Abstract
To respond to the call for the construction of a “double first-class university” in China and implement the “Focus on innovation, focus on enriching the people, and build a moderately prosperous society at a high level” development strategy. Jiangsu Province issued the first round of the “Jiangsu High-level University Construction Program” in 2016. Taking the deepening of the innovation-driven development strategy as the starting point, the main objective of promoting higher education is to strengthen its ability to support economic and social development. In this study, the fuzzy-ANP comprehensive evaluation model is used to create an index system for building high-level universities with Jiangsu Province features. Using this system, high-level university construction in Jiangsu Province is evaluated. The results of the study show that the first round of Jiangsu’s high-level university construction has reached an excellent level and is the most effective in improving the quality of research. In addition, the participating universities are better able to promote socioeconomic development. However, the resources and social reputation of the participating universities are close to the level of excellence. Furthermore, due to the problem of prioritizing research above teaching, the teaching and internationalization levels of the participating universities are rather low.
1. Introduction
In 2021, Chinese Premier Li Keqiang stressed at a symposium on the reform and innovation in higher education that a high level of education is an important reflection of a country’s comprehensive competitiveness. Jiangsu Province, a powerful province in China’s higher education sector, has taken the lead in initiating the construction of high-level universities in 2016. Through the use of evaluation to promote construction, the first round of the construction of high-level universities in Jiangsu, including universities selected for the “double first-class” construction and provincial universities whose comprehensive operation level is among the top 100 in China, has been successfully completed in 2020. Therefore, an evaluation of the overall performance of the first round of high-level university construction in Jiangsu is not only valuable for Jiangsu Province to summarize its experience and carry out subsequent construction, but also sets a benchmark for the construction of high-level universities in China, and further contributes to the advancement of international higher education. Previous research on university evaluation has mainly focused on the selection of evaluation objects, the construction of evaluation dimensions, and the determination of evaluation criteria. In terms of the selection of evaluation objects, scholars have distinguished institutions of higher education into comprehensive, science, arts, and engineering universities according to the proportion of disciplines, or into research, research-teaching, teaching-research, and teaching universities according to the scale of university research [1]. In addition, there is a group of universities involved in government-led university construction projects. Scholars have selected a certain number of universities of the same type and in the same region to evaluate their discipline development, faculty teams, and research activities [2, 3], which is conducive to an understanding of the development of universities as a whole. By contrast, others who use colleges within universities to evaluate the research management and financial situation of colleges [4], which can pinpoint the internal problems of universities and facilitate the development of specific optimization measures.
There are two main types of university evaluation dimensions constructed by existing studies: one is the evaluation of a single dimension such as research situation, teaching situation, faculty team, and social service situation [5–8]. The other is to construct a multidimensional evaluation model that starts with multiple dimensions and provides a comprehensive evaluation of the study population [9–11]. The evaluation of a single dimension is relevant and provides a concrete and intuitive reflection of the strengths and weaknesses of the university. But university development is often multidimensional at the same time, and the dimensions can influence each other. As a result, evaluating from a single dimension makes it impossible to account for the influence of other factors on the assessment objectives and to analyze the overall state of university development in a methodical manner. Further research can reveal that academics focus on performance evaluation research from the dimension of the research situation of universities but less on comprehensive evaluation of their teaching and research performance from the perspective of their functions and social contributions.
In terms of determining assessment criteria, the academic community tends to directly assess university performance in terms of quantifiable evaluation dimensions such as research and teaching output, using QS World University Rankings, Times Higher Education (THE) World University Rankings, Shanghai Ranking’s Academic Ranking of World Universities (ARWU), and USNEWS rankings in the United States, which have great international influence [12]. The academic community has gradually changed from copying international university evaluation criteria to localizing international standards, adopting international standards in terms of student learning activities, faculty, and research, and integrating domestic evaluation criteria for teaching outputs and social services [13]. Scholars tend to highlight the quality of development, services, and contributions of universities, so different evaluation criteria are applied for different types of universities with different construction goals, and a multi-objective optimization approach can be used in the criteria making [14, 15].
In terms of research methods, scholars have mostly used quantitative analysis methods such as PCA methodology, DEA model, BSC method, MCDM method, QFD method, and Type-2 fuzzy set method to evaluate the performance of universities as a whole [5, 6, 16, 17]. However, at present, the domestic and international research on conducting comprehensive multidimensional evaluations of high-level university groups in provincial areas is rare. In fact, the construction of high-level universities is mostly coordinated by each province. Hence, it is especially important to construct evaluation standards adapted to each province’s development needs and to make a comprehensive evaluation of the overall construction of high-level universities in each province. In addition, the construction of universities needs to be assessed in multiple dimensions, but not all dimensions have quantifiable evaluation criteria. Moreover, compared with universities in science and technology, it is difficult to quantify the progress of universities in liberal arts in terms of talent cultivation and teaching output [18].
In light of the above considerations, the index system of the first round of high-level university construction in Jiangsu Province is established in this study using the fuzzy-ANP comprehensive evaluation model and on the basis of High-level University Construction Program in Jiangsu Province and existing literature analysis. In this study, 19 experts and scholars in the field of higher education were invited to participate in the investigation and validation, and the first round of the overall construction of high-level universities in Jiangsu was evaluated on the basis of expert scoring. The rest of this paper is organized as follows. Section 2 describes the setting of the index system. Section 3 introduces the fuzzy-ANP comprehensive evaluation model and analyzes its applicability. Section 4 analyzes the evaluation results. Finally, Section 5 summarizes and elaborates the conclusions of the study.
2. Construction of Evaluation Index System
Educational resources, teaching level, research quality, social reputation, and internationalization level are the five important aspects of assessing high-level universities. For a high-level university, it is the development path for the university to continuously realize its value by improving teaching and internationalization, focusing on research quality, and forming a highly recognized social reputation based on the existing resources [19]. Therefore, in this paper, the secondary indicators involved in the construction of high-level universities in Jiangsu Province are described in five dimensions: educational resources, teaching level, research quality, social reputation, and internationalization level.
2.1. Educational Resources
Educational resources occupy a dominant position in the strategic development of universities. According to the resource dependence theory, the educational resources of universities can be briefly divided into physical, financial, and human resources [20]. Adequate educational resources are the cornerstone of daily teaching in universities [21, 22]. The construction of high-level universities requires sufficient material resources and teaching funds to guarantee basic teaching [23, 24]. At the same time, universities integrate high-quality faculty resources and form teamwork faculty group organizations to carry out teaching and research activities [25]. Therefore, the following three aspects can be considered in improving the educational resources.
2.1.1. Funding Input
The amount of funds invested by universities is the measure of whether the construction of high-level universities in Jiangsu can run efficiently and stably. According to “Provisional Measures for the Management of Comprehensive Award and Subsidy Funds for the Construction of High-level Universities in Jiangsu Province,” for specific scientific research projects, Jiangsu Province implements the form of matching funds subsidy for the construction of universities after the completion of the target requirements. The subsidy is canceled for the projects that do not reach the target. To a certain extent, this drives universities to turn pressure into motivation, on the one hand, to broaden the funding channels of universities and accumulate social donation income by enhancing the reputation of universities, and, on the other hand, to optimize the allocation of education expenditure and focus on the cost efficiency of funding input. According to the Financial System of Universities, this paper subdivides the index into four indicators, including the growth amount of total assets, the total growth amount of four expenses, the growth amount of education expenditure, and the ratio of social donation amount to total income.
2.1.2. Faculty Quality
In constructing high-level universities in Jiangsu, scientific research has gradually developed into a function that distinguishes universities from daily teaching [26, 27]. In this context, a scientific teacher-student ratio can provide solid faculty support for students [28]. In addition, faculty construction should be balanced between quantity and quality, and the percentage of teachers with senior faculty titles, the proportion of teachers with Ph.D. degrees, and the number of distinguished talents can reflect the construction of university faculty to some extent. Accordingly, this paper incorporates four indicators into the evaluation system; these indexes are the faculty-student ratio, the proportion of teachers with senior titles to the total number of teachers, the number of outstanding talents, and the proportion of teachers with doctoral degrees.
2.2. Teaching Level
“The Outline of National Medium and Long-term Education Reform and Development Plan (2010–2010)” states that universities should improve the quality of talent cultivation in all aspects. Additionally, teaching is the primary content of teachers’ assessment, and quality teaching level is the guarantee for promoting high-quality development of higher education [29]. Therefore, this study reflects the teaching level in the following three aspects.
2.2.1. The Situation of University Discipline Construction
According to the “Implementation Plan of Jiangsu University Advantageous Discipline Construction Project,” the participating universities of Jiangsu high-level university construction should strengthen the development of key disciplines and improve the overall teaching quality of the university through discipline development. The academic discipline construction results reflect how closely the high-level university construction is integrated with social development. Therefore, the participating universities of Jiangsu high-level university construction should realize the dynamic adjustment of degree points. Doctoral and master’s degree points are flexibly increased or decreased according to the development prospect of related industries and the needs for social and economic development. The situation of university discipline construction should be subdivided into six indexes to evaluate high-level university construction in Jiangsu Province; these indexes are proportion of doctoral teachers, increase of doctoral points, increase of master’s points, increase of national key disciplines, increase of provincial and ministerial key disciplines, and increase of disciplines ranked in the top 1% of ESI.
2.2.2. Quality of Student Source and Cultivation
Cultivating high-quality talents requires the support of high-quality students [30]. The quality of cultivation of high-quality students is a direct reflection of the effectiveness of high-level university construction. Jiangsu high-level university construction project requires participating universities to innovate talent cultivation mode, optimize, and reform curriculum and teaching methods. We encourage universities to pursue cultivating quality rather than cultivating quantity [31]. It seeks to cultivate high-level comprehensive talents at multiple levels through high-level university construction projects. Quality of student source and cultivation should be subdivided into seven indexes to evaluate high-level university construction in Jiangsu Province; these indexes are the average score of undergraduate freshmen, the ratio of graduate students to undergraduate students, the ratio of international students to undergraduate students, the number of national 100 outstanding doctoral dissertations, the number of provincial outstanding undergraduate dissertations and master’s degree dissertations, the number of student innovation competition awards, and the number of international and domestic accredited undergraduate majors.
2.2.3. Teaching Output
The talent and intellectual advantages of an excellent teaching team are reflected through teaching output. Excellent teaching output can, on the one hand, reflect the solid teaching foundation function of universities and attract excellent students. On the other hand, it can concentrate resources and attract social and government resources to flow into discipline construction and professional construction, forming a virtuous circle and enhancing the core competitiveness of universities [32]. According to the high-quality teaching resources ensemble of the Ministry of Education, teaching output should be subdivided into six indexes to evaluate high-level university construction in Jiangsu Province; these indexes are the number of provincial and ministerial teaching achievement awards, the number of high-quality courses of the Ministry of Education, the number of provincial and ministerial teaching projects, the number of provincial and ministerial teaching platforms, the number of provincial and ministerial teaching courses, and the number of provincial and ministerial teaching materials.
2.3. Research Quality
According to the “National Medium- and Long-term Education Reform and Development Plan (2010–2010),” universities should improve scientific research and are required to improve the innovation and quality-oriented scientific research evaluation mechanism. Despite the fact that certain parts of creating a top-tier institution have competing goals, the primary task of scientific research evaluation is to measure the scientific and social values of scientific research activities [7, 15]. Accordingly, this study improves the research quality from the following three aspects.
2.3.1. Scientific Research Input
Universities are resource-dependent in conducting scientific research activities and need to absorb external research resources continuously. Generally speaking, universities obtain research investment funds through government financial education funding income, tuition income from research grants, income from the transformation of research results, income from social donations, and fund investment and bank loans [7, 23, 33]. In recent years, under the policy background of the Chinese government requiring universities to expand their enrollment, the cost of running universities has increased, and the ceiling of scientific research investment determines the ceiling of scientific research achievements in universities to a certain extent. Therefore, scientific research input should be subdivided into three indexes to evaluate high-level university construction in Jiangsu Province; these indexes are the total amount of scientific research funds, the incremental number of entrusted scientific research funds undertaken by enterprises and institutions, and the incremental number of entrusted scientific research projects undertaken by enterprises and institutions.
2.3.2. Scientific Research Output
Under the rated research investment, the research results achieved by universities with coordinated funding and manpower allocation are measured by research output indicators. The number of authorized patents in universities is an important indicator to measure the degree of close integration between universities and industry [34, 35]. Universities strengthen the transformation of scientific research results into patent R&D, control the quality of patents, and improve the application rate of patents, which can ultimately improve the efficiency of university scientific research output in serving economic and social development. Therefore, scientific research output should be subdivided into six indexes to evaluate high-level university construction in Jiangsu Province; these indexes are the total number of authorized patents, the total number of international and domestic high-level scientific research papers, the total number of national- and provincial-level scientific research platforms, the total number of national- and provincial-level scientific research projects, the number of national- and provincial-level scientific research awards, and the number of international major awards.
2.3.3. Scientific Research Output Efficiency
On February 20, 2020, the Chinese Ministry of Education and Ministry of Science and Technology issued “Several Opinions on Regulating the Use of SCI Paper-related Indicators in Higher Education Institutions to Establish Correct Evaluation Guidance,” which emphasized that scientific research activities in universities should be transformed from focusing on quantity to focusing on quality. In this background, participating universities should pay more attention to the practical application value of scientific research results. The number of citations of high-level theses is not only a sign of the transformation of scientific research output in the field but also a direct reflection of the quality of theses and the value of the contribution of the construction universities in each research field [36]. Moreover, according to “Measures for Sample Inspection of Undergraduate Theses (for trial implementation),” the results of sample inspection of dissertations directly affect the allocation of educational resources. In addition, the patent conversion rate reflects the practical application efficiency of the scientific research output of universities. Therefore, in this paper, scientific research output efficiency should be subdivided into three indexes to evaluate high-level university construction in Jiangsu Province; these indexes are the total number of citations of international and domestic high-level scientific research papers, passing rate of undergraduate and postgraduate dissertation sampling inspection, and patent conversion rate.
2.4. Social Reputation
Social reputation is one of the core competencies of high-level universities, which largely determines the future development of universities. Excellent social reputation not only attracts high-quality students and high-level teachers to universities but also expands the endowment income for universities. Therefore, this study is carried out through the following two aspects.
2.4.1. Service Contribution
Promoting social development is one of the construction goals of colleges and universities, and the construction of high-level universities requires colleges and universities to cultivate outstanding talents who can promote social development and serve as role models. The service contribution of outstanding alumni to the society can highlight the effectiveness of moral education work of colleges and universities, and the reputation effect brought by them is of great significance for colleges and universities to enhance social recognition [37]. Meanwhile, the approval of provincial and ministerial leaders and departments to adopt the results of university decision-making consultation is also a channel for universities to solve social problems and provide decision support for social development [38]. In addition, under the policy background of “stable employment” and “employment preservation” in Jiangsu, the construction of universities to deliver high-level talents to the society is also a reflection of their service contribution. Therefore, service contribution should be subdivided into three indexes to evaluate high-level university construction in Jiangsu Province; these indexes are the number of distinguished alumni, the number of instructions adopted by provincial and ministerial leaders and departments, and the proportion of graduates employed in Jiangsu.
2.4.2. Social Ranking
Universities vary significantly across the country due to their history of establishment and regional cultural traditions. Correspondingly, the rankings of universities in different countries and regions have their own focus and specificity [39–41]. However, internationally recognized ranking rankings can still reflect some of the problems of university development and have significant implications for building high-level universities [42]. This index system selects four highly recognized international rankings to evaluate high-level university construction in Jiangsu Province; these indexes are changes in Times Higher Education World University Rankings, changes in QS World University Rankings, changes in Softbank Academic Ranking of World Universities, and changes in USNEWS Rankings.
2.5. Internationalization Level
The internationalization level is an important way for universities to benchmark with the world’s top universities and to enhance their international reputation. Moreover, the international exchange and cooperation of high-level universities is on the one hand conducive to the integration of resources among universities and the realization of complementary advantages. On the other hand, it can achieve both the localization of high-level university construction and high-quality development with an international vision. Therefore, international communication and cooperation is included as an evaluation index in this study.
2.5.1. International Cooperation and Communication
Promoting universities to improve their internationalization level and achieve world class is the goal of the construction of high-level universities in Jiangsu. The internationalization level of universities determines their influence and discourse in the international society [43]. The construction of Jiangsu high-level university should improve the internationalization collaborative development mechanism, integrate the internationalization concept and strategy into all elements such as departments and faculties as well as teachers, students, and managers within the university, and actively establish a smooth international exchange channel for teachers, students, and foreign introduced talents. For this reason, this index system selects five indexes to reflect the internationalization level comprehensively; these indexes are the number of international cooperation research platforms, the number of international conferences held, the internationalization level of faculty, the number of international joint training programs for students, and the proportion of students studying and visiting abroad.
By combining the experts’ opinion (The Delphi expert group consists of 21 experts in the field of higher education. Three rounds of expert opinions were solicited, 21 questionnaires were distributed in each round, and 21 valid questionnaires were returned in each round. After multiple rounds of evaluation and scoring by experts, 54 tertiary indicators were identified and then divided into 12 secondary indicators and 5 primary indicators based on the correlation between indicators.) using the Delphi method, the index system of the first round of high-level university construction in Jiangsu Province is constructed and is shown in Table 1.
3. Evaluation Model
The ANP is a decision analysis method that combines quantitative and qualitative analysis. Based on the analytic hierarchy process (AHP), feedback and dependency relationships between levels and internal elements are considered [44], while the fuzzy comprehensive evaluation method, which is based on fuzzy mathematics’ membership theory, effectively examines qualitative indexes [45, 46]. Therefore, the fuzzy-ANP comprehensive evaluation model provides numerous advantages in terms of evaluation and analysis. In the process of construction of Jiangsu high-level university, the construction subjects exhibit a clear hierarchy. In other words, all aspects of university construction present obvious dependency relationships. Therefore, the influencing factors of Jiangsu high-level university construction have typical hierarchical and dependency relationships. Therefore, its index system forms an organic whole with hierarchical network structure. Some indicators cannot be quantified because they present a fuzzy character in terms of values. Therefore, it is highly scientific and applicable to evaluate the construction of Jiangsu high-level universities by using the fuzzy-ANP comprehensive evaluation model.
3.1. Constructing the Network Structure of ANP
In the network structure of Jiangsu high-level university construction, the control layer contains the target and criteria; the target is A, and the criteria are the first-level indexes of the index system, including B1, B2, B3, B4, and B5. The network layer includes twelve sets of elements that correspond to second- and third-level indexes of the index system. These sets are C01, C02, C03, C04, C05, C06, C07, C08, C09, C10, C11, and C12. Among them, both the elements and the elements may interact and influence each other, according to which the network structure of ANP is constructed as in Figure 1.
3.2. Determination of the Index Weight
The weights of each indicator were determined with the help of ANP and Delphi expert scoring. The specific process is as follows.
Step 1. build a super matrix. The interactions between the network and control layers are evaluated, the internal relationships between the set of elements and the elements are determined, and the corresponding weights are assigned to the control layer guidelines. The importance of the indicators and guidelines is determined by fixed guidelines while ensuring the independence between the elements. As shown in Table 2, the importance levels among the indicators, using the scale method of 1–9, were compared, after which the AHP method was applied to obtain the weights.
Then, the unweighted supermatrix and the indicator element weights are obtained. The normalized eigenvector values are able to be obtained by the eigenroot method; based on the two-by-two judgment matrix, the super matrix is obtained as follows:
The limit matrix of the weighted supermatrix is obtained by taking infinite powers of the weighted supermatrix . When and the limit converges uniquely, the column vectors in the limit matrix are the weights of each participant index.
Step 2. construct the weighted matrix and weighted super matrix. Under the criterion , the importance of the relative criterion of element is compared to obtain a normalized row sequence vector such as that a weighted matrix is obtained as follows:If the two elements have no interaction with each other, then . The weighted super matrix is constructed as follows:
3.3. Determination of Evaluation Rating and Rules
The evaluation rating is assumed as follows: . The evaluation rating is divided into four grades: good, general, relatively poor, and poor.
The fuzzy relation matrix is defined as follows:
Among them, is a member of the index number of the level number , .
3.4. Determination of the Comprehensive Evaluation Level
A comprehensive evaluation vector is established by the fuzzy comprehensive operation of the fuzzy relation matrix of the set of weights.
In the comprehensive evaluation vector of Jiangsu high-level university construction, it equals to 4. Therefore, the final score obtained by the weighted average method is .
4. Empirical Research
4.1. Weight Calculation
The weights of the indexes are calculated using the above weight calculation method and the super decision software, as shown in Table 3.
Table 3 shows that, among the first-level indicators, the indicator with the largest proportion of weight is research quality, with 58.8%. The next in order is 17.5% for educational resources, followed by 12.2% for teaching level, 6.8% for social reputation, and 4.6% for internationalization level. It can be seen that the index of research quality has the greatest influence on the performance evaluation of the construction of high-level universities in Jiangsu.
In addition, according to Table 3, it can be found that among the second-level indicators, the discipline construction situation has the highest weight of 19.9%, followed by research output of 16.5% and research input of 12%. The lowest weight is service contribution of 0.8%. This indicates that discipline construction, research output, and research input are the main factors affecting the performance evaluation of Jiangsu high-level university construction. By comparison, the weight of service contribution, international cooperation and exchange, social ranking, and material resources are less than 5%. This indicates that these indicators have a small influence on the performance evaluation. On the other hand, the low weight of service contribution indicates that universities can provide decision-making advice to government departments, but it has limited effect on the construction of universities themselves. Moreover, the low weight of international cooperation and exchange and social ranking reflects that the construction of high-level universities in Jiangsu Province is in line with the influential international standards but not limited by them. It also reflects that the construction of Jiangsu high-level universities refers to social ranking but does not blindly pursue the ranking.
Furthermore, based on the weighting of the three-level indicators in Table 4, it can be stated that the indicators with the highest weighting are primarily concerned with evaluating teaching quality and research quality. The number of disciplines in the top 1% of the global ESI ranking, with a weighted of 10.4 percent, has the largest impact on performance evaluation. The number of major international awards won (8.9%), the overall amount of research money (8.2%), the total number of citations of foreign and domestic high-level research publications (7.7%), and the number of national important disciplines (5.3%) are the next most influential indicators.
4.2. Fuzzy Comprehensive Calculation
Selecting a fuzzy measure set , its fuzzy measure benchmark value is .
Assuming that the decision maker’s preference coefficient (Decision maker’s preference coefficient reflects the degree of decision maker’s preference for the upper and lower bound utility values of the indicator interval, representing whether the decision maker values the indicator more highly or less highly.) , the normalized values of the first-level index weights are obtained by normalizing the indicators in Tables 3 and 4 as . The normalized values of the second-level index weights are , , , , .
After the data statistical results were validated by experts, the initial evidence credibility of the second-level indicators of the performance evaluation of the construction of high-level universities in Jiangsu was given. The results of the initial evidence credibility assignment of the second-level indexes are shown in Table 4. The elements in each row of Table 4 are first multiplied by the normalized weight corresponding to each second-level index to obtain the basic credibility of the second-level indexes. Then, the second-level indexes, first-level indexes, and the comprehensive evaluation score of the construction performance of Jiangsu high-level universities were further calculated, which are shown in Tables 5–7.
The final result of the comprehensive evaluation of the construction performance of Jiangsu high-level universities is .
Due to the result , the performance grade of Jiangsu high-level university construction is obtained between general and good; that is, the construction of Jiangsu high-level university basically reaches the good level on the whole.
The data results in Table 6 show that among the five dimensions of the construction of Jiangsu high-level universities, the evaluation score of research quality is the highest, and the construction results reach a good level. Next, in order, are educational resources, social reputation, teaching level, and internationalization level, and the construction results reach the general level. The scores in Table 6 show that the universities participating in the construction of Jiangsu high-level universities have achieved remarkable results in improving the quality of scientific research, although they have made promising achievements in educational resources, social reputation, teaching level, and internationalization level, but there is still some room for improvement. This necessitates a greater integration of resources, a faster pace of building, and an overall improvement in the overall effect of Jiangsu high-level university construction.
As can be seen from Tables 4 and 5, the secondary indexes that reach the good level are research input, research output efficiency, research output, faculty quality, and funding input in order. The high score of scientific research input is mainly attributed to the expansion of the total amount of scientific research funds of the participating universities and the increase of research funds entrusted by enterprises and institutions. The total number of international and domestic high-level scientific research papers cited, the conversion rate of authorized patents, and the passing rate of undergraduate dissertation sampling contribute the most to the efficiency of scientific research output, which reflects that the scientific research achievements of participating universities are highly recognized in the world, and the conversion rate of scientific research achievements is high. Meanwhile, the participating universities have done a good job in guiding undergraduate students to standardize academic work. Among the three levels of indicators under scientific research output, except for the number of major international awards, which is close to but not yet at the good level, the other five indicators, including the total number of authorized patents, have reached a good level, which indicates that the overall scientific research output of the participating universities is fruitful, but they should further promote the high-quality development of scientific research and strive to reach the international first-class level. The excellent level of faculty mainly lies in the considerable number of outstanding talents in the participating universities. This reflects that the sufficient number of outstanding talents is the intellectual support to help the participating universities sprint to high level. In the funding input, the growth of education expenditure reaches an excellent level, which helps to provide a pulling effect for the participating universities to expand the quality students.
Further analysis of Tables 4 and 5 also shows that, except for the five second-level indexes mentioned above, all the other secondary indicators reach the general level, in which the social ranking, service contribution, discipline construction, and material resource score are close to a good level. Specific analysis shows that, firstly, the social ranking of the participating universities has been improved in the international and domestic authoritative rankings, but the overall ranking is still far from the international and domestic first-class level. Secondly, among the service contributions of participating universities, outstanding alumni bring a good accumulation of social reputation for universities, but universities have limited consulting suggestions adopted by provincial and ministerial leaders and departments. This reflects that colleges and universities should base on the platform of Jiangsu high-level university construction and provide more comprehensive and in-place decision-making consulting services for Jiangsu provincial and ministerial leaders and government departments as much as possible, so as to serve the economic and social development of Jiangsu Province indirectly. Moreover, the employment ratio of graduates staying in Jiangsu needs to be improved. This requires the joint efforts of the Jiangsu government and universities to provide more comprehensive employment support policies for graduates. After that, in the construction of disciplines, the number of doctoral and master’s degrees, national and provincial key disciplines, and ESI top 1% disciplines in participating universities have increased considerably, but the overall growth is relatively average. This requires universities to gather their resource advantages to the direction of university characteristic development and do a good job in the construction of characteristic disciplines. Finally, among the material resources, the area per capita of school buildings, the number of books per student, and the number of repositories and databases are relatively adequate, but the participating universities still need to further improve the material resources to further guarantee the learning, teaching and research activities of students and teachers.
In addition, among the second-level indexes that reach good level, the scores of student source and cultivation quality, teaching output, and international communication and cooperation are relatively low. This indicates that the participating universities have certain problems of emphasizing research and neglecting teaching. Therefore, the output of students’ innovation competition awards, national 100 excellent doctoral dissertations, provincial excellent undergraduate, and master’s dissertations needs to be improved; the output of teaching achievements, high-quality courses, teaching platforms, teaching projects, teaching courses, and teaching materials of the Ministry of Education and provincial ministries is slightly weak; the number of international joint training programs for students, the number of international conferences held, and the number of international cooperative research platforms needs to be increased. Moreover, the university should benchmark itself against world-class universities in terms of faculty construction and student training mode, and cultivate international talents based on Chinese soil.
In summary, the participating universities have achieved more excellent results in the first round of Jiangsu high-level university construction. However, there is still some room for improvement on the whole, especially the teaching level and internationalization level still need to be further strengthened.
5. Conclusion
Based on the first round of “Jiangsu High-level University Construction Program” and the existing literature, this study constructs a comprehensive evaluation index system for the construction of Jiangsu High-level University by using the fuzzy-ANP comprehensive evaluation model and Delphi expert scoring method. We have designed the evaluation index system to be able to comprehensively evaluate the construction of high-level universities in Jiangsu Province. Using this system, the first round of Jiangsu high-level university construction was evaluated regarding educational resources, teaching level, research quality, social reputation, and internationalization level. The empirical results are as follows:(1)The first round of Jiangsu high-level university construction basically reached the good level on the whole. Among them, the best results in improving the quality of scientific research are mainly attributed to the steadily improving efficiency of scientific research output and sufficient investment in scientific research of the participating universities. This indicates that the Jiangsu government and Jiangsu enterprises and institutions have invested enough in providing economic support to the participating universities. Moreover, it provides guarantee for universities to absorb high-quality teachers and research teams and carry out research work. Meanwhile, the improvement of the overall scientific research output efficiency of the participating universities is mainly due to the improvement of the conversion rate of authorized patents in the participating universities. The ability of participating universities in the construction of high-level universities in Jiangsu Province to promote local social and economic development has been enhanced.(2)The resources and social reputation of the participating universities in the first round of Jiangsu high-level university construction have not reached the excellent level. The main reason is that the educational resource, service contribution, and social ranking are not outstanding enough. The school space per student, number of books per student, and number of repositories and databases are still not sufficient compared with the increasing number of students. The participating universities have not done enough to provide consulting and advising services for provincial and ministerial leaders and departments. Although the number of key disciplines, and master’s and doctoral programs has increased considerably, the participating universities as a whole are still lacking in the construction of special disciplines.(3)In the first round of Jiangsu high-level university construction, the teaching and internationalization levels of the participating universities are rather low. There is a lack in student source and cultivation quality, teaching output, and international communication and cooperation. This is mainly attributed to the problem of emphasizing scientific research and neglecting teaching in the participating universities. The teaching achievements of the participating universities at the Ministry of Education and provincial levels, the number of students’ innovation competition awards, and the output of excellent dissertations are not abundant. Moreover, the international research exchange activities of the participating universities need to be increased, and the internationalization level of faculty and student cultivation mode is not enough.
Data Availability
The methodology of this paper is the Delphi expert research method and the fuzzy-ANP comprehensive evaluation method. The authors invited 21 experts and scholars in the field of higher education to participate in the survey and validation. Three rounds of expert opinion were solicited, with 21 questionnaires distributed in each round and more than 18 valid questionnaires returned in each round. After multiple rounds of evaluation and scoring by experts, 54 tertiary indicators were identified and then divided into 12 secondary indicators and 5 primary indicators based on the correlation between the indicators. The fuzzy-ANP comprehensive evaluation method is based on the principle of fuzzy relationship synthesis, which quantifies the influencing elements of the target problem and provides a comprehensive evaluation of the reality of the evaluation object from all angles. Based on the indicators determined by the Delphi expert research method, the authors quantitatively analyze the impact elements of the study on the evaluation of the construction performance of high-level universities in Jiangsu Province and complete the comprehensive evaluation. The data for this paper were obtained from 21 Delphi expert research questionnaires and from a special page on the construction of high-level universities on the official website of the Jiangsu Provincial Education Department (http://jyt.jiangsu.gov.cn/col/col38747/index.html).
Conflicts of Interest
The authors declare that they have no conflicts of interest.
Acknowledgments
This work was supported by the Major Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province (no. 2019SJZDA035), the National Natural Science Foundation of China (71871115), Key Project of the Social Science Foundation of Jiangsu Province (22WTA-019), General Project of Social Science Foundation of Jiangsu Province (22GLB032), and Young and Middle-Aged Academic Leaders of Qinglan Project in Jiangsu Province.