Analysis of the Current Status of Financial Management in the Direction of Financial Autonomy of Public Universities in Vietnam

Regarding key schools, the proportion of key schools in the sample accounts for 32%, the proportion of non-key schools mainly accounts for 68%. This proportion is consistent with the overall.

2.2.3.2. Analysis of the current status of financial management towards financial autonomy of public universities in Vietnam

Doubting the factors in the model affecting the financial autonomy of public universities, through the collected data, the author analyzes the correlation of factors affecting the financial autonomy of public universities, specifically through the table

2.32 as follows:

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Table 2.32: β coefficients – assessing the correlation between variables in the research model

Years in operation	Region	Training industry	Key features	Entry point 2009	Entry point 2010	Number of training majors	Classroom area of all types	Total number of permanent lecturers	Ratio of lecturers with PhD or higher	Total revenue in 2009	Land area	Library area	Percentage of lecturers with Master's degree or higher	Dormitory area	Training Links	Teaching CTTT	Financial independence
Number of years of operation dynamic	1.00
Region	-0.23	1.00
Training industry	-0.30	0.54	1.00
Key features	0.05	-0.05	-0.28	1.00
Entry point 2009	0.36	-0.36	-0.37	0.25	1.00
Entry Point 2010	0.41	-0.34	-0.37	0.28	0.97	1.00
Number of training majors	0.18	0.39	0.28	0.13	-0.38	-0.36	1.00
Acreage Classrooms of all kinds	0.44	0.09	-0.02	0.23	-0.02	0.04	0.50	1.00
Total number of permanent lecturers	0.55	0.13	-0.08	0.30	0.06	0.10	0.48	0.75	1.00
Ratio of lecturers with PhD or higher	0.18	-0.32	-0.50	0.59	0.39	0.37	0.07	0.00	0.12	1.00
Total revenue in 2009	0.47	0.19	-0.11	0.50	0.21	0.24	0.37	0.65	0.73	0.27	1.00
Land area	0.14	0.08	-0.09	0.21	-0.40	-0.37	0.47	0.40	0.23	0.05	0.20	1.00
Library area	0.43	-0.06	0.02	0.18	-0.05	0.05	0.63	0.63	0.48	0.22	0.40	0.43	1.00
Ratio of lecturers from MSc and above	0.19	-0.31	-0.33	0.45	0.13	0.15	0.15	0.09	0.09	0.76	0.26	0.03	0.34	1.00
Dormitory area	0.32	-0.16	-0.05	0.13	0.06	0.11	0.28	0.58	0.49	0.19	0.33	0.37	0.65	-0.07	1.00
Mining Link create	-0.06	0.06	-0.22	0.19	0.26	0.23	-0.33	-0.08	-0.17	0.29	0.16	0.06	-0.04	0.09	0.29	1.00
Teaching CTTT	0.37	-0.17	-0.45	0.19	0.00	0.02	0.37	0.39	0.31	0.27	0.26	0.43	0.27	0.16	0.29	0.02	1.00
Financial independence	0.18	-0.24	0.17	0.14	0.18	0.17	-0.06	0.22	0.17	0.09	0.32	0.07	0.19	0.15	0.22	0.24	0.19	1.00

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Source: Data analysis results, using SPSS software - Author synthesized based on the database of appendix 2

The financial autonomy variable is measured by non-state budget revenue/total revenue of public schools. It is recognized that this is only one of the scales showing financial autonomy, but it is a quantified scale and has a basis for analyzing the remaining factors.

After analyzing the collected data, the data in Table 2.32 shows the correlation coefficient β between the variables in the factor. Due to the small sample, the coefficient β >0.15 is statistically significant. The results show that the time of operation of the schools; entrance exam scores in 2009; 2010; classroom area of all types; number of permanent lecturers, total financial revenue are correlated with financial autonomy. No relationship or influence of the remaining factors on financial autonomy was found. For example, if the university opens more training majors, the newly opened majors do not have much training experience, so it is easy to lead to a situation where they cannot recruit students, which will lead to a shortage of revenue, forcing the remaining majors to support revenue to survive, meaning that there is an inverse relationship between the number of majors the school trains and the ability to self-collect. Or the financial autonomy is not influenced or is very little influenced by the region or locality where the school is located (β= -0.24 – the correlation between region and financial autonomy). The land area of the school does not affect financial autonomy, but the area of classrooms that directly generate revenue for the school strongly affects financial autonomy. Through Table 2.32, it seems that the application of advanced programs helps increase revenue for the school.

Based on the data in Table 2.32, the author will select factors that have a close correlation with financial autonomy (β >0.15) for further analysis.

For each factor affecting financial autonomy, the author groups and compares groups of the same factor.

Current status of public assets

One of the prerequisites for public universities to be able to exercise autonomy is existing public assets. Existing public assets include: the school's land area, the floor area of construction directly serving training (specifically: Area of classrooms of all types, library area, laboratory area, practice workshop area), floor area of the school's dormitory. The system of textbooks, lectures, scientific research works, copyrights, etc. However, only the area of classrooms, library area, dormitory area are closely correlated with financial autonomy.

Through analysis, it shows that, in general, the training facilities of schools have been improved a step, but still do not ensure that schools meet the needs of learning and research.

In recent years, the Party and the State have paid attention to investing in education and training, building facilities, and improving equipment... for universities and colleges. Many schools

Benefiting from investment from foreign projects, there are additional facilities such as laboratories, foreign language classrooms, computer systems, etc.

If determined according to the standard of 65 m2 / 1 student, universities and colleges in Hanoi need at least 3,300 hectares; Ho Chi Minh City needs at least 3,100 hectares. Currently, schools in Hanoi have nearly 1,700 hectares, schools in Ho Chi Minh City have about 1,500 hectares. Thus, Hanoi needs to add more than 1,300 hectares of land to existing schools; Ho Chi Minh City needs to add about 1,600 hectares. In general, the whole country, with a scale of nearly 2.2 million students, an average of 65 m2 / 1 student, needs 14,200 hectares, currently there are only nearly 7,000 hectares. Thus, only considering existing schools, the demand

The land area needed is about 7,300 hectares. Many schools in Hanoi and Ho Chi Minh City have an area of less than 2 hectares, such as Ho Chi Minh City University of Architecture (0.6 hectares); Ho Chi Minh City University of Economics and Finance (0.8 hectares); Van Lang University (0.6 hectares). Most schools in the cultural and artistic sectors have small areas (not large enrollment scale) [9].

If calculated for 21 schools in Hanoi in the statistical sample, the area of these schools is only 62 hectares, while the number of students recruited in the two school years 2008-2009 and 2009-2010 is

140,000 students. Thus, the converted area per student is only 44m2 , quite lacking.

much more than the standard presented above. Here, we only mention the land area allocated to each student, not mentioning the land area serving the training process, such as libraries, laboratories, practice rooms, computer rooms, etc. Most schools are still too lacking, unable to meet the needs of teaching and learning according to modern methods to meet quality standards like countries in the region and in the world.

Due to the increasing demand for learning in society, the requirements of socio-economic innovation and international integration pose many new problems, so the shortage of lecture halls, classrooms for students, lack of teachers' offices, lack of textbooks, documents, and lack of learning facilities is still common in most universities and colleges. The training program is outdated and does not integrate into the international training field. In fact, the State's investment sources for university programs in this field through target programs are still very limited. In recent years, the investment rate for target programs accounts for about 5.5-5.8% of total state budget expenditure and about 2%-3% of total social expenditure for universities. With that investment rate, universities are unlikely to be able to conduct research to build and perfect the system of programs, textbooks, and have a modern learning material system, updated with domestic and international situations.

Analysis of the group of indicators to assess the current state of public assets of the school affecting the ability to be financially autonomous has a correlation including: classroom area of all types, library area, dormitory area. The results of data analysis show (see table 2.33).

Table 2.33: Classroom area, library area, dormitory area affect financial autonomy

Classroom area of all types (m 2 )

Financial autonomy ratio corresponding
	43%
From 3001 - 7500	41%
From 7501 - 15000	58%
Greater than 15001	63%
Library area (m2)
Under 1000	43%
From 1001 - 2500	52%
From 2501 - 6000	55%
Greater than 6000	56%
Dormitory area
Under 4000	26%
From 4001 - 10,000	61%
From 10,001 – 20,000	62%
Greater than 20,000	62.5%

Source: Data analysis results, using SPSS software - Author synthesized based on the database of Appendix 2

It can be said that the area of classrooms of all kinds is the main income generating asset of schools, when the area of classrooms of all kinds is larger, the schools have facilities and locations for training. In the current conditions of Vietnam, the ability to apply information technology through the internet is widespread, universities invest in libraries, or dormitories to create better conditions for students to acquire knowledge. From there, it is possible to increase other sources of income besides the state budget.

Current status of teaching staff

Through the teaching staff, it is possible to evaluate the quality of training in the process of building the brand of each school and thereby attract students to these schools. This greatly affects the construction of policies on non-budgetary revenues.

The statistical data of 50 sampled universities, the structure of lecturers and staff of the schools affecting the ability of financial autonomy, are presented in the following table 2.34:

Table 2.34: Teaching staff impact on autonomy

Full-time lecturer (person)

Financial autonomy ratio corresponding
Under 100	50%
From 101 - 200	52%
From 201 - 300	55%
From 301 – 500 Greater than 500	55.6% 58%
Percentage of lecturers with qualifications from Master's degree or higher
Under 40%	56%
From 40.1% - 60%	56%
From 60.1% - 85%	58%
Greater than 85%	58.5%

Source: Data analysis results, using SPSS software - Author synthesized based on the database of Appendix 2

The higher the ratio of lecturers to Masters (including: number of PhDs/PhDs, Associate Professors, Professors), the more autonomy tends to increase.

Responding to the needs of educational development, along with the increase in the number of colleges and

Universities, the number of students and lecturers in schools also increased gradually over the years.

In the 1987-1988 school year, the total number of lecturers nationwide was 20,212, of which only 526 were professors and associate professors. By 2008-2009, the number of lecturers had increased to 61,190 and the number of professors and associate professors had reached 2,286. The number of doctoral and master's degrees also increased to improve the quality of training. In 1991, master's degree training was conducted. By 1997, the whole country had 3,802 master's degree lecturers. After 10 years of training, in 2009, the number of master's degree lecturers had increased to 22,831, 6 times higher than in 1997.

However, the growth rate of the number of lecturers who are Professors and Associate Professors is only concentrated in public universities in large cities (Hanoi, Ho Chi Minh City), which is one of the factors that create deep expertise to attract learners in different professions, leading to the development and economic restructuring not being as expected. This factor is also affected by the nature of the income. The payment for Professors and Associate Professors in universities in particular and society in general is large. Therefore, the high rate of Professors and Associate Professors cannot confirm the high financial autonomy, because in reality, these lecturers mainly train and guide Masters and PhDs (the number of students enrolled in this training system is small compared to university training).

Public university brand

With the current situation in Vietnam, the measurement of the brand of public universities is very limited. The author has pointed out four measurements as follows: entrance exam scores of public universities, whether the university is a key university according to the classification of the Ministry of Education and Training, the number of students of public universities who find jobs in their field of study after graduation, especially reducing the situation where employers have to retrain, and whether the university conducts training according to advanced programs, high-quality programs or not?

The scale of entrance scores of universities over the two years 2009 - 2010 and the number of key schools analyzed shows:

Table 2.35: 2009 entrance scores and the impact of autonomy

Entrance exam scores year

2009

Financial autonomy ratio corresponding
From 13 points – 15 points	44%
From 15.1 points – 17 points	59%
From 17.1 points – 19 points	57%
From 19.1 points – 22 points Greater than 22 points	57.5% 58%

Source: Data analysis results, using SPSS software - Author synthesized based on the database of Appendix 2

In recent years, the entrance exam scores of many schools are low. The Government's policy is to use 3 subjects in the entrance exam, the knowledge used in the entrance exam is basic knowledge. However, looking at the data table 2.35, a surprising thing is that the knowledge used in the entrance exam is basic knowledge, but many schools have an average score of 3 subjects below 15 points (Vietnam's scale is 10 points), but besides that, there are many schools with quite high entrance scores, for example, the University of Economics - Hanoi National University, National Economics University, University of Construction, University of Education...

It can be said that this measure is difficult to convince developed countries, however, currently, according to the author's subjective opinion and according to statistics: universities with high entrance scores are all schools that mostly select excellent students and their chances of getting a better job after graduation are synonymous with the ability to evaluate the brand of that university better.

Schools with admission scores ranging from 15.1 to 17 points and the highest bracket in the statistics appear to have a higher degree of autonomy than the other groups. The autonomy corresponds to the level of

The score from 19.1 to 22 points is 57.5%. It can be said that schools with high entrance scores are more highly regarded and therefore have better financial autonomy.

Current status of advanced training programs of public universities

According to the Prime Minister's decision on the project "Training according to advanced programs at some Vietnamese universities in the period 2008 - 2015" dated October 15, 2008, the criteria for identifying and implementing advanced programs are understood as follows:

 The applied advanced program is a program designed and built by training institutions based on the training program currently being applied at advanced universities in the world (referred to as the original program), including content, methods, training organization and management processes and taught in English; with Marxist-Leninist Science subjects as required for Vietnamese students.

 The original program must be selected from training programs of universities in the top 200 universities in the world in the rankings of prestigious educational associations and organizations in the world or in the top 20% of the best training programs in the rankings of training majors of national or international educational associations and organizations; have advanced content, linked to the socio-economic development orientation of our country and suitable to the implementation capacity of the applied university.

Also according to this decision, the criteria for selecting universities to implement advanced programs are:

Universities are assigned to implement advanced programs when they meet the following criteria:

 The school's advanced training program registration project meets quality standards and is selected according to the general evaluation and selection process prescribed by the Ministry of Education and Training.

 Ensure the quantity and quality of the management staff and permanent lecturers according to regulations, meeting the requirements for implementing advanced quality programs; have a plan for the teaching staff to meet at least 80% of the requirements for the training programs of phase 1, and 100% of the requirements for the training programs of the following phases.

 Ensure facilities are consistent with the training program and teaching staff, strive to prepare adequate equipment and laboratories before teaching specialized subjects.

 Have a specific, feasible plan to ensure funding to implement advanced programs; have the ability to mobilize businesses and other partners to participate in implementing or sponsoring advanced programs.

 Have training experience, especially for the major registered for training under advanced programs; have many achievements in training activities, science and technology activities, innovation in organization and school management. Priority is given to key universities in consideration for

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