Determinants Influencing the Investment Decision of Large Firms in Vietnam

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Introduction

Large firms are always considered as the motive force to lead the market, create development trends, create momentum for each industry as well as be the center for technology development, capital investment, attraction and job creation. make the economy. Investment activities of large firms play an important role in creating investment incentive policies for other economic sectors in the region as well as promoting the development of related industries in the locality. Therefore, attracting large firms to invest in the province is considered as an important motive force promoting the socio-economic development of each region.

Vinh Phuc is a province located in the key economic region of the North in Vietnam with favorable geographical position and natural conditions, with many potentials and advantages for economic development. However, in order to be able to take advantage and promote this potential, it requires large investment resources from investors. Investment capital flows from large firms are the “bait” capital flows to attract the fastest and most powerful investment capital from many other economic sectors for the province's socio-economic development. Along with that, large firms are those that have quick access to the development of advanced technology in the world. This is also the orientation to attract investment of Vinh Phuc to become a sustainable industrial province in the future. However, attracting large firms to invest in the province is not easy because the number of large firms accounts for a rather modest proportion not only in Vietnam but also in the world. Furthermore, large corporations are very careful investors when it comes to selecting locations for their investment activities. Therefore, the article researches and finds out determinants, mainly external determinants, affecting the investment decisions of large non-state firms in Vinh Phuc province when choosing an investment location, thereby helping the local government solve the problem of attracting investment capital from these firms. Through the literature review to find out the proposed determinants and models, with 226 surveys of large non-state firms, using the EFA test and analytical linear regression, making recommendations for the provincial government to have policies book to attract big investors according to the development orientation of the province.

The remainder of this research is structured as follows. Section 2 reviews the studies of in external determinants affecting investment decisions of firms such as: Location, Infrastructure, Politics, Laws and regulations of the locality, Market, Input production cost, Economic, cultural and social. Section 3 describes the data sample collection and methodology employed in the conduct of the research. Section 4 sets out a discussion of key results, while Section 5 shows some key conclusions and implications of the study practice and recommendations.

Literature review

The study only considers external determinants affecting investment decisions of firms, now that the study provides information for localities to have policies that improve investment climate and intrigue firms to invest in locality. The external determinants, also known as elements of the investment environment, are essential for firms to choose and take a decision to invest. Therefore, state and local governments long for ways to strongly entice companies to invest by primary task of improving investment climate determinants.

Infrastructure determinants: Pesaran et al. [1999] show that the satisfaction level of firms when investing in a country is influenced by three determinants: (i) infrastructure; (ii) business policy and service support and (iii) living and working environment. Study by Lu and Yang [2007] evaluated the importance of investment environment determinants, namely, infrastructure for firms' intention to invest in international logistics zones. What’s more, logistic zones enhance infrastructure quality, ranging from the state of transportation and telecommunications systems to the existence of a specialist labor force in order to attract prospective investors.

Politics, laws and regulations of the locality: Kaufmann et al. [2008] asserted that political institutions directly influence the establishment and maintenance of a stable legal system and then have a positive effect on firms' investment decisions. The study of Hallward-Driemeier et al. [2006] demonstrated that stable macroeconomic policies and flexible government policies are two mains for investment intention. Bialowolski and Weziak-Bialowolska [2013] discussed the driving forces determining the investment decisions of companies in Poland, assessing the relation between the branch and company size. The result showed that there is a positive association between the importance attached to determinants influencing investment decisions associated with the legal determinants regardless of companies’ size. Even the choice of investment form of firms can be influenced by political and legal determinants. Having said so, the statistical importance of governance infrastructure as a determinant of US foreign direct investment [Globerman, Shapiro 2002].

Market: According to many previous studies, market determinants such as market size, development potential, degree of competition (strong or weak), and economic growth in the place of investment plays a positive role in attracting investment decisions. The study of Oum and Park [2004] on the importance of European and North American firms’ investment determinants in Korean cities shows that the market or more specifically the market size, the growth potential, geographical location and market access, play a positive role.

In which, market size is an important determining determinant and is a great motivation for firms. The study of Lu and Yang [2007] demonstrated the existence of a positive relationship between market determinants and the investment intention of firms in the international logistics zone. Similarly, when considering the investment behavior of Chinese multinational firms abroad, the study of Buckley et al. [2007] also reaffirmed that the market size of the host country is an important determinant. Firms focus on this determinant, the domestic income (GDP) of the host country also has a positive and strong influence on the investment motivation of firms. The results of Bialowolski and Weziak-Bialowolska study in 2013 showed that: (i) There are two driving forces that determine the investment decisions of Polish companies. Those are macroeconomic determinants and legal determinants; (ii) A positive association between the relative importance of determinants affecting investment decisions related to macroeconomics, regulatory environment, and investment reduction.

Input production cost: In economic activities, cost always plays a leading role, this is even more true with investment activities, because in the end, the most important goal of firms is profit. Therefore, considering cost is inevitable for every business before making an investment decision. Oum and Park have demonstrated that labor, land and other input costs are very important for these companies in making investment decisions from their distribution centers. Lu and Yang have retested this when studying the investment intention of firms in the international logistics zone, the results of this study supported the hypothesis “there is an influence of cost determinant on the investment intention of the firm”. The managers of logistics zone should provide low-cost land and low-cost labor with tax incentive policies if they want to attract investors to invest in the international logistics zone.

Economic, cultural and social determinants: In addition to other determinants such as infrastructure, laws, etc., socio-cultural determinants include: (i) Living standards and public services; (ii) Attitudes of Community towards firms; (iii) Cultural similarity has a significant influence on whether a business decides to invest in a locality. Close socio-cultural patterns is an advantage compared to other firms in the expected localities for investment. It is possible to create certain advantages for firms who have conditions to accelerate and legalize the transfer and assimilation of technology, knowledge and management systems to make investments. [Globerman, Shapiro 2003]. Doan and Jan-Yan [2016] clarified the role of socio-cultural patterns in investment decisions, asserting that the differences in business culture, language, and behavior are detrimental and cause difficulties for firms in accessing information. Thus, they concluded that cultural diversity and differences in the provinces of Vietnam have an influence on the implementation of investment of domestic and foreign firms.

Researching on investment in Vinh Phuc province has a research of Hoang [2019] about “Solutions to attract FDI in Vinh Phuc Province towards sustainability”. The research has given a new approach in attracting FDI in localities in Vietnam in general and Vinh Phuc in particular. The research showed that good deployment of zoning and prioritizing projects with high scientific and technological content which are environmentally friendly, good promotion of investment and fostering dialogue mechanism between leaders and FDI firms are key driving determinants to attract sustainable FDI in Vinh Phuc province. Department of Planning and Investment of Vinh Phuc province [2020] believes that Vinh Phuc will continue to create favorable conditions for development of production and business activities. They are fostering innovation in investment attraction activities, ensuring harmony between benefits of the State, investors and residents; improving the quality of projects to attract new investment in the direction of increasing the content of technology and technical labor; and prioritizing attracting pioneering industries that in the 4th industrial revolution. Thu Hang [2020] also pointed out some of Vinh Phuc's investment attraction orientations in the past period, including improving the investment and business environment, in which investment promotion activities on the spot are emphasized by solutions of concern and immediate settlement of difficulties and problems for firms investing in the province; promoting reform of administrative procedures, implementing the ‘business coffee’ model every Friday, organizations of dialogues with firms by the Provincial People's Committee. Making a plan to improve the investment environment and enhance the provincial competitiveness index (PCI); promulgating specific solutions, removing obstacles related to compensation and land clearance for large scale projects, industrial park infrastructure investment projects; optimising the system of mechanisms and policies on investment attraction and paying attention to infrastructure investment inside and outside industrial parks.

Research methodology

In accordance with the researched characteristics in Vinh Phuc, after gathering determinants through published scientific studies, the study set up a draft scale and interview experts in related fields about the appropriateness of the identified determinants, and in-depth interviews with experts including leaders of Departments of Planning and Investment, leaders of Industrial Parks Management Boards, leaders of large firms in Vietnam and expert at universities.

Table 1: Scale in questionnaire

Using qualitative research methods through interviews with experts, the study selected determinants affecting investment decisions of large firms in Vietnam to build model, including:

Dependent variable: Investment Decision (ID)

Independent variables: External determinants include 9 groups: (1) Location (LO), (2) Infrastructure (IN), (3) Market (MA), (4) Incentive policies (IP), (5) Supporting service (SS), (6) Input costs (IC), (7) Human resources (HR), (8) Quality of Institution (QI), (9) Communication (CO).

Research models and hypotheses: The article proposed the following research model (fig.1):

Fig. 1. Research model proposed

The author conducted an online survey through the investigation channels of the Tax Department, the Management Board of Industrial Parks and the Department of Planning and Investment. The research received responses from 226 firms. All observations ensure completeness, do not miss the values ​​in the questionnaire. The research used descriptive statistical analysis, exploratory determinant analysis (EFA) and regression analysis by SPSS 23 software to determine the relationship between the determinants and investment decisions of the large firms in Vietnam.

Results and discussion

Evaluation of the scale by Cronbach's Alpha reliability coefficient

The results of the analysis of Cronbach’s Alpha coefficient of external determinants (Independent variables) and investment decision (Dependent variable) show that these independent variables satisfy the condition of correlation coefficient of total variable > 0.3. However, the α coefficient has 2 determinants that need to be eliminated. Specifically, the Quality of local management institutions has a coefficient of 0.97 > 0.95. Although we have removed the variables in turn, the coefficient is still 0.961. Thus, this determinant is completely omitted. The Communication determinant also has a rather high Cronbach’s Alpha coefficient of 0.95. When the variable CO2 is removed, the coefficient drops to 0.931, within the acceptable range from 0.60 to 0.95 (Table 1). After evaluating the reliability of the scale, all the remaining variables have the necessary reliability to continue the EFA exploratory determinant analysis.

Table 1. Cronbach’s Alpha coefficient of the external determinants

Exploratory Factor Analysis (EFA)

Exploratory determinant analysis is a statistical technique that helps the study to reduce data to a smaller set of summary variables and to explore the underlying theoretical structure of the phenomena. Besides, the correlation coefficient is zero, so when conducting multiple regression analysis, there is no multicollinearity. Criteria for conducting exploratory determinant analysis is the minimum KMO value of 0.5, the Bartlett test with p-value less than 0.05, the minimum loading determinant of 0.5, the variance extracted is at least 50%, the minimum eigenvalue is 1. Because, exploratory determinant analysis technique does not consider the discriminatory relationship between the dependent and independent variables, but only the relationship between all variables included in the analysis. Therefore, the team will conduct exploratory determinant analysis with independent variables and dependent variables separately. The extraction method is the Principal Component analysis with Varimax rotation to obtain the smallest number of determinants. The analysis results from the data presented below are the results of the third step showing that it is necessary to remove the variables LO3, MA2, MA4, MA6 & IC2 and the second step to remove the variable MA1 & MA5 because the loading determinant is less than 0.5.

Table 2. Analyzing KMO coefficient and Bartlett’s coefficient

With the group of external determinants, the KMO value is 0.901 and the probability level of Bartlett's test is 0.000, showing that the data is completely consistent with the determinant analysis method. The results for the dependent determinant of 0.838 and 0.000, respectively, give the same statement (Table 2).

Table 3. Variance extracted from external determinant analysis

The variance extracted table (Table 3) gives the results of the number of new determinant groups created after EFA analysis and the ratio explaining the change of determinant groups through the Initial Eigenvalues coefficient. With 8 groups of external determinants included in the analysis, 5 new groups of determinants were created with the cumulative explanatory rate of 73.342%. In which determinant group 1 has the most explanation rate of 16,346%, these numbers in groups of determinants 2 to 5 are: 4,813, 1,815, 1,635 and 1.061%, correspondingly. The results of EFA analysis create 5 new determinant groups with the variables having the determinant loading all over 0.5 and sorted from large to small.

Group 1: includes variables of the group of preferential policies, support services, and communication, which are newly named as SUPPORTING SERVICE determinant group. This is the group with the most variables (14 variables) and also the group with the most influence on the data.

Group 2: includes variables of the input cost group, so it is still called EXPENSE determinant group. This group includes 8 variables where Transport cost, and high logistics service variable is the variable with the largest number of loads.

Group 3: includes the variables of the infrastructure group and the geographical location, which is newly named GEOLOGICAL INFRASTRUCTURE determinant group. This group includes 7 variables in which adequate and convenient transportation infrastructure receives the highest rating.

Group 4: includes variables of the human resource group, so it is still called the HUMAN RESOURCES determinant group. The human resource group includes all 5 initial determinants with high appreciation for the Labor variable that meets the expertise of the business.

Group 5: includes only 1 variable of the group of market determinants, so it is called MARKET determinant group. The level of competition is the variable that receives the most attention and is also the determinant with the lowest influence.

Table 4. Variance extracted from dependent determinant analysis

The dependent determinant variable has no change in the number of determinant groups, with the original 4 variables still having only 1 new determinant group with a large explanatory level of 84,090% (Table 4). “Local investment is a right choice” is the variable with the largest number system, demonstrating the consensus in accepting the definition as well as the quality of investment in Vinh Phuc province (Table 5).

Table 5. Matrix of dependent determinants

Model hypothesis test results

After conducting the reliability test and exploratory determinant analysis of EFA, the study took the representative variables for each determinant (through taking the determinant value stored on the software) to include in the analysis multiple regression analysis for 5 influencing determinants obtained from the determinant analysis above, which means 5 independent variables, to measure and evaluate the level of influence on the dependent variable which is investment decision. The observed variables are classified as independent and dependent variables.

Table 6. Linear regression results

The coefficient of determination R^2=0.65 indicates that the built model can explain 65% of the variation of the dependent variable (Table 6). This level of explanation is quite large, so the test results also show that the built regression function is completely suitable. (F_qs=81,797 and probability level is 0.000) (Table 7)

Table 7. Test the relevance of the model ANOVA^a

Table 8. Test the relevance of the model Coefficients^a

The estimated coefficients of determinants 1,2,3,4 are statistically significant at the 1% level (probability level is 0.000) and all have positive signs, showing that they influence investment decisions positively. Meanwhile, only the estimated coefficient of determinant 5 is only statistically significant at 10% (probability level is 0.071) and has a negative sign, showing that there is a negative influence on the dependent variable (Table 8). Based on the normalized absolute value of the coefficient β, it shows that the determinant group (1) Support services has the greatest influence on the dependent variable, followed by the subsequent determinants: (4) Human resources, (3) Geographic infrastructure, (2) Input costs and (5) Market.

Conclusion and recommendations

In short, analysis results: the group of determinants (1) Support services including: preferential policies, support services, communication are the group with the greatest influence on the investment decision, followed by the following groups: (4) Human resources: highly rated the variable Labor meets the expertise of the business; (3) Geographical infrastructure: Adequate and convenient transportation infrastructure is the highest rated; (2) Input costs: Transportation and logistics costs are highly rated and (5) Market: Industry competition is the most concerned variable and also a determinant with minimal influence.

Based on the above research results on attracting investment from large non-state firms in Vinh Phuc, the article has some main recommendations as follows:

First, focusing on supporting services for firms. In fact, Vietnam now has a policy to protect investors and consider investors coming to Vietnam as its citizens. However, it is necessary to: reform administrative procedures, hasten the processing time of administrative procedures, increase access to firms, ensure that officials always maintain an enthusiastic and open attitude to support firms, issue more specific preferential policies to attract large and long-term investors; organize seminars and conferences to guide firms on laws, policies, taxes, procedures, and necessary information; create favorable conditions for firms to have the opportunity to approach and dialogue during the implementation process; build a modern and effective communication system to ensure timely delivery of information, documents, regulations, etc. to firms.

Second, training high-quality human resources and meeting the needs of firms through : introducing policies on training and attracting human resources to ensure a quantity and quality supply for firms, cooperating with universities, colleges, vocational training centers, educational institutions to train and provide quality labor sources suitable to the needs of firms.

Third, investing in the development of infrastructure: There should be traffic projects, investment in infrastructure systems, and fences inside and outside the industrial park, especially to avoid traffic jams on heavy rainy days. Besides, it is necessary to pay attention to improving traffic infrastructure and traffic safety; building, renovating and upgrading drainage systems; ensuring adequate supplies of clean water; and attracting projects to build social housing, housing for workers, housing for professionals, and entertainment areas.

Last, having a policy of attracting and investing in the development of commercial and financial centers, which is also completely reasonable with the wishes of the investment business community in the local area. Trade centers are built and developed to create a business and competitive environment as well as improve people's living standards. It is also necessary to strengthen trade connections with domestic and international localities, raising awareness and understanding about regulations, standards of goods, labor, the environment, rules, trade instructions, benefits and requirements of the Trade Agreement.

About the authors

Minh Phuong Nguyen

Author for correspondence.
Email: Phuongntm@neu.edu.vn
ORCID iD: 0000-0002-5888-4772

Ph.D. (Economics), Senior Lecturer

References

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