# A Dynamic Evaluation Model of University Brand Value Based on Analytic Hierarchy Process

Authors: Mingchao Li; Bin Gong
Journal: Scientific Programming
 (2022)

---

## Abstract

In recent years, great changes have taken place in the economic environment, policies, competitive environment, and market of colleges and universities. Furthermore, factors including the reduction of number of students every year has led to the continuous decline in the number of students enrolled in colleges and universities. Facing this problem, it is essential that colleges and universities should build their own brand value and attract more high school graduates with the brand value of colleges and universities. Nowadays, higher education has been popularized and internationalized, and the competition among colleges and universities has gradually increased. In fact, colleges and universities can obtain high-quality school running resources by relying on their own loyalty, reputation and social status, and can also achieve greater development space in the field of education. Therefore, university managers began to pay attention to their own brand value. The brand value of colleges and universities cannot be directly reflected, but needs to be reflected from different aspects. For this problem, this paper uses analytic hierarchy process (AHP) to study the brand value of colleges and universities. By selecting many aspects as the indicators of the dynamic evaluation system of brand value of colleges and universities, this paper constructs a dynamic evaluation model of brand value of colleges and universities based on analytic hierarchy process. After analysis, the total score of the brand value of a university is 84.12 and the grade is “B.” Based on the analysis of the results, it can be concluded that the overall score of the university is high and has a certain brand value. However, it is weak in talent training and academic reputation.


---

## Body

## 1. Introduction

The brand of colleges and universities is the foundation of standing in the society. If a college has no brand or low brand value, it is difficult to obtain good educational resources and students. Therefore, the brand value of colleges and universities is the foundation of expanding the scale of colleges and universities. Shaping the brand of colleges and universities requires long-term accumulation and the joint efforts of several generations. Once colleges and universities form their own brand value in the society, their influence and social appeal also increase rapidly. Therefore, this paper establishes a dynamic evaluation model of university value based on analytic hierarchy process, uses this model to accurately evaluate the university brand value from many aspects, and comprehensively promotes the promotion of university brand value.The common problems of educational institutes including colleges and universities in China’s system are low efficiency, high investment cost, and insufficient social influence, which have a serious impact on the brand value of colleges and universities. The extensive construction of colleges and universities reduces the brand value of colleges and universities, the serious lack of teachers also interferes with the brand value of colleges and universities, and the quality of students also reduces the brand value. Some colleges and universities arbitrarily adjust the name of colleges and universities, which reduces the brand value of colleges and universities and affects the image of colleges and universities in the society. The improvement of academic reputation is conducive to the improvement of brand value of colleges and universities at home and abroad and plays a certain role in promoting academic research in China. At the same time, there is a relative lack of talent training, and the graduated college students lack management ability and innovation ability. This should be kept in mind that all academia including colleges and universities should improve students’ creativity, formulate courses to spread students’ thinking ability, give full play to students’ imagination and creativity, and create a good research environment for students.In this paper, we describe, in detail, the basic concepts and application steps based on analytic hierarchy process (AHP). Furthermore, we establish a dynamic evaluation system of university brand value based on AHP, combine with statistical analysis, and calculate the system through different levels of weight. Through evaluation, we judge the importance of university brand value according to the weight of each index. On the other hand, through the dynamic evaluation model of university brand value based on analytic hierarchy process, we select some college students to evaluate a university in China and use analytic hierarchy process to dynamically evaluate the university brand value, so as to improve the accuracy of the evaluation results. Based on the analysis of the results, it can be concluded that the overall score of the university is high and has a certain brand value. However, it is weak in talent training and academic reputation. The major innovations and contributions of this paper in the research process are as follows:(i)
Describe in detail the basic concepts and application steps based on analytic hierarchy process (AHP)(ii)
Establish a dynamic evaluation system of university brand value based on AHP and judge the importance of university brand value according to the weight of each index(iii)
Use analytic hierarchy process to dynamically evaluate the university brand value, so as to improve the accuracy of the evaluation results(iv)
We concluded that the overall score of the university is high and has a certain brand value; however, it is weak in talent training and academic reputationThe rest of the paper is organized as follows. In Section2, we offer an overview of the related work. Section 3 is about the analytic hierarchy process (AHP) and its brief introduction along with applications. The AHP is the research methodology used in this research—used in two different case studies. Section 4 illustrates the dynamic evaluation model of university brand value based on analytic hierarchy process. Section 5 describes the dynamic evaluation of university brand value based on analytic hierarchy process. Moreover, experimental details based on our assumptions and evaluation are also presented in this section. Finally, Section 6 concludes this paper and offers several directions for further research and investigation.


## 2. Related Work

In the late 1980s, the American Institute of marketing held the world’s first academic conference on “brand equity.” Since then, some scholars have carried out research in the field of brand equity [1]. Anna et al. proposed that brand equity is the difference of the demander’s brand knowledge under different marketing measures. Based on this perspective, it is pointed out that the brand has high brand value, and the demander can stimulate the purchase desire after identifying some well-known brands [2]. Brand knowledge includes brand impression and brand awareness. This definition is analyzed from the perspective of the demander and is the brand value based on the demander. Hu et al. believe that from this perspective, the research on brand assets and the judgment of the demander’s response to marketing activities can promote enterprises to carry out marketing activities and guide managers to formulate marketing strategies based on this strategic orientation. An important component of the brand knowledge is based on brand awareness. The demander’s ability to identify brand value, followed by brand impression, that is, the demander perceives the brand according to his own memory, and its association has brand significance, that is, the demander’s special preference and intensity in marketing activities [3]. The brand value of colleges and universities is the relationship formed by the long-term interaction between the brand of colleges and universities, students, and employers. We should strengthen the ability to recognize the brand value of colleges and universities and strengthen the ability of students and relevant social personnel to recognize the brand value of higher education. Moreover, this will form a good interpersonal relationship with colleges and universities so as to form loyalty to the brand of colleges and universities and form a value higher than the physical assets of colleges and universities. These are considered as important competitive advantages of colleges and universities in brand value [4].Nguyen et al. pointed out that it is necessary to improve brand awareness through external brand communication and brand embodiment [5]. Chun et al. analyzed from other perspectives and divided brand awareness into two research points: (i) brand memory and (ii) brand recognition [6]. Tribukait et al. studied the expectations and basic requirements of teachers’ teaching, students’ learning, and evaluation [7]. In [8], Uzun et al. deeply studied and investigated the sample information filled in by distance education students and undergraduate students and proposed to evaluate the quality of education service by using perception and teacher expectation. Xiaojuan et al. have concluded through research that the brand driving effect of colleges and universities can stimulate their own development, improve the image of schools and educational institutes in the region, and promote the development of the country [9].Chen et al. constructed a “brand belief model” to classify the brand development into five different levels, namely: (i) product, (ii) company concept, (iii) conceptual brand, (iv) brand spirit, and (v) brand culture [10]. After long-term polishing in the market, the brand is raised to the field of judgment spirit, which is also the highest level of brand development. At this time, the brand is integrated with brand spirit and brand culture. Li et al. believe that the university brand is a teaching concept, school running quality, and teaching characteristics accumulated and precipitated in the development process of the university, and is the recognition of the society for the university. The authors believe that the university should formulate the brand strategy from the core value, obtain a large number of school running resources, and provide students with better educational quality and services [11]. Moreover, Rangkuti et al. analyzed the influence of university brand on students’ school choice from the perspective of high school students and formulated the brand elimination framework for students to choose universities for higher education [12]. Analytic hierarchy process (AHP) is a hierarchical and systematic multicriteria decision-making algorithm that combines quantitative and qualitative analysis. AHP is largely used in the state-of-the-art for decision making in various fields, but its effectiveness is relatively unexplored in modern educational systems [13]. In the next section, we describe the AHP algorithm in detail.


## 3. Analytic Hierarchy Process (AHP)

### 3.1. Concept of Analytic Hierarchy Process (AHP)

Analytic hierarchy process (AHP) is a hierarchical and systematic multicriteria decision-making algorithm combining quantitative analysis and qualitative analysis. The basic characteristics of human rational thinking involve three aspects: judgment, decomposition, and synthesis. The research problems based on AHP also fully show the above contents [14]. The emergence of AHP method completely breaks the communication barrier between decision analysis and decision-makers. For a long time, decision-makers choose AHP method instead of making decisions through decision analysts, so as to effectively improve the reliability, effectiveness, and feasibility of decision-making schemes. Some problems that cannot be solved by quantitative analysis are very suitable for using AHP method, which is also the most ideal mathematical way to deal with this problem. When studying problems based on analytic hierarchy process, it should be completed according to the following steps. First, the hierarchical structure model is constructed, and then the judgment matrix of pairwise comparison is established; then consistency test and hierarchical single sorting are conducted [15]. Figure 1 shows the application flow chart of analytic hierarchy process.Figure 1
Flow chart of analytic hierarchy process.


### 3.2. Basic Steps of Analytic Hierarchy Process

#### 3.2.1. Construct Hierarchical Structure Model

This paper analyzes the brand value of colleges and universities that need to be studied and hierarchizes the problems that need to be analyzed. According to different attributes, the target problem is re decomposed into multiple parts, and each part is called element. The elements under the same level are the criterion level for the lower level elements, which can dominate the lower level elements and are also dominated by the upper level elements. Based on this model, a hierarchical structure from top to bottom is constructed. At the top of the structure is the ideal result or expected goal of the analysis problem, which is called the goal layer. Generally, this layer has only one element. The criterion layer and subcriterion layer belong to the middle layer, in which there are multiple intermediate links related to the completion of the goal. Each scheme for implementing the decision is at the lowest layer, and the number of elements in each layer is no more than 9. On the contrary, it will increase the difficulty of pairwise comparison. If the number of criterion layers is large, multiple subcriterion layers can be formed by decomposing the criterion layer. When solving practical problems, the most critical part is to divide the hierarchy as investigated in [13, 16]. Figure 2 illustrates the hierarchy diagram.Figure 2
Hierarchy chart.


#### 3.2.2. Comparison and Judgment Matrix

Through constructing a hierarchical structure, the hierarchical relationship between different elements can be clearly expressed. For different decision makers, the importance of different criteria in the same layer to the target layer is different, especially when there are multiple factors in the lower layer of any criterion layer, the most important factor in the criterion layer cannot be determined at the first time, resulting in the decision maker being unable to take all factors into account, so as to make contradictory decisions. When dealing with this problem, a judgment matrix of pairwise comparison can be constructed by analytic hierarchy processes [17].Suppose there aren factors X = {x1, x2,…,xn} in z and compare the importance of n factors in z, select xi and xj, and aij represents the comparison result. After the comparison of each factor, A = (aij) n × n to represent the matrix, and matrix A is called the judgment matrix between Z-X, In the AHP algorithm, the importance and relationship of each factor are reflected by the 1–9 scale method. In fact, the 1–9 scale represents the relationship among two or more than two factors based on the human thinking. The basic meaning along with different relationships of the 1–9 scale method is listed in Table 1.Table 1
Basic meanings of the 1–9 scale method.
ScaleBasic meaning1The importance of the two factors was the same3Comparing the two factors, the former is slightly more important than the latter5Comparing the two factors, the former is more important than the latter7Comparing the two factors, the former is far more important than the latter9Comparing the two factors, the former is far more important than the latter2,4,6,8The degree of importance is between two adjacent criteriaThe 1–9 scale method can accurately transform the way of human thinking to judge the importance of various things. When comparing and judging various things, the commonly used words are strong, a bit strong, very strong, and absolutely strong, etc. Therefore, if you want to make an in-depth judgment, you need to add the compromise method to the adjacent judgment level [18]. The 1–9 scale method can be applied in most judgment and decision making. After practical verification by psychologists, the results show that most people have 5 to 9 levels of discrimination ability in judging the same attribute of different things. Using the 1–9 scale can reflect the judgment ability of a considerable number of people [19, 20].


#### 3.2.3. Hierarchical Single Ranking and Consistency Test

This process should be completed in the criterion layer, which requires the problem of arrangement vector betweenn elements. The most commonly used method to deal with this problem is the eigenvalue method. The detailed process is as follows: judgment matrix A and λ Max corresponds to the feature vector W, after normalization, the importance ranking weight between the elements of the same layer and any elements of the upper layer can be obtained [16]. The above is the hierarchical single ranking.The eigenvectorW and the maximum eigenvalue are obtained by using the power method given by Algorithm 1. In the first step, W0 represents the initial value vector, which is given by w0=1/n,1/n,…,1/nT. In second step, for all k = 1,2,...,n, the values of w¯k=Awk−1 is obtained, and wk−1 vector is obtained after normalization. In the third step, the premise of accuracy calculation, if maxwki−wk−1i<ε, where wki is the i component in wk, the settlement will be ended after meeting this requirement, otherwise jump to the second step. Finally, the calculation happens from the following equations.(1)λmax=1n∑i=1nwki¯wk−1i,(2)wkj=w¯ki∑j=1nw¯kj.Algorithm 1: The power method to calculate eigenvector and eigenvalue.
(1)
Suppose W0 represents the initial value vector, then w0=1/n,1/n,…,1/nT(2)
Fork = 1, 2,...,n, w¯k=Awk−1 is obtained, and wk−1 vector is obtained after normalization.(3)
On the premise of accurate accuracy calculation, ifmaxwki−wk−1i<ε, where wki is the i component in wk, the settlement will be ended after meeting this requirement, otherwise jump to the second step.(4)
Calculate next step using equations (1) and (2)


## 3.1. Concept of Analytic Hierarchy Process (AHP)

Analytic hierarchy process (AHP) is a hierarchical and systematic multicriteria decision-making algorithm combining quantitative analysis and qualitative analysis. The basic characteristics of human rational thinking involve three aspects: judgment, decomposition, and synthesis. The research problems based on AHP also fully show the above contents [14]. The emergence of AHP method completely breaks the communication barrier between decision analysis and decision-makers. For a long time, decision-makers choose AHP method instead of making decisions through decision analysts, so as to effectively improve the reliability, effectiveness, and feasibility of decision-making schemes. Some problems that cannot be solved by quantitative analysis are very suitable for using AHP method, which is also the most ideal mathematical way to deal with this problem. When studying problems based on analytic hierarchy process, it should be completed according to the following steps. First, the hierarchical structure model is constructed, and then the judgment matrix of pairwise comparison is established; then consistency test and hierarchical single sorting are conducted [15]. Figure 1 shows the application flow chart of analytic hierarchy process.Figure 1
Flow chart of analytic hierarchy process.


## 3.2. Basic Steps of Analytic Hierarchy Process

### 3.2.1. Construct Hierarchical Structure Model

This paper analyzes the brand value of colleges and universities that need to be studied and hierarchizes the problems that need to be analyzed. According to different attributes, the target problem is re decomposed into multiple parts, and each part is called element. The elements under the same level are the criterion level for the lower level elements, which can dominate the lower level elements and are also dominated by the upper level elements. Based on this model, a hierarchical structure from top to bottom is constructed. At the top of the structure is the ideal result or expected goal of the analysis problem, which is called the goal layer. Generally, this layer has only one element. The criterion layer and subcriterion layer belong to the middle layer, in which there are multiple intermediate links related to the completion of the goal. Each scheme for implementing the decision is at the lowest layer, and the number of elements in each layer is no more than 9. On the contrary, it will increase the difficulty of pairwise comparison. If the number of criterion layers is large, multiple subcriterion layers can be formed by decomposing the criterion layer. When solving practical problems, the most critical part is to divide the hierarchy as investigated in [13, 16]. Figure 2 illustrates the hierarchy diagram.Figure 2
Hierarchy chart.


### 3.2.2. Comparison and Judgment Matrix

Through constructing a hierarchical structure, the hierarchical relationship between different elements can be clearly expressed. For different decision makers, the importance of different criteria in the same layer to the target layer is different, especially when there are multiple factors in the lower layer of any criterion layer, the most important factor in the criterion layer cannot be determined at the first time, resulting in the decision maker being unable to take all factors into account, so as to make contradictory decisions. When dealing with this problem, a judgment matrix of pairwise comparison can be constructed by analytic hierarchy processes [17].Suppose there aren factors X = {x1, x2,…,xn} in z and compare the importance of n factors in z, select xi and xj, and aij represents the comparison result. After the comparison of each factor, A = (aij) n × n to represent the matrix, and matrix A is called the judgment matrix between Z-X, In the AHP algorithm, the importance and relationship of each factor are reflected by the 1–9 scale method. In fact, the 1–9 scale represents the relationship among two or more than two factors based on the human thinking. The basic meaning along with different relationships of the 1–9 scale method is listed in Table 1.Table 1
Basic meanings of the 1–9 scale method.
ScaleBasic meaning1The importance of the two factors was the same3Comparing the two factors, the former is slightly more important than the latter5Comparing the two factors, the former is more important than the latter7Comparing the two factors, the former is far more important than the latter9Comparing the two factors, the former is far more important than the latter2,4,6,8The degree of importance is between two adjacent criteriaThe 1–9 scale method can accurately transform the way of human thinking to judge the importance of various things. When comparing and judging various things, the commonly used words are strong, a bit strong, very strong, and absolutely strong, etc. Therefore, if you want to make an in-depth judgment, you need to add the compromise method to the adjacent judgment level [18]. The 1–9 scale method can be applied in most judgment and decision making. After practical verification by psychologists, the results show that most people have 5 to 9 levels of discrimination ability in judging the same attribute of different things. Using the 1–9 scale can reflect the judgment ability of a considerable number of people [19, 20].


### 3.2.3. Hierarchical Single Ranking and Consistency Test

This process should be completed in the criterion layer, which requires the problem of arrangement vector betweenn elements. The most commonly used method to deal with this problem is the eigenvalue method. The detailed process is as follows: judgment matrix A and λ Max corresponds to the feature vector W, after normalization, the importance ranking weight between the elements of the same layer and any elements of the upper layer can be obtained [16]. The above is the hierarchical single ranking.The eigenvectorW and the maximum eigenvalue are obtained by using the power method given by Algorithm 1. In the first step, W0 represents the initial value vector, which is given by w0=1/n,1/n,…,1/nT. In second step, for all k = 1,2,...,n, the values of w¯k=Awk−1 is obtained, and wk−1 vector is obtained after normalization. In the third step, the premise of accuracy calculation, if maxwki−wk−1i<ε, where wki is the i component in wk, the settlement will be ended after meeting this requirement, otherwise jump to the second step. Finally, the calculation happens from the following equations.(1)λmax=1n∑i=1nwki¯wk−1i,(2)wkj=w¯ki∑j=1nw¯kj.Algorithm 1: The power method to calculate eigenvector and eigenvalue.
(1)
Suppose W0 represents the initial value vector, then w0=1/n,1/n,…,1/nT(2)
Fork = 1, 2,...,n, w¯k=Awk−1 is obtained, and wk−1 vector is obtained after normalization.(3)
On the premise of accurate accuracy calculation, ifmaxwki−wk−1i<ε, where wki is the i component in wk, the settlement will be ended after meeting this requirement, otherwise jump to the second step.(4)
Calculate next step using equations (1) and (2)


## 3.2.1. Construct Hierarchical Structure Model

This paper analyzes the brand value of colleges and universities that need to be studied and hierarchizes the problems that need to be analyzed. According to different attributes, the target problem is re decomposed into multiple parts, and each part is called element. The elements under the same level are the criterion level for the lower level elements, which can dominate the lower level elements and are also dominated by the upper level elements. Based on this model, a hierarchical structure from top to bottom is constructed. At the top of the structure is the ideal result or expected goal of the analysis problem, which is called the goal layer. Generally, this layer has only one element. The criterion layer and subcriterion layer belong to the middle layer, in which there are multiple intermediate links related to the completion of the goal. Each scheme for implementing the decision is at the lowest layer, and the number of elements in each layer is no more than 9. On the contrary, it will increase the difficulty of pairwise comparison. If the number of criterion layers is large, multiple subcriterion layers can be formed by decomposing the criterion layer. When solving practical problems, the most critical part is to divide the hierarchy as investigated in [13, 16]. Figure 2 illustrates the hierarchy diagram.Figure 2
Hierarchy chart.


## 3.2.2. Comparison and Judgment Matrix

Through constructing a hierarchical structure, the hierarchical relationship between different elements can be clearly expressed. For different decision makers, the importance of different criteria in the same layer to the target layer is different, especially when there are multiple factors in the lower layer of any criterion layer, the most important factor in the criterion layer cannot be determined at the first time, resulting in the decision maker being unable to take all factors into account, so as to make contradictory decisions. When dealing with this problem, a judgment matrix of pairwise comparison can be constructed by analytic hierarchy processes [17].Suppose there aren factors X = {x1, x2,…,xn} in z and compare the importance of n factors in z, select xi and xj, and aij represents the comparison result. After the comparison of each factor, A = (aij) n × n to represent the matrix, and matrix A is called the judgment matrix between Z-X, In the AHP algorithm, the importance and relationship of each factor are reflected by the 1–9 scale method. In fact, the 1–9 scale represents the relationship among two or more than two factors based on the human thinking. The basic meaning along with different relationships of the 1–9 scale method is listed in Table 1.Table 1
Basic meanings of the 1–9 scale method.
ScaleBasic meaning1The importance of the two factors was the same3Comparing the two factors, the former is slightly more important than the latter5Comparing the two factors, the former is more important than the latter7Comparing the two factors, the former is far more important than the latter9Comparing the two factors, the former is far more important than the latter2,4,6,8The degree of importance is between two adjacent criteriaThe 1–9 scale method can accurately transform the way of human thinking to judge the importance of various things. When comparing and judging various things, the commonly used words are strong, a bit strong, very strong, and absolutely strong, etc. Therefore, if you want to make an in-depth judgment, you need to add the compromise method to the adjacent judgment level [18]. The 1–9 scale method can be applied in most judgment and decision making. After practical verification by psychologists, the results show that most people have 5 to 9 levels of discrimination ability in judging the same attribute of different things. Using the 1–9 scale can reflect the judgment ability of a considerable number of people [19, 20].


## 3.2.3. Hierarchical Single Ranking and Consistency Test

This process should be completed in the criterion layer, which requires the problem of arrangement vector betweenn elements. The most commonly used method to deal with this problem is the eigenvalue method. The detailed process is as follows: judgment matrix A and λ Max corresponds to the feature vector W, after normalization, the importance ranking weight between the elements of the same layer and any elements of the upper layer can be obtained [16]. The above is the hierarchical single ranking.The eigenvectorW and the maximum eigenvalue are obtained by using the power method given by Algorithm 1. In the first step, W0 represents the initial value vector, which is given by w0=1/n,1/n,…,1/nT. In second step, for all k = 1,2,...,n, the values of w¯k=Awk−1 is obtained, and wk−1 vector is obtained after normalization. In the third step, the premise of accuracy calculation, if maxwki−wk−1i<ε, where wki is the i component in wk, the settlement will be ended after meeting this requirement, otherwise jump to the second step. Finally, the calculation happens from the following equations.(1)λmax=1n∑i=1nwki¯wk−1i,(2)wkj=w¯ki∑j=1nw¯kj.Algorithm 1: The power method to calculate eigenvector and eigenvalue.
(1)
Suppose W0 represents the initial value vector, then w0=1/n,1/n,…,1/nT(2)
Fork = 1, 2,...,n, w¯k=Awk−1 is obtained, and wk−1 vector is obtained after normalization.(3)
On the premise of accurate accuracy calculation, ifmaxwki−wk−1i<ε, where wki is the i component in wk, the settlement will be ended after meeting this requirement, otherwise jump to the second step.(4)
Calculate next step using equations (1) and (2)


## 4. Dynamic Evaluation Model of University Brand Value Based on AHP

### 4.1. Brand Value Evaluation Theory

The establishment of brand requires the joint construction of marketing activities, products, and needs. The brand can fully show the mutual needs between people and products and also has a direct impact on the selection of advertising channels and marketing activities [21]. In addition, the brand on assets also shows that it has some assets, which proves the brand value on three levels, namely, market level, demander level, and capital level. The income formed by the above activities is called brand value. Yu et al. pointed out that three perspectives can be unified in a theoretical framework. Based on the direct impact of nonmarketing strategies and enterprise marketing strategies on the brand, these nonmarketing strategies involve competitor strategies, 4P combination strategies, lifestyle, consumer values, market environment, etc., so as to arouse the demand of the demander, Therefore, the “ideas” of brand demanders have an impact on enterprise output and performance, including capital market performance and product market performance. Figure 3 shows the three-dimensional perspective of the brand value.Figure 3
Three-dimensional perspective of brand value.


### 4.2. University Brand Value Service Model

The brand value of colleges and universities is directly related to the level of brand knowledge and understanding of the demander. Zhong et al. pointed out that brand awareness should be reflected from two different aspects: (i) external brand communication and (ii) enterprise brand [22]. Furthermore, the brand value should be reasonably divided into brand identification and brand memory, as shown in Figure 4.Figure 4
University brand value model.Based on the achievements of scholars in the study of brand value and service value, the following university brand values are defined here [23]. The brand value of colleges and universities is that the brand of colleges and universities forms a kind of cognition of the brand of colleges and universities through long-term interaction and communication with employers and students, which can promote colleges and universities to have good preferences and contacts, so as to strengthen the brand popularity and loyalty of colleges and universities [24, 25].


### 4.3. Construction of Dynamic Evaluation Model of University Brand Value Based on Analytic Hierarchy Process

#### 4.3.1. Constructing the Dynamic Evaluation System of University Brand Value Based on Analytic Hierarchy Process

The analytic hierarchy process (AHP) selected in this paper belongs to the subjective decision-making method. After the index weight is clear, it is decomposed into the hierarchical structure model into target layer, criterion layer, and index layer. When establishing the university brand value evaluation model based on analytic hierarchy process, we should first build different levels in this model, and then statistically analyze the factors at different levels, so as to clarify the overall goal of each factor, that is, the weight of university brand value, as shown in Figure5.Figure 5
Evaluation system of university brand value based on analytic hierarchy process.


#### 4.3.2. Calculate Index Weight

According to the concept and application process of analytic hierarchy process given above, the weights of different indicators in the university brand value index system are calculated according to this process, as shown in Table2.Table 2
Primary index judgment matrix and index weight.
AB1B2B3B4The weightB112130.53B221/321/30.21B31/21/2110.12B4211/21/20.14(1) Primary Index Weight. Evaluation model of university brand value target level based on Analytic Hierarchy Process:(3)A=0.53B1+0.21B2+0.12B3+0.14B4.(2) Academic Reputation Index Weight. The academic reputation index weight of each index is calculated using Table 3.Table 3
Academic reputation judgment matrix and weight of each index.
B1C11C12C13The weightC11121/20.42C121/211/30.27C1321/310.31Single-level evaluation model of academic reputation:(4)B1=0.42C11+0.27C12+0.31C13.(3) A Single-Level Evaluation Model of Academic Reputation. The teacher resource judgment matric and index weight are shown in Table 4.Table 4
Teacher resource judgment matrix and index weight.
B2C21C22C23The weightC21111/20.17C2231/210.54C2321/320.29Single level evaluation model of teacher resources:(5)B2=0.17C21+0.54C22+0.29C23.(4) Weight of Comprehensive Indicators of Teaching Quality. The teaching quality judgment matrix and index weight are shown in Table 5.Table 5
Teaching quality judgment matrix and index weight.
B3C31C32C33The weightC31131/20.35C321/2110.16C33221/30.49Single-level evaluation model of teaching quality:(6)B3=0.35C31+0.16C32+0.49C33.(5) Weight of Comprehensive Indicators of Talent Training. The talent training index and weight matrix are shown in Table 6.Table 6
Talent training index and weight matrix.
B4C41C42C43The weightC411330.59C421/3120.25C431/31/210.16Single-level evaluation model of talent training:(7)B4=0.59C41+0.25C42+0.16C43.Through the above calculation, it can be concluded that in the dynamic evaluation system of university brand value based on analytic hierarchy process, the weights of the first-class indicators academic reputation, teacher resources, teaching quality, and talent training are 0.54, 0.21, 0.12, and 0.14, respectively. Thus, accounting for the highest proportion of academic reputation, which has the greatest impact on the total index weight of the standard level. The weight of the second-level index academic reputation is 0.42, 0.27, and 0.31 for the number of national papers, the number of excellent papers at the school level, and the number of international awards for students, respectively. The index with the highest weight in academic reputation is the number of national papers. This should be noted that among the secondary indicators of teacher resources, the corresponding weights of teacher team structure, teacher strength, and doctoral teachers are 0.17, 0.54, and 0.29, respectively—where the teacher strength has the highest weight.Moreover, among the secondary indicators of teaching quality, the corresponding indicators of the basic knowledge ability, professional and technical ability, and personal practical ability are 0.35, 0.16, and 0.49, respectively. We observed that among which the index with the highest weight is personal practical ability. Similarly, among the secondary indicators of talent training, the corresponding weights of the student employment, innovation ability, and management ability are 0.59, 0.25, and 0.16, respectively—in which the highest weight is allocated to the student employment. The specific weights are shown in Table7:Table 7
Dynamic evaluation model of university brand value based on analytic hierarchy process (AHP).
Ability to manageRule layerThe weightIndex layerThe weightUniversity brand value dynamic evaluation system based on analytic hierarchy processAcademic reputation0.54Number of national papers0.42Number of excellent university papers0.27Number of international award students0.31Teacher resources0.21Structure of teaching staff0.17Faculty0.54Proportion of PhD teachers0.29The quality of teaching0.12Basic knowledge ability0.35Professional and technical ability0.16Personal practical ability0.49Cultivation of talents0.14Students employment0.59The innovation ability0.25Ability to manage0.16The proportion of various indicators in the total target weight is shown in the bar chart in Figure6. Among the primary indicators, the highest proportion is academic reputation, which accounts for 54%, followed by teacher resources, and the lowest proportion is teaching quality, which accounts for 12%. Among the secondary indicators, the highest weight is the employment of students, and the specific weight proportion is shown in Figure 6:Figure 6
Proportion of overall weight of evaluation indicators.The analysis of the data, as shown in Figure6, shows that the highest proportion of the total weight of secondary indicators is student employment C41, accounting for 14.75%, and the lowest proportion is professional and technical ability C32 and management ability C43, accounting for 4%. This shows that when evaluating the brand value of colleges and universities, students’ management ability and professional, as well as, technical ability are not important indicators, and the weight is low in the evaluation.


## 4.1. Brand Value Evaluation Theory

The establishment of brand requires the joint construction of marketing activities, products, and needs. The brand can fully show the mutual needs between people and products and also has a direct impact on the selection of advertising channels and marketing activities [21]. In addition, the brand on assets also shows that it has some assets, which proves the brand value on three levels, namely, market level, demander level, and capital level. The income formed by the above activities is called brand value. Yu et al. pointed out that three perspectives can be unified in a theoretical framework. Based on the direct impact of nonmarketing strategies and enterprise marketing strategies on the brand, these nonmarketing strategies involve competitor strategies, 4P combination strategies, lifestyle, consumer values, market environment, etc., so as to arouse the demand of the demander, Therefore, the “ideas” of brand demanders have an impact on enterprise output and performance, including capital market performance and product market performance. Figure 3 shows the three-dimensional perspective of the brand value.Figure 3
Three-dimensional perspective of brand value.


## 4.2. University Brand Value Service Model

The brand value of colleges and universities is directly related to the level of brand knowledge and understanding of the demander. Zhong et al. pointed out that brand awareness should be reflected from two different aspects: (i) external brand communication and (ii) enterprise brand [22]. Furthermore, the brand value should be reasonably divided into brand identification and brand memory, as shown in Figure 4.Figure 4
University brand value model.Based on the achievements of scholars in the study of brand value and service value, the following university brand values are defined here [23]. The brand value of colleges and universities is that the brand of colleges and universities forms a kind of cognition of the brand of colleges and universities through long-term interaction and communication with employers and students, which can promote colleges and universities to have good preferences and contacts, so as to strengthen the brand popularity and loyalty of colleges and universities [24, 25].


## 4.3. Construction of Dynamic Evaluation Model of University Brand Value Based on Analytic Hierarchy Process

### 4.3.1. Constructing the Dynamic Evaluation System of University Brand Value Based on Analytic Hierarchy Process

The analytic hierarchy process (AHP) selected in this paper belongs to the subjective decision-making method. After the index weight is clear, it is decomposed into the hierarchical structure model into target layer, criterion layer, and index layer. When establishing the university brand value evaluation model based on analytic hierarchy process, we should first build different levels in this model, and then statistically analyze the factors at different levels, so as to clarify the overall goal of each factor, that is, the weight of university brand value, as shown in Figure5.Figure 5
Evaluation system of university brand value based on analytic hierarchy process.


### 4.3.2. Calculate Index Weight

According to the concept and application process of analytic hierarchy process given above, the weights of different indicators in the university brand value index system are calculated according to this process, as shown in Table2.Table 2
Primary index judgment matrix and index weight.
AB1B2B3B4The weightB112130.53B221/321/30.21B31/21/2110.12B4211/21/20.14(1) Primary Index Weight. Evaluation model of university brand value target level based on Analytic Hierarchy Process:(3)A=0.53B1+0.21B2+0.12B3+0.14B4.(2) Academic Reputation Index Weight. The academic reputation index weight of each index is calculated using Table 3.Table 3
Academic reputation judgment matrix and weight of each index.
B1C11C12C13The weightC11121/20.42C121/211/30.27C1321/310.31Single-level evaluation model of academic reputation:(4)B1=0.42C11+0.27C12+0.31C13.(3) A Single-Level Evaluation Model of Academic Reputation. The teacher resource judgment matric and index weight are shown in Table 4.Table 4
Teacher resource judgment matrix and index weight.
B2C21C22C23The weightC21111/20.17C2231/210.54C2321/320.29Single level evaluation model of teacher resources:(5)B2=0.17C21+0.54C22+0.29C23.(4) Weight of Comprehensive Indicators of Teaching Quality. The teaching quality judgment matrix and index weight are shown in Table 5.Table 5
Teaching quality judgment matrix and index weight.
B3C31C32C33The weightC31131/20.35C321/2110.16C33221/30.49Single-level evaluation model of teaching quality:(6)B3=0.35C31+0.16C32+0.49C33.(5) Weight of Comprehensive Indicators of Talent Training. The talent training index and weight matrix are shown in Table 6.Table 6
Talent training index and weight matrix.
B4C41C42C43The weightC411330.59C421/3120.25C431/31/210.16Single-level evaluation model of talent training:(7)B4=0.59C41+0.25C42+0.16C43.Through the above calculation, it can be concluded that in the dynamic evaluation system of university brand value based on analytic hierarchy process, the weights of the first-class indicators academic reputation, teacher resources, teaching quality, and talent training are 0.54, 0.21, 0.12, and 0.14, respectively. Thus, accounting for the highest proportion of academic reputation, which has the greatest impact on the total index weight of the standard level. The weight of the second-level index academic reputation is 0.42, 0.27, and 0.31 for the number of national papers, the number of excellent papers at the school level, and the number of international awards for students, respectively. The index with the highest weight in academic reputation is the number of national papers. This should be noted that among the secondary indicators of teacher resources, the corresponding weights of teacher team structure, teacher strength, and doctoral teachers are 0.17, 0.54, and 0.29, respectively—where the teacher strength has the highest weight.Moreover, among the secondary indicators of teaching quality, the corresponding indicators of the basic knowledge ability, professional and technical ability, and personal practical ability are 0.35, 0.16, and 0.49, respectively. We observed that among which the index with the highest weight is personal practical ability. Similarly, among the secondary indicators of talent training, the corresponding weights of the student employment, innovation ability, and management ability are 0.59, 0.25, and 0.16, respectively—in which the highest weight is allocated to the student employment. The specific weights are shown in Table7:Table 7
Dynamic evaluation model of university brand value based on analytic hierarchy process (AHP).
Ability to manageRule layerThe weightIndex layerThe weightUniversity brand value dynamic evaluation system based on analytic hierarchy processAcademic reputation0.54Number of national papers0.42Number of excellent university papers0.27Number of international award students0.31Teacher resources0.21Structure of teaching staff0.17Faculty0.54Proportion of PhD teachers0.29The quality of teaching0.12Basic knowledge ability0.35Professional and technical ability0.16Personal practical ability0.49Cultivation of talents0.14Students employment0.59The innovation ability0.25Ability to manage0.16The proportion of various indicators in the total target weight is shown in the bar chart in Figure6. Among the primary indicators, the highest proportion is academic reputation, which accounts for 54%, followed by teacher resources, and the lowest proportion is teaching quality, which accounts for 12%. Among the secondary indicators, the highest weight is the employment of students, and the specific weight proportion is shown in Figure 6:Figure 6
Proportion of overall weight of evaluation indicators.The analysis of the data, as shown in Figure6, shows that the highest proportion of the total weight of secondary indicators is student employment C41, accounting for 14.75%, and the lowest proportion is professional and technical ability C32 and management ability C43, accounting for 4%. This shows that when evaluating the brand value of colleges and universities, students’ management ability and professional, as well as, technical ability are not important indicators, and the weight is low in the evaluation.


## 4.3.1. Constructing the Dynamic Evaluation System of University Brand Value Based on Analytic Hierarchy Process

The analytic hierarchy process (AHP) selected in this paper belongs to the subjective decision-making method. After the index weight is clear, it is decomposed into the hierarchical structure model into target layer, criterion layer, and index layer. When establishing the university brand value evaluation model based on analytic hierarchy process, we should first build different levels in this model, and then statistically analyze the factors at different levels, so as to clarify the overall goal of each factor, that is, the weight of university brand value, as shown in Figure5.Figure 5
Evaluation system of university brand value based on analytic hierarchy process.


## 4.3.2. Calculate Index Weight

According to the concept and application process of analytic hierarchy process given above, the weights of different indicators in the university brand value index system are calculated according to this process, as shown in Table2.Table 2
Primary index judgment matrix and index weight.
AB1B2B3B4The weightB112130.53B221/321/30.21B31/21/2110.12B4211/21/20.14(1) Primary Index Weight. Evaluation model of university brand value target level based on Analytic Hierarchy Process:(3)A=0.53B1+0.21B2+0.12B3+0.14B4.(2) Academic Reputation Index Weight. The academic reputation index weight of each index is calculated using Table 3.Table 3
Academic reputation judgment matrix and weight of each index.
B1C11C12C13The weightC11121/20.42C121/211/30.27C1321/310.31Single-level evaluation model of academic reputation:(4)B1=0.42C11+0.27C12+0.31C13.(3) A Single-Level Evaluation Model of Academic Reputation. The teacher resource judgment matric and index weight are shown in Table 4.Table 4
Teacher resource judgment matrix and index weight.
B2C21C22C23The weightC21111/20.17C2231/210.54C2321/320.29Single level evaluation model of teacher resources:(5)B2=0.17C21+0.54C22+0.29C23.(4) Weight of Comprehensive Indicators of Teaching Quality. The teaching quality judgment matrix and index weight are shown in Table 5.Table 5
Teaching quality judgment matrix and index weight.
B3C31C32C33The weightC31131/20.35C321/2110.16C33221/30.49Single-level evaluation model of teaching quality:(6)B3=0.35C31+0.16C32+0.49C33.(5) Weight of Comprehensive Indicators of Talent Training. The talent training index and weight matrix are shown in Table 6.Table 6
Talent training index and weight matrix.
B4C41C42C43The weightC411330.59C421/3120.25C431/31/210.16Single-level evaluation model of talent training:(7)B4=0.59C41+0.25C42+0.16C43.Through the above calculation, it can be concluded that in the dynamic evaluation system of university brand value based on analytic hierarchy process, the weights of the first-class indicators academic reputation, teacher resources, teaching quality, and talent training are 0.54, 0.21, 0.12, and 0.14, respectively. Thus, accounting for the highest proportion of academic reputation, which has the greatest impact on the total index weight of the standard level. The weight of the second-level index academic reputation is 0.42, 0.27, and 0.31 for the number of national papers, the number of excellent papers at the school level, and the number of international awards for students, respectively. The index with the highest weight in academic reputation is the number of national papers. This should be noted that among the secondary indicators of teacher resources, the corresponding weights of teacher team structure, teacher strength, and doctoral teachers are 0.17, 0.54, and 0.29, respectively—where the teacher strength has the highest weight.Moreover, among the secondary indicators of teaching quality, the corresponding indicators of the basic knowledge ability, professional and technical ability, and personal practical ability are 0.35, 0.16, and 0.49, respectively. We observed that among which the index with the highest weight is personal practical ability. Similarly, among the secondary indicators of talent training, the corresponding weights of the student employment, innovation ability, and management ability are 0.59, 0.25, and 0.16, respectively—in which the highest weight is allocated to the student employment. The specific weights are shown in Table7:Table 7
Dynamic evaluation model of university brand value based on analytic hierarchy process (AHP).
Ability to manageRule layerThe weightIndex layerThe weightUniversity brand value dynamic evaluation system based on analytic hierarchy processAcademic reputation0.54Number of national papers0.42Number of excellent university papers0.27Number of international award students0.31Teacher resources0.21Structure of teaching staff0.17Faculty0.54Proportion of PhD teachers0.29The quality of teaching0.12Basic knowledge ability0.35Professional and technical ability0.16Personal practical ability0.49Cultivation of talents0.14Students employment0.59The innovation ability0.25Ability to manage0.16The proportion of various indicators in the total target weight is shown in the bar chart in Figure6. Among the primary indicators, the highest proportion is academic reputation, which accounts for 54%, followed by teacher resources, and the lowest proportion is teaching quality, which accounts for 12%. Among the secondary indicators, the highest weight is the employment of students, and the specific weight proportion is shown in Figure 6:Figure 6
Proportion of overall weight of evaluation indicators.The analysis of the data, as shown in Figure6, shows that the highest proportion of the total weight of secondary indicators is student employment C41, accounting for 14.75%, and the lowest proportion is professional and technical ability C32 and management ability C43, accounting for 4%. This shows that when evaluating the brand value of colleges and universities, students’ management ability and professional, as well as, technical ability are not important indicators, and the weight is low in the evaluation.


## 5. Dynamic Evaluation of University Brand Value Based on Analytic Hierarchy Process

### 5.1. Data Sources

According to the results of this paper, the dynamic evaluation model and index system of the university brand value based on analytic hierarchy process are constructed. According to this method, the brand value of a 211 university in China is evaluated and analyzed by 20 independent students, and the scores are scored according to the evaluation criteria of the university brand value, as shown in Table8. The comprehensive score can be calculated by normalizing the score and substituting it into the evaluation model. The following table shows the evaluation criteria of the brand value of colleges and universities. Note that we assume four levels, and this may vary with respect to the evaluation size and number of factors.Table 8
Evaluation standard of brand value in colleges and universities.
IndicatorsLevelA(>)90B(80–90)C(60–80)D(<60)College brand value levelHigherGoodGeneralThe lower


### 5.2. Dynamic Evaluation Results of University Brand Value

Through the evaluation and scoring of 12 indexes by 20 independent students, we calculate the average value of each index given by all students and list the average scoring of each index, as shown in Table8.According to the average scores, as illustrated in Table9, we can calculate the evaluation score of each index in the criterion layer using the following equations:Academic reputation single level scoring:B1 = 0.42C11 + 0.27C12 + 0.31C13 = 0.42 × 78.4 + 0.27 × 81.9 + 0.31 × 88.5 = 82.476Single level scoring of teacher resources:B2 = 0.17C21 + 0.54C22 + 0.29C23 = 0.17 × 92.1 + 0.54 × 89.6 + 0.29 × 78.7 = 86.864Single level scoring of teaching quality:B3 = 0.35C31 + 0.16C32 + 0.49C33 = 0.35 × 91.8 + 0.16 × 92.3 + 0.49 × 86.4 = 89.234Single level scoring of talent training:B4 = 0.59C41 + 0.25C42 + 0.16C43 = 0.59 × 79.5 + 0.25 × 87.1 + 0.16 × 82.2 = 81.832Dynamic evaluation results of university brand value based on analytic hierarchy process (AHP):A = 0.53B1 + 0.21B2 + 0.12B3 + 0.14B4 = 84.12Table 9
Average student evaluation.
NumberThe evaluation indexAverage1Number of national papers78.42Number of excellent university papers81.93Number of international award students88.54Structure of teaching staff92.15Faculty89.66Proportion of PhD teachers78.77Basic knowledge ability91.88Professional and technical ability92.39Personal practical ability86.410Students employment79.511The innovation ability87.112Ability to manage82.2By substituting the average evaluation scores of 20 students into the dynamic evaluation model of university brand value based on analytic hierarchy process, this paper calculates that the scores of criteria level indicators academic reputation, teacher resources, teaching quality, and talent training indicators are 82.476, 86.864, 89.234, and 81.832, respectively. Compared with the evaluation standards of university evaluation values listed in the above table, the results show that the level of the thought index is “B.” After comprehensive calculation, the total score of brand value of the university is 84.12, which also belongs to “B” level. Based on the analysis of the results, it can be concluded that the overall score of the university is high and has a certain brand value. However, it is weak in talent training and academic reputation. Compared with other universities, the findings reveal that the number of academic papers published is less and its position in the academic field is slightly lower than other universities.From the above two aspects, we conclude that the university should strengthen the academic ability of college students, encourage students to conduct scientific research, publish papers in relevant fields, and win honors in the international field. The improvement of academic reputation is conducive to the improvement of brand value of colleges and universities at home and abroad and plays a certain role in promoting academic research in China. At the same time, there is a relative lack of talent training, and the graduated college students lack management ability and innovation ability. Colleges and universities should improve students’ creativity, formulate courses to spread students’ thinking ability, give full play to students’ imagination and creativity, and create a good research environment for students.


## 5.1. Data Sources

According to the results of this paper, the dynamic evaluation model and index system of the university brand value based on analytic hierarchy process are constructed. According to this method, the brand value of a 211 university in China is evaluated and analyzed by 20 independent students, and the scores are scored according to the evaluation criteria of the university brand value, as shown in Table8. The comprehensive score can be calculated by normalizing the score and substituting it into the evaluation model. The following table shows the evaluation criteria of the brand value of colleges and universities. Note that we assume four levels, and this may vary with respect to the evaluation size and number of factors.Table 8
Evaluation standard of brand value in colleges and universities.
IndicatorsLevelA(>)90B(80–90)C(60–80)D(<60)College brand value levelHigherGoodGeneralThe lower


## 5.2. Dynamic Evaluation Results of University Brand Value

Through the evaluation and scoring of 12 indexes by 20 independent students, we calculate the average value of each index given by all students and list the average scoring of each index, as shown in Table8.According to the average scores, as illustrated in Table9, we can calculate the evaluation score of each index in the criterion layer using the following equations:Academic reputation single level scoring:B1 = 0.42C11 + 0.27C12 + 0.31C13 = 0.42 × 78.4 + 0.27 × 81.9 + 0.31 × 88.5 = 82.476Single level scoring of teacher resources:B2 = 0.17C21 + 0.54C22 + 0.29C23 = 0.17 × 92.1 + 0.54 × 89.6 + 0.29 × 78.7 = 86.864Single level scoring of teaching quality:B3 = 0.35C31 + 0.16C32 + 0.49C33 = 0.35 × 91.8 + 0.16 × 92.3 + 0.49 × 86.4 = 89.234Single level scoring of talent training:B4 = 0.59C41 + 0.25C42 + 0.16C43 = 0.59 × 79.5 + 0.25 × 87.1 + 0.16 × 82.2 = 81.832Dynamic evaluation results of university brand value based on analytic hierarchy process (AHP):A = 0.53B1 + 0.21B2 + 0.12B3 + 0.14B4 = 84.12Table 9
Average student evaluation.
NumberThe evaluation indexAverage1Number of national papers78.42Number of excellent university papers81.93Number of international award students88.54Structure of teaching staff92.15Faculty89.66Proportion of PhD teachers78.77Basic knowledge ability91.88Professional and technical ability92.39Personal practical ability86.410Students employment79.511The innovation ability87.112Ability to manage82.2By substituting the average evaluation scores of 20 students into the dynamic evaluation model of university brand value based on analytic hierarchy process, this paper calculates that the scores of criteria level indicators academic reputation, teacher resources, teaching quality, and talent training indicators are 82.476, 86.864, 89.234, and 81.832, respectively. Compared with the evaluation standards of university evaluation values listed in the above table, the results show that the level of the thought index is “B.” After comprehensive calculation, the total score of brand value of the university is 84.12, which also belongs to “B” level. Based on the analysis of the results, it can be concluded that the overall score of the university is high and has a certain brand value. However, it is weak in talent training and academic reputation. Compared with other universities, the findings reveal that the number of academic papers published is less and its position in the academic field is slightly lower than other universities.From the above two aspects, we conclude that the university should strengthen the academic ability of college students, encourage students to conduct scientific research, publish papers in relevant fields, and win honors in the international field. The improvement of academic reputation is conducive to the improvement of brand value of colleges and universities at home and abroad and plays a certain role in promoting academic research in China. At the same time, there is a relative lack of talent training, and the graduated college students lack management ability and innovation ability. Colleges and universities should improve students’ creativity, formulate courses to spread students’ thinking ability, give full play to students’ imagination and creativity, and create a good research environment for students.


## 6. Conclusions and Future Work

The improvement of brand value of colleges and universities is reflected in the investment of education, the output of talents, and the training process. This paper uses analytic hierarchy process (AHP) to establish a dynamic evaluation system and model of brand value of colleges and universities and selects a number of indicators for evaluation, which can more truly reflect the brand value of colleges and universities. Combined with quantitative analysis and qualitative analysis, evaluate the brand value of colleges and universities as a whole, so that the results can reflect the real value of the data. In the process of empirical analysis, 20 students are selected to score several indicators affecting the brand value of colleges and universities, and the average score is calculated. This value is substituted into the established university brand dynamic evaluation model for calculation. The results show that the comprehensive score of the university is 84.12 and the grade is “B,” which is one of the universities with high brand value in China. We observed that there is a relative lack of talent training, and the graduated college students lack management ability and innovation ability. Furthermore, colleges and universities should improve students’ creativity, formulate courses to spread students’ thinking ability, give full play to students’ imagination and creativity, and create a good research environment for students. The indicators selected in this paper can comprehensively cover all aspects of the brand value of colleges and universities, so the results are of high value and can be applied in practice. In the future, we will evaluate the problem in a large space while considering large number of universities and students. Similarly, other factors should be considered that could more accurately classify the universities brand values.



---

*Source: 7602186-2022-03-23.xml*