5	1	2
U₄₅	1/6	1/3	1/6	1/2	1

The above content obtains the weights of each three-level indicator of the sub-criteria layer. Here, the weights of the two-level indicators of the criteria layer are also required. The specific method is the same as above. Two comparison matrices of the two-level indicators need to be constructed, and then the eigenvalues and eigenvectors of the comparison matrices need to be calculated through Matlab software, and the specific method is as follows:

From the above Table 6, it can be concluded that the judgment matrix of the criterion layer is $A = [\begin{matrix} 1 & 4 & 3 & 5 \\ 1 / 4 & 1 & 1 / 3 & 2 \\ 1 / 3 & 3 & 1 & 4 \\ 1 / 5 & 1 / 2 & 1 / 4 & 1 \end{matrix}]$ . Matlab software is used to solve the eigenvalue and eigenvector of A. The results show that the maximum eigenvalue of the matrix λ_max = 4.1145, the corresponding eigenvectors are (0.8689, 0.1592, 0.4381, 0.1223). Check the consistency, $CI = \frac{λ_{max} - 4}{4 - 1} = 0.0381$ , $CR = \frac{CI}{RI} = \frac{0.0381}{0.90} = 0.0424 < 0.1$ . Finally, the weight of the feature vector W = (0.535; 0.121; 0.269; 0.075) is obtained by normalization.

Table 6

Pairwise comparison judgment matrix under criterion level

Index	U₁	U₂	U₃	U₄
U₁	1	4	3	5
U₂	1/4	1	1/3	2
U₃	1/3	3	1	4
U₄	1/5	1/2	1/4	1

The weight summary table shown in the above Table 7 can be obtained by summarizing the weights of all indexes.

Table 7

Index weight summary

Target layer	Second level index	Weight	Third level index	Weight
Evaluation index system of core competitiveness of pharmaceutical enterprises (U)	Scale (U₁)	0.535	Total assets (U₁₁)	0.601
			Main business income (U₁₂)	0.202
			Number of employees (U₁₃)	0.117
			Product line type (U₁₄)	0.080
	Management nature (U₂)	0.121	Operating profit margin (U₂₁)	0.236
			Return on equity (U₂₂)	0.355
			Cost profit margin (U₂₃)	0.109
			Earnings per share (U₂₄)	0.072
			Turnover rate of total assets (U₂₅)	0.049
			Annual net cash flow (U₂₆)	0.127
			Turnover rate of accounts receivable (U₂₇)	0.029
			Quick ratio (U₂₈)	0.023
	Innovativeness (U₃)	0.269	Book value of intangible assets (U₃₁)	0.042
			R &D investment proportion (U₃₂)	0.195
			Number of domestic invention patents (U₃₃)	0.127
			Core technology products (U₃₄)	0.663
	Growth (U₄)	0.075	Profit growth rate of main business (U₄₁)	0.327
			Net profit growth rate (U₄₂)	0.117
			Growth rate of total assets (U₄₃)	0.432
			Growth rate of net assets (U₄₄)	0.075
			Net cash flow growth from operating activities (U₄₅)	0.049

(2) Fuzzy comprehensive evaluation

Fuzzy comprehensive evaluation is based on some concepts of fuzzy mathematics. Some evaluation methods are provided for practical comprehensive evaluation problems. Specifically, the fuzzy comprehensive evaluation is based on fuzzy mathematics. Based on the principle of fuzzy relation synthesis, this paper quantifies some factors which are not clear and easy to be quantified. It is a method to comprehensively evaluate the subordinate level of the evaluated things from multiple factors. In general, the specific process of fuzzy comprehensive evaluation is divided into the following steps, the specific contents are as follows:

Establish the evaluation index system. In fuzzy comprehensive evaluation, the index set of fuzzy evaluation should be determined first: U=u₁, u₂, ... , u_m, which means that the evaluated object can be evaluated from m aspects, that is, the evaluated object has m secondary indicators. The sub-indicator sets of each secondary indicator can be expressed as follows: u₁ = u₁₁, u₁₂, ... , u_1r, u₂ = u₂₁, u₂₂, ... , u_2r, u_m = u_m₁, u_m₂, ... , u_mr, indicating that the evaluated object can be evaluated from the above aspects.

Table 8

Corresponding table of meaning score and characterization

Degree of satisfaction	Excellent	Good	Commonly	Poor	Very poor
Score	90–100	70–90	50–70	30–50	10–30

Set up the comment set of evaluation index. Comment set refers to a linguistic description of the evaluation results of various levels of indicators. It refers to the set of comments given by the evaluator to each evaluation indicator. Generally, V is used to represent the comment set: V = V₁, V₂, ... , V_n. In this paper, the evaluation index set is summarized as follows: excellent; good; general; poor; very poor. The specific approach is to adopt five levels of attitude and assign a corresponding value of 0–100. The satisfaction score of service level and satisfaction level are corresponding, as shown in the Table 8 above.

In this paper, AHP is used to determine the weight of the evaluation index of the core competitiveness of pharmaceutical listed companies.

According to the frequency statistics of the evaluation level of each factor by the experts, the scores of the evaluation object on each index can be determined as p_i = p_i1, p_{i
₂}, ... , p_in (i = 1, 2, ... , n) after sorting them out. Besides p_ij can be expressed as the subordinate level of the evaluation object on the i^th index. A single factor fuzzy comprehensive evaluation matrix can be constructed for a row p_i. r represents the number of elements in the factor set x_i and n represents the number of elements in the indicator comment set.

Comprehensive evaluation. We can get the fuzzy comprehensive evaluation model of the core competitiveness of the pharmaceutical industry: B = A·P.

$\begin{matrix} A = (α_{1}, α_{2}, \dots, α_{m}), B = (b_1, b_2, \dots, b_n), \\ P = {| p_ij |}_{mn} \end{matrix}$ (2)

The elements in A represent the weight of the index, the elements in B represent the score of each rating, and the elements in P represent the proportion of the number of people in each rating. According to this formula, we can get the value of the fuzzy vector B of the service level.

4 Empirical study

4.1 Data collection and sorting

After the establishment of the evaluation index system of the core competitiveness of Listed Companies in the pharmaceutical industry, this paper collates the indicators of Hengrui pharmaceutical by consulting the annual report of Listed Companies in 2018 and searching online data, as shown in the above Table 9.

Table 9
Collection of evaluation index data of Hengrui pharmaceutical

Evaluating indicator Data Evaluating indicator Data

Total assets 223.61 billion yuan Turnover rate of accounts receivable 5 times

Main business income 174.18 billion yuan Quick ratio 6.83

Number of employees 21016 people Book value of intangible assets 2.73 billion yuan

Operating profit margin 26.39% R &D investment proportion 15.33%

Return on equity 20.61% Profit growth rate of main business 19.68%

Cost profit margin 33.40% Net profit growth rate 23.33%

Earnings per share 1.1 yuan/share Growth rate of total assets 23.96%

Turnover rate of total assets 0.7 times Growth rate of net assets 28.37%

Annual net cash flow –3.96 billion Yuan Net cash flow growth from operating activities 27.74 billion yuan

Evaluating indicator	Data	Evaluating indicator	Data
Total assets	223.61 billion yuan	Turnover rate of accounts receivable	5 times
Main business income	174.18 billion yuan	Quick ratio	6.83
Number of employees	21016 people	Book value of intangible assets	2.73 billion yuan
Operating profit margin	26.39%	R &D investment proportion	15.33%
Return on equity	20.61%	Profit growth rate of main business	19.68%
Cost profit margin	33.40%	Net profit growth rate	23.33%
Earnings per share	1.1 yuan/share	Growth rate of total assets	23.96%
Turnover rate of total assets	0.7 times	Growth rate of net assets	28.37%
Annual net cash flow	–3.96 billion Yuan	Net cash flow growth from operating activities	27.74 billion yuan

Table 10

Statistical table of questionnaire data

Index		Comment set and corresponding proportion
	Excellent	Good	Commonly	Poor	Very bad
Total assets (U₁₁)	0.4	0.4	0.1	0.1	0.0
Main business income (U₁₂)	0.5	0.2	0.2	0.1	0
Number of employees (U₁₃)	0.3	0.4	0.3	0.1	0
Product line type (U₁₄)	0.4	0.4	0.2	0	0
Operating profit margin (U₂₁)	0.7	0.2	0.1	0	0
Return on equity (U₂₂)	0.6	0.3	0.1	0	0
Cost profit margin (U₂₃)	0.5	0.4	0.1	0	0
Earnings per share (U₂₄)	0.6	0.2	0.2	0	0
Turnover rate of total assets (U₂₅)	0	0.1	0.7	0.2	0
Annual net cash flow (U₂₆)	0	0	0.3	0.4	0.3
Turnover rate of accounts receivable (U₂₇)	0.1	0.4	0.5	0	0
Quick ratio (U₂₈)	0.1	0.3	0.3	0.2	0.1
Book value of intangible assets (U₃₁)	0.5	0.3	0.2	0	0
R &D investment proportion (U₃₂)	0.7	0.2	0.1	0	0
Number of domestic invention patents (U₃₃)	0.4	0.3	0.2	0.1	0
Core technology products (U₃₄)	0.3	0.4	0.2	0.1	0
Profit growth rate of main business (U₄₁)	0.8	0.2	0	0	0
Net profit growth rate (U₄₂)	0.8	0.1	0	0.1	0
Growth rate of total assets (U₄₃)	0.5	0.3	0.2	0	0
Growth rate of net assets (U₄₄)	0.6	0.4	0	0	0
Net cash flow growth from operating activities (U₄₅)	0.1	0.2	0.4	0.3	0

The frequency statistics of 10 experts on the evaluation level of each factor are sorted out and normalized. The specific expert survey data results are shown in the Table 10 above.

4.2 Analysis process

According to the weight of each index obtained by AHP and the single factor fuzzy comprehensive evaluation matrix obtained by fuzzy comprehensive evaluation method, and then combined with the formula of the fuzzy comprehensive evaluation, the specific implementation steps are as follows:

$\begin{matrix} B_{1} = A_{1} \cdot P_{1} = [\begin{matrix} 0.601 & 0.202 & 0.117 & 0.080 \end{matrix}] \\ \cdot [\begin{matrix} 0.4 & 0.4 & 0.1 & 0.1 & 0 \\ 0.5 & 0.2 & 0.2 & 0.1 & 0 \\ 0.3 & 0.4 & 0.3 & 0.1 & 0 \\ 0.4 & 0.4 & 0.2 & 0 . & 0 \end{matrix}] \\ = [\begin{matrix} 0.409 & 0.360 & 0.152 & 0.092 & 0 \end{matrix}] \end{matrix}$ (3)

$\begin{matrix} G_{1} = B_{1} * V^{T} = [\begin{matrix} 0.409 & 0.360 & 0.152 & 0.092 & 0 \end{matrix}] \\ \cdot [\begin{matrix} 95 & 80 & 60 & 40 & 20 \end{matrix}]^{T} = 80.46 \end{matrix}$ (4)

$\begin{matrix} B_{2} = A_{2} P_{2} = \\ [\begin{matrix} 0.236 & 0.355 & 0.109 & 0.072 & 0.049 & 0.127 & 0.029 & 0.023 \end{matrix}] \\ \cdot [\begin{matrix} 0.7 & 0.2 & 0.1 & 0 & 0 \\ 0.6 & 0.3 & 0.1 & 0 & 0 \\ 0.5 & 0.4 & 0.1 & 0 & 0 \\ 0.6 & 0.2 & 0.2 & 0 & 0 \\ 0 & 0.1 & 0.7 & 0.2 & 0 \\ 0 & 0 & 0.3 & 0.4 & 0.3 \\ 0.1 & 0.4 & 0.5 & 0 & 0.0 \\ 0.1 & 0.3 & 0.3 & 0.2 & 0.1 \end{matrix}] \\ = [\begin{matrix} 0.481 & 0.235 & 0.178 & 0.065 & 0.040 \end{matrix}] \end{matrix}$

$\begin{matrix} G_{2} = B_{2} * V^{T} = [\begin{matrix} 0.481 & 0.235 & 0.178 & 0.065 & 0.040 \end{matrix}] \\ \cdot {[\begin{matrix} 95 & 80 & 60 & 40 & 20 \end{matrix}]}^{T} = 78.5 \end{matrix}$ (5)

$\begin{matrix} B_{3} = A_{3} \cdot P_{3} = [\begin{matrix} 0.042 & 0.195 & 0.127 & 0.663 \end{matrix}] \\ \cdot [\begin{matrix} 0.5 & 0.3 & 0.2 & 0 & 0 \\ 0.7 & 0.2 & 0.1 & 0 & 0 \\ 0.4 & 0.3 & 0.2 & 0.1 & 0 \\ 0.3 & 0.4 & 0.2 & 0.1 & 0 \end{matrix}] \\ = [\begin{matrix} 0.407 & 0.355 & 0.186 & 0.079 & 0 \end{matrix}] \end{matrix}$ (6)

$\begin{matrix} G_{3} = B_{3} * V^{T} = [\begin{matrix} 0.407 & 0.355 & 0.186 & 0.079 & 0 \end{matrix}] \\ \cdot {[\begin{matrix} 95 & 80 & 60 & 40 & 20 \end{matrix}]}^{T} = 81.39 \end{matrix}$ (7)

$\begin{matrix} B_{4} = A_{4} \cdot P_{4} = [\begin{matrix} 0.327 & 0.117 & 0.432 & 0.075 & 0.049 \end{matrix}] \\ \cdot [\begin{matrix} 0.8 & 0.2 & 0 & 0 & 0 \\ 0.8 & 0.1 & 0 & 0.1 & 0 \\ 0.5 & 0.3 & 0.2 & 0 & 0 \\ 0.6 & 0.4 & 0 & 0 & 0 \\ 0.1 & 0.2 & 0.4 & 0.3 & 0 \end{matrix}] \\ = [\begin{matrix} 0.621 & 0.247 & 0.106 & 0.026 & 0 \end{matrix}] \end{matrix}$ (8)

$\begin{matrix} G_{4} = B_{4} * V^{T} = [\begin{matrix} 0.621 & 0.247 & 0.106 & 0.026 & 0 \end{matrix}] \\ \cdot {[\begin{matrix} 90 & 70 & 50 & 30 & 10 \end{matrix}]}^{T} = 86.16 \end{matrix}$ (9)

$\begin{matrix} P = [\begin{matrix} B_{1} & B_{2} & B_{3} & B_{4} \end{matrix}] \\ = [\begin{matrix} 0.409 & 0.360 & 0.152 & 0.092 & 0 \\ 0.481 & 0.235 & 0.178 & 0.065 & 0.040 \\ 0.407 & 0.355 & 0.186 & 0.079 & 0 \\ 0.621 & 0.247 & 0.106 & 0.024 & 0 \end{matrix}] \end{matrix}$ (10)

$\begin{matrix} B_{4} = A_{4} \cdot P_{4} = [\begin{matrix} 0.327 & 0.117 & 0.432 & 0.075 & 0.049 \end{matrix}] \\ \cdot [\begin{matrix} 0.8 & 0.2 & 0 & 0 & 0 \\ 0.8 & 0.1 & 0 & 0.1 & 0 \\ 0.5 & 0.3 & 0.2 & 0 & 0 \\ 0.6 & 0.4 & 0 & 0 & 0 \\ 0.1 & 0.2 & 0.4 & 0.3 & 0 \end{matrix}] \\ = [\begin{matrix} 0.433 & 0.335 & 0.161 & 0.080 & 0.001 \end{matrix}] \end{matrix}$

Based on the above analysis, the comprehensive evaluation score of Hengrui pharmaceutical’s core competitiveness can be obtained. Here, the score value selects the corresponding middle number, namely

$\begin{matrix} G = B * V^{T} = [\begin{matrix} 0.433 & 0.335 & 0.161 & 0.080 & 0.001 \end{matrix}] \\ \cdot [\begin{matrix} 95 & 80 & 60 & 40 & 20 \end{matrix}]^{T} = 80.90 \end{matrix}$ (11)

4.3 Result analysis

Through the above empirical analysis, we can conclude that Hengrui pharmaceutical is a relatively competitive pharmaceutical enterprise. In fact, Hengrui pharmaceutical is the leading enterprise in China’s pharmaceutical industry, which has a certain scale, but the enterprise does not continue to take scale as its core competitiveness promotion direction. In 2018, Hengrui pharmaceutical will invest 15.33% of its business income in R&D, which is more than many enterprises in the same industry. Under the background of high risk and high return in the pharmaceutical industry, such high investment combined with correct decision-making of the leadership will inevitably cause great changes in the core competitiveness of the enterprise. Combined with the rapid development momentum of Hengrui pharmaceutical in recent years, it is proved that the core competitiveness evaluation model adopted in this paper is feasible to a certain extent.

5 Conclusions

As a new capital intensive and technology-intensive enterprise, biomedical enterprises should pay more attention to the cultivation of the core competitiveness of enterprises when dealing with a complex environment and gaining competitive advantage. Therefore, the evaluation of the core competitiveness of biomedical enterprises is the objective demand of the theoretical and business circles. This paper analyzes the conceptual model, based on literature research, initially formed the index system of the evaluation of the core competitiveness of pharmaceutical enterprises, and finally determined the index system through empirical analysis. Next, the paper paves the way for the basic knowledge of fuzzy mathematics, such as fuzzy set and fuzzy operation, and then discusses the steps of fuzzy comprehensive evaluation in detail, in which the weight is determined by the method of tomographic analysis. Finally, through the annual report data of Hengrui pharmaceutical, the case analysis is carried out to verify the operability of the index system, and the core competitiveness of Hengrui pharmaceutical is evaluated by fuzzy comprehensive evaluation, and the comprehensive evaluation value is obtained, which is consistent with the stock trend of the company.

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