Prediction model for foreign direct investment in thai nguyen province

PREDICTION MODEL IN ATTRACTING FOREIGN DIRECT
INVESTMENT IN THAI NGUYEN PROVINCE
A Doctor Thesis Presented to
The Faculty of Graduate School
Southern Luzon State University, Lucban, Quezon, Philippines
in Collaboration with
Thai Nguyen University, Socialist Republic of Vietnam
In Partial Fulfillment of the
Requirement for the Degree
Doctor of Business Administration
Trinh Viet Hung
(Hung)
April 2014

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CERTIFICATE OF ORIGINALITY
This is to certify that the research work / thesis entitled “Analysis of
Factors Affecting Foreign Direct Investment and the Construction Of Prediction
Model for a Sustainable FDI Attraction to Thai Nguyen Province”, orally
defended/ presented under the DBA Program jointly offered by Southern Luzon State
University of the Republic of the Philippines and Thai Nguyen University of the
Socialist Republic of Vietnam, embodies the result of original and scholarly work
carried out by the undersigned.
This thesis does not contain words or ideas taken from published sources
or written works by other persons which have been accepted as basis for the award of
any degree from other higher education institutions, except where proper referencing
and acknowledgement were made.
_____________________
Researcher/Candidate
Date Orally Defended: __________________
Noted:
ASSOC. PROF. NGUYEN TUAN ANH
Dean
International School
Thai Nguyen University
Date: __________________

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ABSTRACT
The objectives of the study is to analyse the factors affecting FDI attraction to
Thai Nguyen Province. The study was conducted in August 2013 in Thai Nguyen.
The data utilized in the research included primary data obtained through a
questionnaire survey with 32 FDI investors in Thai Nguyen Province in August 2013
and secondary data from statistical yearbook and reports of the provincial and central
government. The results obtained from exploratory factor analysis and multivariate
regression analysis showed that factors affecting FDI attraction to Thai Nguyen
Province included: Policy, Confidence of Investors, Infrastructure. In which, Policy
has the highest fluence on FDI attraction. The study also constructed a prediction
model for FDI attraction to Thai Nguyen Province.

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Table of content
CERTIFICATE OF ORIGINALITY................................................................................. 2
ABSTRACT ........................................................................................................................ 3
ACKNOWLEDGEMENTS................................................................................................ 4
LIST OF TABLES.............................................................................................................. 8
LIST OF FIGURES............................................................................................................ 9
CHAPTER 1...................................................................................................................... 10
INTRODUCTION ............................................................................................................ 10
Background of the study............................................................................................... 10
Statements of the problem ............................................................................................ 15
Research objectives ....................................................................................................... 16
1.1. Hypothesis.......................................................................................................... 16
1.2. Scope and Delimitation of the Study ................................................................. 17
1.3. Significance of the study .................................................................................... 18
CHAPTER 2...................................................................................................................... 21
REVIEW OF RELATED LITERATURE AND STUDIES............................................. 21
2.1. Review of Related Literatures................................................................................ 21
2.2. Review of related studies........................................................................................ 24
2.3. Conceptual Framework.......................................................................................... 30
CHAPTER 3...................................................................................................................... 32
RESEARCH METHODOLOGY ..................................................................................... 32
3.1. Locale of the study.................................................................................................. 32
3.2. Research Design ..................................................................................................... 32
Figure 6. Research Design............................................................................................. 32
3.3. Unit of analysis ....................................................................................................... 33
3.4. Data......................................................................................................................... 33
Sources of Data.............................................................................................................. 33
Population, Sample size and Sampling Techniques ....................................................... 33
Instrument of data collection ......................................................................................... 33
3.5. Description of Respondents.................................................................................... 34
3.6. Statistical Treatment.............................................................................................. 35
CHAPTER 4...................................................................................................................... 37
DATA PRESENTATION, ANALYSIS AND INTERPRETATION............................... 37
4.1. Analysis of primary data on investors’ expert opinion on factors affecting FDI
attraction to Thai Nguyen Province.............................................................................. 37
4.2. Analysis of secondary data on factors affecting FDI in Thai Nguyen Province ... 51

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CHAPTER 5...................................................................................................................... 59
Summary of Findings, Conclusions and Recommendations............................................ 59
5.1. Summary of Findings ............................................................................................. 59
5.2. Conclusion ......................................................................................................... 69
5.3. Recommendations.............................................................................................. 71
1. Thai Nguyen Province should focus on offering financial incentives for FDI
investors. For real estate businesses, Thai Nguyen Province should focus on interest
rate preferentials; for companies in manufacturing and processing industries, tax and
land incentives for factory construction may take better effects. ................................ 71
2. Thai Nguyen Province should develop its electric and water supply to ensure the
production and manufacturing of FDI investors and have contingency plans for
emergency cases. ........................................................................................................... 71
3. Thai Nguyen Province should improve the confidence of investors by applying
transparent and equal policies for all investors. Information about investment and
investment policies should be published in the portal of Thai Nguyen Province. The
province should also increase its PCI to improve the confidence of foreign investors.71
4. Thai Nguyen Province should support foreign investors in training human
resource by cooperating with foreign companies in recruitment process and training
(such as language and skills in working in an international environment). Workers
who are introduced to foreign companies should be the ones who are skillful and has
strong sense of discipline............................................................................................... 71
5. Thai Nguyen Province should develop its supporting industries to supply
materials and reduce the costs for major industries. ................................................... 72
6. The transport system should be improved............................................................ 72
7. Thai Nguyen Province should maintain its stable economic growth, which is
attractive to the investors.............................................................................................. 72
8. Based on the changes of variables in the model (3), Thai Nguyen Province can
make decisions on how to attract FDI appropriately................................................... 72
9. The following further research can be conducted to develop the result of this
study:............................................................................................................................. 72
Direction 1: quantify the policy factors into an equivalent amount of money that the
investors may receive from the application of specific policies so that the model can
approach the reality. ..................................................................................................... 72
Direction 2: further research can be conducted to explore specific needs of the
investors, focusing on the factors which have been found in this study as well as the
the fulfilment ability of Thai Nguyen Province in those factors. Solutions should be
proposed for both sides. ................................................................................................ 72
Direction 3: the study has proposed solutions to attract FDI, but has not suggested
any solution to retain the investors and expand their business in Thai Nguyen.
Therefore further study can be conducted with this objective. ................................... 72
REFERENCES ................................................................................................................. 73

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Hair, J.F. et. al. 2009. Multivariate Data Analysis (7th Edition). Prentice Hall.............. 74
Stevens, J.P. 2002. Applied Multivariate Statistics for the Social Sciences, Fifth Edition.
Taylor and Francis group................................................................................................. 74
APPENDIX ....................................................................................................................... 76
Appendix A.................................................................................................................... 77
QUESTIONNAIRE SURVEY FORM FOR INVESTORS/ ........................................ 77
BẢNG CÂU HỎI ĐIỀU TRA....................................................................................... 77
Appendix B.................................................................................................................... 81
RESULT OF REGRESSION ANALYSIS ON SAS..................................................... 81
2 GDP 2 0.1739 0.6926 14.5651 5.66 0.0387........................... 86
CURRICULUM VITAE ............................................................................................... 87
Major Field: Economics......................................................................................... 87
Degree obtained: Masters’ Degree.......................................................................... 87
Year of Graduation: 2010 ........................................................................................ 87
WORK EXPERIENCES........................................................................................... 88

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LIST OF TABLES
Table Page
Table 1. Correlation Analysis between FDI and socio-economic
index (2000-2012)
Table 2. Five point Likert’s Scale
Table 3. Description of Respondents’ Profile
Table 4. Factors before conducting EFA
Table 5. Correlation among variables (survey questions)
Table 6. Rotated component matrix
Table 7. Component Score Coefficient Matrix
Table 8. Reliability of the Exploratory Factors
Table 9. Average Mean Distribution of Investors’ Responses to
Factors affecting FDI attractiveness of Thai Nguyen
Province
Table 11. Simple correlation between FDI attractiveness and its
predictor factors
Table 12. Result of simple linear regression analysis on FDI
attractiveness as perceived by investors and its predictor
variables
Table 13. Summary of Backward Elimination
Table 14. Descriptive statistics of FDI and its predictor variables
from 2000 to 2013
Table 15. Simple Correlation Analysis between FDI and its
predictor variables
Table 16. Result of simple linear regression analysis on FDI in Thai
Nguyen Province and its predictor variables
Table 17. Summary of Forward Selection

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LIST OF FIGURES
Figure Page
Figure 1. Gross Domestic Products of Thai Nguyen Province (2000-
2013)
Figure 2. GDP by sectors in Thai Nguyen Province (2000-2013)
Figure 3. Registered FDI in Thai Nguyen Province (2000-2013)
Figure 4. Comparison of registered FDI among provinces (2010-
2013)
Figure 5. Conceptual Framework
Figure 6. Research Design
Figure 7. Model testing (primary model)
Figure 8. Model testing (secondary model)

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CHAPTER 1
INTRODUCTION
In recent years, a big change in trend of FDI inflows with a remarkable growth
in FDI to developing countries has been witnessed. Especially in 2012, developing
countries have surpassed their developed counterparts in attracting FDI with 9
developing countries ranked in top 20 FDI attractive countries (UNCTAD, 2013).
As reported by the United Nations Conference on Trade and Development
(UNCTAD, 2012), developing countries in Asia are the leadings to attract FDI during
the period from 2008 to 2012. Despite the decrease of 7% in FDI inflows in the whole
region in 2012, some countries including Vietnam were bright spots for labor-
intensive FDI. Vietnam was also considered one of most FDI attractive among low-
income host countries (together with Combodia, Myanmar and Philippines).
UNCTAD (2012) forecasted that Vietnam would be one of the potential attractive
hosts for the period 2013-2015.
Background of the study
Thai Nguyen Province is the central province of the Northern mountainous and
midland region of Vietnam in terms of politics and economy. It is also considered the
socio-economic gateway connecting the mountainous and the Red River Delta. Thai
Nguyen Province has border with Bac Can province in the North, Vinh Phuc, Tuyen
Quang in the West, Lang Son and Bac Giang in the East and Hanoi capital in the
South.
Thai Nguyen also has a very convenient location for transportation which is 50
kilometers far from Noi Bai International airport, 200 kilometers far from China and
200 kilometers from Hai Phong port. Thai Nguyen is also a transporting intersection

11
through the system of roads, railways, waterways. Thai Nguyen is located on the
highway 3 from Hanoi to Bac Can, Cao Bang and the border gate with China.
Thai Nguyen has a population of more than 1.2 million with variety of ethnic
groups such as King, Tay, Nung, San Diu, H’mong, San Chay, Hoa and Dao. In
addition, Thai Nguyen is also known as the third largest human resource development
center after Hanoi and Ho Chi Minh City with Thai Nguyen University, more than 11
colleges, 9 vocational colleges which offers training for more than 100.000 people
every year.
Thai Nguyen has abundant and diverse natural resources which can be
considered as a comparative advantage for the development of mining, and
metallurgical industry. Coal reserves in Thai Nguyen ranked second in the country
with fat coal reserves of more than 15 million tons, charcoal reserves of around 90
million tons, ferrous metals include tin, lead, zinc, tungsten, gold, copper, nickel,
mercury, etc. Minerals for construction materials are also potentials for cement and
paving stones manufacturing.
Infrastructures of the province such as electricity, water supply,
telecommunications and transportation have also been developed and convenient.
In recent years, there have been positive changes in the socio-economy of the
province with the growth in production in important industries, growth has been
witnessed in all sectors, especially non-public sector has shown its roles in the multi-
sector economy.

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1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
0
5000
10000
15000
20000
25000
30000
35000
Figure 1. Gross Domestic Products of Thai Nguyen Province (2000-2013)
Figure 1 illustrates annual GDP growth of Thai Nguyen Province, from which
it can be seen that GDP increased gradually with years at the equal or higher in
compared with the whole country. In 2012, GDP of the province reached 29.508
billion VND, increased by 16% in compared with 2011.
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
0
20
40
60
80
100
Figure 2. GDP by sectors in Thai Nguyen Province (2000-2013)
GDP(BillionVND)
Year
GDPbysector(%)
Year
Agriculture and Forestry
Industry and Construction
Service

13
Figure 2 shows GDP by sectors in Thai Nguyen Province, which has
transformed positively from 2000 to 2013. Growth in Industry and Construction
sector increased faster while that in Agriculture and Forestry sector grew slower than
the other sectors. The economy transformed sustainably.
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
0
500
1000
1500
2000
2500
Figure 3. Registered FDI in Thai Nguyen Province (2000-2013)
Figure 3 describes foreign direct investment registered to Thai Nguyen
Province in the duration of 2000-2013. In general, registered FDI in Thai Nguyen
Province had not many changes during 2000-2012 except for 2004 and 2007 when
registered FDI reached 148.1 million USD and 117.8 million USD.
However, in the first six months of 2013, registered FDI soared to 2.14 billion
USD which is an extraordinary increase in FDI inflows to the province.
RegisteredFDI(MillionUSD)
Year

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2009 2010 2011 2012 2013
0
500
1000
1500
2000
2500
Figure 4. Comparison of registered FDI among provinces (2010-2013)
Figure 4 compares registered FDI between Thai Nguyen Province and other
provinces in the Northern region from 2010 to 2013. During 2010-2012, registered
FDI in Thai Nguyen Province was much lower than other provinces while that of Bac
Ninh, Quang Ninh and Phu Tho was quite high. However, in 2013, registered FDI to
Thai Nguyen Province increased dramatically to times of FDI to other provinces.
FDI had a positive effect to the economic growth, export and unemployment of
Thai Nguyen and contributed to the development of the province.
Table 1. Correlation Analysis between FDI and socio-economic index
(2000-2012)
FDI GDP EXP UNE
FDI 1
GDP 0.554 1
EXP 0.719** 0.931*** 1
UNE -0.574* -0.387 -0.327 1
* Significant a probability of 0.05
** Significant a probability of 0.001
*** Significant a probability of 0.0001
Where:
GDP : Gross Domestic Products (Billion VND)
FDI : Annual disbursed FDI (Million USD)
EXP : Export value (Thousand USD)
UNE : Unemployment rate (%)
RegisteredFDI(MillionUSD)
Year
Thái Nguyên
Bắc Giang
Phú Thọ
Quảng Ninh
Bắc Ninh
Vĩnh Phúc

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FDI had a significant positive correlation with GDP growth and export value of
the province and had a negative impact to reduce unemployment rate. However, in the
past thirteen years, FDI inflows to Thai Nguyen Province was instable and
unpredictable. Particularly in 2013, FDI inflows to Thai Nguyen Province increased
significantly.
This situation raised to the researcher a question on which factors affecting FDI
inflows to Thai Nguyen Province and what can be proposed as recommendation for
the province to maintain stable FDI inflows in order to help promote the socio-
economic development of the province.
After reviewing literature and studies relating to status of FDI in Vietnam,
especially in Thai Nguyen Province, the researcher came to a decision to conduct this
research with the aims of analyzing factors influencing FDI inflows and finding out
the core problems in FDI attraction to the province, from which to come up with
recommendations for Thai Nguyen to employ and apply the most effective methods
into FDI attraction.
For all the reasons above, the researcher would like to conduct the study entitled:
“Analysis of Factors Affecting Foreign Direct Investment and the Construction
Of Prediction Model for a Sustainable FDI Attraction to Thai Nguyen Province”
and propose it to Thai Nguyen Province with the expectation of supporting the
development of the province in particular and the whole region in general.
Statements of the problem
The research aims at determining and analyzing factors affecting foreign direct
investment to Thai Nguyen Province necessary in maintaining stable FDI inflows.
The factors that were taken into account came from the Economic and market factors,
Political and policy factors, Natural resources and geographical conditions, Social

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conditions. Thereafter, the researcher will propose appropriate solutions and
suggestion to enhance the FDI inflows to Thai Nguyen Province.
Research objectives
This study aimed to formulate the prediction model in attracting FDI in Thai
Nguyen Province. Particularly, the purpose of this study is to answer the following
questions:
1. What is the profile of the company in terms of:
- Name;
- Country of investor;
- Years of investment in Thai Nguyen Province;
- Nature of business;
- Investment capital.
2. What are factors affecting FDI attractiveness of Thai Nguyen province based
from investors’ expert opinion in terms of:
- Economic and market factors;
- Natural conditions and infrastructure;
- Political and policy factors;
- Social condition factors;
What model can best predict FDI inflows to Thai Nguyen Province?
3. What strategies should be proposed for the enhancement of FDI inflows in
Thai Nguyen Province?
1.1.Hypothesis
The study focused to test these two hypotheses:
(1) Factors affecting FDI attractiveness to Thai Nguyen Province:
= 0
+ 1
× + 2
× + 3
× + 4
×

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Where:
OAS : Overall assessment of FDI attractiveness as perceived by investors
POL : Policy factors
ING : Natural resource, and geographical factors
ECO : Economic and market factors
SOL : Social conditions
The hypothesis to be tested is:
: = = = = 0
: ≠ 0 ( = 1 ÷ 4)
(2) Prediction model of FDI registered to Thai Nguyen Province:
= + × + × + × + × . + × .
+ × . + × + × + × +
Where:
FDI : FDI registered in Thai Nguyen Province in year t (Million USD)
GDP : Gross domestic products in year t-1 (Billion VND)
EXP : Export value of Thai Nguyen Province in year t-1 (Thousand USD)
PCI : Provincial competitiveness index in year t-1
P.FIN : Financial incentives for investors in year t (if yes: 1, if no: 0)
P.LAND : Land incentives for investors in year t (if yes: 1, if no: 0)
P.ADMIN : Administrative privileges for investors in year t (if yes: 1, if no: 0)
INFR : National budget expenditure for development in year t-1 (Billion VND)
INFL : Inflation rate in year t-1 (%)
URB : Urbanization year t-1 (%)
The hypothesis to be tested is:
: = = = = = = = = = 0
: ≠ 0 ( = 1 ÷ 9)
1.2.Scope and Delimitation of the Study
The study aims to determine and analyze the factors affecting FDI attraction to
Thai Nguyen Province. The researcher proposed to collect primary data through
information provided by questionnaire survey for respondents who were holding a
management position at 32 FDI enterprises in Thai Nguyen Province in August, 2013.
The secondary data was also obtained from reports on socio-economy, yearly
statistical books and reports of the Vietnam Chamber of Commerce and Industry from
2000 to 2013.

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1.3.Significance of the study
The results of this research will be of benefit to the policy makers of Thai
Nguyen Province in shape an appropriate promotion policy to maintain the FDI
inflows to Thai Nguyen as what it performed in 2013. Also, limitation and drawbacks
in provincial strategy of FDI attraction will also be found, from which will help them
to design better strategy for FDI attraction for the province. Moreover, the results
shall be used as a significant reference for the provincial government to make the
most realistic development plan which is suitable with the characteristics of the
province, attach FDI attraction to the long-term development of Thai Nguyen
Province, and to draw focused policies in the development plan of the province.
If the results of this research is applied, it would help to enhance the FDI
attraction performance of Thai Nguyen Province in the most sustainable way. This, in
turn, will help to improve the growth and development of Thai Nguyen, create more
jobs and reduce poverty and unemployment.
The research will also enable FDI investors to raise the voice of their seeking
for an effective and competitive investing environment. This will create more
available opportunities for investors if they invest to Thai Nguyen.
The results shall also be applied to other provinces in the Northern mountainous
region of Vietnam which have similar conditions to Thai Nguyen, this will forms a
basis for nearby provinces to conduct further research to give their own solutions for
their provinces.
For the researcher, the study is considered as an opportunity for her to have a
better understanding about the investments of Thai Nguyen Province. This will also
bring her more broader and deeper research ideas on FDI.

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1.4.Definition of terms
Foreign Direct Investment Investment from one country into another
(normally by companies rather than
governments) that involves establishing
operations or acquiring tangible assets,
including stakes in other businesses
Registered FDI Total amount of FDI as registered in the
business registration to Thai Nguyen
Province
Disbursed FDI The amount of FDI disbursed at the time
of survey
Provincial Competitiveness Index Introduced in 2005 as the results of
fruitful collaboration between the
Vietnam Chamber of Commerce (VCCI)
and the U.S Agency for International
Development (USAID), the Provincial
Competitiveness Index (PCI), in order to
promote the development of the private
sector, is designed to assess the ease of
doing business, economic governance,
and administrative reform efforts by local
governments of 63 provinces and cities in
Vietnam.
Financial Incentives Incentives given to the investors such as:
tax incentives, interest rate incentives.

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Land Incentives Incentives given to the investors such as:
land leasing, facilities
Administrative Incentives Incentives given to the investors such as:
assistance during administrative
procedures, investment and trade
promotion, etc.

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CHAPTER 2
REVIEW OF RELATED LITERATURE AND STUDIES
This chapter presents the general discussion of the literatures and studies on
the foreign direct investment and its effect factors in the global and Vietnamese
context.
2.1. Review of Related Literatures
In any country, despite its level of development, resources for investment to
create new values and assets for the society are necessary for economic growth and
social development. Resources can be mobilized from both internal and external
forces from foreign countries. With regard to a developing country as Vietnam, with
the limitation in internal resources, and accumulation ability is low while demands for
investment are very high, resources from foreign direct investment then plays a very
important role.
According to the International Monetary Fund (IMF), FDI is defined as "an
investment for the long-term relationship”. According to this definition, an
organization in an economy (direct investor) obtained long-term benefits from a
business located in an economy.
United Nations Conference on Trade and Development UNCTAD also provides
a definition of FDI. Accordingly, FDI inflows include capital provided (either directly
or through a related company) by a foreign direct investment for FDI enterprises, or
home equity that foreign direct investment received from FDI enterprises. FDI has
three components: equity capital, reinvested earnings and loans within the company.
According to the 1987 Vietnamese Investment Law, foreign direct investment
is that foreign investors bring capital into Vietnam in cash and other assets to conduct

22
legitimate investment activity on a contractual basis or establishment of joint venture
company or 100% foreign investment company.
From the above definitions, foreign direct investment can be defined as
follows: “Foreign Direct Investment to a country is that foreign investors bring capital
in the forms of cash or assets in order to take the ownership or management of a
business in that country with the aim of benefit optimization”. Therefore, FDI is
always a type of business with a foreign firm. Two major features of FDI are the
existence of international capital movement and the investors use and manage their
capital directly.
The impacts of FDI to the economy of the recipient country depend on
elements of the macroeconomy such as: savings-investment ratio, international
economic and financial integration level. FDI influences the macroeconomy by (1)
increasing investment capital in recipient countries, (2) a more stable capital than
loans and (3) improving integration, external influences and reformation of the
economy, which cannot be achieved by internal capital.
FDI affects economic growth by increasing products or improving the
effectiveness natural resources use in recipient countries. This can be done through
channels: import-export, spillover effects and external effects to domestic enterprises.
Previous studies on effects of FDI to the economic growth have concluded:
Most of empirical research indicated that FDI in general has positive impact
on products and income of the recipient country, in plus to what domestic investment
can make. However, it is quite difficult to evaluate the degree of influence (OECD,
2002).
FDI, however, seemed to have less positive effects on economic growth in less
developed countries. Obviously, developing countries need to reach a specific level of

23
educational, technological and scientific development before being benefited from
foreign direct investment. Another element that also prevents a country in optimizing
the benefits of FDI is an inaccurate and less developed financial market (Hermes and
Lensink, 2000).
However, most of studies revealed positive effects of FDI to the economy (De
Mello (1999), Xu (2000), Reisen và Soto (2000))
Trade and investment were concluded to be interactive channels in foreign
investments. However, recipient countries need to consider short and mid-term effects
of FDI on foreign trade, particularly when facing financial pressure. Studies related to
this issue showed that in a developed country with a specific industrialization level,
FDI will help increase the international trade for the economic integration. Two
channels of tranferring the impacts of FDI to trade includes: the development of
business network and the importance of branches in distribution, sales and marketing
of multinational companies. It could be seen that FDI attraction ability of a
developing country is under a great influence of the ability of investor to approach
import and export activities. Therefore, countries who want to receive investments
should consider opening trade to be a strategy in attracting FDI in order to optimize
the benefits from this source of capital.
Technology transfer was considered as one of the most important external
impacts of FDI to a recipient country. However, the level of techonology development
of the recipient country is also important in this case. Previous studies showed that
whether FDI had positive or negative influence on products growth also depends on
the differences in technological development levels between domestic businesses and
foreign investors. When the technological development levels of domestic companies

24
is much lower than foreign investors, it will be more difficult for the former to receive
technological transfer from the latter.
The impacts of FDI on human resource development oftens take effects
through the government policies rather than individual FDI enterprises. Once a person
is employed, their knowledge and skills will be improved during their work and
training. Foreign investors also play an important and positive role in training the
human resource for the domestic partners that they are cooperating, including their
suppliers. When the human resource is improved, it can also result in a resonant
impact in circulating labor among firms, as well as enable staff to become the
business owners.
FDI and the presence of multinational companies has a great influence on
creating a competitive market in recipient countries. Foreign investors play the role of
improving the competitiveness and finally the growth in products, the decrease in
price and the effectivess of using human resources.
2.2. Review of related studies
A number of research has been conducted to define determinants of FDI. In this
section, the researcher focused on the publications in the context of developing
countries, especially in Asia as well as publication on FDI in Vietnam. Different
factors were concluded to be significant elements of FDI inflows, which can be
divided into groups as follows:
1. Economic and market factors
Among factors that were found to be important in encouraging FDI, products
seems to be discovered as contribute to FDI inflows by most researchers. Marcelo and
Mário (2004)’s research on a sample of 33 developing countries who played the role
of FDI hosts during the period from 1975 to 2000 using panel data methodology

25
found that the average rate of gross national products (GNP) growth over the previous
5 years had significant influence on FDI inflows. Holland and others (2000) also
mentioned in their paper on FDI in Eastern and Central Europe that a country growth
potential will attract more FDI. The same conclusion was also produced by Morisset
(2000) and Moosa (2002).
Another trend of studies on the relationship between FDI and GDP growth was
the reverse causality between these two variables. Borensztein and others (1995)
studying on data for the 1970 – 1989 period concluded that the effect of FDI on
economic growth depends on the level of human capital in the host countries. The
higher of human capital level, the more positive effect. Also, FDI encourage
economic grow through the increase of supplemental activities.
Economic index and its stability also tend to result in an attractive sign for
foreign direct investors. Justice (2012) researched on a number of previous papers on
FDI in Ghana said that many research showed that the exchange rate had a great
influence, especially volatility of exchange rate made a negative impact on FDI
inflow to the whole economy. Bende - Nabende (2002) collected data over the 1970 –
2000 also revealed the important role of real effective exchange rates to FDI of 19
Sub-Saharan African countries .
According to Ohlin (1933), low rates of interest in the host country would
produce high profits and possibility of financing, which motivated foreign investors.
Garibaldi and others (2001) suggested a number of economic variables such as market
size, fiscal deficit, inflation and exchange regime, risk analysis, economic reforms,
trade openness, availability of natural resources, barriers to investment and
bureaucracy which were significant in attracting FDI to transition economies.

26
Market size was also the conclusion of other authors: Holland and others (2000),
Campos and Kinoshita (2003), Bandera and White (1968), Schmitz and Bieri (1972),
Lunn (1980): one-period-lagged GNP, Root and Ahmed (1979), Torrisi (1985),
Schneider and Frey (1985), Petrochilas (1989), Wheeler and Mody (1992), Bende -
Nabende (2002), and Justice (2012).
In addition, the accession of economic clusters and/or regional blocs also enable
host countries to enhance FDI inflow performance (Asiedu, 2006, Campos and
Kinoshita, 2003). Evidence from Vietnam also revealed that after Vietnam acceded
the World Trade Organization in 2007, FDI inflows in Vietnam has significant
positive impact on attracting FDI in the 3 years thereafter (Chien, Zhang, and Giang,
2012).
The macroeconomic stability was indentified by inflation and risk rating, those
variables also played an important negative role in FDI attracting, in which inflation
had greater influence in a larger sample while the latter took the role in a smaller
sample in the model of Marcelo and Mario (2004).
Other economic and market factors namely fiscal deficit, economic reform
(Garibaldi and others, 2001), per capita energy consumption (Marcelo and Mario,
2004), export, especially manufacturing export (Harinder and Kwang, 1995),
privatisation of public enterprise (Chuhan et al., 1996), were also explored to be
significant in FDI attraction.
2. Political and policy factors
One of the first issues to be taken into consideration when a firm decides to
invest is the political stability of the destination country since the investor will take
many risks from external environment in an instable host.

27
Political risks were considered as negative factor to FDI attraction, including
change in government leadership (Root and Ahmed, 1979), intracountry political
events (Nigh, 1985), number of political strikes and riots in host countries (Schneider
and Frey, 1985) and other sociopolitical instability. According to Justice and Gloria
(2012), degree of democracy in host countries was also important variable for FDI
inflows.
As found by many researchers, host country’s policy is among leading factors in
attracting FDI inflows through its effects on trade restriction, cost of labor, exchange
rate, corporate tax, etc. (Demekas et al., 2007). Loree and Guisinger (1995) studying
determinants of foreign direct investment by the United States in 1977 and 1982
revealed that host country’s policy was significant variable in developed countries
while it was not high rated in developing countries. Asiedu and Brempong (2000) in
their research on “The Effect of the Liberalization of Investment Policies on
Employment and Investment of Multinational Corporations in Africa” found that
countries with open policies would attract more FDI.
Trade barriers, especially foreign trade barriers are one of the most challenging
for foreign investor in making decision in investing to a country. Restrictions in trade
and investment would cause reduction in FDI inflows as resulted by Nunnenkamp and
Spatz (2002), Basu and Srinivasan (2002), and Campos and Kinoshita (2003).
Spearman correlation conducted by Nunnenkamp and Spatz (2002) showed that
administrative bottlenecks and foreign trade restriction had negative impacts to FDI.
Conversely, the degree of trade openness in host country would improve FDI
attraction were also proved by Morisset (2000), Garibaldi and others (2001), Asiedu
(2002), Bende - Nabende (2002), Justice and Gloria (2012).

28
Trade policy of a country could also be expressed through tax policy, however,
recent evidence showed that tax has insignificant role in attracting FDI. Obwona
(2002) said that generous incentive packages: tax holidays, exemptions were not
much effective on FDI to Uganda. Another test by Harinder Singh, Kwang W. Jun
(1995) on determinants of FDI in developing countries also supported the “tariff
hopping” hypothesis, in which, tax on international trade and transactions caused
uncompetitiveness in exporting to a potential host country, FDI thus would be better
way of market penetration.
The greatest point in the study of Harinder and Kwang (1995) was finding that
an export orientation in policy is the strongest variable to explain the FDI
attractiveness of a host country. This hypothesis was also proved by Lucas's (1993) in
Southeast Asian countries and Bende and Nabende (2002) in 19 SSA countries.
Harinder and Kwang (1995) also pointed out the importance of creating a good
business operating environment in attracting FDI.
In Vietnam, policies for investment promotion were applied widely in the
country with the aim of improving FDI attraction (Thinh, 2011). However, the results
were not as high as expected in some regions. Long (2007) in his study on
“Foreigners poised to celebrate tax parity” reached a surprising conclusion on the
effectiveness of policies for investment promotion that there was an inverse trend of
FDI inflows in regions/provinces where stronger promotion policies were introduced.
Incentive policies did not always show its effectiveness but varied in different
contexts.
3. Natural resources and geographical conditions
Natural resources were argued to have great influence on FDI attraction (Asiedu
and Lien (2004), Deichmann et al. (2003), Onyeiwu and Shrestha (2004) and Jadhav

29
(2012). Ohlin (1933) also concluded that secure sources of raw materials are
determinant for FDI attraction. Campos and Kinoshita (2003) and Garibaldi and
others (2001) also included abundant natural resources in the motivations for FDI
attraction in transition countries during 1990-1998. Natural resources also impacted
the decision making of investment by foreign investors in Vietnam (Loc and Tuyet,
2013).
Geographical location and infrastructure were of concern to foreign investors, in
which, the quality and development of infrastructure played a very important role in
decision making of investment (Asiedu (2002), Hollenstein (2005), Jovana Trkulja
(2005), Anh and Thang (2007), Loc and Tuyet (2013)).
4. Social conditions
Foreign investment is producing outside of the home country, firms therefore
will have less initiatives in employing labor for the production process. Labor, at this
stage, is a heavy burden to foreign investors. As found in previous papers, investors
would be most concerned about years of schooling of labor force (Nunnenkamp and
Spatz, 2002), level of schooling (Marcelo and Mario, 2004), cost/wages of labor
(Campos and Kinoshita (2003), Flamm (1984), Schneider and Frey (1985), Lucas
(1993), and Wheeler and Mody (1992). Human capital was also found to be more
significant in less developed countries than in developed countries (Buckley and
others, 2002).
Human capital and cost of labor were also assessed by Vietnamese and Chinese
researchers to be significant in attracting FDI (Anh and Thang (2007), Thinh (2011),
Loc and Tuyet (2013), Li (2005)).
Cultural gap could effect FDI inflows which was mentioned in studies in the
field of international business and investors were likely to invest in a country with

30
similar culture with their home country (Gao, 2005). This also explained the reason
why investments developed within a region more than cross-region (Galan and
Gonzalez, 2001).
The Vietnam Chamber of Commerce and Industry introduced Provincial
Competitiveness Index (PCI) in their cooperation with the US Agency for
International Development to support investors in identify whether a potential host
province is appropriate. This indicators has long been used by foreign investors to
assess the business environment of a region/province in Vietnam. However, previous
research also revealed that in the period 2001-2010, high PCI provinces attracted less
FDI than the others (Chien, Linh and Zhang, 2012). Two dummy events in 2005 and
2007 with the issuance of Vietnamese Law of Investment and Vietnamese accession
to WTO were also found to boost FDI inflows to the country dramatically.
In addition, in Vietnam, the administrative procedures and support by the local
government had a great influence on FDI attraction. This may be implied by the time
of administrative procedures processing, skills and attitudes of administrative staff,
the availability and willingness of the local government in assisting investors, and
favourable response to the queries of investors if necessary (Loc and Tuyet, 2013).
2.3. Conceptual Framework
Based from the readings of related literature and studies, the researcher
designed his research paradigm in order to accomplish the objectives of the study.
Below is the illustration of his study that will provide direction to attain the objectives:
The research utilized both primary and secondary data to analyze the FDI
attractiveness of Thai Nguyen Province and to predict registered FDI to this province.
Basically, the investors were asked for their opinion on economic and market
condition, policy situation, Natural resource, geographical and infrastructure

31
characteristics and social condition of Thai Nguyen Province. The investors also gave
their opinion on how attractive Thai Nguyen Province was to them as a destination of
investment. The researcher would then analyze the correlation between the opinion on
the investment condition and the FDI attractiveness of Thai Nguyen Province. From
this analysis, the researcher would find out among the given factors, which had the
most impacts to their decision of investment to the province.
Regarding the second path of the research, the researcher wanted to test how
independent variables namely: Economic growth, Export value, Provincial
Competitiveness Index, Incentive policies, Investment for infrastructure, Inflation rate,
Urbanization affected the FDI registered in Thai Nguyen Province from 2000 to 2013.
From this, the researcher aimed to develop a prediction model for FDI registered in
Thai Nguyen Province in the next years based on the independent variables.
Independent variables Dependent variable
1. Primary data: Investors’
expert opinion on factors
affecting FDI in Thai
Nguyen Province:
1.1. Economic and market
factors
1.2. Policy factors
1.3. Natural resource,
geographical and
infrastructure factors
1.4. Social condition
FDI attractiveness of Thai
Nguyen Province
2. Secondary data:
2.1. Economic growth
2.2. Export value
2.3. Provincial
Competitiveness Index
2.4. Incentive policies
2.5. Investment for
infrastructure
2.6. Inflation rate
2.7. Urbanization
Predicted FDI in Thai
Nguyen Province
Figure 5. Conceptual Framework

32
Literature &
study review
Primary data
Secondary
data
Individual
factors
Overall
opinion
Influence of expert
opinion on individual
factors to overall
investors’ expert opinion
Influence of individual
factors to FDI attraction
in Thai Nguyen
Province
2. Prediction of FDI
attraction in Thai
Nguyen
Research
objectives
1. Prediction of
investors’ decision on
investing in TN
CHAPTER 3
RESEARCH METHODOLOGY
This chapter presents the research methodology which includes research design,
description of the respondents, population, sample size and sampling techniques,
research instrument, data gathering procedure and statistical treatment applied for the
analysis of data in this study.
3.1. Locale of the study
The research was conducted on the administrative staff of 32 FDI
investors/companies who were investing in Thai Nguyen Province in August, 2013.
The secondary data were collected from Socio-economic Report of the Central
Government and Thai Nguyen Provincial Government, reports from General Statistics
Office, reports of Vietnam Chamber of Commerce and Industry from 2000 to 2013.
3.2. Research Design
The study utilized both primary data and secondary data in doing research.
Research process is illustrated in the diagram below:
Figure 6. Research Design

33
3.3. Unit of analysis
The unit of analysis in this study is administrative and management staff of 32
FDI companies investing in Thai Nguyen Province in August 2013.
3.4. Data
Sources of Data
Primary data were collected by utilizing questionnaire surveys on administrative
and management staff of 32 FDI companies investing in Thai Nguyen Province in
August 2013. Secondary data were collected from Socio-economic Report of the
Central Government and Thai Nguyen Provincial Government, reports from General
Statistics Office, reports of Vietnam Chamber of Commerce and Industry from 2000
to 2013.
Population, Sample size and Sampling Techniques
In August, 2013, there were 32 FDI companies investing and operating their
investment in Thai Nguyen Province, the researcher conducted the research on the
population of 32 FDI companies and did the survey on 180 respondents who were
holding a management position of those companies.
Instrument of data collection
The researcher collected primary data from respondents who 180 respondents
who were holding a management position of FDI companies in Thai Nguyen Province
by doing survey with questionnaire checklist which is designed with two parts of
contents as follows:
Part 1 includes detail information of the companies’ profile such as: name of
the company, country of investment, years of investment, nature of business, total
investment capital.

34
Part 2 consists of questions regarding investors’ expert opinion on factors
affecting decision of investing in Thai Nguyen Province.
The researcher collates data and measures the investors’ expert opinion using
five point Likert’s Scale as described in Table 2.:
Table 2. Five point Likert’s Scale
Rating
Scale
Interval Choice Description Verbal
Interpretation
5 4.20 - 5.00 Strongly Agree (SA) Excellent
4 3.40 - 4.19 Agree (A) Good
3 2.60 - 3.39 Neither Agree Nor Disagree (NN) Fair
2 1.80 - 2.59 Disagree (D) Poor
1 1.00 - 1.79 Strongly Disagree (SD) Needs
Improvement
The researcher also contacted the Provincial Government, Department of
Provincial Statistics, Vietnam Chamber of Commerce and Industry, search on website
of General Statistics Office and reports of state and provincial government for data on
FDI such as: FDI inflows in Thai Nguyen, gross domestic products of Thai Nguyen,
export values of Thai Nguyen, provincial competitiveness index, government’s
investment on infrastructure, inflation rates and urbanization rate of Thai Nguyen
Province from 2000 to 2013.
3.5. Description of Respondents
Table 3. Description of Respondents’ Profile
No Respondents' Profile Items Total Percent
1 Country of investor
Singapore 2 6.25
Japan 2 6.25
Taiwan 7 21.88
Germany 3 9.38
China 8 25
Korea 9 28.13
Malaysia 1 3.13
Total 32 100

35
No Respondents' Profile Items Total Percent
2 Years of investment
From 0 to under 5 years 18 56.25
From 5 to under 10 years 13 40.63
From 10 years above 1 3.13
Total 32 100
3 Nature of business
Agriculture, Forestry and
Fishery 1 3.13
Mining 2 6.25
Processing and
Manufacturing industry 20 62.5
Water supply and waste
disposal 1 3.13
Construction 2 6.25
Wholesaling and retailing,
automobile repairing 2 6.25
Accommodation and
catering services 1 3.13
Real estate 1 3.13
Medical and social services 1 3.13
Arts and entertainment 1 3.13
Total 32 100
4
Total investment capital
registered
Under 20.000 USD 29 90.63
From 20.000 USD to under
50.000 USD 2 6.25
From 50.000 above 1 3.13
Total 32 100
3.6. Statistical Treatment
In order to analyze primary data, the following statistical treatments were
utilized to synthesize gathered data:
- KMO-Bartlette and Cronbach Alpha testing were utilized to evaluate the
scale and the correlation among survey questions as the basis for Exploratory Factor
Analysis.
- Exploratory Factor Analysis (EFA) was employed to remove unqualified
questions in the questionnaire and to group correlated questions (components) into
factors for further analysis. It aims to find out statistically significant factors from
existing variables by using rotation and extraction techniques.

36
- Frequency and Percentage of distribution is used to aggregate profile of the
respondents concerning companies’ profiles.
- Mean, Standard Deviation, Min, Max and Coefficient of Variation were
utilized to describe the gathered data.
- Simple correlation analysis was used to compare the FDI attraction and its
predictor variables, and to compare the investors’ expert overall opinion and
individual factors.
- Finally, stepwise regression analysis with forward selection was applied to
identify variables with the most significant effect on FDI attraction as well as
investors’ expert opinion on FDI attraction in Thai Nguyen Province.

37
CHAPTER 4
DATA PRESENTATION, ANALYSIS AND INTERPRETATION
This chapter presents the research results, the interpretation and the analysis of
the data from the sub-problems mentioned in the study.
4.1. Analysis of primary data on investors’ expert opinion on factors affecting
FDI attraction to Thai Nguyen Province
The questionnaire had 33 questions included in 4 factor groups: (1) Economic
and Market Factors, (2) Policy Factors, (3) Natural Resource, Geographical and
Infrastructure Factors, and (4) Social Condition, and 3 questions which measured the
overall assessment of FDI investors. Questions (variables) before analysis were
grouped into factors as described in the Table 4, all of them were 5 Point Likert
Rating Scale questions.
Table 4. Factors before conducting EFA
Factors Variables (questions)
1. Economic and Market Factors eco1, eco2, eco3, eco4
2. Policy Factors pol1, pol2, pol3, pol4, pol5, pol6, pol7
3. Natural Resource, Geographical
and Infrastructure Factors
ing1, ing2, ing3, ing4, ing5, ing6, ing7, ing8,
ing9, ing10, ing11, ing12
4. Social Condition sol1, sol2, sol3, sol4, sol5, sol6, sol7, sol8,
sol9, sol10
5. Overall assessment oas1, oas2, oas3
Table 2 describes factors (groups of questions) and variables (questions) in each
factor, in which:
- Economic and Market Factors include 4 variables (4 questions);
- Policy Factors include 7 variables;
- Natural Resource, Geographical and Infrastructure Factors include 12
variables;

38
- Social Conditions include 10 variables;
- Overall Assessment includes 3 variables.
There were 36 variables (questions) used to conduct the Exploratory Factor
Analysis.
Exploratory Factor Analysis (EFA)
The objective of Exploratory Factor Analysis (EFA) is to rearrange the questions
in the questionnaire into factors where items in each factors has significant
correlations. The found factors are called exploratory factors and will be used as
variables for further analysis to indentify the factors affecting FDI attractiveness to
Thai Nguyen Province as perceived by the investors among those factors.
Step 1: Test the requirement to apply EFA
- Sample size: the number of observations were 180 (more than 50,
according to ) and were more than 4 times of the variable (question) number. The
number of question in each factor was more than 3. According to (Hoang and Chu,
2008, Hair et al., 2009, Stevens, 2002, Habing 2003), the requirement of sample size
was fulfilled.
- Correlation among variables: the researcher applied Kaiser-Meyer-Olkin
(KMO) and Bartlett measure to test the correltation among variables. The test used
PASW 10 and produced the results as shown in the Table 5:
Table 5. Correlation among variables (survey questions)
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .806
Bartlett's Test of Sphericity Approx. Chi-Square 4790.038
df 630
Sig. .000

39
The result indicated that KMO measure was 0.806 > 0.5 and Bartlett test
produced the Sig.=.000<0.05, according to Kaiser (1974), the requirement of
correlation among variables was fulfilled to conduct EFA.
Step 2: Factors extraction and rotation
Table 6 illustrated the result of the first extraction and rotation of variables and
factors. After rotation, there were two variables moved among factors, namely: ing12
was moved from “Natural Resource, Geographical and Infrastructure Factors” to
“Policy Factors” due to its stronger correlation with other variables of the latter.
Similarly, oas3 was moved from “Overall Assessment” to “Social Condition”.
The result revealed that the lowest score coefficient of all factors (or factor
loading) are higher than 0.5. According to Hair et al. (2009, 116), those factors are
eligible to conduct EFA because their score coefficients are higher than 0.5.
Step 3: Name and interprete new factors
Based on the result of factor extraction and rotation in Step 2, new factors were
found and named as follows:
- Factor 1 including 8 items (variables) namely: pol1, pol2, pol3, pol4, pol5,
pol6, pol7, ing12, which was were questions on investors’ expert opinion on policies
of Thai Nguyen Province in attracting FDI in Thai Nguyen, was named “Policy
factors – POL”.
- Factor 2 including 8 items (variables) namely: ing1, ing2, ing3, ing4, ing5,
ing6, ing7, ing8, which was were questions on investors’ expert opinion on the
natural resource and geographical condition of Thai Nguyen Province, was named
“Natural Resource and Geographical Factors – ING”.
- Factor 3 including 8 items (variables) namely: sol1, sol2, sol3, sol4, sol5,
sol6, sol7, oas3, which were questions on investors’ expert opinion on their

40
confidence in the prospects of investing in Thai Nguyen Province, was named
“Confidence of Investors – CONF”.
- Factor 4 including 3 items (variables) namely: sol8, sol9, sol10, which were
questions on investors’ expert opinion on the labor force of Thai Nguyen Province,
was named “Labor – LAB”.
- Factor 5 including 4 items (variables) namely: eco1, eco2, eco3, eco4, which
were questions on investors’ expert opinion on economic and market factors, was
named “Economic and Market Factors – ECO”.
- Factor 6 including 3 items (variables) namely: ing9, ing10, ing11, which
were questions on investors’ expert opinion on infrastructure of Thai Nguyen
Province, was named “Infrastructure – INFR”.
- Factor 7 including 2 items (variables) namely oas1, and oas2, which were
questions on overall assessment of investors on FDI attractiveness of Thai Nguyen
Province, was named “Overall Assessment – OAS”.
From Table 7., the extraction and rotation result on PAWS 18 has formulated
the equation of the new factors as follows:
POL = 0.131*pol1 + 0.176*pol2 + 0.187*pol3 + 0.222*pol4 + 0.174*pol5 +
0.114*pol6 + 0.054*pol7 + 0.165*ing12
ING = 0.164*ing1 + 0.167*ing2 + 0.162*ing3 + 0.143*ing4 + 0.109*ing5 +
0.157*ing6 + 0.165*ing7 + 0.16*ing8
CONF = 0.234*sol1 + 0.177*sol2 + 0.189*sol3 + 0.174*sol4 + 0.211*sol5 +
0.146*sol6 + 0.215*sol7 + 0.122*oas3
LAB = 0.365*sol8 + 0.357*sol9 + 0.344*sol10
ECO = 0.295*eco1 + 0.428*eco2 + 0.365*eco3 + 0.227*eco4
INFR = 0.421*ing9 + 0.343*ing10 + 0.325*ing11
OAS = 0.453*oas1 + 0.439*oas2

41
Step 4: Testing the reliability of the new factors
Table 8. Reliability of the Exploratory Factors
Factors Cronbach’s Alpha Lowest Corrected Item-Total Correlation
POL .936 .515
ING .920 .474
CONF .866 .542
LAB .903 .783
ECO .811 .576
INFR .720 .528
OAS .961 .924
Cronbach’s Alpha and Item-total correlation (correlation between a factor and
its variables) were used to test the reliability of the new factors. The result shows that
Cronbach’s Alpha of all factors were higher than 0.6 and the lowest corrected item-
total correlations were higher than 0.3. According to Nunnally and Burnstein (1994),
the factor can be used if it has Cronbach’s Alpha at least 0.6 and the questions with
Corrected Item-Total Correlation below 0.3 will be removed. From the results, all the
factors were eligible to be used as the measurement tools for this research and no
question was removed from the questionnaire. All the questions and factors are
eligible for further analysis.
Exploratory factors namely POL, ING, CONF, LAB, ECO, INFR could be used
as predictor variables (independent variables) to predict OAS (overall assessment of
investors on FDI attractiveness). In later pages, the reseacher will present the result of
defining factors which have the highest influence on FDI attractiveness (OAS) among
six found factors.

42
Table 9. Average Mean Distribution of Investors’ Responses to Factors affecting FDI attractiveness of Thai Nguyen Province
Indicators
Code Manufacturing
and Processing
Industries
Other industries Total
Mean VI Mean VI Mean VI
I. Policy factors POL 3.45 Good 3.36 Fair 3.42 Good
1. Thai Nguyen Province has appropriate incentive policies for different investing industry pol1 3.18 Fair 3.04 Fair 3.13 Fair
2. Investment licensing procedure in Thai Nguyen Province is rapid and easy pol2 3.35 Fair 3.19 Fair 3.29 Fair
3. The One Gate administration procedure of Thai Nguyen Province helps reduce unofficial
expenses for foreign investors
pol3
3.40 Good 3.34 Fair 3.38 Fair
4. Thai Nguyen province has appropriate financial incentives for foreign investors pol4 3.39 Fair 3.43 Good 3.41 Good
5. A complete law is implemented adequately in order to support foreign investors in
business premises
pol5
3.38 Fair 3.29 Fair 3.35 Fair
6. Thai Nguyen Province supports high qualified human resource training pol6 3.26 Fair 3.06 Fair 3.18 Fair
7. Thai Nguyen has land incentives for foreign investors pol7 3.85 Good 3.87 Good 3.86 Good
8. Thai Nguyen issues appropriate policies to develop supporting industries ing12 3.81 Good 3.63 Good 3.74 Good
II. Natural resource, and geographical factors ING 3.35 Fair 3.57 Good 3.43 Good
1. Thai Nguyen is the center of the Northern mountainous region of Vietnam, which creates
opportunities for investors to approach and expand their business to the whole region
ing1
3.23 Fair 3.56 Good 3.36 Fair
2. Thai Nguyen has a suitable climate for the development of agriculture and forestry ing2 3.16 Fair 3.35 Fair 3.23 Fair
3. Thai Nguyen has large natural superficies ing3 3.05 Fair 3.31 Fair 3.15 Fair
4. Thai Nguyen has abundant natural resources and mineral for mining and processing
industry
ing4
3.63 Good 3.84 Good 3.71 Good
5. Thai Nguyen is located in a very convenient position for transportation from
manufacturing to consuming places
ing5
6. Thai Nguyen is less impacted by calamity than other regions of the country ing6 3.71 Good 3.79 Good 3.74 Good
7. Thai Nguyen has adequate land resource to fulfill the demand of the investors ing7 3.17 Fair 3.49 Good 3.29 Fair
8. Thai Nguyen has the developed educational and medical system ing8 3.35 Fair 3.65 Good 3.46 Good

43
Indicators
Code Manufacturing
and Processing
Industries
III. Confidence of investors in prospects of investing in Thai Nguyen CONF 3.51 Good 3.65 Good 3.57 Good
1. Investors can easily meet and consult the governors and officials of Thai Nguyen
government when request
sol1
2. The investors do not meet difficulties caused by the administration of the government
officials during procedures
sol2
3. It is consistent in operating works with the investors between the leaders and the
implementers
sol3
4. There is no priority for domestic investors sol4 3.18 Fair 3.32 Fair 3.23 Fair
5. All commitments with investors have been completed sol5 3.73 Good 4.03 Good 3.84 Good
6. PCI index of Thai Nguyen Province is stable, which reassures the investors sol6 3.02 Fair 3.09 Fair 3.04 Fair
7. Thai Nguyen Province has young population and abundant human resource sol7 3.48 Good 3.65 Good 3.54 Good
8. Investors believe in the long run development of the company if investing in Thai Nguyen oas3 3.40 Good 3.37 Fair 3.39 Fair
IV. Labor force LAB 2.67 Fair 4.58 Excellent 3.39 Fair
1. The labor force commit the regulation of the company and have strong commitment with
the company
sol8
2.68 Fair 4.59 Excellent 3.40 Good
2. Labor cost of Thai Nguyen Province is relatively lower than other regions sol9 2.73 Fair 4.57 Excellent 3.43 Good
3. Expenses that investors need to bear for labor training is low sol10 2.60 Poor 4.57 Excellent 3.34 Fair
V. Economic and market factors ECO 3.34 Fair 3.52 Good 3.41 Good
1. Thai Nguyen economy grows stably eco1 3.38 Fair 3.51 Good 3.43 Good
2. Thai Nguyen economy’s structure appropriately for the industry of investment eco2 3.53 Good 3.74 Good 3.61 Good
3. The competitiveness of Thai Nguyen Province is not very high among investors, which is
the opportunities for the investor to expand its production
eco3
3.37 Fair 3.54 Good 3.43 Good
4. Material and service costs is low which help reduce the production and business costs eco4 3.10 Fair 3.29 Fair 3.17 Fair
VI. Infrastructure INFR 3.08 Fair 3.23 Fair 3.14 Fair

44
Indicators
Code Manufacturing
and Processing
Industries
1. Thai Nguyen has adequate electric and water supply for production and manufacturing ing9 2.65 Fair 2.66 Fair 2.66 Fair
2. Thai Nguyen has a good transport system which ensure the transportation for business ing10 2.89 Fair 3.24 Fair 3.02 Fair
3. Thai Nguyen has good telecommunication system ing11 3.69 Good 3.79 Good 3.73 Good
Overall Assessment on FDI attractiveness of Thai Nguyen Province OAS 3.68 Good 3.79 Good 3.72 Good
1. Your overall assessment on FDI attractiveness of Thai Nguyen Province to the investors oas1 3.67 Good 3.79 Good 3.72 Good
2. You will expand your investment scale to Thai Nguyen Province oas2 3.69 Good 3.78 Good 3.72 Good

45
Table 9 describes the assessment of the investors on factors identified after
EFA, including: Policy factors, Natural resource, and geographical factors,
Confidence of investors in prospects of investing in Thai Nguyen, Labor force,
Economic and market factors, Infrastructure and Overall Assessment on FDI
attractiveness of Thai Nguyen Province. The results showed that in general, most of
the factors were rated at Good and Fair. The factor which was highest rated was
Confidence of investors in prospects of investing in Thai Nguyen, i.e. 3.57, rated
to Good. Two factors which were lowest rated were Infrastructure, i.e. 3.14, rated to
Fair, and Labor Force, at 3.39, rated to Fair. Especially, the item “Expenses that
investors need to bear for labor training is low” was lowest rated by the investors of
Manufacturing and Processing Industries, at 2.60, rated to Poor, while investors of
other industries high rated for this item, at 4.57, rated to Excellent.
However, Weighted Mean analysis on investors’ expert opinion could not
identify the factors that affect the FDI attractivenss of Thai Nguyen Province to the
foreign investors. In the next sections, the researcher will present the result of
research to identify the affecting factors and factors affecting FDI attractiveness of
Thai Nguyen Province.

46
Table 11. Pearson correlation between FDI attractiveness and its predictor factors
OAS POL ING CONF LAB ECO INFR
OAS 1
POL 0.627*** 1
ING 0.039 0.054 1
CONF 0.310*** 0.271*** 0.091 1
LAB 0.018 -0.044 0.070 0.012 1
ECO 0.269*** 0.347*** 0.102 0.504*** 0.032 1
INFR 0.223** 0.115 -0.016 0.334*** 0.060 0.349*** 1
** Significant at the probability of 0.001
*** Significant at the probability of 0.0001
Trong đó:
OAS : Overall assessment of investors on FDI attractiveness of Thai Nguyen Province
ING : Natural resources and geographical factors
CONF : Confidence of investors in the prospects of investing in Thai Nguyen Province
LAB : Labor force
INFR : Infrastructure

47
Table 11 presents the result of simple correlation between FDI attractiveness
and its predictor variables. The result revealed that the overall assessment on FDI
attractiveness of Thai Nguyen Province (OAS) was highly influenced by Policy
Factor (POL), i.e. 62.7%, Confidence of the investors in the prospects of investing in
Thai Nguyen Province, at 31%, Economic and Market Factors, namely 26.9%, at the
significant probability of 0.0001 and by Infrastructure at 22.3%, at the significant
probability of 0.001.

48
Result of stepwise regression analysis to identify factors affecting FDI
attractiveness of Thai Nguyen Province as perceived by the investors
The above factors were then used in the linear regression analysis to indentify
the factors affecting FDI attractiveness as perceived by the investors. The sample
formulation is as follow:
Y= X1, X2, X3,…, Xn
Where: Y was dependent variable (FDI attractiveness of Thai Nguyen
Province as perceived by the investors)
X1, X2, X3,…, Xn were predictor variables (influencing factors)
The application of this model in the case of FDI attractiveness in Thai Nguyen
Province produced the formulation as follow:
OAS = POL, ENT, CONF, LAB, PSC, INFR
Where: OAS : Overall assessment of investors on FDI
attractiveness of Thai Nguyen Province
ING : Natural resources and geographical factors
CONF : Confidence of investors in the prospects of investing
in Thai Nguyen Province
LAB : Labor force
Table 12. Result of simple linear regression analysis on FDI attractiveness as
perceived by investors and its predictor variables
Variable Parameter
Estimate
Standard Error Type II
SS
Giá trị F Pr > F
Intercept 0.75388 0.31605 3.64889 5.69 0.0181
POL 0.58177 0.06272 55.18491 86.05 <0.0001
CONF 0.15942 0.08303 2.36438 3.69 0.0565
INFR 0.12889 0.06371 2.62506 4.09 0.0446
R-square = 0.4243 và C(p) = 1.8935
Table 12 shows the result of Pearson linear regression analysis with backward
selection on FDI attractiveness as perceived by investors and its predictor variables.
Factors that were selected as factors affecting FDI attractiveness were POL (Policy

49
Factors), CONF (Confidence of investors in the prospects of investing in Thai
Nguyen Province), and INFR (Infrastructure). These factors can explain 42.43% the
variation of investors’ expert opinion on FDI attractiveness of Thai Nguyen Province.
Table 13. Summary of Backward Elimination
Step Variable
removed
Numer
Vars In
Partial R-
squared
Model R-
squared
C (p) F
Value
Pr > F
1 ING 5 0.0000 0.4272 5.0044 0.00 0.9470
2 ECO 4 0.0013 0.4259 3.3976 0.40 0.5303
3 LAB 3 0.0017 0.4243 1.8935 0.50 0.4802
Table 13 showed the summary of backward elimination where three factors
were deselected from the model, namely ING (Natural Resources and Geographical
Factors), ECO (Economic and Market Factors), and LAB (Labor Forces).
From the above result, investors’ expert opinion on FDI attractiveness of Thai
Nguyen Province were defined as follow:
= . + . × + . × + . × ( )
adj = 0.424
Where: OAS : Overall assessment of investors on FDI attractiveness
of Thai Nguyen Province
CONF : Confidence of investors in the prospects of investing in
Thai Nguyen Province

50
Model testing
Measured OAS
0 1 2 3 4 5 6
PredictedOAS
0
1
2
3
4
5
6
y = 0.425x + 2.134
R² = 0.427
Figure 7. Model testing (primary model)
Figure 7 shows the comparison between the overall assessment of investors as
obtained by the regression model and the measured overall assessment of investors on
FDI attractiveness of Thai Nguyen Province. The results revealed that the prediction
model could explain 42.4% the variation of actual OAS.

51
4.2. Analysis of secondary data on factors affecting FDI in Thai Nguyen Province
Table 14. Descriptive statistics of FDI and its predictor variables from 2000 to
2013
Variable Mean Std Dev Minimum Maximum CV
FDI 190.28 588.21 2.69 2141.5 309.1%
GDP 11485.43 8834.06 3016.79 29508.03 76.9%
EXP 64.79 45.29 18.5 142.27 69.9%
PCI 20.85 22.46 0 57 107.8%
P.FIN 0.15 0.38 0 1 244.1%
P.LAND 0.31 0.48 0 1 156.1%
P.ADMIN 0.69 0.48 0 1 69.4%
INFR 448.90 355.32 135.6 1249.5 79.2%
INFL 7.80 6.69 -1.77 23.12 85.8%
URB 24.71 1.99 22.16 28.45 8.1%
Where:
P.ADMIN : Administrative privileges for investors in year 1 (if yes: 1, if no: 0)
Table 14 illustrates the results of descriptive statistics of FDI and its predictor
variables. The variable which has the highest coefficient of variation were FDI, i.e.
309.1%, and the lowest coefficient of variation was the urbanization (URB), at 8.07%.

52
Table 15. Pearson Correlation Analysis between FDI and its predictor variables
FDI GDP EXP PCI P.FIN P.LAND P.ADMIN INFR INFL URB
FDI 1
GDP 0.599* 1
EXP 0.464 0.935*** 1
PCI -0.060 0.651* 0.803* 1
P.FIN 0.720*** 0.275 0.154 -0.244 1
P.LAND 0.492 0.420 0.372 0.144 0.640* 1
P.ADMIN 0.178 0.615* 0.637* 0.644* -0.178 0.083 1
INFR 0.440 0.940*** 0.871*** 0.605* 0.193 0.457 0.511 1
INFL -0.052 0.518 0.730** 0.789** -0.182 0.118 0.671* 0.501 1
URB 0.555** 0.979*** 0.935*** 0.690** 0.255 0.484 0.696** 0.925*** 0.608* 1
* Significant at the probability of 0.05
** Significant at the probability of 0.01
*** Significant at the probability of 0.001
Where:

53
Table 15 illustrates the Pearson correlation between FDI registered in Thai
Nguyen Province and its predictor variables. From the result, it can be seen that FDI
was highly influenced by gross domestic products in the previous year, at 59.9% and
the urbanization in the previous year, i.e. 55.5%, and the Financial incentives for
investors in that year, at 72% (significant at the probability of 0.001).

54
Result of stepwise regression analysis to identify factors affecting FDI in
The factors were then used in the linear regression analysis to indentify the
factors affecting of FDI in Thai Nguyen Province. The sample formulation is as
follow:
Y= X1, X2, X3,…, Xn
Where: Y was dependent variable (FDI in Thai Nguyen Province)
X1, X2, X3,…, Xn were predictor variables (influencing factors)
The application of this model in the case of FDI in Thai Nguyen Province
produced the proposed formulation as follow:
FDI = GDP, EXP, PCI, P.FIN, P.LAND, P.ADMIN, INFR, INFL, URB
Where:
Table 16. Result of multiple linear regression analysis on FDI in Thai Nguyen
Province and its predictor variables
Variable Parameter
Estimate
Standard Error Type II
SS
Giá trị F Pr > F
Intercept -286.25436 166.81480 375824 2.94 0.1169
GDP 0.02888 0.01214 722116 5.66 0.0387
P.FIN 941.34230 285.62199 1386313 10.86 0.0081
R-square = 0.6926 và C(p) = 14.5651
Table 16 shows the result of multiple linear regression analysis with forward
selection on FDI registered in Thai Nguyen Province and its predictor variables.
Factors that were selected as factors affecting FDI were GDP (Gross Domestic

55
Products), and P.FIN (Administrative privileges for investors in year 1). These factors
explained 69.26% the variation of FDI in Thai Nguyen Province.
Table 17. Summary of Forward Selection
Step Variable
entered
Numer
Vars In
Partial R-
squared
Model R-
squared
C (p) F
Value
Pr > F
1 P.FIN 1 0.5187 0.5187 24.7665 11.85 0.0055
2 GDP 2 0.1739 0.6926 14.5651 5.66 0.0387
Table 17 showed the summary of forward selection where two factors were
selected to the model, namely GDP (Gross Domestic Products), and P.FIN
(Administrative privileges for investors in year 1). The other factors (EXP, PCI,
P.LAND, P.ADMIN, INFR, INFL, and URB) were not selected to the model.

56
Construction of prediction model for FDI in Thai Nguyen Province
Proposed equation:
FDI = β0+β1X1+β2X2+…+βnXn
Where: FDI is registered in Thai Nguyen Province in year t
X1, X2, X3,…, Xn are predictor variables (influencing factors)
β0, β1, β2,…,βn are the parameter estimate of predictor variables
From the result of regression analysis, FDI in Thai Nguyen Province were
defined as follow:
= − . + . × + . × . ( )
adj = 0.6926
Where: FDI : Registered in Thai Nguyen Province in year t (Million USD)
The model (2) can explain 69.26% the variation of FDI in Thai Nguyen
Province.
However, if the model (2) is used to predict FDI registered to Thai Nguyen
Province there will be the case that FDI is lower than 0 which is not significant in
terms of practical application, if:
−286.25 + 0.02888 × + 941.34 × . < 0
⟺ < 9911.704 − 32594.875 × .
P.FIN is a dummy which receives only one of two values, either 0 (if there was
no financial incentives in the year) or 1 (if there were financial incentives), therefore,
the disequation can be written as follows:
⟺
< 9911.704 . = 0
< −22683.171 . = 1 ( )

57
GDP always receives a greater value than 0, so the latter case will not happen.
Therefore, the disequation is equivalent to:
⟺
. = 0
< 9911.704
In short, if P.FIN is equal to 0 and GDP is lower than 9911.704 simultaneously,
the predicted FDI registered to Thai Nguyen Province according to the model (2) is
lower than 0, which is not significant in terms of practical application (because FDI
value is always equal to or higher than 0).
In order to fix this drawback of the model (2), the researcher propose the new
model as follows:
=
⎣
⎢
⎢
⎢
⎡
. = 0
< 9911.704

− . + . × + . × .
. = 1
. = 0
≥ 9911.704
( )
According to the model (3), FDI always receive the value which is equal to or
higher than 0. The value of 0 appears when P.FIN is equal to 0 and GDP is lower than
9911.704 simultaneously.
The next section of the study will present the model testing and identify the
accuracy of the model in reality.

58
Model testing
In order to test the prediction model (3), the researcher has compared the results
of FDI registered to Thai Nguyen Province as being predicted from the model and the
measured FDI registered.
Measured FDI registered
0 500 1000 1500 2000 2500
PredictedFDIregistered
0
200
400
600
800
1000
1200
1400
1600
1800
Y = 0.656x + 130.2
R² = 0.756
Figure 8. Model testing (secondary model)
Figure 8 shows the comparison between the predicted FDI registered to Thai
Nguyen Province as obtained by the prediction model (3) and the measured FDI
registered to Thai Nguyen Province over the past 14 years. The results revealed that
the prediction model could explain 75.6% the variation of actual registered FDI.

59
CHAPTER 5
Summary of Findings, Conclusions and Recommendations
This chapter presents the summary of the findings from the research, the
conclusions and the recommendations to improve FDI inThai Nguyen Province.
5.1. Summary of Findings
Based on the analysis and interpretation of the data, the following findings
were obtained from the results of the study:
5.1.1. Result of primary data analysis
a. Profile of respondents
1. At the time of research, there were 14 investors (accounted for 43.75%)
having been investing in Thai Nguyen Province for more than 5 years, in which 1
investor has invested for more than 10 years and 13 investors has invested for from
5-10 years, including 1 investor in Real Estate, 1 investor in Arts and Entertainment.
The result showed that most of the investors that have been investing for a long time
in Thai Nguyen Province, i.e. 11 investors, came from the Processing and
Manufacturing Industry, whose products were heavy industry and tea. The heavy
industry utilised the main materials of steel which is the major natural resource of
Thai Nguyen Province, with high level of reserves and good quality. Tea has also
been known as the famous agricultural product of Thai Nguyen as the province has
suitable soil and climate for the production of this.
As for the only one investor in Arts and Entertainment which is the Quy Hoang
Van Company from China investing in the Nui Coc Lake park, the place is the most
famous tourist attraction of Thai Nguyen which attracts around 300,000 tourists
every year. Therefore, this is still a potential place for investment which has not been
taken advantage of and will be of benefit to the investor in the future.

60
Most of the investors who have the investment duration under 5 years in Thai
Nguyen (i.e. 50%) came from the Processing and manufacturing industry with the
main products of heavy industry and devices and components.
2. The proportion of the Processing and Manufacturing reached the highest
among the investing industries in Thai Nguyen (of 62.5%) with the main product of
heavy industry. This may be due to the fact that Thai Nguyen is the cradles of heavy
industry of the country since 1960. At the moment, Thai Nguyen still rank top in
terms of steel reserve and the steel processing industry in Vietnam. The province
therefore became more attractive with investors of this industry compared with other
provinces and other industries.
3. Most of investors in Thai Nguyen Province had the registered capital of less
than USD 20,000, there were only 3 investors that had the registered capital of from
USD 20,000 and above, in which 2 investors had the registered capital of under USD
50,000, including:
- Nasteel Vina company of Nasteel Asia Pte Ltd. (Singapore): construction
steel processing, and
- Mani, Inc. (Japan): medical instruments processing for export.
And only one investor who had the registered investment capital of from USD
50,000 and above: Samsung Electronics Vietnam Thái Nguyên, Ltd.: mobile devices,
electronics, telecommunications.
According to the researcher, there might be some reasons that motivated those
companies to invest in Thai Nguyen Province as follows:
- Nasteel Asia Pte Ltd. (Singapore) invested in steel processing industry using
the iron ore reserves of Thai nguyen from the Trai Cau iron mine which had the
reserves of more than 60 million tons, and the Tien Bo iron mine which had the

61
reserves of more than 30 million tons, and other mines which had the total reserves
of more than 30 million tons. This was the abundant resource for the processing and
manufacturing of the company.
- Mani, Inc. (Japan) invested in the medical instruments processing industry
from 2004 which was one of the areas of investment that were particularly
encouraged for investment, which received special investing incentives, including:
land leasing incentives (at the rate of 50% of other leasing price of other investment
projects at the same location), VAT incentives, corporate tax incentives.
- Samsung Electronics Vietnam Thái Nguyên, Ltd. invested in Thai Nguyen
Province from 2013 in the mobile devices, electronics, telecommunications has
received the very special incentive policies of Thai Nguyen Province and Vietnam
Government, i.e.: 4 years full exemption, 50% exemption in the next 9 years for
corporate tax, and 50% exemption in the next 3 years for corporate tax for one
project; 50% exemption for land leasing with the maximum total land acreage of 100
ha). In addition, the company was also received 100% export-import tax incentives,
contractor tax incentives, 100% land leasing for the whole duration of the project.
Mani, Inc. (Japan) project has created permanent jobs for almost 2,000 people
with the average income of more than 4 million dong per per son per month, and
contribute to the state budget of 26.2 billion dong.
Samsung Electronics Vietnam Thái Nguyên, Ltd. project was expected to creat
more than 30,000 jobs in the first year and 50,000 jobs in the future. In addition, the
operation of the company in Vietnam will also promote the supporting industry to
provide components for Samsung products and attract more FDI to Thai Nguyen
Province.

62
The result of exploratory factor analysis from the items of questionnaire has
identified the factors for analysis which were: OAS (Overall assessment of investors
on FDI attractiveness of Thai Nguyen Province), POL (Policy factors), ING (Natural
resources and geographical factors), CONF (Confidence of investors in the prospects
of investing in Thai Nguyen Province), LAB (Labor force), ECO (Economic and
market factors), INFR (Infrastructure). All of the found factors met the requirements
of reliability for further analysis.
b. Descriptive statistical analysis of new factors
From the result of descriptive statistics, it can be seen that most of the items
were highly rated, at Good and Moderately Good, however, the coefficient of
variation was quite high, from 25% to 35%. This revealed that the investors had
different opinions on the factors. Particularly, CV of LAB was 34.9%, INFR: 31.9%
and ING: 30%.
c. Weighted Mean Analysis
The results of weighted mean analysis showed that in general, most of the
factors were rated at Good and Fair. The factor which was highest rated was
Confidence of investors in prospects of investing in Thai Nguyen, i.e. 3.57, rated
to Good. Two factors which were lowest rated were Infrastructure, i.e. 3.14, rated to
Fair, and Labor Force, at 3.39, rated to Fair. Especially, the item “Expenses that
investors need to bear for labor training is low” was lowest rated by the investors of
Manufacturing and Processing Industries, at 2.60, rated to Poor, while investors of
other industries high rated for this item, at 4.57, rated to Excellent. This helped to
explain why the coefficient of variation of this factor was high in descriptive
statistical analysis.

63
The cause of this phenomenon might come from the higher requirements of
high qualified labor in the Manufacturing and Processing Industries than other
industries, and the workers in this area need to be well trained in order to handle the
assigned tasks. Therefore, the low cost and abundant labor in Thai Nguyen at this time
cannot meet the requirements of this industry, and foreign investors have to bear the
training expense to improve the quality of labor. In contrast, other industries do not
require high technical labor, the investors will be easier in accepting workers with
lower quality as well as bear lower expenses in training their workers.
According to Table 9, some incentive policies of Thai Nguyen has not been
highly appreciated by the investors, including: appropriate policies for different areas
of investment, licensing procedure, unofficial expenses, business premises, human
resource training. The above policies were rated at Fair, which was not good and
need some improvement. Meanwhile, POL (incentives policy for investors) was
selected as one of the factors that affected directly to the investor’s expert opinion on
the attractiveness of Thai Nguyen Province to investors with the highest parameter
estimate (Fomulation 1), which means that experts rating POL highly tend to highly
rate the attractiveness of Thai Nguyen Province. Therefore, solutions should focus on
the improvements of the policies that were rated as Fair in order to improve the
opinion of experts.
d. Analysis of factors affecting FDI attractiveness of Thai Nguyen Province
as perceived by the investors
Simple correlation analysis showed that as perceived by the investors, the
following had great influences on their assessment of FDI attractiveness of Thai
Nguyen Province:

64
Factors Correlation with OAS
(%)
p
POL (Policy Factors) 0.627*** < .001
CONF (Confidence of investors on the
prospects of investing in Thai Nguyen) 0.310***
< .001
ECO (Economic and Market Factors) 0.269*** < .001
INFR (Infrastructure) 0.223** < .01
Investors’ expert opinion on the above factors had positive relationships with
their opinion on FDI attractiveness of Thai Nguyen Province, it means that when an
investors had a positive assessment on those factors, they would tend to have a
positive assessment on FDI attractiveness of Thai Nguyen Province. In other words,
the investors might consider those factors more than the remaining factors in
assessing the FDI attractiveness of Thai Nguyen Province. The investors may see the
potentials of investing in Thai Nugyen Province if those factors satisfy them.
Regression analysis has then identified the factors affecting FDI attractiveness
of Thai Nguyen Province, which affected the dependent variables as in the following
equation:
= . + . × + . × + . × ( )
adj = 0.424
Where: OAS : Overall assessment of investors on FDI attractiveness
of Thai Nguyen Province
CONF : Confidence of investors in the prospects of investing in
The results showed that the factor that had the greatest influence on FDI
attractiveness of Thai Nguyen Province is Policy Factors (POL) with its weight was
0.582, followed by Confidence of investors in the prospects of investing in Thai
Nguyen Province and Infrastructure.

65
The accuracy rate at R2
= 42.4% was quite low. However, the objective of the
construction of the equation was not for prediction but for finding the factors affecting
FDI attractiveness of Thai Nguyen Province. The dependent variable in this equation
was not FDI value invested in Thai Nguyen Province but the investors’ assessment on
the FDI attractiveness of Thai Nguyen Province. The regression analysis aimed to find
out the relationship between the investors’ expert opinion on individual factors and
overall assessment on investing environment of Thai Nguyen Province.
The result of analysis showed that the investors’ expert opinion on policy,
confidence of investors on the prospects of investing in Thai Nguyen Province, and
infrastructure will affect their assessment on whether Thai Nguyen is an attractive and
potential destination for investment. According to the result, these assessment will
explain 42.7% the variation of their overall assessment on FDI attractiveness of Thai
Nguyen Province.
Figure 7 shows that the opinion of expert as calculated using the formulation (1)
met 42.4% the variation of experts’ opinion measured. However, the formulation (1)
was constructed not for the objective of predicting the dependent variable (OAS) but
finding out the factors that affected the experts’ opinion and eliminating factors that
indirectly affect through selected factors (eliminating the collinear phenominum).
As the result, there were 2 factors that affected directly the opinion of investors’
expert, namely POL (incentive policies for investors) and CONF (confidence of
investors in the prospect of investing in Thai Nguyen Province), which means that
when any of the two factors or both change will cause the change in the experts’
opinion on the attractiveness of Thai Nguyen Province.
5.1.2. Result of secondary data analysis
a. Descriptive statistics

66
The result of descriptive statistical analysis on secondary data of FDI and its
predictor variables from 2001 to 2013 showed the high variation of these indicators in
this period, particularly:
- FDI has the coefficient of variation of 309.1% showed a dramatic variation in
FDI registered to Thai Nguyen Province, this has been caused by the fluctuation in
FDI inflows. In almost the years from 2001 to 2012, FDI registered in Thai Nguyen
Province were not very high, aroung 20 million USD per year, except for 2004 (148.1
million USD), and 2007 (117.78 million USD). However, in 2013, FDI registered in
Thai Nguyen Province soared to 2.14 billion USD, which came from the investment
of Samsung Electronics Vietnam to the Yen Binh Industrial Zone (Pho Yen District,
Thai Nguyen). This change led to the high coefficient of variation of 309.1% in FDI.
- The dummies in the models also took the high CV, for instance: P.FIN
(244.1%) and P.LAND (156.1%), which meant that the policy of Thai Nguyen
Province for foreign investment were instable with years, especially policy on tax and
land incentives.
b. Analysis of factors affecting FDI registered to Thai Nguyen Province
Simple correlation analysis identified that FDI registered to Thai Nguyen
Province was affected by the following variables:
Variables Relationship with FDI (%) p
GDP 59.9 <.05
P.FIN 72 <.001
URB 55.5 <.01
These factors had great and positive influences on FDI registered to Thai
Nguyen Province.

67
In a reverse trend, Provincial Competitiveness Index had a negative impact on
FDI, which is reverse to the expectation of the researcher.
Regression analysis with forward selection has found two factors which had
greatest influence on FDI, including P.FIN and GDP, as defined in the following
equation:
= − . + . × + . × . ( )
adj = 0.6926
These two factors explained 69.26% the variation of FDI during the period. The
other factors which also had strong correlation with FDI but were not selected to the
model, including: INFR, URB and EXP because these also had strong correlation with
GDP and through GDP impacted FDI (collinear phenomenon).
5.1.3. Construction of prediction model of FDI in Thai Nguyen Province
Regression analysis with forward selection has constructed the prediction model
for FDI in Thai nguyen Province as follows:
=
⎣
⎢
⎢
⎢
⎡
. = 0
< 9911.704

− . + . × + . × .
. = 1
. = 0
≥ 9911.704
( )
adj = 0.756
The model (3) has been developed from the model (2) and has resolved its
drawback based on a practical hypothesis that FDI is always equal to or higher than 0.

68
Therefore, the model (3) is more practically significant than the model (2) in practice.
This model can explain 75.6% the variation of FDI in reality.
From the model, it can be seen that when Thai Nguyen province applied
financial incentives for foreign investors (P.FIN = 1) FDI could increase by 941.34
million USD. Similarly, when GDP growth increases by 1,000 billion VND per year,
FDI registered to Thai Nguyen could increase by 30 million USD.
The prediction model revealed the significance of financial incentives to foreign
investors. In 2004 and 2013, Thai Nguyen has various financial incentives in order to
attract more FDI. Particularly:
- In 2004, there were two FDI enterprises who received financial incentives
when investing to Thai Nguyen, including Nasteel Asia Pte Ltd. (Singapore) and
INTRA Corp. (Japan). Nasteel Asia Pte Ltd. which is a deep steel processing
company, has received incentives in natural tax, export tax and corporate tax. This
company has also received preferentials in land such as rental costs in the first years
of investment. INTRA Corp. invested in real estates business at Xuong Rong lake in
Thai nguyen, aside from corporate tax incentive, the company also received interest
rate incentives. The interest was deducted from the rental expenses after the project
finishes instead of paying interest to the bank.
- In 2013, Samsung Electronics Vietnam Thai Nguyen (SEVT) implemented 4
different projects in Yen Binh Industrial Zone in Thai Nguyen including a Samsung
Thai Nguyen high-tech factory, a microprocessors and integrated circuits processing
project and two high-tech projects of its subsidiaries. Samsung was offered corporate
tax incentives which is equal to 10% per year during 30 years from the starting date of
operation; duty free in 4 years from profitable starting year and reduction of 50% of

69
tax in the following 9 years. While other companies received only 25% corporate tax
incentive.
The above financial preferentials for FDI investors have contributed to the
investing decision making of foreign investors in Thai Nguyen and helped improve
FDI in Thai Nguyen in those years.
5.3. Conclusion
1. Investors’ expert opinion on affecting factors
The results of weighted mean analysis showed that in general, most of the
factors were rated at Good and Fair. The factor which was highest rated was
Confidence of investors in prospects of investing in Thai Nguyen. Two factors
which were lowest rated were Infrastructure and Labor Force. Especially, the item
“Expenses that investors need to bear for labor training is low” was lowest rated by
the investors of Manufacturing and Processing Industries while investors of other
industries high rated for this item.
Descriptive statistical analysis also showed the high variation in investors’
expert opinion on individual factors, particularly Labor force had the highest
variation, which meant that the investors had very different opinion on this item.
2. Factors affecting FDI attractiveness of Thai Nguyen Province
Simple correlation analysis indicated that factors affecting FDI attractiveness of
Thai Nguyen Province include: POL (Policy Factors) – 62.7%, CONF (Confidence of
investors in the prospects of investing in Thai Nguyen) – 31%, ECO (Economic and
Market Factors) – 26.9%, and INFR (Infrastructure) – 22.3%.
Regression analysis with forward selection found the factors affecting FDI
attractiveness of Thai Nguyen province including: POL (Policy Factors), CONF

Prediction model for foreign direct investment in thai nguyen province

Prediction model for foreign direct investment in thai nguyen province

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