Organizational quality specific immune evaluation model based on optimal combination weighting

Abstract

Facing the increasingly fierce competition in the current society, enterprises must take corresponding measures to deal with the dynamic environment. In order to improve their competitive advantages, they must pay more attention to the quality of their product, activate the organizational quality specific immune. This study takes organizational quality specific immune as the entry point to construct the organizational quality specific immune evaluation indicator system, and establishes three criteria layers of organizational quality monitoring and cognition, organizational quality defense, clearance and repair, and organizational quality memory and immune stabilization, there are a series of indicators under each criterion layer. Then this study constructs the organizational quality specific immune evaluation model based on optimal combination weight methods, and the optimal combination weighting model is introduced to conduct empirical study of evaluating organizational quality specific immune with 15 large-scale manufacturing enterprises in eastern regions. And the pros and cons of the organizational quality specific immune status of 15 large-scale manufacturing enterprises in eastern regions are finally obtained. The organizational quality specific immune evaluation indicators, organizational quality specific immune evaluation model based on optimal combination weighting methods and empirical analysis results of organizational quality specific immune evaluation based on optimal combination weighting methods and model will provide theoretical significance and practical enlightenment for enhancing organizational quality performance and organizational health.

Keywords

Optimal combination weighting organizational quality specific immune organizational quality specific immune evaluation model empirical analysis

1. Introduction

With the current rapid development of economy and technology, it has had a two-way impact on human society. Along with the rapid development and change of human society, it has also brought a series of problems, including the survival pressure facing enterprises. Faced with a turbulent market environment and uncertain survival factors, competition among enterprises is becoming increasingly fierce. And how can companies improve their own competitive advantages? In addition to responding to the changing needs of customers and the varied prices of suppliers, the quality of corporate products is particularly important. In recent years, catastrophic incidents caused by product quality issues have emerged endlessly. Sudan Red Incident, Clenbuterol Incident, Fuyang Milk Powder Incident, and Dye Bun Event, especially the Sanlu Milk Powder Incident, have caused great influences throughout the country and the world. From the series of events that have occurred so far, it can be seen that the quality of the company’s products is the top priority and has to attract the attention of the academic and business circles.

This type of situation in the enterprise is very similar to the biological organism’s ability to survive in the face of various uncertain environments [1, 2]. Every biological organism is almost exposed to the environment of countless bacteria and viruses, but it can still survive in a healthy way [3, 4]. The reason is that each biological organism has an immune system that protects its health [1, 5]. It can be seen from biological organisms that businesses can also generate corresponding immune systems in many environments similar to bacteria and viruses [6, 7]. In recent years, domestic scholars have conducted related research on organizational immune and organizational quality specific immune, and conducted in-depth research using PP method and fit method, and have achieved certain results. However, there is currently a lack of discussion on the evaluation of organizational quality specific immune using the optimal combination weighting models from the established organizational quality specific immune indicators systems. This study constructs the organizational quality specific immune evaluation indicator system and organizational quality specific immune evaluation model based on the theoretical framework of organizational quality specific immune and optimal combination weight methods, and further carries out empirical study of organizational quality specific immune evaluation with 15 large-scale manufacturing enterprises in eastern regions. The purposes and goals of this study is to evaluate and measure the organizational quality specific immune based on the organizational quality specific immune evaluation indicator system and organizational quality specific immune evaluation model from the perspectives of organizational immune, organizational quality immune, organizational quality specific immune, and in order to find out the evaluation indicators that affect the organizational quality specific immune and continuously enhance organizational quality performance and organizational health.

2. Organizational quality specific immune indicator evaluation system construction

“Quality is the life of an enterprise” has gradually penetrated into the hearts of everyone, and organizational quality immune has naturally become the core of organizational immune. Some scholars have pointed out the definition of organizational immune, namely manufacturing enterprises identify and recognize external and internal dissidents, eliminate the factors that cause corresponding threats, and generates memories for them, thereby maintaining the overall security and development of enterprises [6, 7]. It is pointed out that organizational quality immune can be divided into organizational quality non-specific immune and organizational quality specific immune. Among them, organizational quality non-specific immune refers to the innate general immune behavior of enterprises against aliens generated internally and externally. It is generally the first line of defense for enterprises to deal with risk factors, including organizational structure, organizational culture and system rules [1]. Organizational quality specific immune refers to the environment of the company’s organizational structure, organizational culture, and system rules, and carries out specific immune behaviors. It belongs to the second line of defense for enterprises to deal with risk factors, including organizational quality monitoring and cognition, quality defense, clearance and repair, and organizational quality memory and immune stabilization [1].

2.1 Organizational quality monitoring and cognition

Organizational quality monitoring and cognition are derived from the organization’s perception of the uncertain factors that arise inside and outside the enterprise. Lv and Wang believe that when organizations face a complex and changing environment, when a certain stimulus is generated, the organization needs to respond accordingly at the first time, and this requires the organization to have a certain perception of the stimulus so that it can take corresponding action [3]. In addition, organizational surveillance is divided into external surveillance and internal surveillance. It is necessary to avoid the enterprise from recognizing harmful factors as beneficial factors, and also to prevent the enterprise from evading beneficial factors as harmful factors, thereby maintaining the development of the enterprise [1].

2.2 Organizational quality defense, clearance and repair

Lv and Wang indicate that defense is a response made after monitoring and cognition of the external and internal environment. It is also a mistake made by individuals that must be collectively avoided [3]. Zhao believes that organizational immune defense is to effectively remove harmful factors existing inside and outside the enterprise under the premise of effective surveillance and cognition, and is divided into several functions of “mutation-selection-coordination-clearance” [4].

Table 1
Organizational quality specific immune evaluation indicator system

Serial number	Criterion layer	Indicator layer	G1 weight	G2 weight	Entropy weight	Deviation weight	Combination weight
1	Organizational quality	Organizational quality external	0.040	0.078	0.037	0.052	0.058
	monitoring and cognition	environment monitoring
2		Organizational quality internal	0.044	0.073	0.038	0.053	0.057
		environment monitoring
3		Organizational quality internal	0.049	0.068	0.040	0.052	0.056
		activities and behavior monitoring
4		Value judgement	0.058	0.058	0.054	0.055	0.056
5		Cognitive motivation	0.076	0.053	0.059	0.054	0.057
6		Cognitive diversity	0.106	0.049	0.013	0.056	0.053
7	Organizational quality	Leadership value	0.023	0.057	0.053	0.055	0.052
8	defense, clearance and	Employee involvement	0.026	0.054	0.036	0.050	0.047
9	repair	Supplier relationship management	0.028	0.051	0.019	0.045	0.042
10		Customer demand	0.034	0.048	0.034	0.052	0.046
11		Product design	0.044	0.041	0.046	0.055	0.048
12		Process management	0.062	0.038	0.061	0.065	0.055
13		Statistical control and feedback	0.093	0.035	0.112	0.052	0.058
14	Organizational quality	Learn	0.018	0.062	0.219	0.047	0.071
15	memory and immune	Recording	0.024	0.059	0.037	0.051	0.049
16	stabilization	Summary	0.031	0.055	0.034	0.051	0.048
17		Save	0.043	0.044	0.038	0.055	0.048
18		Spread and diffusion	0.065	0.040	0.034	0.051	0.046
19		Communication control and	0.103	0.037	0.037	0.049	0.049
		supervision

2.3 Organizational quality memory and immune stabilization

Lv and Wang believe that organizational memory is a summary and record of organizational surveillance and organizational defense, and the best results of immunization will ultimately be reflected in the organization, structure, and culture of the enterprise in order to enhance its development [1]. Yang and Wang believe that the most important thing for an enterprise is the coordination and cooperation between employees, machines, and technology. In addition, the basis for enterprises to achieve organizational quality immune memory is coordination and cooperation and employee motivation [6]. Shi et al. believe that enterprises should make employees themselves aware of the importance of organizational quality memory, motivate employees to be spontaneous in achieving organizational quality memory, and let them learn and improve independently to achieve the effect of improving corporate performance [7].

2.4 Organizational quality specific immune evaluation indicator system construction

(1)
Reflect the connotation of organizational quality monitoring and cognition through six indicators: organizational quality external environment monitoring, organizational quality internal environment monitoring, organizational quality internal activities and behavior monitoring, value judgment, cognitive motivation, and cognitive diversity.
(2)
Reflect the connotation of organizational quality defense, clearance and repair through seven indicators: leadership value, employee involvement, supplier relationship management, customer demand, product design, process management, statistical control and feedback.
(3)
Reflect the connotation of organizational quality memory and immune stabilization through six indicators: learn, recording, summary, save, spread and diffusion, communication control and supervision.

To sum up, the evaluation indicator system of organizational quality specific immune is established, including three criteria of organizational quality monitoring and cognition, organizational quality defense, clearance and repair, organizational quality memory and immune stabilization, and a total of 19 indicators corresponding to organizational quality monitoring and cognition, organizational quality defense, clearance and repair, organizational quality memory and immune stabilization, as shown in Table 1.
3. Organizational quality specific immune evaluation model based on optimal combination weighting methods

3.1 Thoughts on organizational quality specific immune evaluation model construction

Meng and Li [8], Chen et al. [9], Chi et al. [10], Fan et al. [11], Chen et al. [12], Han and Yang [13], Yu et al. [14], Li et al. [15], Guo and Zhong [16], Meng and Li [17], Cai et al. [18], Xu and Guan [19], Li et al. [20], Zhang and Huang [21] have carried out the relevant concepts, frameworks, principles, steps, procedures and contents of the combination weighting methods. The thoughts on organizational quality specific immune evaluation model construction are as follows: (1) Scoring the organizational quality specific immune evaluation indicators; (2) Choose the single evaluation methods, namely G1 method, G2 method, entropy method and deviation method to weight the evaluation indicators; (3) Corresponding to different evaluation methods, calculate the corresponding weight coefficients that fuse and integrate the advantages of G1 method, G2 method, entropy method and deviation method, and finally form the optimal combination weighting methods and model, obtain the optimal combination weights; (4) Carry out empirical analysis of organizational quality specific immune evaluation, calculate the scores of the organizational quality specific immune evaluations of each manufacturing enterprise, and make out and ranks the orders of organizational quality specific immune of manufacturing enterprises, sort out the organizational quality specific immune status of each manufacturing enterprise.

G1 method and G2 method consider the importance and priority of the evaluation indicators, expound the priority relationships among evaluation indicators, and determine the each evaluation indicator weight subjectively, reflect the importance preferences of evaluation indicators. Entropy method can consider the uncertainty and certainty of the evaluation indicators, and objectively determines the weight of each evaluation indicator. Deviation method takes the deviation as the starting points, objectively determines the weight of each evaluation indicator, takes the evaluation indicators sequences of the actual research objects as the basic points, explores the differences and similarities among the actual evaluation indicators sequences of research objects as the actual points, sets the evaluation indicators sequences of the target research objects as the goal points, analyzes the similarities and differences among the evaluation indictors, expounds the identification and interpretation of the evaluation indicators, calculates the deviation values of the actual, target and overall mean values corresponding to all the evaluation indicators.

The optimal combination weighting methods integrate the main advantages of the subjective weighting methods and the objective weighting methods, avoid the disadvantages and limitations of the subjective weighting methods and the objective weighting methods, make good use of a variety of weighting methods to mutually verity and demonstrate the weights of the evaluation indicators, and ensures the subjectivity and objectivity of each weighting method of each evaluation indicator. Finally, the combination coefficients and adjustment coefficients are introduced, the subjective weights and objective weights are integrated to obtain the accurate weights of evaluation indicators, enhance the feasibility, effectiveness and operability of the optimal combination weight methods, apply the optimal combination weighting methods in the evaluation process of organizational quality specific immune. The applicability of the optimal combination weighting methods in the field of quality management is enhanced and improved, and the subjectivity and objectivity of optimal combination weighting methods are cross demonstrated and verified.

3.1.1 Determination of G1 weight

(1) Determine the order relationship between each evaluation indicator by $G1$ method;

(2) The ratio $r_{k}$ given by the experts to the degree of importance of the neighboring evaluation indicators, that is, rational assignment;

(3) The $G1$ weight $w_{m}$ corresponding to the $m$ indicator is:

$\displaystyle w_{m}=\left(1+\sum\limits_{k=2}^{m}{\prod r_{k}}\right)^{-1}$ (1)

(4) According to the weight of the $m$ indicator $w_{m}$ the weight of the $m-1,\ldots,3,2$ indicator is:

$\displaystyle w_{k-1}=r_{k}w_{k},k=m,m-1,\ldots,3,2$ (2)

Among them, $w_{k-1}$ is the weight of the $G1$ method corresponding to the $k-1$ indicator; $r_{k}$ is the rational value given by the expert.

3.1.2 Determination of G2 weight

(1) Use the $G2$ method to determine the order relationship between each evaluation indicator;

(2) The $x_{m}$ given by the expert is the least important indicator;

(3) The expert gives the ratio $a_{k}$ of other indicators $x_{k}$ to the least important indicator $x_{m}$ , that is, rational assignment;

(4) The $G2$ weight $w_{k}$ corresponding to the $k$ indicator is:

$\displaystyle w_{k}=a_{k}\left/\sum\limits_{k=1}^{m}{a_{k}}\right.$ (3)

Among them, $w_{k}$ is the weight of the $G2$ method corresponding to the $k$ indicator; $a_{k}$ is the rational value given by the expert; $m$ is the number of organizational quality specific immune evaluation indicators.

$G1$ method and $G2$ method are characterized by weighting indicators according to the subjective ranking method. The more important the indicators, the greater the weight.

3.1.3 Determination of entropy weights

(1) The entropy value of the $j$ indicator is $e_{j}$ , and its calculation formula is:

$\displaystyle e_{j}=-\frac{1}{\ln n}\sum\limits_{i=1}^{n}{f_{ij}}\ln(f_{ij})$ (4)

Among them, $e_{j}>0$ , $x_{ij}$ is the value of the $j$ indicator in the $i$ evaluation object $(i=1,2,\ldots,n;j=1,2,\ldots m)$ , $\sum\limits_{i=1}^{n}{x_{ij}}$ is the sum of the values of the $j$ indicator in all the evaluation objects; $f_{ij}$ is the $j$ indicator in the $i$ evaluation object. The characteristic proportion of each indicator, the formula is:

$\displaystyle f_{ij}=x_{ij}\left/\sum\limits_{i=1}^{n}{x_{ij}}\right.$ (5)

(2) The entropy weight corresponding to the $k$ indicator is:

$\displaystyle w_{k}=\frac{1-e_{j}}{n-\sum\limits_{i=1}^{n}{e_{i}}}=\frac{1+% \frac{1}{\ln(n)}\times\sum\limits_{i=1}^{n}{\left[x_{ik}\left/\sum\limits_{i=1% }^{n}\right.{x_{ik}}\right]\times\left[\ln\left(x_{ik}\left/\sum\limits_{i=1}^% {n}\right.{x_{ik}}\right)\right]}}{\sum\limits_{k=1}^{m}{\left\{1+\frac{1}{\ln% (n)}\times\sum\limits_{i=1}^{n}{\left[x_{ik}\left/\sum\limits_{i=1}^{n}\right.% {x_{ik}}\right]\times\left[\ln\left(x_{ik}\left/\sum\limits_{i=1}^{n}\right.{x% _{ik}}\right)\right]}\right\}}}$ (6)

The characteristic of entropy weighting is that for the evaluation indicator, the greater the difference between the values of the same evaluation indicator, the greater the weight.

3.1.4 Determination of deviation weights

(1) $w_{i}$ is the weight corresponding to the $i$ indicator, $w_{i}\geqslant 0$ ; $p_{ij}(i=1,2,\ldots,m;j=1,2,\ldots,n)$ is the normalized value of the $i$ indicator in the $j$ evaluation object; then the indicator corresponding to the $j$ evaluation object and other evaluation objects The deviation between the values is:

$\displaystyle F_{ij}(w)=\sum\limits_{i=1}^{m}{|p_{ij}w_{i}-p_{ik}w_{i}|},k=1,2% ,\ldots,n$ (7)

(2) The total deviation between all evaluation objects and other evaluation objects in the $i$ indicator is:

$\displaystyle F_{i}(w)=\sum\limits_{j=1}^{n}{F_{ij}}(w)=\sum\limits_{j=1}^{n}{% \sum\limits_{k=1}^{n}{|p_{ij}-p_{ik}|}}w_{i}$ (8)

(3) Based on the principle of maximizing deviation, the optimization model is:

$\displaystyle\max F(w)=\sum\limits_{i=1}^{m}{\sum\limits_{j=1}^{n}{\sum\limits% _{k=1}^{n}{|p_{ij}-p_{ik}|}}}w_{i}$ $\displaystyle\textit{s.t.}\left\{{\begin{array}[]{l}w_{i}\geqslant 0\\ \sum\limits_{i=1}^{m}{w_{i}^{2}=1}\\ \end{array}}\right.$ (9)

(4) The above optimization model is solved and normalized, and the weight of the deviation method is:

$\displaystyle w_{i}=\frac{\sum\limits_{j=1}^{n}{\sum\limits_{k=1}^{n}{|p_{ij}-% p_{ik}|}}}{\sum\limits_{i=1}^{m}{\sum\limits_{j=1}^{n}{\sum\limits_{k=1}^{n}{|% p_{ij}-p_{ik}|}}}}$ (10)

Among them, $\sum\limits_{j=1}^{n}{\sum\limits_{k=1}^{n}{|p_{ij}-p_{ik}|}}$ is the deviation obtained by subtracting the absolute values of the values of all the evaluation objects in the $i$ indicator and summing them up, which is $F_{i}$ ; $\sum\limits_{i=1}^{m}{\sum\limits_{j=1}^{n}{\sum\limits_{k=1}^{n}{|p_{ij}-p_{% ik}|}}}$ is the sum of the deviation of all indicators.

The weight of the deviation method is characterized by the ratio of the deviation of the $i$ indicator to the total deviation. The larger the weight is, the greater the weight is.

3.2 Optimal combination weights based on two factors

3.2.1 Calculation of optimal weights based on two factors

$w_{k}(k=1,2,3,4)$ is the weight obtained by $G1$ method, $G2$ method, entropy method, and deviation method, then the formula for calculating the combined weight is:

$\displaystyle w=\sum\limits_{k=1}^{l}{\alpha_{k}}w^{k}$ (11)

where $\alpha_{k}$ is the combination coefficient and $\sum\limits_{k=1}^{l}{\alpha_{k}}=1,x_{k}\geqslant 0$ .

3.2.2 Determination of combination weight coefficient

(1) The weighted score of each evaluation object and the minimum generalized distance of the ideal point are:

$\displaystyle\min\sum\limits_{i=1}^{n}{d_{i}}=\sum\limits_{i=1}^{n}{\sum% \limits_{j=1}^{m}{\sum\limits_{k=1}^{l}{\alpha_{k}}}}w_{j}^{k}(1-x_{ij})$ (12)

Among them, $d_{i}$ is the generalized distance between the formaldehyde of each evaluation object and the ideal point; $\alpha_{k}$ is the combination coefficient; $w_{j}^{k}$ is the weight of the $j$ indicator corresponding to the $k$ weighting method; $x_{ij}$ is the normalized value of the $j$ indicator of the $i$ evaluation object.

The advantage of obtaining the coefficient of the combined weight by the above formula is that the weighted score of each evaluation object and the minimum generalized distance of the ideal point are obtained, that is, the principle that the closer the distance to the ideal point is, the higher the score is.

(2) In order to reflect the consistency between the weighting results, we introduce the Jaynes maximum entropy principle, and establish the objective function on the basis of the smallest difference in weighting results, that is:

$\displaystyle\max H=-\sum\limits_{k=1}^{l}{\alpha_{k}}\ln\alpha_{k}$ (13)

The advantage of obtaining the combination weight coefficient by the above formula is that it avoids the single contribution of the method for determining the weight to the result of determining the combination weight, which also eliminates the problem that has no effect on the combination weight.

Based on the above factors, the objective function is established, which is:

$\displaystyle\min\mu\sum\limits_{i=1}^{n}{\sum\limits_{j=1}^{m}{\sum\limits_{k% =1}^{l}{\alpha_{k}}}}w_{j}^{k}(1-x_{ij})+(1-\mu)\sum\limits_{k=1}^{l}{\alpha_{% k}}\ln\alpha_{k}$ (14) $\displaystyle\textit{s.t.}\sum\limits_{k=1}^{l}{\alpha_{k}}=1,x_{k}\geqslant 0$

Among them, the parameter is used to represent the balance coefficient between two targets and $0<\mu<1$ . In this study, 0.5 is selected.

The combination coefficient $\alpha_{k}$ obtained according to the Lagrange function is:

$\displaystyle\alpha_{k}=\frac{\exp\left\{-\left[1+\mu\sum\limits_{i=1}^{n}{% \sum\limits_{j=1}^{m}{w_{j}^{k}}}(1-z_{ij})/(1-\mu)\right]\right\}}{\sum% \limits_{k=1}^{l}{\exp\left\{-\left[1+\mu\sum\limits_{i=1}^{n}{\sum\limits_{j=% 1}^{m}{w_{j}^{k}}}(1-z_{ij})/(1-\mu)\right]\right\}}}$ (15)

3.3 Organizational quality specific immune evaluation equation based on optimal combination weighting

The combined weight vector obtained by Eq. (11) is transposed to $W^{T}$ , and this is multiplied with the score $X$ of each indicator to obtain the score $R$ of the organizational quality specific immune evaluation. The calculation formula is:

$\displaystyle R=W^{T}\times X=(r_{1},r_{2},r_{3},\ldots,r_{n})$ (16)

By sorting the score $r_{i}(i=1,2,3,\ldots,n)$ of each evaluation object in the score $R$ , it is the ranking of the organizational quality specific immune status of each evaluation object.

4. Empirical analysis of organizational quality specific immune evaluation

4.1 Sample selection

This study selects 15 large-scale manufacturing enterprises in eastern regions as samples, and invites thirty middle-senior managers to score each indicator of the organizational quality specific immune of 15 large-scale manufacturing enterprises. This study makes out the questionnaires using the scales. The collecting data of the questionnaires of 15 large-scale manufacturing enterprises are through on-site interviews and on-site distributing questionnaires. The scales use Likert ways with the scoring of 1-7, 1-7 scales indicate disagree, more disagree, somewhat disagree, uncertain, somewhat agree, more agree, agree, the scoring results are shown in Table 2. All the proposed evaluation indicators are subjective, and the data of the subjective evaluation indicators derive from questionnaires, the Cronbach’s values are all higher than 0.7, the CITC values are all higher than 0.5, the KMO values are all higher than 0.7, the factor loadings and CR values are all higher than 0.6, the AVE values are all higher than 0.5, the scales have relatively good reliability and validity test, the evaluation indicators are accurately quantified.

Q ${}_{1}$ –Q ${}_{15}$ are 15 manufacturing enterprises respectively. P ${}_{1}$ –P ${}_{6}$ are the six indicators of organizational quality monitoring and cognition, namely organizational quality external environment monitoring, organizational quality internal environment monitoring, organizational quality internal activities and behavior monitoring, value judgment, cognitive motivation, and cognitive diversity. D ${}_{1}$ –D ${}_{7}$ are seven indicators of organizational quality defense, clearance, and repair, namely leadership value, employee involvement, supplier relationship management, customer demand, product design, process management, statistical control and feedback. M ${}_{1}$ –M ${}_{6}$ are six indicators of organizational quality memory and immune stabilization, namely learn, recording, summary, save, spread and diffusion, communication control and supervision.

Table 2
Organizational quality specific immune evaluation indicator scores of 15 large-scale manufacturing enterprises in eastern regions

Serial number	Indicator	Q ${}_{1}$	Q ${}_{2}$	Q ${}_{3}$	Q ${}_{4}$	Q ${}_{5}$	Q ${}_{6}$	Q ${}_{7}$	Q ${}_{8}$	Q ${}_{9}$	Q ${}_{10}$	Q ${}_{11}$	Q ${}_{12}$	Q ${}_{13}$	Q ${}_{14}$	Q ${}_{15}$
1	P ${}_{1}$	3	2	5	4	6	6	5	7	3	1	6	4	3	6	2
2	P ${}_{2}$	4	3	3	5	7	7	6	2	2	1	4	5	3	6	4
3	P ${}_{3}$	5	3	7	5	3	1	4	3	6	3	2	7	3	2	5
4	P ${}_{4}$	1	3	2	4	7	3	7	7	4	3	1	5	3	3	2
5	P ${}_{5}$	5	4	7	7	4	2	3	2	5	1	1	4	2	2	2
6	P ${}_{6}$	2	4	6	4	7	7	2	1	4	5	7	3	4	2	3
7	D ${}_{1}$	5	3	3	3	5	7	6	6	1	1	2	5	3	2	2
8	D ${}_{2}$	5	5	5	6	6	7	3	2	5	1	3	2	4	6	3
9	D ${}_{3}$	2	3	7	4	5	3	6	4	5	4	7	5	6	6	7
10	D ${}_{4}$	4	3	2	6	3	6	7	4	7	4	6	3	1	6	5
11	D ${}_{5}$	7	5	2	2	5	4	3	7	5	4	1	4	1	6	5
12	D ${}_{6}$	6	6	4	7	2	1	5	1	7	6	1	2	7	5	6
13	D ${}_{7}$	4	6	7	3	5	5	2	3	1	6	2	6	5	3	2
14	M ${}_{1}$	3	5	2	5	6	3	7	4	2	1	5	3	5	3	5
15	M ${}_{2}$	4	5	7	3	2	4	5	2	6	7	1	3	5	3	5
16	M ${}_{3}$	7	5	6	3	3	5	4	5	6	7	3	2	1	5	3
17	M ${}_{4}$	5	6	3	6	2	1	6	7	4	2	4	6	4	7	3
18	M ${}_{5}$	5	6	3	7	3	5	3	4	2	1	5	7	5	3	6
19	M ${}_{6}$	5	4	2	6	4	6	4	6	4	2	6	2	1	7	4

Table 3

$G1$ legal assignment of quality specific immune indicators in 15 large-scale manufacturing enterprises in eastern regions

Serial number	Indicator layer	Rational assignment	Serial number	Indicator layer	Rational assignment
1	$P_{1}$	–	11	$D_{5}$	$D_{4}/D_{5}=1.2$
2	$P_{2}$	$P_{1}/P_{2}=1.4$	12	$D_{6}$	$D_{5}/D_{6}=1.1$
3	$P_{3}$	$P_{2}/P_{3}=1.3$	13	$D_{7}$	$D_{6}/D_{7}=1.1$
4	$P_{4}$	$P_{3}/P_{4}=1.2$	14	$M_{1}$	–
5	$P_{5}$	$P_{4}/P_{5}=1.1$	15	$M_{2}$	$M_{1}/M_{2}=1.6$
6	$P_{6}$	$P_{5}/P_{6}=1.1$	16	$M_{3}$	$M_{2}/M_{3}=1.5$
7	$D_{1}$	–	17	$M_{4}$	$M_{3}/M_{4}=1.4$
8	$D_{2}$	$D_{1}/D_{2}=1.5$	18	$M_{5}$	$M_{4}/M_{5}=1.3$
9	$D_{3}$	$D_{2}/D_{3}=1.4$	19	$M_{6}$	$M_{5}/M_{6}=1.3$
10	$D_{4}$	$D_{3}/D_{4}=1.3$

With the help of SPSS 22.0 software, the correlation coefficients among all the evaluation indicators in the organizational quality specific immune indicator system are between 0.35 and 0.62, $p<$ 0.05 or $p<$ 0.01, the correlation coefficients among all the evaluation indicators in the organizational quality specific immune indicator system indicate that there are significantly positive correlations among all the

Table 4

Levels and comprehensive evaluation and ranking of organizational quality specific immune of 15 large-scale manufacturing enterprises in eastern regions

Serial number	Scoring basis		Levels and comprehensive evaluation of organizational quality specific immune of 15 large-scale manufacturing enterprises in eastern regions
			Q ${}_{1}$	Q ${}_{2}$	Q ${}_{3}$	Q ${}_{4}$	Q ${}_{5}$	Q ${}_{6}$	Q ${}_{7}$	Q ${}_{8}$	Q ${}_{9}$	Q ${}_{10}$	Q ${}_{11}$	Q ${}_{12}$	Q ${}_{13}$	Q ${}_{14}$	Q ${}_{15}$
1	Comprehensive	Score	4.51	4.392	4.49	4.875	4.794	4.673	4.955	4.318	4.103	3.136	3.574	4.352	3.647	4.362	3.928
	evaluation
		Sort	5	7	6	2	3	4	1	10	11	15	14	9	13	8	12
2	P	Score	1.3890	1.2190	1.8380	1.7880	2.1660	1.8200	1.8370	1.5590	1.3970	0.8250	1.2760	1.8360	1.1630	1.2940	1.1130
		Sort	9	12	2	6	1	5	3	7	8	15	11	4	13	10	14
3	D	Score	1.6610	1.5730	1.4990	1.5370	1.5300	1.6320	1.5620	1.3230	1.5020	1.3210	1.0340	1.3520	1.3650	1.6510	1.4550
		Sort	1	4	9	6	7	3	5	13	8	14	15	12	11	2	10
4	M	Score	1.4600	1.6000	1.1530	1.5500	1.0980	1.2210	1.5560	1.4360	1.2040	0.9900	1.2640	1.1640	1.1190	1.4170	1.3600
		Sort	4	1	13	3	14	9	2	5	10	15	8	11	12	6	7

evaluation indicators. The mean values of VIF are lower than 10, the multicollinearity among all the evaluation indicators is not serious.

4.2 Calculation of combination weights

(1) Calculation of $G1$ weight

1) Invite an expert to subjectively rank the three criteria layers (organizational quality monitoring and cognition $X_{1}$ , organizational quality defense, clearance and repair $X_{2}$ , and organizational quality memory and immune stabilization $X_{3}$ ) in the order of $X_{1}>X_{2}>X_{3}$ .

2) According to the rational value given by the expert, $r_{k}$ is: $r_{2}=X_{1}/X_{2}=1.2$ , $r_{3}=X_{2}/X_{3}=1.1$ .

3) The rational assignment $r_{j}(j=2,3)$ is substituted into the Eqs (1) and (2), and the $G1$ weight corresponding to each criterion layer is obtained.

In the same way, the weight of each indicator layer corresponding to the criterion layer can be obtained. The rational assignment is shown in Table 3. The finally obtained $G1$ weight is listed in the fourth column of Table 1.

(2) Calculation of weights of single evaluation methods

Substituting the values in Table 2 into Eqs (3)–(10) respectively, and finally obtaining the weights of the $G2$ method, entropy method, and deviation method, which are listed in columns 5, 6, and 7 in Table 1 respectively.

(3) Calculation of combination weights

By substituting each numerical value in Table 2 and the corresponding weights of columns 4–7 in Table 1 into Eq. (15), the combination coefficient $\alpha_{k}=(0.108,0.349,0.129,0.414)$ corresponding to each evaluation method can be obtained.

Columns 4–7 and the combination coefficient $\alpha_{k}$ in Table 1 are substituted into Eq. (11), and finally the combination weight of each indicator is obtained and listed in the 8th column of Table 1.

4.3 Comprehensive evaluation results

The combination weight of the eighth column in Table 1 and each value in Table 2 are substituted into Eq. (16), and the total score of each enterprise and the score of each criterion layer are finally obtained and sorted. The results are shown in Table 4.

4.4 Organizational quality specific immune status

According to the eighth column of Table 1, it can be known that the most important factor affecting the quality specific immune of the 15 large-scale manufacturing enterprises in eastern regions is external environmental monitoring, whose weight is 0.058; Statistical control and feedback, whose weight is 0.058; And learning, whose weight is 0.071. The indicators that have less impact on the specific immunity of corporate organizations are supplier relationship management, whose weight is 0.042; Customer needs, whose weight is 0.046; And dissemination and diffusion, whose weight is 0.046.

According to Table 4, among the 15 large-scale manufacturing enterprises in eastern regions, the 7th enterprise with the best organizational quality specific immune status has a score of 4.955; The worst is the 10th enterprise with a score of 3.136; And the 2nd the scores of the four companies and the 14th company are in the middle.

5. Conclusion

This study takes organizational quality specific immune as the entry point to construct the organizational quality specific immune evaluation indicator system, and which includes three criteria layers of organizational quality monitoring and cognition, organizational quality defense, clearance and repair, and organizational quality memory and immune stabilization. Then this study fuses and integrates the advantages of the $G1$ method, $G2$ method, entropy method, and deviation method in order to weight the evaluation indicators and determine the combined weight, forms the optimal combination weighting logicality and operation principles, constructs the organizational quality specific immune evaluation model based on optimal combination weight methods, and the optimal combination weighting model is introduced to conduct empirical study of evaluating organizational quality specific immune with 15 large-scale manufacturing enterprises in eastern regions. The empirical analysis results indicate that the optimal combination weighting methods can avoid the disadvantage of the single weighting method that contributes too little to the results. At the same time, the optimal combination weighting methods including the $G1$ method, $G2$ method, entropy method, and deviation method can be introduced into the specificity of organizational quality specific immune, which can be used in the scope of organizational quality specific immune and organizational quality. The methods can be proved to be effective and feasible through empirical analysis. In immunization, the advantages and disadvantages of organizational quality specific immune of 15 large-scale manufacturing enterprises in eastern regions are compared. The pros and cons of the organizational quality specific immune status of 15 large-scale manufacturing enterprises in eastern regions are finally obtained. The theoretical framework of organizational quality specific immune evaluation indicator system and the empirical analysis methods and models will provide theoretical basis, theoretical foundation and practical enlightenment for improving organizational quality performance and enhancing organizational health.

Footnotes

Acknowledgments

This research is funded by scientific research project of education department of Liaoning province (No. JJW202015408).

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Organizational quality specific immune evaluation model based on optimal combination weighting

Abstract

Keywords

1. Introduction

2. Organizational quality specific immune indicator evaluation system construction

2.1 Organizational quality monitoring and cognition

2.2 Organizational quality defense, clearance and repair

Table 1 Organizational quality specific immune evaluation indicator system

2.4 Organizational quality specific immune evaluation indicator system construction

3.1 Thoughts on organizational quality specific immune evaluation model construction

3.1.1 Determination of G1 weight

3.2.1 Calculation of optimal weights based on two factors

4.1 Sample selection

Table 2 Organizational quality specific immune evaluation indicator scores of 15 large-scale manufacturing enterprises in eastern regions

4.3 Comprehensive evaluation results

4.4 Organizational quality specific immune status

5. Conclusion

Footnotes

Acknowledgments

References

Table 1
Organizational quality specific immune evaluation indicator system

Table 2
Organizational quality specific immune evaluation indicator scores of 15 large-scale manufacturing enterprises in eastern regions