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The Impact of the Government's Role on Attracting Investment to Marine Economic Development in Hai Phong City

Nguyen Thach Dang

Department of Political Economy, University of Economics and Business, Vietnam National University, Hanoi, Vietnam

Abstract: This study examines the impact of the Government's role on attracting investment to marine economic development in Hai Phong city. By reviewing research and consulting with experts, the constituent factors are identified as the legal system, and marine economic development planning, management system, and policy making, policy enforcement and inspection, examination of policy implementation. These are independent variables included in the research model with the aim of examining their impact on investment attraction to marine economic development in Hai Phong city. Through the survey of 312 samples as managers, officials working in government agencies and business representatives in the marine economy, the research paper performed primary data analysis. many different methods such as: "Analysis of reliability coefficients of scales", "descriptive statistical analysis of observed variables", "exploratory factor analysis EFA", "linear regression analysis calculate the impact of factors", "ANOVA analysis", "test the difference between the surveyed object groups". The results show that the study has identified a linear regression model that shows the impact relationship between the state role in investment attraction to marine economic development to assess in detail the impact level of each intrinsic factor. Although the magnitude of the impact is not large, it also affirms the importance of the activities of the local government to attract investment to develop the marine economy in Hai Phong city.

Keywords: investment attraction, the marine economic sector, the role of state, marine economic developing in Hai Phong city

Received November 01, 2020; Revised December 02, 2020; Accepted December 09, 2020

Citation: Nguyen Thach Dang, The Impact of the Government's Role on Attracting Investment to Marine Economic Development in Hai Phong City. Journal of Finance and Economics, 9 (1). 1-10. January 2021. doi:10.12691/jfe-9-1-1

1. Introduction

Reference [1,2] show with the goal of macroeconomic development, the operation of the local government is one of the important factors considered in investors' decision-making.

The role of the state in the locality is most clearly shown in policy development and policy implementation as a basic element to attract investment for economic development. Many researchers believe that policies such as support for land access, finance or environmental protection have a strong impact on enterprises as in [3,4,5,6]. Usually, the difference that each locality makes will form a competitiveness to attract investment to promote However, the difference in natural factors is no longer considered much in the current context, but mainly lies in the local government facilitating enterprises to access resources. In particular, local governments also constantly have to evaluate the context and effectiveness of policies as well as control the implementation of policies. In [7], the role of the state is increasingly confirmed in investment attraction by a policy system with easy conditions for business to operate and grow. A small or lacks resources country can still attract investment through institutional and legal reforms and the development of appropriate and attractive policy systems as in [8,9,10].

Reference [8,11] shows: Whatever the development of the market economy, the role of the state is still very important, directly or indirectly promoting the socio-economic situation. In a market economy with the state management, the authority and responsibility of all levels and sectors in the establish and implementation of planning, especially economic development planning, will help localities orient investment attraction strategies as in [12] and [13]. In [13,14], economic development planning is identified based on local advantages and development objectives in a certain period. In addition, the formation of administrative levels and the adjustment of the size of local administrative units in Vietnam is to strengthen the role of macroeconomic management in localities. Basically, the role of the state in the market economy such as the role of regulating, creating an equal economic relationship, attracting investment ... must be shown in legal documents as in [15]. The role of supporting and fostering the creativity of local governments is becoming increasingly important for businesses. At the same time, businesses put localities in competition with each other according to criteria such as local labor, services for businesses, infrastructure ...

VCCI gives the provincial competitiveness index (PCI) to evaluate and rank the quality of economic governance and build a favorable business environment for private enterprises development of provincial governments in Vietnam from 2005 to present. The PCI also points out the implications of the state's role in investment attraction in localities mainly around policies related to the favorable investment environment. From the PCI indicators, the legal environment, administrative procedures, and economic policies greatly affect the investment decisions of enterprises, especially in local as in [16]. Reference [17], [18] shows: In addition, to ensure the efficiency of investment attraction, policy implementation must be controlled by local state management agencies. Thus, the investment attraction for economic development is done firstly in the legal system to formulate, enforce and test policies.

Marine economy is an important economic sector, which is concerned by many countries around the world because the resources from the sea are huge. There are many different indicators to evaluate the level of marine economic development. The traditional evaluation criteria for marine economic development such as the growth of the number of enterprises, value added or the contribution of marine economic sectors to GDP as in [19] are often mentioned in many studies. Reference [20] shows: the gross value added (GVA) related marine becomes an important factor in the national income account in marine areas. More specifically, the marine economy can be divided into eight sectors: communications and shipping, aquaculture, marine salt exploitation, beach sand mining, tourism, marine energy, seawater use and marine medicine. The assessment for investment expansion, attracting businesses, increasing jobs and workers in the marine economy should be done regularly in economic statistics as in [21,22]. The expansion of economic sectors also implies marine economic development.

Besides, marine economy development must be sustainable. When countries and localities exploit marine resources, they will have to face resource depletion, environmental pollution ... So local governments must have sustainable approach to develop long-term marine economic sectors. Reference [23] shows: evaluating the marine economic development, it is necessary to add criteria for safe exploitation, using measures to minimize marine pollution. By the way, the environmental measure have to add in the assessment of marine economic development as in [20]. In addition, the satisfaction of businesses with the marine economic development policy is also an evaluation criterion that should be considered. When satisfied, they will focus on investing more, expanding production and contributing to the development of the local marine economy in [24].

Reference [25] shows: there is an impact relationship between government activities and marine economic development. Marine economy can be developed thanks to the State's implementation of planning and building a suitable marine economic exploitation strategy for each different period such as the strategy of expanding the sea area or promoting offshore exploitation ... The state also determines the marine economic sectors, making policies and implementing them in a consistent way as in [23]. In addition, if the local government does not strictly inspect and control the implementation of policies, especially the policies related to safe exploitation, pollution reduction, the marine economy will not sustainable development. In Vietnam, the marine economic development planning gives directions to help localities exploit their advantages to boost production and business, especially in the field of seaports and fisheries, increase competitiveness in parallel with environmental protection towards sustainable development. With Reference [24,26], marine strategy has a strong impact on economic activities. In order to be effective, it is also necessary for the government to regularly check and control policy implementation in order to eliminate the negative effects that inhibit development.

In order to develop the marine economy, it is important that the number of businesses operating in this sector increases, and the scope of industries to expand. That means that investors must pay attention to production and business activities exploiting marine resources. In coastal areas, trying to attract investment capital from local authorities is an important way to develop marine economy as in [27,28].

Hai Phong is an important port city, the largest industrial and seaport center in the North of Vietnam, and is also the economic, cultural, medical, educational, scientific, commercial and technological center of Northern coastal region. This is the 3rd largest city in the country, the 2nd largest in the North after Hanoi. Hai Phong is also one of five central cities. Hai Phong is also a locality with large coastal, sea and island areas in the national maritime strategy. With 125km of coastline and more than 4000 km of inland sea surface, Hai Phong has many potentials and strengths, holding an important position in the economy, society, information technology and security and defense of the region. North Vietnam and the whole country, on two corridors - one belt of economic cooperation between Vietnam and China. Hai Phong is also a traffic hub for the sea in the North. Not only that, the advantage of a deep-water port makes sea transportation in this city very developed and is also one of the growth engines of the key economic region in the North. In the past 10 years, the coastal and marine economy has contributed about 30% to the total GDP of the city; The GDP of Hai Phong sea area also accounts for more than 30% of GDP of the country's coastal and marine economy and has a higher economic growth rate than the national coastal zone. Hai Phong port is ranked as the most important port among 536 seaports in Southeast Asia. However, at present, the exploitation of natural resources and advantages from the sea in Hai Phong has not achieved efficiency in the sustainable marine economy development. This limitation not only from the marine economic development policy but also from the investment attraction policy with the core of low competitiveness or attractive investment conditions. This raises the issue of needing to have a clear study of the impact of the state role in investing attraction to develop marine economic in Hai Phong city.

Up to now, there has been no research to build a model to evaluate the impact of the state in attracting investment to develop marine economy, but in different angles, this relationship has been mentioned in experiments. This study will determine each of the factors that constitute the role of the state in attracting investment and their impact on the development of the marine economy in Hai Phong city. From there, local authorities can come up with specific strategies to attract investment in marine economic development effectively.

2. Methodology

2.1. Hypotheses and Research Models

The hypothesis is that it is possible to evaluate the impact of the state's role in attracting investment to marine economic development through considering the impact of each internal element of the role of the state on economic development. marine health in the direction of the direction. Research will give results that accept or reject the hypothesis. From there, the topic assesses the impacts of each factor based on the response of the surveyed object. As follows:

H1: The legal system related to investment attraction has a positive effect on marine economic development

H2: The marine economic development planning has a positive influence on the marine economic development

H3: Management system to attract investment has a positive impact on marine economic development

H4: Policy making that have a positive impact on marine economic development

H5: Policy enforcement positively affects marine economic development

H6: Inspection, examination policy enforcement that positively affect marine economic development

From the above hypothesis, variables are included in the research model with the aim of considering the influence of each factor showing the role of the state in attracting investment to local marine economic development.

Figure 1. Model of the impact of the state's role in attracting investment to marine economic development

By expert method (in-depth interviews 10 experts who are scientists, managers in the field of economics, economic management), 10/10 answers agree with the impact factors are summed up. combined. These relationships are cause and effect relationship, which can describe theoretical predictions about the impact of the state role in attracting investment to marine economic development. Since then, the influence model is built including 6 independent variables, 1 dependent variable as in Figure 1. The number of observed variables for the independent variable includes 30 and 6 observed variables for the dependent variable in Table 1.

Table 1. The observed variables of the independent variable in the model

Table 2. The observed variables of the dependent variable in the model

2.2. Data Collection Methods

To assess the impact of the state's role in attracting investment to the marine economic development of Hai Phong, the author used primary data collected through survey by questionnaires.

In order to collect primary data effectively, the author performs the following steps:

Step 1: Analyze the research works overview, select the information to build the initial research model.

Step 2: Survey experts to select and adjust the research model

Step 3: Develop questionnaires

• Objective of questionnaires: The questionnaire was set up to get the authentic opinions of the surveyed subjects to collect their assessment about the role of the state in attracting investment that impact of marine economic development in Hai Phong city.

• Respondents: Managers, officials working at the Department of Planning and Investment, Department of Finance, Department of Industry and Trade, Department of Natural Resources and Environment, Economic Zone Authority, Department of Tourism, Department Transportation of Hai Phong City, representatives of businesses related to marine economy include: logistics enterprises, seaports, marine tourism and seafood production.

• Content of the questionnaire: relating to factors that are the content of the state's role in attracting investment to marine economic development in Hai Phong city. Questions associated with research models are built in the process of reviewing research works and theory related to the topic.

Step 4: Survey

• Survey location: The survey was conducted at the administrative agencies in Hai Phong city, some businesses related to marine economy are operating in Hai Phong city.

• Sampling objective: to select a representative sample for many groups of people related to marine economy. The evaluation of the sample will find the current trend of the research problem.

• Sample structure:

For this topic, due to the limited time of survey as well as the synthesis of sample determination theories, the expected sample size of the author is n> 300 samples to ensure reliability and stability. when analyzing. Since then, 320 questionnaires were distributed. After entering and cleaning data, the number of valid questionnaires were used for analysis is 312.

2.3. Data Analysis Method

This test is carried with the use of SPSS software version 20.0. By using calculation tools, illustration and test, the study will show the result of liner regression indicating the degree of influences of independent variables on dependent variables in attracting investment with 5% p-value.

In this study, there are 5 types of data analysis techniques to be applied, including demographic description, descriptive statistics, reliability test analysis, linear regression, and ANOVA analysis. Demographic and descriptive statistics are two major data analysis techniques whether the author utilizes SPSS to take a summary on how many respondents to choose each point in Likert 5 points of scale. On the other hand, the author adapts the rule of thumb provided whether this researcher indicates that mean value will represent for the agree level of the respondents. In more detail, mean value of factor which is higher than 3.5, in between 2.5 and 3.5, and less than 2.5 will indicate for the context of which the respondents have high, medium and low agree with the questionnaire’s contexts. Furthermore, the author also applies reliability test analysis on organizational commitment, compensation management in the conceptual research model. According to [29], reliability test analysis will provide to the researchers the level of reliability in the survey scale. This analysis consists of 3 statistical tests, including Cronbach’s alpha value should be higher than 0.6, Corrected Item-Total Correlation should be higher than 0.3, and Cronbach’s alpha if Item Deleted should be less than Cronbach’s alpha value in overall. The last but not least is linear regression whether this data analysis techniques will provide to the researchers on how factors in conceptual research model relate with each other. Finally, ANOVA analysis is performed among different groups of objects with components of the structural model that have been tested to find significant differences of some specific groups" as in [30].

3. Results and Discussion

3.1. Assessment Scale

In Table 3, the scales are well built. All of the coefficients of Cronbach's Alpha are quite high.

Table 3. The caption should be placed above the table

3.1.1. Inspection Reliability for the Independent Variable “Legal system”

In Table 4, the scale "Legal system" has 4 observed variables with Cronbach's alpha coefficient of 0.869 reaching the highest level of confidence in the scales. Considering the total variable correlation coefficient also gives high numbers, the lowest is 0.742>0.3, ensuring that the given variables are good and can continue with other analyzes.

Table 4. Reliability for the scale “Legal system”

3.1.2. Inspection Reliability for the Independent Variable “Marine economic development planning”

The scale for the independent variable "Marine economic development planning" is built by 5 observed variables in Table 5. Cronbach's Alpha coefficient of 0.794> 0.5 ensures that this variable can exist in the model. The total variable correlation coefficients of the component variables are not high. Even if the variable QH2 only reached 0.498 but still ensures> 0.3 and the elimination of that variable also makes Cronbach's Alpha coefficient increase to 0.856 but that is not necessary. Therefore, all observed variables are retained for the following analysis.

Table 5. Reliability for the scale “Marine economic development planning”

3.1.3. Inspection Reliability for the Independent Variable “Management system”

In Table 6, this scale has a reliability of 0.760> 0.5 should be accepted. With 5 observed variables, the total variable correlation coefficient respectively 0.640; 0.538; 0.507; 0.635 and 0.562 are both greater than 0.3. Thus, the observed variables are guaranteed to be reliable and are kept for the following analysis steps.

Table 6. Reliability for the scale “Management system”

3.1.4. Inspection Reliability for the independent Variable “Policy making”

This scale is performed with 5 observed variables in Table 7. Although the observed variables are not as high as the above scales, they still ensure> 0.3 and the elimination of the variable does not make the model achieve a higher level of confidence. Therefore, the observed variables are retained for further analysis.

Table 7. Reliability for the scale “Policy making”

3.1.5. Inspection Reliability for the Independent Variable “Policy enforcement”

Table 8 show the scale "Policy enforcement" has Cronbach's alpha coefficient of 0.841> 0.5. This is a large factor that represents a highly reliable scale. In addition, the smallest total variable correlation coefficient is 0.728> 0.3, so it meets the requirements to perform the next analysis.

Table 8. Reliability for the scale “Policy enforcement”

3.1.6. Inspection Reliability for the INDEPENDENT Variable “Inspection, examination”

Observing Table 9, we can see that the scale "Inspecting, examination" has Cronbach's Alpha coefficient of 0.751 which is a good coefficient. The total variable correlation coefficients are all greater than 0.3, so they meet the requirements for further analysis.

Table 9. Reliability for the scale “Inspection, examination”

3.1.7. Inspection Reliability for the Dependent Variable “Marine economic development in Hai Phong”

With the analysis of 6 observed variables in Table 10, the scale "Development of marine economy" has Cronbach's alpha coefficient of 0.816 which is a good coefficient with high reliability. The total variable correlation coefficient is low, click 0.652> 0.3 is satisfactory. If we exclude this observational variable, Cronbach's Alpha coefficient dropping from 0.816 to 0.784 is not recommended. The other coefficients have a similar situation. Therefore, all variables are kept for further analysis.

Table 10. Reliability for the scale “Marine economic development in Hai Phong”

3.2. Exploratory Factor Analysis

Table 11 show KMO coefficient of the independent variables in the obtained model is 0.778> 0.5 with sig = 0.00<0.05, which satisfies the conditions for EFA analysis.

After testing Cronbach's Alpha, the model accepted 30 observed variables and performed factor analysis on these 30 variables.

Table 11. KMO and Bartlett's Test of independent variables

When the scale combination is analyzed, there are 6 factors drawn corresponding to 6 independent variables. The total variance extracted by 69.779%> 50% shows that the 6 factors extracted have explained 69.779% of the variation of the data.

The interpretation of factors is done on the basis of recognizing observed variables with large transmission coefficients in the same factor. EFA analysis results shown in the factor matrix after rotation in Table 12. The factor load coefficients are> 0.5, so the variables are kept the same, not removed. From there, the model extracted 6 independent factors.

Table 12. Rotated Component Matrix of independent variables

Analysis of the factors of the dependent variable in Table 13, we can see that the coefficient KMO is 0.646> 0.5 with sig = 0.00 <0.05, so factor analysis is appropriate.

Table 13. KMO and Bartlett's Test of dependent variables

Total variance extracted by 71.072%> 50% should be representative of variation. Principal Component Analysis extraction with Varimax rotation was performed and extracted a factor that could explain the variation of the data. The coefficients in the factor matrix are> 0.5, in Table 14 showing that this dependent factor is related to the model and ensures full satisfaction of EFA conditions.

Table 14. Rotated Component Matrix of dependent variables

Thus, after factor analysis, there is no factor that does not guarantee the interpretation of the data variation of the model. The model is fully preserved.

3.3 Correlation Analysis

After performing factor analysis, 6 independent variables (with 30 observed variables) and 1 dependent variable (with 6 observed variables) were included in the model test. Factor value is the average of the observed components of that factor. Pearson correlation analysis was used to consider the suitability of components in the regression model. The results of regression analysis will be used to test the hypotheses.

3.3.1. Test the Correlation Coefficient

Correlation coefficient test is used to test linear relationships between the independent variables and the dependent variable. The correlation coefficient (r) indicates the degree of linear relationship tightness, the closer r is to 1, the higher the degree of tightness, and r = 0 indicates that the variables are not linearly related.

The inspection is done in two sides (2 - tailed). The correlation coefficient between the variables with itself is 1, among the variables are> 0. According to the correlation matrix, the correlation coefficient between the independent variables and the dependent variable is significant at 0.01. The corresponding coefficients are:

- The variable "Policy enforcement" and the dependent variable has a correlation coefficient of 0.639. This is the average correlation.

- The variable "Legal system" and the dependent variable have a correlation coefficient of 0.483.

- The variable "Policy making" and the dependent variable have a correlation coefficient of 0.607

- The variable "Management system" and the dependent variable is 0.429

- The variable "Marine economic development planning” and the dependent variable is 0.519

- The variable "Inspection, examination" and the dependent variable is 0.465

Thus, the lowest correlation coefficient is between the variable "Management system" and the dependent variable "Marine economic development in Hai Phong” This suggests that the level of impact of this variable on the dependent variable is not as high as the other independent variables in the conditions in Hai Phong city. However, this variable still represents an average degree of correlation.

The highest correlation level is the variable "Policy enforcement" with the dependent variable, showing that this factor is always important to assess the level of marine economic development. This is the most complicated factor. But it is the most powerful factor that can make the dependent variable fluctuate the most.

In addition, the matrix table also shows that the independent variables also have certain correlations to each other. That means that when implementing one independent variable, it can affect another independent variable, thereby also changing the employee's satisfaction level in the job. The assumptions are not rejected and can be included in the model to explain the dependent variable.

3.3.2. Regression Analysis

Regression analysis was performed with 6 independent variables, including: Legal system (PL), Marine economic development planning (QH), Management system (TC), Policy making (CS), Policy enforcement (TH) and Inspection, examination (KT). The dependent variable is Marine Economic Development in Hai Phong (HL).

Values of the independent variables are averaged based on the observed components of those independent variables. The value of the dependent variable is the average of the observed variables for marine economic development. Analysis was performed using the Enter method. The variables are included at the same time to see the matching of the variables. The results of regression analysis are as follows:

The results in Table 15 show that the regression model is relatively consistent with the significance level of 0.05. Adjusted R2 coefficient = 0.667 means that there is about 66.7% of marine economic development variance which is explained by 6 independent variables.

Table 15. Assessment of fit of the model

The F-test used in the variance analysis Table 16 is a hypothesis test of the suitability of the overall linear regression model. The idea of this test is to consider a linear relationship between the dependent variable and the independent variables. In the ANOVA analysis table, we see very small sig value (sig = 0.00), so the regression model is suitable and usable.

Table 16. Testing ANOVA

Table 17. Regression Results in the Model

ANOVA test results show that: F = 63,500 (sig = 0,000). The VIF value of each largest variable equal to 1.483 as in Table 17 is quite small (less than 2). Therefore, the multi-collinearity phenomenon has no influence on the interpretation results of the model. Reference [31,32,33] shows the rule is that when a VIF exceeds 2 is a sign of multiple collinearity. Sig of the largest factors of the variable "Organizational management to attract investment" is 0.005 <0.05, so all variables are accepted.

The regression equation shows the impact of the internal factors of the role of the state in attracting investment to the marine economic development in Hai Phong city, is shown through the following equation (Using the equation has removed the constant):

Inside:

Y: Marine economic development in Hai Phong (PT)

X1: Policy enforcement (TH)

X2: Management system (TC)

X3: Marine economic development planning (QH)

X4: Inspection, testing (KT)

X5: Policy development (CS)

X6: Legal institutions (PL)

3.4. The Impact of the Government’s Role on Attracting Investment to Marine Economy Development in Hai Phong City

By analyzing the linear regression model built by primary data, the impact of the state's role in investment attraction on marine economic development is assessed as follows:

Firstly, the factor "The legal system” of investment attraction is assessed to have a positive impact on marine economic development. The coefficient β5 = 0.215 shows that if the legal system with regulations to encourage investment and business development as well as focus on marine economic sectors, it will promote the development of marine economy in Hai Phong city. However, the impact level is not assessed as high, ranking only 5 out of 6 influencing factors. Respondents in the survey believe that the legal system is the basis to regulate economic development activities, but it is general, oriented and local governments can only receive and implement it. subject to change. In addition, the legal system such as the Investment Law, Enterprise Law is quite stable, there is not much change or the amplitude of changes in the legal system will not be large, so compared to other factors, the impact level. Direct development of the marine economy in localities such as Hai Phong is not clear.

Second, marine economic development planning is considered to have a positive impact on the marine economic development in Hai Phong city. Based on the marine strategy, the city government develops a plan for each industry and economic sector, exploiting the advantages of the sea, creating a clear direction to attract investment. From the marine economic development planning, related businesses will find opportunities, potentials as well as challenges in the investment process. Therefore, the investment attraction to marine economic development will become more transparent. For Hai Phong city, when the marine economic development plan is fully and clearly implemented, exploiting the advantages as well as encouraging the expansion of fields, marine economic sectors increase by 1 the standard deviation value will increase by 0.266 the standard deviation value of the level of marine economic development here. Therefore, to promote the marine economy development, Hai Phong city government needs to implement the planning of marine economic sectors, publicize the planning and regularly review and adjust the plan to suit the circumstances. new scene on socio-economic, science and technology and international integration.

Third, the management system to attract investment although having the weakest impact on the marine economic development in Hai Phong city compared to other factors, it also has a positive effect with the coefficient β2 = 0.150. This shows that if there is a positive change in the management apparatus to attract investment 1 standard deviation will increase 0.150 units of standard deviation level of marine economic development in Hai Phong city. The city's investment attraction management apparatus has been built upon regulations and political institutions from the central to local levels. The change is possible through effective rearrangement of positions, tasks, assignment of responsibilities, as well as improving the quality of staff working in the management apparatus.

Fourthly, building policies to attract investment has a strong impact on marine economic development because this is a direct and highly proactive factor of the local government. With the coefficient β4 = 0.327, if policies to attract investment are more efficient than 1 standard deviation, the level of marine economic development in Hai Phong city will increase by 0.327 standard deviation units. Policies such as supporting enterprises to develop markets, accessing land, reducing administrative procedures, increasing professional training, international cooperation ... the more favorable conditions for businesses, the more industries marine economy develops.

Fifth, policy implementation demonstrates a strong impact on marine economic development in Hai Phong. The survey participants said that when there is a good policy but ineffective implementation, it will not bring the desired marine economic development. Therefore, the research results also show that this is the most influential factor with the coefficient β1 = 0.373, the significance level sig = 0.000 <0.05, so the hypothesis is accepted .. This shows that when implementing policies The efficiency increases by more than 1 standard deviation, the level of marine economic development in Hai Phong city will be raised by 0.373 standard deviation units. This is also the most complicated factor directly related to the interests of businesses, so problems are also prone to occur. Therefore, in order to develop the marine economy, first of all, the city government must have plans and solutions to implement the policies that follow the set goals.

4. Conclusion

The marine economy in Hai Phong city develops mainly on the growth of both quality, and quantity of businesses operating in related industries and fields. The assessment of the impact of the state's role in attracting investment to marine economic development not only clearly determines the level of influence but also serves as a scientific basis for proposing solutions to attract investment for development, developing the city's marine economy effectively. Although the magnitude of the impact is not large, it also affirms the importance of the activities of the local government to attract investment to develop the marine economy of the port city directly under the Central Government.

Acknowledgements

The authors would like to thank the leadership, teachers, staff of University of Economics and Business, Vietnam National University. We would like to express my sincere and deepest thanks Associate Professor Ph.D. Nguyen Duy Dung has always motivated, enthusiastic support and guidance me to complete this paper. I extend my sincere thanks to the leadership team, staff of the People's Committee of Hai Phong city and the businesses who have participated in the interview.

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