Nghiên cứu các nhân tố tác động đến năng lực đổi mới của doanh nghiệp công nghiệp công nghệ cao tại một số tỉnh trọng điểm miền nam việt nam tt tiếng anh

MINISTRY OF EDUCATION AND TRAINING
UNIVERSITY OF ECONOMICS HO CHI MINH CITY

…………………

BÙI NHẬT LÊ UYÊN

RESEARCHING OF FACTORS IMPACT
INNOVATION CAPACITY OF HIGH TECHNOLOGY
INDUSTRIAL ENTERPRISES
IN VIETNAM SOUTHERN’S FOCAL PROVINCES

SPECIALIZATION: COMMERCIAL BUSINESS
CODE: 93 40 121

SUMMARY OF DOCTOR OF PHILOSOPHY THESIS

THÀNH PHỐ HỒ CHÍ MINH, NĂM 2018


Thesis was completed at:
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LIST OF RESEARCH PAPERS
A. Key research papers relate to the thesis
1. Bùi Nhật Lê Uyên, 2016. Innovation capacity – the solution for Ho Chi
Minh manufacture businesses in integrated period. Industry and Trade
magazine, Vol 7, 07/2016, p.94-101
2. Đoàn Thị Hồng Vân và Bùi Nhật Lê Uyên, 2016. Enhance innovation
capacity - the important solutions to help Vietnam businesses for sustainable
development. Journal of economic development, Nov.2016, p.271-289.
3. Đoàn Thị Hồng Vân và Bùi Nhật Lê Uyên, 2017. Factor effecting
innovation capacity in Vietnamese Southern high technology industries.
Journal of economic development, volume 24, issue 3, p.66-93
B. Other research papers
4. Đoàn Thị Hồng Vân và Bùi Nhật Lê Uyên, 2015. Viet Nam's innovative
capacity in the context of integrating ASEAN economic community.
Proceedings of scientific workshop: ASEAN Economic Community opportunities and challenges for Vietnamese enterprises, University of

Economics and Finance, p.27-34.
5. Bùi Nhật Lê Uyên, 2016. Human resource problem for innovation activities
of high-tech enterprises in the integration period. Proceedings of science and
technology conference 2016, Ho Chi Minh City University of Technology,
p.93-96.


CHAPTER 1
RESEARCH OVERVIEW
1.1.

Research base

1.1.1.

The necesscity of research
High-tech industry plays a particularly important role in the national
economy. But in Vietnam, in the current period, due to many subjective and
objective reasons, the innovation capacity of enterprises in this field is very
limited. Therefore, to improve the capacity of innovation, we firstly need to
identify the factors that affect it.
Besides, innovation capacity is also a research issue that the world and
domestic science is very interested in. Evidence is in the world there have been
many research projects on innovation capacity in the field of high technology.
However, beside the academic value, these studies also had theoretical gaps.
Moreover, there are only few research projects in Vietnam that directly
address factors affecting innovation capacity. On that basis, the author would
like to affirm the thesis "Researching on factors impact innovation capacity of
high-tech industrial enterprises in Vietnam Southern’s focal provinces" is a
necessary direction, because of its importance and contribution to both science

and practice.
1.1.2. Research background
1.1.2.1.
Theoretical background
Many scientists in the world studied in innovation and have proven
that the success of a business in knowledge-based economy depends on how
to improve its innovation capacity (Danquaha and Amankwah-Amoahb, 2017;
Azevedo et al., 2007). Therefore, this is the subject that many studies in the
world and in domestic towards: how to motivate innovation through
researching the factors that affect it. That is also the research issue of this
thesis. From that, the relationship between innovation capacity and a number
of factors such as total quality management (TQM), organizational learning,
government support, collaboration network, knowledge absorptive capacity,
internal human resources... was explored. But the results in levels of influence
was different. There were many arguments and research gaps as TQM’s role.


In addition, most studies measured the concept of "Government
support" through participation in R&D projects that funded by the
Government. However for developing countries such as Vietnam whether this
measurement is really effective when applied. For the concept of internal
human resources, Bantel and Jackson (1989), Koroglu and Eceral (2015)
argued that behind the successful innovation of an organization that was
managed by educated and professional personnel. Whereas Dakhli and De
Clercq (2004) argued that the ability to accumulate work experiences over
time would create important skills for the individuals rather than themselves
qualification.
Moreover, there is one issue not to be clarified, there is always a
debate about how to measure innovation capacity (Kanji, 1996; Prajogo and
Sohal, 2003; Tang, 1998).

On the other hand, in domestic research, there are many articles on
innovation capacity, but most of them are scientific reports, articles in
seminars, mainly in the form of an overview, explanation of terms, reality
analysis and proposed solutions...So that, the author has less opportunities to
learn experiences in designing research, methodology, data collection and
analysis, econometric modeling, building and testing measurement scale...
from local authors.
1.1.2.2.
Practical backgound
The reality of Vietnam's innovation capacity is still difficult problem.
Factors impact innovation, such as government support, collaboration
networks, human resource quality are limited, even R&D activities are
considered as minority.
In terms of R&D capacity, most domestic producers only focus on
development rather than research. About human resources in our country,
especially Ho Chi Minh City, are not trained according to international
standards. The scale of training is sparse, spontaneous and non-oriented. They
care about quantity than quality lead to lacking of quantity and not ensure
quality in human resources.
The government's role is very important in promoting innovation,
because there are many drawbacks in the high-tech industry that businesses
face to like as problems of copyright, commercial disputes, the quality of


education and training... All of matters contributed to create the barriers in
innovating and growing.
1.2. Research questions and objectives
1.2.1. Research questions
The thesis should clarify the following research questions:
- What factors that impact the innovation capacity of high-tech

industrial enterprises, research cases in Vietnam Southern’s focal provinces?
- How is the correlation and the degree of impact between these
factors to innovation capacity?
- Which factor’s scale should be developed, supplemented or
measured to be appropriate when testing in Vietnam Southern’s focal
provinces?
- What is the differences between the factors affecting the innovation
capacity in domestic and FDI sector ?
1.2.1. Research objectives
The overall objective was to identify factors and assess their impact
on innovation capacity of high-tech industrial enterprises, in case of testing in
some of key provinces of Vietnam Southern.
Detail objectives:
- Analyze the relationship between factors based on theory, thereby
determining the factors affecting the innovation capacity.
- Evaluate the impact of factors on innovation capacity through
testing hypotheses in the research model.
- Develop scale by discovering and adding new observed variables for
the factors that do not have complete scale when testing in Vietnam.
- Evaluate the influence of factors on innovation capacity in
comparison between domestic enterprises and FDI enterprises based on the
difference test.
1.3. Research’s subject and scope
1.3.1. Research subject: the research subject is enterprise-level innovation
capacity and measured through product innovation and process innovation.


1.3.2. Research scope
Research time:
Research theory: theory of innovation and innovation capacity was in

the period from 1911 to 2017.
Research reality: Primary data on innovation capacity of high-tech
enterprises was surveyed in 2012-2014 and proposing management
implications for 2019-2025.
Research space:
In some of focal provinces of Vietnam Southern, including Ho Chi
Minh city, Binh Duong, Dong Nai and Vung Tau.
The high technology sectors were surveyed as following: electronics,
microelectronics; precision mechanics and automation; information
technology and telecommunications; pharmaceuticals, biotechnology; high
tech services.
1.4. Research methodology
The author chose mix method is as the main research method, in
which:
Qualitative research was conducted through two techniques: in-depth
interview and focus group discussion in order to adjust the content of
observable variables to suit the characteristic of Vietnam businesses in hightech industry and to explore new observable variables for the concepts has
controversial scale (Government support and internal human resource).
Quantitative research was conducted in two phases: a preliminary
study of 89 samples to evaluating concept scales and official study of 380
samples to testing research model and hypotheses.
The data were cleaned and processed in software SPSS20 and
Amos20 with Cronbach's alpha technique, Exploratory Factor Analysis
(EFA), Confirmatory factor analysis (CFA) and Structural Equation
Modelling (SEM).
1.5. Thesis’s contribution
1.5.1. New point of thesis


- The author proposed a research model on factors affecting the

innovation capacity of high-tech industrial enterprises, firstly tested in a
number of key provinces of Vietnam Southern.
- Adjust and develop the original scale by adding new observable
variables for concept of Government support and internal human resource.
- Adjust and develop the scale of innovation capacity towards forming
a quantitative scale.
- Analyze and compare the impact of each factor to innovation
capacity between domestic enterprises and FDI enterprises.
1.5.2. Academic contribution
+ Systematize innovation theory and the model of factors that
influence innovation capacity in the world from 1911to 2017. This is a useful
reference for future studies in the same field.
+ This is an academic research that is inherited and supplemented,
firstly tested in Vietnam. Therefore, it is basis of succession for Vietnam
researchers on innovation capacity in the coming years.
+ Research contributes to develop the scale of factors that influencing
to innovation capacity, step by step perfecting the methodology in measuring
innovation capacity and related concepts.
1.5.3. Practical contribution
+ The thesis’s results supports the policy makers as well as the
managers of high technology enterprises.
+ The thesis’s management implications facilitate to implement many
applied projects or propose appropriate strategies for enterprises (domestic or
FDI) to improve their innovation capacity.
1.6. Thesis’s structure
Chapter 1: RESEARCH OVERVIEW
Chapter 2: THEORETICAL BASIS AND RESEARCH MODEL
Chapter 3: RESEARCH DESIGN
Chapter 4: ANALYSIS OF RESEARCH RESULTS
Chapter 5: CONCLUSION AND MANAGEMENT

IMPLICATIONS
SUMMARY OF CHAPTER 1


CHAPTER 2
THEORETICAL BASIS AND RESEARCH MODEL
2.1. Concept of innovation, innovation capacity and high technology
2.1.1. Innovation
2.1.1.1. Concept of innovation
Innovation theory is the foundation for the birth of the concept of innovation
capacity, which was formed in the 1911s and has a long history of
development. Over time, the concept of innovation is increasingly
consolidated and improved. According to Brilman, J. (2002, page 28),
"innovation is the way to apply a creative idea to help businesses develop and
adapt quickly in a competitive environment." Another concept of Damanpour
and Aravind (2011, p. 427), “innovation is the process from creating,
developing and transforming ideas into new products, new processes, new
organizational structures or new administration methods"...
Thus, from synthesizing the concepts of innovation from many empirical
studies in the world, the author drawed the concept of innovation that was
suitable for this thesis, which is a process related to the use of enterprise
resources to make efforts to improve and develop completely new products or
processes for businesses. Therefore, innovation is very important and has
always been the biggest concern of many businesses, governments and
research institutes (Hekkert and Negro, 2009).
2.1.1.2. Classification of innovation
In this thesis, the author only approached two forms of innovation,
that is product innovation and process innovation according to OECD’s
classification (2005) and Lugones (2012).
According to OECD (2005), Product innovation is the birth of a new

good or service or significant improvements in existing goods and services.
Process innovation is the implementation innovation or had a significant
improvement in production method or delivery method, which includes
important changes in technology, equipment or software.
According to Lugones (2012), Product innovation is introduction to
market a new product or new service that owns technical specifications,


components, material characteristics or functionality totally different in
compare with previous products. Or a new product or service has significant
improvements on existing products/services. Process innovation is a new
process or significant improvement on an existing process.
2.1.2. Innovation capacity
2.1.2.1. Concept of innovation capacity
In this study, the author agrees with previous conclusions and presents
thesis’s point of view. Innovation capacity is ability of an enterprise to use
internal resources or external resources to conduct innovation activities by
producing and introducing to the market completely new products or new
processes or making changes and significant improvements on existing
products/processes.
2.1.2.1. The importance of innovation capacity
According to Suarez (1990), the economy of a nation, a region or a
geographic area that has the capacity to innovate rapidly, it can not only attract
skilled and experienced human resources, but also promote growth in income
and trade in the region. In contrast, the innovation capacity depress in any
country, region or geographic region will be an early warning of difficulties
and decline in future (Suarez, 1990)... Therefore, innovation capacity is very
important to create competitiveness, allowing businesses to compete
effectively in international markets (Williams and Hare, 2012; FernándezMesa and Alegre, 2015).
2.1.3. High technology and innovation capacity in high tech

2.1.3.1. The concept of high technology
In Vietnam, according to the High Technology Law No. 21/2008 /
QH12 (Quoc Hoi, 2008), "High technology is a technology with a high content
of scientific research and technological development; integrated from modern
technological and scientific achievements; to create products with superior
quality and features, high added value, environmentally friendly; plays an
important role in the formation of a new production or service industry or
modernize the existing manufacturing and service industry ”.


In this thesis, the author approached high-tech industrial enterprises
in accordance with the Law on High Technology No. 21/2008, which are
enterprises that produce high-tech products, these products need to meet the
following criteria:
- High proportion of value added in product value structure;
- High competitiveness and great socio-economic efficiency;
- Ability to export or replace imported products;
- Contribute to improving national capacity on science and
technology.
2.1.3.2. Innovation capacity in high tech
The relationship between high technology enterprises and innovation
is always inseparable. This is the most distinctive characteristic and it’s
difficult to find in other fields, because the high tech buisinesses exist in the
environment of vehement compete where high-tech products always change
rapidly, product life cycle is short, the new technology is introduced today but
technology will became popular in the coming days and gradually degenerate
over time. That is the reason why high-tech industries are constantly innovate
or on the other hand innovation is as vital elements in this area. (Goldman,
1982; Riggs, 1983; Shanklin and Ryans, 1984; Nystrom, 1990).
2.2. Basis theory and model of innovation capacity in the world

2.2.1. Basis theory
The author studied basis theories from 1911 until now, to evaluate the overall
development of the theory along with the formation of relevant research
concepts. However, in this thesis, the author only focuses on analyzing some
of basis theories, such as Schumpeter's theory, Nelson theory, NIS theory,
innovation capacity theory.
2.2.1.1. Schumpeter, J.A (1911)
Joseph Schumpeter analyzed the systematic innovation process when he
emphasized innovation as the force for growth. Schumpeter appreciated the


ability to adapt to market pressure and demand. This principle of Schumpeter
laid the foundation for the development of the theory and concept of
innovation capacity in the 90s.
Schumpeter's theory appreciated the role of knowledge, the process of finding
and disseminating knowledge is the force to promote innovation. Therefore,
for sustainable development, enterprises need to know how to apply new
knowledge and new technologies to create growth value. This principle laid
the foundation for two factors were absorptive capacity and organization
learning.
2.2.1.2. Nelson, R (1977; 1982, 1993)
Nelson's innovation theory (1977; 1982, 1993) clearly explained the nature of
innovation, which is a constant and high-risk change, because innovation
depends on market demand. However, if not innovate, organizations will
become less competitive than competitors. To reduce risk, innovation can
implement improvements instead of comprehensive innovation and should
have interaction in an innovative network. Nelson's theory laid the foundation
for the concept of collaboration network that studied by empirical studies later.
2.2.1.3. National Innovation Systems theory
The theory of national innovation system (NIS) focuses on analyzing the

innovation system of countries, emphasizing the element of technological
innovation. According to Freeman and Perez (1988, p. 591) a national
innovation system is “a network of public and private organizations that has
many interactive activities such as importing, modifying and disseminating
new technology in which the Government plays an important role in working
closely with industry and scientific institutions”. Thus, it can be said that NIS
theory is the foundation for two factors of collaboration network and the
Government support.
2.2.1.4. Innovation capacity theory
During the 80s, 90s and later, the theory of innovation from the previous
generation inspired many researchers to explore and gradually improve the
theory of innovation capacity. Suarez-Villa (1990) said that innovation
capacity motivate new technology was born, new technology is the sign of
growing economy. Suarez-Villa affirmed that leading innovation companies
always have a strong culture in mission and vision as well as establishing a


business philosophy in which emphasize continuous improvement, customer
orientation and total quality management. These statements are closely related
to the principles of TQM.
2.2.2. Innovation capacity’s models in high technology industry
Jantunen (2005) explored the relationship between the
environmental dynamics, absorptive capacity and innovation capacity.
However, the research’s result only demonstrated the role of knowledge
utilization and environmental dynamics. Both of them showed positive role
and impact to innovation capacity. The study’s implication is only businesses
had good knowledge processing capabilities can be equipped method to
refresh the knowledge base and exploit available knowledge to develop new
products to meet market demand.
Tseng et al, (2011), from the Jantunen’s study (2005), Tseng et al.

(2011) continued to affirm the role of absorptive capacity for innovation. He
analyzed whether knowledge input and knowledge diffusion can increase the
efficiency of innovation. The testing result supported the hypothesis that
knowledge input positively influence innovation. Similarly, the spillovers
effect of knowledge from the business themself, from foreign semiconductor
companies and from non-semiconductor companies hold a dominant position
in impacting to innovation. Beside, absorbtive capacity had also a positive
impact on innovation capacity.
Rangus, K. and Slavec, A. (2017), Rangus and Slavec (2017)
continued to explore the relationship between absorptive capacity and
innovation capacity. Research also explored the role of organizational
characteristics such as decentralization, employee participation to enhancing
innovation. Research’s results demonstrated the role of decentralized culture,
employee engagement and absorptive capacity impact to innovation capacity.
From then, innovation influenced the business’s performance.
Hung et al., (2010). The objective of the study was to determine the
relationship between total quality management (TQM); organizational
learning and innovation capacity, including product innovation, process
innovation and organizational innovation. Hung et al used mixed method. The
results showed that relationships achieved statistical significance in the
positive correlation between TQM and organizational learning to innovation


capacity. In addition, the learning process of the organization is the foundation
for innovation because it is an opportunity to learn, collaborate and encourage
employees to create new knowledge, share and apply that knowledge,
especially learning strategies play the most important role in promoting
learning in organization.
Kang and Park (2011), Kang and Park analyzed the impact of
collaborative relationship between firms, the role of human resources for

R&D, as well as government support on innovation capacity. Research used
quantitative methods. The results demonstrated that cooperation between
firms impact to innovation, in which the downstream and upstream
international relationship represented a dominant influence on the innovation.
The role of government and human resources for R&D also positively
influenced innovation capacity.
2.3. Proposing the research model and analyzing the process of forming
the hypotheses
2.3.1. Proposed the research model
The research model of thesis was based on the basis theory of
Schumpeter, Nelson's theory and NIS theory, combined with research gaps
that were explored in process of literature review (Total Quality Management
will impact innovation capacity in positive or negative schools; the original
scale of government support, internal human resources and innovation
capacity was suitable totally or not when testing in Vietnam, if no, were there
an additional adjustment), along with building of research hypothesises that
based theory and expert interviews.


Figure 2-10: Model of factors affecting to the innovation capacity
of business in high-tech industries
Source: author’s research
2.3.2. Analyzing the process of forming the hypotheses in research model
2.3.2.1. Total quality management (TQM) and innovation capacity
The relationship between innovation capacity and the principles of
TQM is found in the theory of Suarez-Villa (1990). TQM has been proven
useful administrative solution in innovation and improving business’s
competitive advantage. Besides, if an organization commits to apply the
principles of TQM into its operating systems, the efforts for innovation will
bring expected results. Thus, in this study, the author agreed that TQM would

contribute to improving innovation capacity and proposing hypothesis H1
with positive effects.
Hypothesis H1: Total Quality Management positvely affects to the
innovation capacity of high-tech industrial businesses (H1 marked +)
2.3.2.2. Organization learning and innovation capacity
Derived from Schumpeter theory (1911), there are many different
definitions of organization learning. According to studies of của Argyris and
Schon (1978); Bontis, Crossan and Hulland (2002); Nonaka and Takeuchi
(1995); Davenport and Prusak (1998); Rothaermel and Deeds (2004); Hung et
al., (2010)…confirmed learning effort is the source of knowledge for


innovation. For that reason, the author believed in the role of organizational
learning and hypothesis H2 was proposed.
Hypothesis H2: The Organization learning positvely affects to the
innovation capacity of high-tech industrial businesses (H2 marked +)
2.3.2.3. Government support and innovation capacity
The concept of government support stemmed from basis theory of
National innovation system (NIS), which is an interactive system of private
enterprises, universities, scientific institutions and the government. This
system produces science and technology within national borders, in which the
government holds an important role (Niosi et al., 1993). Thus, the Government
not only acted as an investors and financial support for the research and
development of the enterprises, but also promote innovation capacity through
regulating supported mechanism such as subsidy, tax incentive, loan or R&D
human resources (Wallsten, 2000; Beugelsdijk and Cornet, 2002; Romijn and
Albaladejo, 2002; Souitaris, 2002; Park, 2006; Kang and Park, 2011...). From
these arguments about the Government’s role, we proposed hypothesis H3 as
below
Hypothesis H3: The Government support positvely affects to the

innovation capacity of high-tech industrial businesses (H3 marked +)
2.3.2.4. Collaboration network and innovation capacity
The theory of Nelson (1977; 1982, 1993) and the theory of national
innovation system (NIS) are the inspiration for schools of research on
collaborative networks in promoting innovation. According to Ahuja, G.
(2000); Becheikh et al,. (2006); Kang and Lee (2008); George, G. et al,.
(2002); Hagedoorn (1993); Romijn and Albaladejo (2002); Rothaermel and
Deeds (2006)... emphasized the collaboration in the value chain is a
prerequisite for transferring of knowledge and technical know-how.
Cooperation also contributes to setting up standard in the industry as well as
improving the application of new techniques.
From the point of view, this study hoped that if an organization
possesses high quality workforce, have a good educational background, skills,
flexibility and resolving job thoroughly, will bring the strength for innovation
capacity.
Hypothesis H6: Internal human resources positvely affects to the
innovation capacity of of high-tech industrial businesses


2.3.2.7. Ownership status and innovation capacity
Hypothesis H7: There exists a difference between domestic high-tech
enterprises and foreign high-tech enterprises (FDI sector) in the level of
influence/impact of total quality management (TQM), organizational learning
(OL), Government support (GS), collaboration network (CN), absorptive
capacity (AC) and internal human resources (IHC) to innovation capacity
(IC).
SUMMARY OF CHAPTER 2


CHAPTER 3

RESEARCH DESIGN
3.1. Research process
3.1.1. Research process
The research process of the thesis consists of 4 stages
Stage 1: Determine research problem
Stage 2: Add new observation variables to develop and improve the scale of
research concepts
Stage 3: Testing research model and hypothesis
Stage 4: Management implications for research results
3.1.2. Process of development and completion of the scale
In this study, the author applies the process of building observation variables
of Churchill (1979); Steenkamp and Van Trijp (1991), this process was
applied in Vietnam by Nguyen Dinh Tho (2007), with the following three
basic steps: (1) Building observed variables; (2) Evaluate the scale of the
preliminary stage and (3) Evaluate the scale at the official stage.
3.2. Research methodology
The study used mixed methods, including qualitative research and
quantitative research to adjust, supplement, modify and testing scale, testing
research model and hypotheses:
3.2.1. Qualitative research aims to develop and improve the scale of
research concepts
In-depth interview
In-depth interview was carried out with 5 experts who are extensive
experienced researchers in Vietnam Southern high-tech industry. All of them
affirm the important role of Total Quality Management (TQM), organizations
learning, Government support, absorptive capacity, internal human resources
and collaboration network to innovation capacity. In this research stage, the
authors explore and collect information maximally on research topics,
especially the concepts need to rebuild the scale. Based on that work, authors
will adjust or supplement new observable variables from the original scale to

build the first draft scale.


Thus, the results of in-depth interview had contributed for the
development of the first draft scale that used in focus group discussions.
Focus - group
The specialists take part in the focus group including 8 managers who
understand business’s development process and determinate innovation
capability as an indispensable objective. In this stage, the main objective focus
to assess the first draft scale’s content and build the second draft scale for
quantitative research in the next stages. The authors choose focus group
method because it’s suitable with exploitation information and exchange of
views between the members in the group. The author show that the opposition
and similarity in discussion to realize latent aspects of research.
3.2.2. Quantitative research
Preliminary research
Preliminary research was conducted through interview by
questionnaire. Sample size n = 89, sampling method was selected to detect
errors in the questionnaire and testing scale initially.
This survey’s subject was the senior managers of high-tech businesses
in Vietnam southern (Ho Chi Minh city, Dong Nai province, Binh Duong
province, Vung Tau city) in the following fields: information technology and
communication; pharmaceuticals, biotechnology; nanotechnology, energy;
mechatronics, automation, microelectronics and high-tech services. Reason
for choosing the object is the managers, directly in charge of the business plan,
research and development department (R&D), marketing and
market...because they deeply understand of their developing capacity, engage
in strategic planning as well as implement annual potential technological
projects. They realize daily reality of the business and desire to enhance
innovation capacity for growth.

The data was tested via analyzing Cronbach's alpha and Exploratory
Factor Analysis (EFA).
Official research
The study was conducted by surveying questionnaire (official scale).
Sample size n = 400. Sampling process is conducted as follows: from the
crowd (N = 800), calculate the hops k = N/n = 800/400 = 2. This survey’s
subject was the senior managers of high-tech businesses in Vietnam southern
(Ho Chi Minh city, Dong Nai province, Binh Duong province, Vung Tau city)


in the following fields: information technology and communication;
pharmaceuticals, biotechnology; nanotechnology, energy; mechatronics,
automation, microelectronics and high-tech services.
The data was cleaned and processed in software SPSS20 and Amos20
with Cronbach's alpha technique, Exploratory Factor Analysis (EFA),
Confirmatory factor analysis (CFA) and Structural Equation Modelling
(SEM).
3.3. Analyze the formation and development of research concept’s scale
3.3.1. Innovation capacity
The concept of innovation capacity (variable code: IC) consists of 5
statements (5 observed variables) and only emphasized product innovation
and process innovation.
1) Number of new product lines are introduced within 2012-2014 of
this company ?
2) Number of changes or improvements to existing product lines
within 2012-2014 of this company ?
3) Number of new equipment or technology are applied in the
production process of this company within 2012-2014 ?
4) Number of new input materials are applied in the production
process of this company within 2012-2014 ?

5) Number of organisational changes or improvements made in the
production processes of this company within 2012-2014 ?
3.3.2. Government support
The study inherited Wallsten's scale (2000), together with the results of indepth interview that helped the author add two new observable variables for
Government Support scale (GS) with 3 statements as follows:
1) Our company participated in R & D projects funded by the Government =>
Wallsten (2000)
2) Government facilitate for our company access to preferred loans => new
observable variables
3) Government facilitate for our company training and development of
professionals human resources => new observable variables
3.3.3. Internal human resources


The scale of Internal human resource concept (IHC) described by the
following 7 statements:
1) Human resources in our company are highly skilled
2) Human resources in our company are very intelligent and creative.
3) Human resources in our company is considered to be the best in this field.
4) Human resources in our company are specialized on their jobs.
5) Human resources in our company are always thinking and creating new
ideas and knowledge.
6) Human resources in our company are trained in professional environments..
7) Human resources in our company always work best and committ to making
efforts to achieve our goals.
3.3.4. Total quality management (TQM)
In this study, TQM is measured through 4 components: (1) The support of
senior managers; (2) Employee involvement; (3) Continuous improvement
and (4) Customer-orientation. The author applies the scale of Coyle-Shapiro
(2002); Zeitz et al (1997) to measure TQM.

3.3.5. Organization learning
The author applied the original scales of Watkins and Marsick, (2003);
Rhodes, Hung, Lok, Lien, and Wu (2008) that tested for 1139 high-tech
enterprises in Taiwan. At the same time, qualitative research also unified this
scale after adjusting the structure and words.
3.3.6. Absorptive capacity
The author applied the original scale of Jantunen (2005) which has been tested
in the field of information technology, telecommunications and measured
absorption capacity through 3 components: Knowledge acquisition,
Knowledge dissemination and Knowledge utilization.
3.3.7. Cooperation network
Inheriting the scale of Stuart et al. (2007), Kang and Park (2011), the author
measures the collaborative network based on the assessment of cooperation
(both formal and informal) between joint with related parties (domestic and
international) with Likert scale.
3.3.8. Ownership status (Control variables)
The author used the question "What is your company’s ownership status?" to
measure it, which suggests selecting 3 groups of businesses: 100% domestic


business; 100% foreign direct invesment or joint venture between Vietnamese
enterprises and foreign enterprises.
3.4. The preliminary quantitative research
Preliminary research should be ensured four steps: (1) Cronbach's
alpha analysis; (2) EFA analysis for each concept scale; (3) General EFA
analysis for concepts and (4) Testing cronbach's alpha coefficient of extracted
components in step 3. Data was obtained 89 complete questionnaires (n = 89).
The results of the study accomplished its role in verifying the reliability of the
conceptual scale and extracting 10 components:
- Total Quality Management (TQM) has three components that was

extracted from EFA’s result, it has 14 observable variables compared to 16
observable variables of original scale, in which component of top management
support (TQMTM) has observable 6 variables; component of continuous
improvement has 4 observable variables (TQMCI) and component of
customer focus (TQMCF) has 6 observable variables.
- Organizational learning (OL) has 2 components that was extracted
from EFA’s result, with 6 observable variables; including learning strategy
has 6 observable variables; learning culture has 2 observable variables
- Government support (GS) still remain content value of original
scale, only 1 component that was extracted from EFA’s result, with 3
observable variables.
- Absorptive capacity (AC) has 2 components that was extracted from
EFA’s result, with 6 observable variables, including knowledge
dissermination (ACKD) has 3 observable variables and knowledge acquisition
(ACKA) has 3 observable variables.
- Internal human resource (IHC) only has 1 components that was
extracted from EFA’s result, with 7 observable variables.
- Collaboration network (CN) has 1 components that was extracted
from EFA’s result, with 2 observable variables..
SUMMARY OF CHAPTER 3


CHAPTER 4
OFFICIAL QUANTITATIVE RESEARCH’S RESULT
4.1. Testing the concept’s scale
Testing the concept’s scales to ensure reliability before testing the
model and research hypotheses. The study uses the following methods:
exploratory factor analysis (EFA), Cronbach's alpha reliability and
confirmatory factor analysis (CFA).
There are 10 components that extracted from EFA results.

To ensure the reliability for these scales, the study tests Cronbach's
alpha for extractive components from the analysis of EFA. The result showed
that the coefficient of α of all components is greater than 0.6 and the corrected
item-total correlation is greater than 0.3.
CFA’s result showed all scales achive the unidimesionality,
composite reliability, variance extracted (some scales accepted), cronbach's
alpha, convergent validity and discriminant validity.
4.2. Testing of model and hypotheses
4.2.1. Testing research model
Model has Chi-square = 952.008, df= 480 (P = 0.000), Chi-square /
df = 1.932 (according to Carmines and McIver, (1981), in some cases
CMIN/df can be ≤ 3), RMSEA = 0.048, TLI = 0.903 and CFI = 0.912 > 0.9,
thus the model fits with market data.
In addition, the regression weights have demonstrated the relationship
between the concepts of total quality management (TQM), internal human
resources (IHC), absorptive capacity (AC), collaboration network (CN),
Government support (GS) with innovation capacity (IC), because p-values <
0.1, has statistical significance at 90% level of reliability. The regression
weights marked “+”, confirmed that TQM, IHC, AC, CN, GS positively
impact to the innovation capacity (Table 4-7).
The standardized regression weights are positive and also show the
degree of influence between them (Table 4-7), in which, collaboration
network (CN) strongly impact to innovation capacity because absolute value
of standardized weight is highest 0.395. The next important role is total quality
management (TQM), this concept has standardized weight is 0.276, internal
human resources (IHC) ranked 3rd with standardized weight is 0.234, the 4th


important belongs the government support has standardized weight 0.172 and
absorptive capacity (AC) has the lowest standardized weight is 0.107.

Although 5 concepts of TQM, AC, IHC, GS and CN only explain
51.5% of the variations of innovation capacity
Table 4-7: The relationship between the concepts in research model
Standardized
Unstandardized regression weights
regression
Relationship
weights
IC
IC
IC
IC

<--<--<--<---

TQM
AC
IHC
CN

IC <--- GS

Estimate
14.205
18.276
5.744
7.825

S.E.
6.014

9.216
2.491
1.678

C.R.
2.370
1.983
2.305
4.654

P
.018
.059
.025
***

Label
par_31
par_32
par_33
par_34

Estimate
.276
.107
.234
.395

15.329

8.257

1.856

.036

par_35

.172

Source: Author’s official research results
4.2.2. Testing research hypotheses
Rsearch has 6 hypotheses about relationships between concepts. The
SEM results verify these relationships by following:
H1: Total Quality Management positvely affects to the innovation
capacity of business in Vietnam southern high-tech industry.
Testing result show that p-value = 0.018 < 0.1, achieve statistical
significance, at level of reliability 90% (Table 4-7). Thus the hypothesis H1 is
accepted.
H2: The Organization learning positvely affects to the innovation
capacity of business in Vietnam southern high-tech industry.
The result does not reach statistical significance when p-value = 0.382 >
0.1, at level of reliability 90%. Hence, the hypothesis H2 is not accepted.
H3: The Government support positvely affects to the innovation
capacity of business in Vietnam southern high-tech industry.
The study’s result clearly reflects reality when the Government
support has p-value = 0.036 < 0.1, achieve statistical significance at 90%


reliability (Table 4-7) and standardized regression weights in relationship with

innovation capacity reach 0.172. Therefore hypothesis H3 is accepted.
H4: The collaboration network positvely affects to the innovation
capacity of business in Vietnam southern high-tech industry.
Testing result shows the p value = *** <0.001, has statistical
significance at level of reliability 90% (Table 4-7). Thus the hypothesis H4 is
accepted. The standardized regression weights of this relationship is 0.395, to
assert the importance of international collaboration network in business’s
perception.
H5: The absorptive capacity positvely affects to the innovation
capacity of business in Vietnam southern high-tech industry.
Testing result shows p-value = 0.059 <0.1, has statistical significance
at level of reliability 90% (Table 4-7). The standardized regression weights of
this relationship is 0.107. So hypothesis H5 is accepted.
H6: Internal human resources positvely affects to the innovation
capacity of business in Vietnam southern high-tech industry.
Testing result shows p-value = 0.025 <0.1, has statistical significance
at level of reliability 90% (Table 4-7). Thus hypothesis H6 is accepted.
4.2.3. Testing the difference due to ownership status
The estimation results for difference due to ownership status showed that Pvalue = 0.009 (<0.05). We conclude that there is a difference in interaction of
factors to innovation capacity between domestic enterprises and FDI
enterprises
For FDI enterprises, the relationship between absorptive capacity
(AC), internal human resources (IHC) and innovation capacity (IC) not
achieve statistical significant. It emphasizes the importance of the other three
factors, such as total quality management (TQM), collaboration networks
(CN) and government support (GS).
For domestic enterprises, TQM and AC were not statistical
significant in relation to IC, as p-value = 0.208 and 0.954 (> 0.1). While all
three variables are internal human resources (IHC); collaboration network
(CN) and government support (GS) was statistical significant.

SUMMARY OF CHAPTER 4