Average Score of Evaluation Scales for Enterprises Participating in Industry Clusters

Table 4.11 shows that the scale of policies for developing the supporting industry is highly appreciated, with an average score ranging from 3.32 to 3.49. When the policies for developing the supporting industry come into practice, especially preferential policies on capital sources, especially bank loans, will help businesses to further strengthen their financial potential.

In recent times, the system of policies and mechanisms of the Government, the State Bank, and the Ministries/Agencies have been focusing on providing very good support for businesses, especially SMEs, such as Decree 39/2018/ND-CP detailing a number of articles of the Law on Support for SMEs [16]; Decree 34/2018/ND-CP on Credit Guarantee Fund for SMEs [17]; Decree 38/2018/ND-CP on investment for innovative start-up SMEs [18]. The system of policies and mechanisms of the State Bank on currency, credit and interest rates. In which, SMEs are a priority group in concentrating capital for production and business, supporting loan interest rates (applying a ceiling on short-term loan interest rates in VND). In addition, SMEs operating in the fields of agriculture and rural areas; export; Supporting industry and high-tech enterprises... are supported by credit policies for this sector of the Government, the State Bank and each locality has policies on investment stimulus; supporting industry and key product development; policies on restructuring agriculture and rural areas.

In recent times, Vietnam has had many mechanisms and policies to support and prioritize the development of this industry such as: "The 2014 Investment Law and Decree No. 118/2015/ND-CP [9] guiding the Investment Law have stipulated that supporting industries are a field with special investment incentives in Vietnam. Corporate income tax (CIT) incentives for investment projects in the production of priority supporting industry products have also been stipulated in Law No. 71/2014/QH13 amending and supplementing a number of articles of the Tax Laws..." (Government, 2014), [7]

In addition, the Government has issued "Decree No. 111/2015/ND-CP on the development of supporting industries [8] with 06 industries receiving support and incentives. Including: Textile - garment, leather - footwear, electronics, automobile manufacturing and assembly, mechanical engineering, supporting industry products for high technology". This Decree specifically stipulates incentives on corporate income tax, import and export tax, value added tax and credit. In particular, SMEs producing supporting industry products in the list of priority supporting industry products for development are also entitled to incentives on investment credit and land rent.... Next, the State's Supporting Industry Development Program for the period 2016 - 2025 is expressed through "Decision No. 68/QD-TTg dated January 18, 2017" [13] and the Regulations on management and implementation of the Supporting Industry Development Program are expressed in "Decision No.

10/2017/QD-TTg dated April 3, 2017” [14] and “Circular No. 29/2018/TT-BTC dated March 28, 2018 Guiding the establishment, management and use of funds for the Support Industry Development Program” [5]…

4.2.1.10. About Enterprises participating in industry clusters

Table 4.12. Average scores of assessment scales for enterprises participating in industry clusters

Unit: Point

Enterprises participating in industry clusters

(Min 1 – Max 5)

Average score
CLKN_1	Supporting industry enterprises create value chains from the raw material supply stage. production materials	3.25
CLKN_2	Supporting industry enterprises create consumer product value chains.	3.39
CLKN_3	Supporting industry enterprises participate in supporting industry associations	3.39
CLKN _4	Supporting industry enterprises meet production scale requirements	3.48
CLKN_5	Supporting industry enterprises can be raw material suppliers, manufacturers, distribution when participating in industry clusters.	3.43

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Source: Author's survey results

Table 4.12 shows that enterprises participating in industry clusters are highly appreciated, in which the scale of "Supporting industry enterprises meeting the required production scale" has the highest average score of 3.48 points. When supporting industry enterprises participate in industry clusters, the condition of meeting the required production scale is extremely important to ensure that enterprises operate in a chain.

Currently, the scale and capacity of supporting industry enterprises are still limited. This is reflected in the small number of enterprises participating in supporting industry, low production capacity, lack of financial resources, lack of high-quality human resources and technology to improve productivity. Domestically produced supporting industry products are mainly components and simple details, with low average technology content, and small value in the product value structure. However, this has limited the number of enterprises participating in industry clusters.

According to statistics, the current rate of domestic enterprises participating in the supply chain of end-to-end manufacturing corporations in Vietnam at the end of 2019 was 30%, a good increase compared to the figure of more than 10% at the end of 2018. More importantly, the potential and opportunities for Vietnamese supporting industry enterprises to participate in the global value chain are expanding because Vietnam is

is expected to be the industrial production center of the region in the near future. Economic experts believe that supporting industrial enterprises, especially supporting industries, to transform production and increase the proportion of domestic supply is necessary to promote the development of supporting industries and contribute to attracting and retaining investors. (Ministry of Industry and Trade 2011-2020), [2]

4.2.1.11. About CNHT Enterprises participating in the Multinational Corporation network

Table 4.13. Average scores of assessment scales for CNHT Enterprises participating in the Multinational Corporation network

Unit: Point

Enterprises participating in the Multinational Corporation network

(Min 1 – Max 5)

Average score
National Team_1	CNHT enterprises participating in branches of the national corporation network	3.33
National Team_2	CNHT enterprises have business strategies based on competitive advantages. industry picture	3.49
National Team_3	Products of supporting industry enterprises meet the differences of each nation.	3.34
National Team_4	Supporting industry enterprises create prestige and brand when participating in the Trade Union. National Team	3.23
National Team_5	CNHT enterprises clearly understand and promptly grasp technical agreements, marketing agreements, research cooperation, management cooperation development programs...	3.38

Source: Author's survey results

Table 4.13 shows that the average score of the scales for supporting industry enterprises participating in the Multinational Corporation network ranges from 3.23 points to 3.49 points, which is quite high. Supporting industry enterprises participating in the Multinational Corporation network will help supporting industry enterprises gain prestige and competitiveness domestically and internationally.

According to statistics from the Ministry of Industry and Trade in 2019, “Vietnam has 1,800 enterprises producing spare parts and components, of which only about 300 enterprises participate in the production network of multinational corporations. The number of enterprises operating in the supporting industry currently accounts for nearly 4.5% of the total number of enterprises in the processing and manufacturing industry, creating jobs for more than 550,000 workers”. (Ministry of Industry and Trade 2011-2020), [2]

To achieve the Government's goal in Resolution 115/NQ-CP in 2020, " By 2025, Vietnamese enterprises will be able to produce supporting industrial products."

highly competitive, meeting 45% of essential needs for domestic production and consumption, accounting for about 11% of the total industrial production value; by 2030, meeting 70% of domestic needs, accounting for about 14% of industrial production value" The Ministry of Industry and Trade has researched and advised the Government to develop the Law on Supporting Industry and at the same time advised on adjusting and amending problematic and unreasonable regulations in Decree No. 111/2015/ND-CP dated November 3, 2015 related to Supporting Industry [8].

4.2.2. Results of screening survey forms

As presented in the research method section, the author conducted a survey of 600 people who are officers and employees working at 20 Vietnamese commercial banks with the percentage of survey votes shown in Table 4.14.

Table 4.14. Results of screening survey forms

STT

BANK	NUMBER VOUCHER	PROPORTION (%)	STT	BANK	NUMBER VOUCHER	PROPORTION (%)
1	VIETINBANK	40	6.7	11	KLB	30	5.0
2	BIDV	40	6.7	12	TECHCOMBANK	30	5.0
3	VCB	40	6.7	13	NAB	30	5.0
4	ACB	30	5.0	14	OCB	30	5.0
5	ABB	20	3.3	15	MB	20	3.3
6	BAC A BANK	20	3.3	16	SCB	30	5.0
7	LPB	30	5.0	17	SGB	30	5.0
8	EAB	30	5.0	18	SHB	30	5.0
9	SEABANK	30	5.0	19	VIETA BANK	30	5.0
10	MSB	30	5.0	20	EXIMBANK	30	5.0

Source: Survey results synthesis

4.2.3. Results of survey sample analysis

Data collected from 600 valid questionnaires will be used for analysis to answer the research questions. After reviewing, “cleaning” the data and processing primary data through Excel software, the data is imported into SPSS 25 software to conduct analysis and evaluation. The results of the analysis process are presented specifically in the following sections.

Table 4.15. Results of survey sample analysis

Sex

		Frequency	Percent
Valid	Male	250	41.6
	Female	350	58.4
	Total	600	100
Age
		Frequency	Percent
Valid	Under 35 years old	200	33.3
	35 years old – 45 years old	100	16.7
	45 years old – 55 years old	200	33.3
	Over 55 years old	100	16.7
	Total	600	100
Education level
		Frequency	Percent
Valid	Secondary, College	50	8.3
	University	350	58.4
	Master	190	31.6
	Dr.	10	1.7
	Total	600	100
Number of years working in the bank
		Frequency	Percent
Valid	Under 5 years	90	15
	From 5 years – 10 years	300	50
	From 10 years – 20 years	100	16.7
	Over 20 years	110	18.3
	Total	600	100
Income level
		Frequency	Percent
Valid	Under 10 million	100	16.7
	From 10 million - 15 million	100	16.7
	From 15 million - 20 million	200	33.3
	Over 20 million	200	33.3
	Total	600	100

Source: Author's research results

The data in Table 4.15 shows:

Regarding gender: In the total sample of 600 people surveyed, 250 participants were male (accounting for 41.6%) and 350 participants were female (accounting for 58.4%). Thus, there are few

The difference in the number of men and women at commercial banks when conducting the survey is completely consistent with the characteristics of the banking industry in Vietnam.

Regarding age : According to the survey results, the number of samples under 35 years old is 200 people, accounting for 33.3%; Age from 35 to 45 is 100 people, accounting for 16.7%; Age from 45 to 55 is 200 people, accounting for 33.3% and over 55 years old is 100 people, accounting for 16.7% of the total number of samples surveyed. With the above figures, it can be seen that the staff at Vietnamese commercial banks are quite young, this workforce is dynamic, and adapts quickly to the development of modern banking technology.

Regarding educational level : The staff working at Vietnamese commercial banks are mainly university graduates with 350 people, accounting for 58.4%. In addition, in the survey sample, there are also 50 people with intermediate and college degrees, accounting for 8.3%; 190 people with master's degrees, accounting for 31.6% and 10 staff with doctoral degrees, accounting for 1.7%.

Regarding income: staff at Vietnamese commercial banks have a fairly high income, mainly in the range of 15-20 million and over 20 million with 200 people, accounting for 33.3%. With such an income level, it is enough to ensure people's lives compared to other current business sectors in Vietnam. In addition, the number of employees with incomes below 10 million and 10-15 million also accounts for a fairly high proportion with 100 people (accounting for 16.7%).

4.2.4. Results of analysis of reliability and validity of the scale

4.2.4.1 Assessing the reliability of the scale through Cronbach's Alpha test

The Cronbach's Alpha reliability coefficient method was used before the EFA exploratory factor analysis to eliminate inappropriate variables because they could create spurious factors. The criteria applied to assess the reliability of the scale are that the observed variables must have a corrected item-total correlation coefficient greater than 0.3 and the scale's Alpha reliability (Cronbach's Alpha) greater than 0.6. In the observed variables, after excluding variables with a total correlation coefficient less than 0.3 (the level of association between each variable in the corresponding factor with the remaining variables is low), including: QLRR3, TTKH4, KNQL1 . The study eliminated these variables in the subsequent analysis. When re-checking the reliability of the scale through the Cronbach's Alpha coefficient and the correlation coefficient of the remaining variables, we see that the scale with these variables ensures reliability (Cronbach's Alpha > 0.6).

Table 4.16: Results of reliability testing of the scale

Encryption

Variable description	Cronbach's alpha	Conclude
CSTD	Credit policy	0.721	Accept
QTTD	Credit process	0.632	Accept
QLRR	Risk Management	0.724	Accept
TTKH	Customer information	0.77	Accept
Science and Technology	Science and technology	0.654	Accept
KNQL	Management experience	0.656	Accept
NLTC	Financial capacity	0.614	Accept
PAKD	Business plan	0.611	Accept
CSPT	Development policy	0.712	Accept
CLKN	Industry cluster	0.653	Accept
National Team	Multinational Corporation	0.773	Accept

Source: Synthesized from research results

The test results in Table 4.16 show that the observed variables all have a total correlation coefficient greater than 0.3 and the Cronbach's Alpha coefficient is greater than 0.6, proving that the scale used ensures reliability. (Appendix 06)

4.2.4.2 Exploratory factor analysis EFA

The results of factor extraction of observed variables are summarized in table 4.17.

Table 4.17: Factor rotation matrix results

Symbol

Factor rotation matrix
F1	F2	F3	F4	F5	F6	F7	F8	F9	F10
CLKN1	.802
CLKN2	.780
CLKN3	.767
CLKN5	.734
National Team 4	.668
National Team 5	.658

National Team 1

.650
QLRR3	.802
QLRR2	.730
QLRR1	.686
QLRR4	.673
QLRR5	.663
NLTC1		.774
NLTC2		.692
NLTC3		.663
NLTC5		.637
NLTC4		.612
CSTD1			.676
CSTD2			.668
CSTD3			.600
CSTD4			.599
Science and Technology 1				.719
Science and Technology 5				.629
Science and Technology 3				.601
Science and Technology 4				.509
CSPT2					.829
CSPT4					.639
CSPT5					.615
CSPT3					.523
QTTD1						.716
QTTD3						.682
QTTD4						.656
KNQL1							.845
KNQL3							.818
KNQL2							.613
TTKH1								.674
TTKH2								.534
TTKH3								.486
PAKD1									.812
PAKD5									.728

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