Knowledge Sharing Intention Among Employees in SMEs: A Case Study of Ho Chi Minh City

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UNIVERSITY OF ECONOMICS HO CHI MINH CITY
International School of Business
------------------------------
Ta Tran Trung
KNOWLEDGE SHARING INTENTION AMONG
EMPLOYEES IN SMALL AND MEDIUM SIZED
ENTERPRISES: A CASE IN HO CHI MINH
CITY, VIETNAM
MASTER OF BUSINESS ADMINISTRATION
1

UNIVERSITY OF ECONOMICS HO CHI MINH CITY
International School of Business
------------------------------
Ta Tran Trung
KNOWLEDGE SHARING INTENTION AMONG
EMPLOYEES IN SMALL AND MEDIUM SIZED
ENTERPRISES: A CASE IN HO CHI MINH
CITY, VIETNAM
MASTER OF BUSINESS ADMINISTRATION
SUPERVISOR: Dr. TRAN PHUONG THAO
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ACKNOWLEDGEMENT
I would like to express my deep gratitude to my supervisor, Dr. Tran Phuong
Thao for het patient attitude, valuable comment, helpful advice and continuous
encouragement during the time of research and writing this research work.
My grateful thanks are also extended to my friends, my lecturers and Research
Committee for their valuable time as their insightful comments and meaningful
suggestions were contributed significantly for my completion of this research.
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LIST OF ABBREVIATION WORDS
CEO: Chief Executive Officer
CFA: Confirmatory Factor Analysis EFA Exploratory Factor Analysis
GDP: Gross Domestic Product
ITC: Information and communication technology
SEM: Structural Equation Modeling
SMEs: Small and medium sized enterprises
TRA: The Theory of Reasoned Action
VND: Vietnamese Dong
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LIST OF TABLES
Table 1 A summary of prior studies on knowledge sharing.............................................16
Table 2 Measurement Scale..............................................................................................19
Table 3 Descriptive statistics............................................................................................21
Table 4 Means and Cronbach alpha of items after deleting items results........................25
Table 5 Pattern matrix ......................................................................................................27
Table 6 KMO and Bartlett's Test......................................................................................28
Table 7 SEM Hypothesis testing results...........................................................................32
Table 8 Multi-group analysis results ................................................................................34
LIST OF FIGURES
Figure 1. Conceptual model ..............................................................................................17
Figure 2. CFA model.........................................................................................................29
Figure 3. SEM Results.......................................................................................................31
Figure 4. Multi-group analysis model ...............................................................................33
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TABLE OF CONTENTS
1. Introduction ................................................................................................................................ 2
2. Literature review and hypothesis development .......................................................................... 6
2.1. Foundational theory ............................................................................................................ 6
Social Exchange Theory ............................................................................................................. 6
Theory of Reasoned Action ......................................................................................................... 8
2.2. Related review and hypothesis ............................................................................................ 9
3. Research methodology ............................................................................................................. 17
3.1. Research procedure ........................................................................................................... 17
3.2. Measurements ................................................................................................................... 18
3.3. Sampling and methods ...................................................................................................... 20
3.3.1 Sampling .................................................................................................................. 20
3.3.2 Methods ................................................................................................................... 22
4. Data analysis and results .......................................................................................................... 23
4.1. Reliability analysis ............................................................................................................ 23
4.2. Exploratory Factor Analysis ............................................................................................. 26
4.3. Confirmatory Factor Analysis ........................................................................................... 28
4.4. SEM modeling .................................................................................................................. 30
4.5. Hypothesis testing ............................................................................................................. 31
4.6. Multi-group analysis results (The moderating effect results) ........................................... 32
5. Conclusions and implications .................................................................................................. 35
5.1. Conclusions ....................................................................................................................... 35
5.2. Implications ....................................................................................................................... 35
5.3. Limitations and directions for future research .................................................................. 38
References ..................................................................................................................................... 40
Appendix 1. Questionnaire English version ............................................................................ 49
Appendix 2. Bảng câu hỏi khảo sát (Questionnaire Vietnamese version) ............................... 53
Appendix 3. Cronbach’s alpha results ..................................................................................... 57
Appendix 4. EFA results .......................................................................................................... 59
KMO and Bartlett's Test ............................................................................................................... 59
Appendix 5. CFA results .......................................................................................................... 62
Appendix 6. SEM results ......................................................................................................... 66
Appendix 7. Multi-group analysis results ................................................................................ 70
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Abstract
Knowledge is a valuable asset, a creativity, innovation, and potential contribution for the
development of business. That is the reason why knowledge sharing is researched to find
out the way to promote knowledge sharing, to take advantage of this core competency.
A survey with a convenience sample of about 450 SMEs employees in Ho Chi Minh City
was conducted with 18 variables and 429 observations valid samples in order to assess an
overview of the opinions of all employees in SMEs on intend to share knowledge. The
data were analyzed by Reliability Analysis, EFA, CFA, SEM method and the results
indicated factors Image, Subjective norms and Rewards have positive influence on the
intention to share knowledge and Individual culture has a significant moderating effect on
the relationship between both Image and Subjective norms toward intention to share
knowledge. Based on the finding of the research, the organization should respect and
listen to the opinions of the employees and create the awareness of knowledge sharing as
a must. As majority of prior researches on enterprise knowledge sharing focus mainly on
the public sector, large private companies, these new findings can be investigated in
further research, because sharing knowledge in SMEs is still a new concept in developing
country as Vietnam.
Keywords
knowledge sharing intention, small and medium sized enterprises, Subjective
norms, Image, Rewards, Intention to share knowledge, Individual culture.
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1. Introduction
Managing knowledge effectively is believed to be crucial to the achievement of the
organization, specifically in those companies that want to maintain their dominance
through creativity (Dieng, 2000). As more companies try to increase benefit by widen
their knowledge assets, a lot of enterprises have considered knowledge sharing as part
of their strategy. It is believed that knowledge sharing has been concerned by many
academics and professionals globally. Zakaria, Amelinckx and Wilemon (2004) confirm
that the role of knowledge sharing within a team should be emphasized. Blair (2002)
believes that when employees in the organization gain a lot of knowledge in their
organization, the organization has something far more valuable than data and
information.
Many prior studies show that collaboration and knowledge sharing are important factors
that organization should applied so as to attain continued competitive advantage
(Tapscott & Williams, 2006). Cyril Eze, Guan Gan Goh, Yih Goh and Ling Tan (2013)
state that a number of SMEs are manipulate knowledge management program to keep
up with or stay ahead of their competitors as a business leader.
In Vietnamese organizations, it is easy to see that the tendency to approach new things in
knowledge has evolved since the "Doi Moi" era to adapt to the globalized economy.
Although the sharing of knowledge is often seen as something new and meaningful in the
context of Vietnam (Dong, Gia Liem, & Grossman, 2010), Dong et al., (2010) reveal that
this is in fact only strongly empower individuals to access organizational knowledge
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instead of sharing their knowledge to other members. Beside the practicality of
knowledge sharing in companies, there are existing elements restraint knowledge sharing
culture, including the lack of organizational structures, unfriendly sharing working
environment, and denominational segregation (Davenport & Prusak, 1998; as cited in
Hendriks, 1999). Additionally, the fact is that SME enterprises occupy most of the
companies in Vietnam and contribute most of the domestic work (Swierczek & Ha,
2003; Dan, 2008). In general, the ineffective knowledge sharing system can make
employees in a company unable to improve their knowledge and transfer their experience
to other members. On the other hand, a rich and effective knowledge sharing system can
help employees save time and effort to solve problems that arise in the workplace.
Witherspoon, Bergner, Cockrell and Stone (2013) believe that the future success of the
organization will depend on sharing knowledge and this will be a vital strategy in the
new era. It is understood that an organization will create a better working environment
for development and innovation as it builds a better and more effective knowledge
sharing system. In addition, Desouza and Awazu (2006) state that common knowledge of
employees of SMEs is deep and broad, and it can actively support small business in
knowledge sharing. Prior studies also indicate some of the factors that impact the
knowledge sharing intension such as company rewards, reciprocity, ICT use, knowledge
self-efficacy and top management support (Chang, Hsu, Shiau, & Tsai, 2015; Dong et al.,
2010; Kanzler, Niedergassel, & Leker, 2012; Tohidinia & Mosakhani, 2010). However,
as given by Tohidinia and Mosakhani (2010) almost studies take into account
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determinants of knowledge sharing intention in a specific group of people or a whole
population. Notably, studies by Fathi, Eze and Goh (2011) and also Chong, Chong and
Wong (2007) indicate that the majority of prior researches on enterprise knowledge sharing
focus on the public sector, large private companies, while very few focus on knowledge
management conducted in SMEs. Additionally, according to Yu (2014), individual culture
in different countries may affect the knowledge sharing intention, but there are not many
studies investigating the influence of this factor on knowledge sharing intention. In SMEs
the knowledge management model which is basically based upon knowledge sharing –
through constant and open communication (often SME strength) – the making explicit of
often buried or tacit knowledge held by all employees (Gray,
2006). Gold, Malhotra and Segars (2001) emphasize that knowledge infrastructures such as
technology, structure and culture along with knowledge acquisition, conversion, application
and protection are essential organizational capabilities for higher organizational
performance. Therefore, SMEs need to identify the influence of personal culture on the
sharing of knowledge to bring more valuable benefits to their organization.
It is believed that large firm with large customer base tent to perceive a Knowledge
management system more useful and have a better chance to apply Knowledge
management system to build sustain competitive advantage. Besides, SMEs are known
of lacking of knowledge management practices even though they have a strong
communication links and social networks in the organization. It is said that knowledge
sharing especially tacit knowledge, is highly and actively interacted in SMEs. As more
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and more researches are interested in exploring this tacit knowledge sharing which is
very valuable and difficult to codify, SMEs could benefit from this advantage
compared to bigger organizations.
While there are many documents indicate some examples of research related to
knowledge sharing, previous studies show that there is not much study on the intention
to share knowledge in developing economies like Vietnam. With a relatively large
population, Vietnam has a thriving economy, always focused on strengthening global
trade relations. With these factors, the economy is considered as the most remarkable
economy in Southeast Asia (Doan Ngoc & Nguyen, 2013). With these factors, the
economy is considered as the most remarkable economy in Southeast Asia (Doan Ngoc
& Nguyen, 2013). The role of SMEs in Vietnam is widely accepted as the main driving
force for the national economy (Molnar, Nguyen, Homolka, & Macdonald, 2011).
According to statistics from the Ministry of Justice, there is a strong growth of Vietnamese
SMEs over the past few years, accounting for 97% of the total number of domestic
enterprises. In addition, there are many important roles and benefits of SMEs, such as
creating jobs, increasing income for workers, encouraging social capital for investment and
development, reducing poverty in the local area. SMEs generate more than half of new jobs;
using up to 51% of the workforce and contributing up to 40% of GDP (Phan, Nguyen, Mai,
& Le, 2015). Therefore, by investigating the importance of knowledge sharing for SMEs in
Vietnam, the study could help to improve the knowledge
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sharing culture of SMEs, thereby contributing significantly to the development
of business in Vietnam.
Dong et al. (2010) argues that Vietnam is still at the beginning of its own preparations
for full participation in the knowledge economy. Even though a lot of research papers
have been implemented to produce research on knowledge management and innovation
strategies, research based on the context of the Asia Pacific region is still in the
development stage. Additionally, as argue by Dong et al. (2010), many prior studies take
into account large companies instead of SMEs. Thus, the findings of this study could be
embedded in Vietnamese contexts to find the practical ways for enterprises to implement
successfully and fill the gap of studying the moderating role of individual culture in the
relationship between factors and knowledge sharing intention in order to contribute to the
development of SMEs in Vietnam.
2. Literature review and hypothesis development
2.1. Foundational theory
Social Exchange Theory
Social exchange theory is a social psychological and sociological perspective that
describes social change and stability as a process of negotiated exchanges between
parties. Social exchange theory posits that human relationships are formed by the use of
a subjective cost-benefit analysis and the comparison of alternatives. In other words, this
theory believe that people rely on the costs and benefits related to forming relationships,
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rather than just relying on emotions. It is applicable not only in the relationship
between individuals together, but also be applied in the relationship between colleagues
at work and other relationships
George and Homans (1961) develope Social exchange theory. They demonstrate that
interactive behavior of human beings are shaped by awareness of the benefits and costs,
and also introduced the concept of psychology as well as the proposed reward society.
The theory of social exchange suggests that people interact with others based on their
self-interest assessment of the costs and benefits of those interactions. Generally, people
always not only seek to increase their benefits but also decrease their costs when using
their limited resources or interacting with others. The cost here is something that is
considered negative to an individual such as the use of limited resources such as time,
money and effort into a relationship. For example, if a friend has a habit of borrowing
money, maintaining a relationship with him or her is considered a relatively high cost.
This theory is considered to be an extremely important document in the interpretation and
prediction of social behavior and built on the concept that people share their information
and knowing with those who have a give and take relationship rather than relying on
incentives. Based on the idea that knowledge sharing is a shape of social exchange, some
previous research use this idea to analyze as well as forecast the intention to share
knowledge (Bock, Zmud, Kim, & Lee, 2005; Kankanhalli, Tan, & Wei, 2005). Constant,
Kiesler and Sproull (1994) show that although individuals tend to exchange their
knowledge spontaneously, they are unlikely to exchange their knowledge if they feel that
the asker are not useful to them. In other words, people will be more willing in sharing
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knowledge when they predict a mutual relationship that will shape with the requester.
This is a mutually beneficial relationship.
Theory of Reasoned Action
The Theory of Reasoned Action are considered pioneering in the field of psychosocial
research (Fishbein & Ajzen, 1977). This theoretical model shows that behavior is decided
by the intention to achieve that behaviour. In the development of the theory of reasoned
action, Fishbeint instead analyzes attitudes toward an object, then analyzes attitudes
toward a behavior related to that object. For example, while most theorists have measured
attitudes towards a book in trying to predict reading behavior, Fishbein demonstrate that
measuring attitudes toward reading behavior will make better forecasts (compared to
measuring attitudes toward books) on reading behavior.
Theory of reasoned action supposes that humans are born rational and convince that the way
people behave is decided by 3 factorials: attitude toward the behaviour, subjective norms
and behavior intention. According to theory of reasoned action, the mindset of a person
towards a behaviour is decided by his attitudes about the outcomes of this behaviour. This
theory is applied to social psychology to describe human behavior and it has been used in
many fields of study including psychology, management and marketing. The theory of
reasoned action is applied in many research as a model for testing many types of behaviors
like behavioral communication, consumer behaviour, and health behaviour. Shimp and
Kavas (1984) apply this theory to the study of the use of coupons by consumers. Bock et al.
(2005) claim that extrinsic motivators, social psychologycal forces and organizational
environment factors could impact knowledge sharing
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intentions. Ho, Hsu and Oh (2009) use this theory to study behavioral communication in
the organization. The result is that the more indirect decisions that are made in the
organization, the more ineffective the sharing of knowledge, and to encourage knowledge
sharing, corporate managers should avoid indirect decisions.
2.2. Related review and hypothesis
Knowledge sharing intention
Knowledge is a flexible concept, which is difficult to describe by range or visibility.
Although there are many different expressions, there is a strong consensus among
scholars and specialists that knowledge is an essential element in helping organizations
achieve success. Knowledge is debatably one of the most vital factors leading
innovation in modern economy today (Grant, 1996; Stewart, 1997). Although
knowledge is useful for personal understanding, it will also be helpful to others when it
is shared. According to Kumar and Raduan (2012) knowledge sharing can define as a
social interaction culture, involving the exchange of woker expertise, acquirements and
skills across the company. Knowledge sharing takes place when organizational
colleagues share material, thoughts, proposals and knowledge related to organizations
together (Bartol & Srivastava, 2002).
Organizational culture is a field that is clearly expressed in knowledge sharing literature
(Al-Alawi, Al-Marzooqi, & Mohammed, 2007). One critical side of knowledge sharing is
culture, defined as “the sum of the values, rituals, symbols, beliefs, and thought processes
that are learned, shared by a group of people, and transmitted from generation to
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generation” (Cateora & Graham, 2007). Many prior studies examine factors
influencing Knowledge sharing. Among these factors, several are selected to examine
are as below. Subjective norm
Azjen and Fishbein, the inventers of the theory of reasoned action, state subjective norms
is a collection perceived prospects from related individuals or groups along with
intentions to comply with these forecast. Perceived subjective norms are a critical factor
that can impact intention toward a particular behavior (Tohidinia & Mosakhani, 2010). In
general, people tend to do something when they actively evaluate the behavior and when
they think that others think they should do it (Celuch & Dill, 2011). Kuo and Young
(2008) suggest that beside attitude, compatibility and self-efficacy, subjective norms
somewhat described the individual’s knowledge sharing intentions.
Some researchers show that the better the subjective norms to share knowledge is, the better
the knowledge sharing intention will be (Bock et al., 2005). As people want to be
recognized and famouse by other people, understanded subjective norms is important to
develope their intention to share knowledge (Sun & Scott, 2005). Vietnamese employees in
SMEs are not exceptional. Further, Vietnamese employees in SMEs usually appreciate
harmony, loyalty and are oriented towards collectivism and long standing affected by
Confucian values and ideals. Generally people with more collective-orientation are more
happly to be allocated and dedicate to their organization. Consequently, they are more
willing to share their experiences with others to enable the development of their
organization. One person’s collectivism is found by Hwang and Kim (2007) to be
supportively related to his attitude toward using the group email function in an online
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classroom management system to share knowledge. Accordingly, one hypothesis is
suggested as follow:
Hypothesis H1: Subjective norm has a positive influence on Intention to
share knowledge among employees in SMEs
Image
Generally, reputation is more and more significant. People desire to build their image as
professionals in an enterprise (Huang, Davison, & Jibao, 2008). One solution to build
their image is to share their experience and information with their colleagues.
Obviously, people will gain respect and reputation when they share useful knowledge
(Constant et al., 1994). Being more renowned by colleagues is a good chance for them to
enhance their career.
People believe that they can improve their social position and their image when
sharing knowlegde (Hsu & Lin, 2008). Knowledge allows workers to be recognized
and appreciated by their superiors. It enhances the staff’s respectability and image
(Kankanhalli et al., 2005). Studies by Huang et al. (2008) and Kankanhalli et al. (2005)
find that image and knowledge sharing behavior have a definite relation.
Since Vietnamese employee is collectivism, they really care for what people talk about them
(Chang et al., 2015). Hsu and Lin (2008) recommend that the more respectation or a better
image through knowledge sharing that employees could earn, the more willingness they
share. Besides, SMEs employees are young and they want build a solid foundation for their
professional image and personal brand. By sharing knowledge at their
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workplace, they can build good reputation and personal image, especially when media
being an ubiquitous part of our lives. Accordingly, one hypothesis is suggested as
follow: Hypothesis H2: Image has a positive influence on Intention to share knowledge
among employees in SMEs
Reward
Researchers define organizational rewards as both financial and non-financial benefits
that a worker achieves while working in an company (Malhotra, Budhwar, & Prowse,
2007). The prior researches classified 3 specific kinds of rewards that an employee looks
for from their company: extrinsic rewards, intrinsic rewards and social rewards
(Williamson, Burnett, & Bartol, 2009). More specifically, extrinsic rewards are suggested
by the organization from out-of-job content while in the other hand, intrinsic rewards are
offered by the organization from on-job content and results to employee’s development
(Williamson et al., 2009). Social rewards come from the connection with other colleagues
on the job.
The social-exchange perspective debates that people evaluate the overall value of a specific
relationship by subtracting its costs from the rewards it provides “Worth = Rewards –
Costs”. If the answer is greater than zero, it is a positive relationship. On the contrary, a
lower than zero answer indicates a negative relationship. The value of a relationship affects
its outcome, or whether people will endure with a relationship or put an end to it. Positive
relationships are predictable to exist, whereas negative one will possibly end. This research
therefore anticipate that when employees understand that they
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can earn more rewards by sharing their knowledge, they would provide a better
willingness to contribute and obtain knowledge.
People believe that having rewards when sharing knowledge is important (Kankanhalli
et al., 2005). Riege (2005) believes that lacking strong reward and recognition systems
may discourage workers to share their knowledge. On the other hand, an organization
should create an appropriate knowledge sharing encouragement system to support
knowledge contribution of organizational members (Chua, 2003). Both intrinsic and
extrinsic rewards are persistently described to be efficient factors for workforces to share
their understandings (Abdullah, Hassim, & Chik, 2009). It is believed that SMEs
employees could be easily encouraged to share knowledge because of economic
incentive, such as increased earnings and they will increase their commitment to their
organization. Accordingly, one hypothesis is suggested as follow:
Hypothesis H3: Rewards have a positive impact on sharing knowledge intention
among employees in SMEs.
Individual culture
Despite from the same country, two individuals might have various cultural values (Lee,
Choi, Kim, & Hong, 2007). Gallivan and Srite (2005) prove that the ethnic background,
region, and society might influence the cultural values (Gallivan & Srite, 2005). Further,
many previous studies suggest that cultural values should be measured at the individual
level of analysis (Srite & Karahanna, 2005). Base on Hofstede’s four dimensions to
measure national cultures, Chang et al. (2015) indicate that the awareness of benefits
and risk costs relates to individualism or collectivism and uncertainty prevention when
13

sharing knowledge, when other extents are declined the willingness to share thinking,
feelings, and experiences. Hence, in this study, individual culture includes both
Individualism and Collectivism. Individualism represents a society in which the
connection among people are weak: a man is only try to take care of himself and his
family. In the other hand, Collectivism represents a society in which people from birth
are included in strong and cohesive groups. These groups are considered to protect them
continuously throughout the life of the members in exchange for their loyalty (Hofstede,
1991).
Previous studies indicate that individuals in different culture have different processes of
knowledge sharing (Ardichvili, Maurer, Li, Wentling, & Stuedemann, 2006; Zhang,
Ribiere, & Thippaya, 2008). More pariticularly, interpreting the self is emphasized by
collectivism as an extension of one’s in-group and selecting in-group goals over private
goals. Conversely, Individualism clarify them self as distinct from one’s in-group and
choosing to personal goals over in-group goals. Individuals high on collectivist
orientation prioritize collectives’ demands and interests and are more willing to share
what they know with their society even though they perceive that such sharing involves
individual cost, because collectives’ demands and interests are related to the in-group
members’ long-term and overall interests by the collectivists. Some researchers propose
to promote knowledge sharing in organizations through boosting employees’ collectivism
orientation (Hwang & Kim, 2007). The Vietnamese profile is one of collectivism, similar
to other Asian countries. Further, SMEs employees normally come from country side and
deeply and affected by values and ideals of Confucian. To deal with the existing
14

limitation, the prior studies investigate how Individual cultural diversity affects
different factors significant for sharing knowledge in SMEs (Kanzler et al., 2012).
Accordingly, three hypotheses are suggested as follow:
Hypothesis H4a: The higher the degree of Individual culture, the higher the effect of
Subjective Norms on Intention to share knowledge among employees in SMEs
Hypothesis H4b: The higher the degree of Individual culture, the higher the effect of
Image on the SME employee Intention of sharing knowledge among employees in SMEs
Hypothesis H4c: The higher the degree of Individual culture, the higher the effect of
Reward on the SME employee Intention to share knowledge among employe
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Table 1 A summary of prior studies on knowledge sharing
Variables Item Code References
Rewards 1. It is important to be promoted when I share my REW1 Kankanhalli et al.,
knowledge. 2005
2. It is important to get a better work assignment when I REW2
share knowledge
3. It is important to get a higher salary when I share my REW3
knowledge
4. It is important to get a higher bonus when I share my REW4
knowledge
5. It is important to get more job security when I share REW5
my knowledge
Subjective 1. My CEO thinks that I should share my knowledge SNO1 Bock et al., 2005
norms with other members in the organization
2. My colleagues think that I should share my
knowledge with other members in the organization SNO2
3. My CEO thinks that I should share my knowledge
with other members in the organization
SNO3
Image 1. Sharing my knowledge improves my image within the IMG1 Kankanhalli et al.,
organization 2005
2. People in the organization who share their knowledge IMG2
have more prestige than those who do not
3. Sharing my knowledge improves others recognition of IMG3
me.
4. When I share my knowledge, the people I work with
respect me. IMG4
5. When I share my knowledge, my superiors praise me.
IMG5
Knowledge 1. I will share my knowledge on an ordinary basis in the KSI1 Moon and Kim,
sharing future 2001
intension 2. I will frequently share my knowledge in the future KSI2
3. I will strongly recommend others to share knowledge
KSI3
Individual 1. Individual rewards are more significant than ICU1 Yoon, 2009
culture organization welfare
2. Individual success is more significant than ICU2
organization success
3. Being independence is more significant than being ICU3
accepted as a member of an organization
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Figure 1. Conceptual model
Based on the above discussion, a model is suggested as follow:
3. Research methodology
3.1. Research procedure
The thesis process covers several stages, including literature review, research design,
qualitative method, main survey and data analysis which illustrated in the below process.
Based on literature from previous research about the Knowledge sharing intention in
SMEs, we proposed six hypotheses. After that, we adjusted the model and chose the
initial the scale for questionnaire of the study. Through the previous relevant researches,
the questionnaire was built then running the pilot test for checking the efficiency and the
meaning of the questions. The pilot test was purposed to explore and define the relevant
items and building a completed questionnaire. Then, the in-depth interviews with 10
employees in was carried out after finishing the questionnaire to get the right items with
17

Vietnamese employees. Then, we checked the words used in the first measurement scales
and modify them to be more appropriate and easy understanding. Though the previous
literature included most of the measures of the constructs, this step is essential to make
them suitable and understandable in studying context. After the qualitative research, we
adjusted the questionnaire again to be more appropriate to Vietnam market and to
understand more easily. When we designed the questionnaire properly, the main
investigation was implemented widely by using convenience samples which collected
from employees in Ho Chi Minh city.
3.2. Measurements
In the questionnaire, existing scale items from prior studies are used. The five-item scale
by Kankanhalli et al. (2005) is employed to measure the factor Rewards. Then the three-
item scale by Bock et al. (2005) is employed to assess the factor Subjective norms, the
five-item scale by Kankanhalli et al. (2005) to assess the factor Image, the three-item
scale by Yoon (2009) to measure the moderator Individual culture and finally the three-
item scale by Moon and Kim (2001) to measure the Intention to share knowledge.
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Table 2 Measurement Scale
Variables Item Code References
Rewards 1. It is important to be promoted when I share my REW1 Kankanhalli et al.,
knowledge. 2005
2. It is important to get a better work assignment when I REW2
share knowledge
3. It is important to get a higher salary when I share my REW3
knowledge
4. It is important to get a higher bonus when I share my REW4
knowledge
5. It is important to get more job security when I share REW5
my knowledge
Subjective 1. My CEO thinks that I should share my knowledge SNO1 Bock et al., 2005
norms with other members in the organization
knowledge with other members in the organization SNO2
SNO3
Image 1. Sharing my knowledge improves my image within the IMG1 Kankanhalli et al.,
organization 2005
2. People in the organization who share their knowledge IMG2
3. Sharing my knowledge improves others recognition of IMG3
me.
4. When I share my knowledge, the people I work with
respect me. IMG4
IMG5
Knowledge 1. I will share my knowledge on an ordinary basis in the KSI1 Moon and Kim,
sharing future 2001
intension 2. I will frequently share my knowledge in the future KSI2
KSI3
Individual 1. Individual rewards are more significant than ICU1 Yoon, 2009
culture organization welfare
2. Individual success is more significant than ICU2
organization success
3. Being independence is more significant than being ICU3
accepted as a member of an organization
19

3.3. Sampling and methods
3.3.1 Sampling
According to Hair, Black, Babin and Anderson (2009), the smallest sample to apply for
analysing statistics is followed the general rule which is 5 times greater or equal than
the numbers of variables, but not less than 100.
A survey with a convenience sample of about 450 SMEs employees was conducted. The
questionnaire was spread through social media including Google docs and e-mail or send
the hard copy of survey directly to employees. The original English questionnaire was
translated into Vietnamese. Current study conducted this procedure because English is
not well understood by all employees in Vietnamese employees. The respondents could
answer the survey by clicking on the link and keying their answers and submitting the
link to the researcher.
After distributing 450 respondents, 435 questionnaires were collected, 429 questionnaires
were selected for data analyzed with SPSS 20 software. For gender distribution, there are
205 respondents are males (48%), which is lower than the numbers of 224 female
respondents (52%). The data show that the respondents are from 30 to 35 years old plays the
biggest part with 45% (143 respondents). Respondents who less than 30 years old are at the
second biggest part with 133 respondents (38%). Respondents from 36-40 years old is at the
third place with 64 respondents that make up 15%. And the minority
20

respondents are from 40 years old and above with only 8%. This result describes the
circumstance of Vietnam SMEs when young generation nowadays usually chooses small
& medium enterprises for their challenge at work.
Table 3 Descriptive statistics
Characteristics Number Percentage
Gender
Male 205 48%
Female 224 52%
Education
Below University Graduation 217 50%
University Graduation 209 49%
Master/PhD 3 1
Salary
> 10 million VND per month 133 31%
10 – 15 million VND per month 184 43%
16 – 20 million VND per month 92 21%
≥ 20 million VND per month 20 5%
Age
< 30 years old 165 38%
30-35 years old 166 39%
36-40 years old 64 15%
≥ 40 34 8%
The table also presents the data concerning the Level of education of employees
working in companies. The majority of employees are Below University Graduation
which made up 50% (217 respondents) while the amount of University Graduation is
49% (209 respondents) and Master/PhD with 1% (3 respondents). The result reveal that
there is a good system in term of educational level of workforces in enterprises.
21

Finally, the summary description table shows the income per month of the respondents.
It showed that the group of employees has income from 10 – 15 million VND per month
is the majority with 184 respondents (43%). 133 respondents (31%) have income less
than 10 million VND and 92 employees earns from 15 – 20 million VND per month,
equivalent to 21%. The lowest percentage belonged to employees earns from more than
20 million VND per month with 5% (20 respondents)
3.3.2 Methods
The data of this study is processed with five main stages including sample Descriptive
Statistic, Reliability Analysis, Exploratory Factors Analysis, Confirmatory Factor
Analysis, and Structural Equation Modeling.
Reliability Analysis
First, Cronbach’s α values is used to evaluate if the measures are reliable. The
Cronbach’s Alpha is the most popular objective measure of reliability of the scale.
Cronbach’s Alpha is a statistical test if the correlation of the items in the scale is relative
to each other. Consequently, this method of analysis can remove inappropriate variables
and limit junk variables in the study process and evaluate the reliability of the scale
through the Cronbach’s Alpha coefficient (Hair, Black, Babin, Anderson, & Tatham,
1998).
Exploratory Factor Analysis (EFA)
22

In the second step, Exploratory Factor Analysis (EFA) is implemented to test the number
of factors extracted to explore the relationship between independent variables. Factor
analysis is a multivariable statistical technique which defines the fundamental structure
among a large amount of variables (Hair et al., 1998). The two primary purposes of
factor analysis are to summarize the information included in a large amount of variables
and make the data condensed into smaller number of factors (Hair et al., 1998).
Confirmatory Factor Analysis (CFA)
Next, Confirmatory Factor Analysis (CFA) is conducted to test whether the
measurement model reliable and valuable. Based on CFA results, the convergent validity
is concluded by average variance extracted (AVE) and the discriminate validity is
identified by correlation between items.
Structural Equation Modeling (SEM)
Finally, structural equation modeling (SEM) is conducted to the hypothesized model and
estimated path coefficients for each proposed relationship in the structural model. SEM is
a widespread statistical approach to test hypotheses about observed and latent variables
relations (Hoyle, 1995). Rigdon (1998) defined that SEM is a methodology to represent,
estimate, and test a theoretical network of linear relations between variables. SEM is used
to test the moderating impact of Individual culture in this study.
4. Data analysis and results
4.1. Reliability analysis
23

This study firstly used Cronbach alpha and explanatory factor analysis (EFA) to test
reliability and convergent validity of the scale. The alpha coefficient normally ranges
from 0 to 1 and where the alpha coefficient is greater than 0.7 this can be considered an
acceptable reliability. According to the analysis results above, most of the scales were
quite good factor alpha. The result was one variable is deleted from reliability test
analysis which is the second variable of sharing knowledge intention. The variable was
deleted as it has overall Cronbach’s alpha value lower than Cronbach’s alpha if Item
Deleted value. Cronbatch’s Alpha coefficients ranged from 0.799 to 0.886. The corrected
Item-total correlation of these scales also met the criterion of above 0.3. Therefore, all the
constructs were qualified to use for the next step analysis, factor analysis discovered
EFA.
24

Table 4 Means and Cronbach’s alpha of items after deleting items results
Variable Item-Total Statistics Reliability
Statistics
Scale Mean if Scale Variance Corrected Item- Cronbach's Alpha if Item Cronbach's N of
Item Deleted if Item Deleted Total Correlation Deleted Alpha Items
Knowledge sharing Intention (KSI1, KSI2, KSI3)
KSI1 3.18 1.302
KSI3 3.69 .643
.712
.712
.802 2
Reward (REW1, REW2, REW3, REW4, REW5)
REW1
REW2
REW3
REW4
REW5
17.08 6.871 .654
17.10 6.618 .685
17.15 6.241 .710
17.12 6.253 .708
17.11 6.676 .665
.843
.835
.828
.829
.840
.895 5
Subjective norms (SNO1, SNO2, SNO3)
SNO1
SNO2
SNO3
6.49 2.316 .664
6.54 2.347 .652
6.68 2.180 .621
.707
.719
.756
.799 3
Image (IMG1, IMG2, IMG3, IMG4, IMG5)
IMG1
IMG2
IMG3
IMG4
IMG5
14.24 11.057 .706
14.03 11.403 .733
14.12 11.083 .770
14.04 11.384 .707
13.97 10.296 .720
.865
.860
.851
.865
.865
.886 5
Individual Culture (ICU1, ICU2, ICU3)
ICU1
ICU2
ICU3
8.70 1.737 .680
8.66 1.818 .676
8.66 1.650 .704
.769
.774
.745
.828 3
25

4.2. Exploratory Factor Analysis
The next step after testing Cronbach’s Alpha coefficient, the measure continued to be
analyzed by EFA analysis method to test the relationships among internal variables. This
research followed a strict criterion to delete factors which their loadings were lower than
0.5 and the components with Eigenvalue higher than 1.0 were retained. The result was
the KMO value = 0.793 > 0.5, the significant value p < 0.05, all factor loading > 0.5.
The analysis, which used Rewards, Subjective norms, Image, and Individual culture to
operationalize Knowledge sharing intension in SMEs, confirmed the high internal
consistency reliability of this instrument, indicating sampling adequacy, validity,
factorability and reliability of the questionnaire.
26

Table 5 Pattern matrix
Pattern Matrixa
Factor
1 2 3 4
IMG3 .834
IMG2 .784
IMG5 .780
IMG4 .763
IMG1 .761
REW3 .781
REW4 .768
REW2 .746
REW5 .740
REW1 .708
SNO1 .823
SNO2 .766
SNO3 .681
KSI3 .885
KSI1 .805
Extraction Method: Principal Axis Factoring.
Rotation Method: Promax with Kaiser Normalization.
a. Rotation converged in 5 iterations.
After testing with Cronbatch’s Alpha, EFA was used to test the relationship among
internal variables. According to Pallant (2001), Factor analysis is suitable for data if
satisfies the followings: The Kaiser-Meyer-Olkin value (KMO) is 0.6 or greater; The
Bartlett’s test of inadequate is statistically significant: p < 0.05; The transmission
coefficient variables (factors loading) is less than 0.5 or the difference between the two
factors less than 0.3 will be disqualified.
27

Table 6 KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.
Approx. Chi-Square
Bartlett's Test of Sphericity df
Sig.
.793
2935.889
105
.000
The result was the KMO value = 0.793, the p-value <0.05, all factor loading>0.5. The
analysis confirmed the high internal consistency reliability of this instrument, indicating
sampling adequacy, validity, factorability and reliability of questionnaire.
4.3. Confirmatory Factor Analysis
28

Figure 2. CFA model
Next, the measure continued to be analyzed by CFA analysis method to test whether
the measurement model reliable and valuable. The CFA results showed the model fit if
Cmin/df was less than 3 with p-value larger than 5%. A CFI value is more than 0.95 is
good, more than 0.9 is traditionally, and more than 0.8 is sometimes permissible. The
root mean square error of approximation (RMSEA) avoided issues of sample size by
analyzing the discrepancy between the hypothesized models, with optimally chosen
29

parameter estimates, and the population covariance matrix. A value of 0.1 or less was
indicated and acceptable model fit.
The result of CFA was: Chi-square = 198.851, Degrees of freedom = 84, Chi-square/df
= 2.367, CFI = 0.6, TLI = 0.95, RMSEA = 0.057. This result showed that the
measurement in this study is appropriate to the data.
The criteria of Factor loading were greater than 0.5 significantly (p-value < 0.05). Most
the factor loadings were greater than 0.5. Then, convergent validity of this measurement
scale was accepted.
4.4. SEM modeling
The structural equation modeling (SEM) results illustrated that the theoretical model
matched with the data: chi-square= 198.851, CFI=0.96, RMSEA=0.057, GFI=0.945,
AGFI=0.921. All factor loadings on the latent constructs were found significant and
substantial (≥0.50). The model also demonstrated that all paths were statically significant
(p < 0.05).
30

Figure 3. SEM Results
4.5. Hypothesis testing
31

Table 7 SEM Hypothesis testing results
Estimate S.E. C.R. P Label
(H2) KSI <--- IMG .172 .057 3.028 .002
(H3) KSI <--- REW .181 .068 2.646 .008
(H1) KSI <--- SNO .422 .086 4.898 ***
IMG3 <--- IMG 1.000
IMG2 <--- IMG .915 .051 17.865 ***
IMG5 <--- IMG 1.119 .063 17.720 ***
IMG4 <--- IMG .935 .053 17.671 ***
IMG1 <--- IMG .975 .057 17.236 ***
REW3 <--- REW 1.000
REW4 <--- REW .997 .062 15.979 ***
REW2 <--- REW .879 .057 15.340 ***
REW5 <--- REW .850 .058 14.760 ***
REW1 <--- REW .795 .055 14.515 ***
SNO1 <--- SNO 1.000
SNO2 <--- SNO .965 .073 13.252 ***
SNO3 <--- SNO 1.027 .079 13.065 ***
KSI3 <--- KSI 1.000
KSI1 <--- KSI .944 .121 7.771 ***
The result showed that P-value of H1 is less than 0.001, H2 is 0.002 and H3 is 0.008. It
means that H1, H2 and H3 are accepted. In other words, Subjective norms, Image and
Reward has positive impacts on the intention of sharing Knowledge in SMEs
4.6. Multi-group analysis results (The moderating effect results)
32

Figure 4. Multi-group analysis model
Multi-group analysis in SEM was used to put the moderating effect of Individual
culture into tests. Individual culture was separated into low group and high group.
The result showed that P-value of H4a is less than 0.008, H4b is less than 0.001 and
H4c is 0.022. It means that H4a and H4c are accepted.
33

Table 8 Multi-group analysis results
(H4b) KSI <--- IMG .512 .065 7.906 ***
(H4c) KSI <--- REW .219 .096 2.289 .022
(H4a) KSI <--- SNO .446 .169 2.638 .008
IMG3 <--- IMG
IMG2 < IMG
IMG5 <--- IMG
IMG4 < IMG
IMG1 <--- IMG
REW3 < REW
REW4 <--- REW
REW2 <--- REW
REW5 <--- REW
REW1 <--- REW
SNO1 < SNO
SNO2 <--- SNO
SNO3 < SNO
KSI3 <--- KSI
KSI1 < KSI
1.000
.794 .063 12.572 ***
.853 .065 13.165 ***
.932 .043 21.536 ***
.752 .062 12.058 ***
1.000
1.060 .093 11.413 ***
.934 .084 11.089 ***
.828 .085 9.703 ***
.773 .077 10.032 ***
1.000
1.286 .194 6.618 ***
1.149 .171 6.712 ***
1.000
.602 .080 7.487 ***
The results of the multi-group analysis indicated that Individual culture had a
noteworthy moderating impact on Image and Subjective norms toward Knowledge
sharing intention relationship in SME enterprises. Individual culture also had significant
moderating impact on the relationship between Reward and Knowledge sharing
intention in SME enterprises.
34

5. Conclusions and implications
5.1. Conclusions
This study shows the effect of Subjective norms, Image and Rewards on Intention to
share knowledge SMEs with 429 employees in SMEs. The data is analyzed by Reliability
Analysis, EFA, CFA, SEM method.
The results of this study indicate that Subjective norms, Image and Reward have positive
influences on the Knowledge sharing intention. The positive effect of Subjective norms
on the intention of sharing Knowledge in SMEs also consistent with results of prior
studies of Bock et al.(2005), Hwang and Kim (2007). Reward is also concluded to play
an important role on Knowledge sharing intention in SMEs. This supports previous
findings of Kankanhalli et al. (2005), Hsu and Lin (2008), Huang et al. (2008).
Predictably, the Image is anticipated that have an optimistic impact on intention of
sharing knowledge in SMEs. This is consistent with prior studies of Chua (2003),
Kankanhalli et al. (2005), Riege (2005), Abdullah et al. (2009).
The results also indicate that Individual culture has a noteworthy moderating impact on
Image, Reward and Subjective norms toward Knowledge sharing intention relationship in
SME enterprises.
5.2. Implications
When employees believe that sharing information and knowledge will be beneficial for
them, for the organization and contribute to the development of enterprise would be
boosted intend to share their knowledge for colleagues. As Reward is important for the
35

economic contribution of information as well as knowledge, the organization should
recognize the contributions of their employees and offers them appropriate incentives or
motivation (Grant, 1996). Organizations can provide many forms of remuneration
including basic salary increases, bonuses, job safety and chances for advancement
(Zhang et al., 2008). Besides, because the greater the subjective norms of knowledge
sharing is, the greater the willingness of knowledge sharing will be, the organization
should respect and listen to the opinions of the employees. The organizations have to
create the awareness of knowledge sharing as a must. Consequently, their employees will
understand that knowledge sharing is a subjective norms and they will be more willing to
share their understanding and knowledge in practice.
As studies have shown that Rewards and Subjective norms can influence knowledge
sharing attitude of the employees in an organization, companies can create better
motivation for employees to work hard by giving the reward for employees with specific
gifts. Organization can award important employee contributions to the company. This
will encourage healthy competition and create excitement at work. When the effort of the
staff is paid properly, they will feel comfortable and the performance will be higher. This
is clearly a great result for both workers and employers. However, the organization
should not wait until the end of the year to recognize the staff. Instead, the company
should do this at any time and of course, such rewards are held semi-annually or
quarterly. One thing organizations need to take into consideration is to diversify the
reward form, gather ideas and use them in turn. The reason is because rigid rewards in a
form are sometimes counterproductive. Managers should ensure that the reward is done
36

openly with the presence of numerous employees and leaders in the company. Thus, the
person who is honored and rewarded will feel more proud, and the more trust in the
organization will be. This is also the message, motivating efforts, striving in the work of
the remaining staff. Managers should keep in mind that every employee has their own
strengths and weaknesses, so building trust among employees is the key to helping
employees maximize their latent capacity.
From the research results, several suggestions for enhancing the knowledge sharing
motivation among staff in the organization have been proposed. Specifically,
organization can reference 4 active list below. Firstly, organization should periodically
evaluate and record the level of knowledge sharing of each employee for appropriate
reward policy. Secondly, organization might change corporate culture in a way that
encourages sharing and helps employees understand knowledge is power, but knowledge
sharing brings greater power. Next, company can promote the current organizational
culture in the direction of balancing group roles and common interests of the
organization. Finally, manager should organize common events to raise awareness for
the social benefits of employees.
One more thing that managers need to keep in mind is that there are so many different
types of personal culture that will determine the employee's beliefs, values and
professional ethics. It is unlikely that any manager can not grasp the knowledge of every
culture in the world and gain the skills and knowledge to deal with their employees.
Instead, managers should develop the capacity to recognize individual cultures and
build trust, values, and employee ethics. Especially in the management of rewarding
37

employees, managers need to develop a rational reward system for the company. The
reason for this may be because employees maybe want to avoid excessive rewards for
themselves or to limit workplace conflicts. When a community builds a unity and
solidarity, their employees tends to care about others in the community. They will be
more concerned about how their performance influencing their peers and this may result
in them changing their behavior. Apply this to the reality of businesses in Vietnam, where
collective employees tend to work for the community, if one recognizes "my victory is
your loss", they may be willing to diminish their performance or reduce their actual
performance, to avoid excessive rewards for themselves or to limit workplace conflicts.
These new findings and ideas can be investigated in further research because sharing
knowledge is still a new concept in developing country as Vietnam. On the basis of that,
the staff will empathize and share more knowledge in the workplace.
5.3. Limitations and directions for future research
The findings of this study must be considered with some limitations. Firstly,
although Ho Chi Minh City is among the big cities of Vietnam was chosen to conduct the
research, it may not represent for all employees in SMEs. Therefore, further studies
should extend the research scope to other provinces in Vietnam. Secondly, this study
assumes that employees in the different organization have the same knowledge to share.
Therefore, the type of knowledge should be examined more detail in the future research.
Besides, this study considers Intention to share knowledge regardless the level of position
of employees working in their organizations. Hence, the level of position should be
38

examined in the future research. Besides, the sample size is small, other factors that
may affect the monetary policy, such as organizational culture, professional ethics and
leadership, are ignored.
39

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sharing intention. Chinese Management Studies, 8(1), 149. Retrieved from
http://search.proquest.com/docview/1658153364?accountid=63189
Zakaria, N., Amelinckx, A., & Wilemon, D. (2004). Working Together Apart? Building a
Knowledge-Sharing Culture for Global Virtual Teams. Creativity and Innovation
Management, 13, 15–29.
47

Zhang, Q., Ribiere, V. M., & Thippaya, C. (2008) in O’Sullivan, K. (Ed.), Strategic
Knowledge Management in Multinational Organizations, Information Science
Reference, Hershey, PA, pp. 40-52.
48

Appendix 1. Questionnaire English version
Hello Sir and Madam,
I am Ta Tran Trung, studying Master at ISB – International school of Business.
Currently, I am conducting a survey about knowledge sharing intention in small and
medium sized enterprises in HCMC, Vietnam. The research proposes to find out
solutions to improve knowledge sharing system in small and medium sized enterprises
in Vietnam. I hope you can spend your precious time to answer below questions. All
information provided is confidential and only used for research purpose.
In this survey, there is no right or wrong answer, you only need to choose the answer
that best fit to you.
Sincerely thanks for your support.
1. Are you currently working at a small and medium sized enterprises?
Yes (Please answer next question)
No (Please stop the questionnaire here, thank you)
PART 1:
Please only choose one option for each question below to indicate your agreement
level. (1: I strongly disagree; 5: I strongly agree)
49

Questions 1 2 3 4 5
1. It is important to be promoted when I share my
knowledge.
2. It is important to get a better work assignment when I
share knowledge
3. It is important to get a higher salary when I share my
knowledge
4. It is important to get a higher bonus when I share my
knowledge
5. It is important to get more job security when I share
my knowledge
knowledge with other members in the organization
9. Sharing my knowledge improves my image within
the organization
10. People in the organization who share their knowledge
50

11. Sharing my knowledge improves others
recognition of me.
12. When I share my knowledge, the people I work
with respect me.
14. I will share my knowledge on a regular basis in
the future
15. I will frequently share my knowledge in the future
17. Individual rewards are more important than
group welfare
18. Individual success is more important than
group success
19. Having independence is more important than
being accepted as a member of a group
51

PART 2:
1. Your gender:
Male Female
2. Your age:
< 30 30-40 41-50 > 50
3. Your degree?
Below University Graduation University Graduation Master/PhD
4. Your monthly income?
> 10 million VND per month
10 – 15 million VND per month
16 – 20 million VND per month
≥ 20 million VND per month
Thank you for your support.
52

Appendix 2. Bảng câu hỏi khảo sát (Questionnaire Vietnamese version)
Kính chào Anh/Chị.
Tôi là Tạ Trần Trung - học viên Cao học tại Viện Đào tạo Quốc tế ISB. Hiện tôi đang
tiến hành khảo sát hành vi chia sẻ kiến thức trong các doanh nghiệp vừa và nhỏ tại Việt
Nam. Nghiên cứu nhằm tìm ra giải pháp cải thiện hệ thống chia sẻ thông tin kiến thức tại
Việt Nam. Rất mong Anh/Chị dành chút thời gian để trả lời một số câu hỏi sau đây. Mọi
thông tin Anh/Chị cung cấp sẽ được bảo mật và chỉ được dùng cho mục đích nghiên cứu.
Trong khảo sát này, không có câu trả lời nào là đúng hay sai. Anh/Chị chỉ cần chọn câu
trả lời phù hợp nhất với mình.
Chân thành cảm ơn sự giúp đỡ của Anh/Chị.
1. Anh/chị hiện tại có đang làm việc tại doanh nghiệp vừa và nhỏ không?
Có (mời trả lời những câu tiếp theo)
Không (xin chân thành cám ơn, anh/chị có thể dừng khảo sát)
PHẦN 1:
Đối với mỗi phát biểu Anh/Chị vui lòng chỉ đánh vào một con số thể hiện mức độ đồng ý
theo quy ước sau: (1: Hoàn toàn không đồng ý; 5: Hoàn toàn đồng ý)
53

Câu hỏi 1 2 3 4 5
1. Điều quan trọng là được thăng chức khi tôi chia sẻ
kiến thức của mình
2. Điều quan trọng là nhận được công việc, nhiệm vụ
thích hợp hơn khi tôi chia sẻ kiến thức của mình
3. Điều quan trọng là nhận được thu nhập cao hơn khi tôi
chia sẻ kiến thức của mình
4. Điều quan trọng là nhận được phần thưởng cao hơn
khi tôi chia sẻ kiến thức của mình
5. Điều quan trọng là có được thêm sự an toàn trong
công việc khi tôi chia sẻ kiến thức của mình
6. CEO của tôi nghĩ rằng tôi nên chia sẻ kiến thức
của mình với các thành viên khác trong tổ chức
7. Đồng nghiệp của tôi nghĩ rằng tôi nên chia sẻ kiến
thức của mình với các thành viên khác trong tổ chức
8. CEO của tôi nghĩ rằng tôi nên chia sẻ kiến thức
của mình với các thành viên khác trong tổ chức
9. Chia sẻ kiến thức cải thiện hình ảnh của tôi trong tổ
chức
10. Những người trong tổ chức chia sẻ kiến thức của họ
có nhiều uy tín hơn những người không làm điều này
54

11. Chia sẻ kiến thức cải thiện sự nhìn nhận của người
khác đối với tôi.
12. Khi tôi chia sẻ kiến thức của mình, những người
tôi làm việc chung tôn trọng tôi.
13. Khi tôi chia sẻ kiến thức của tôi, cấp trên của tôi khen
ngợi tôi.
14. Tôi sẽ chia sẻ kiến thức của tôi như là một hành động
rất thường xuyên trong tương lai
15. Tôi sẽ thường xuyên chia sẻ kiến thức của mình
trong tương lai
16. Tôi sẽ đề nghị những người khác chia sẻ kiến thức
17. Phần thưởng cá nhân quan trọng hơn lợi ích nhóm
18. Thành công riêng lẻ của cá nhân quan trọng hơn
thành công nhóm
19. Có được sự độc lập trong công việc quan trọng
hơn việc được chấp nhận là thành viên của nhóm
55

PHẦN 2:
1. Giới tính của Anh/Chị:
Nam Nữ
2. Vui lòng cho biết tuổi của Anh/Chị thuộc nhóm nào ?
Dưới 30 Từ 30 đến 40 Từ 41 đến 50 Trên 50
3. Bằng cấp chuyên môn của Anh/Chị?
PTTH hoặc thấp hơn Tốt nghiệp Đại học Trên Đại học
4. Thu nhập hàng tháng của
Anh/chị? Dưới 10 triệu đồng
Từ 10 triệu đồng đến 15 triệu đồng
Từ 16 triệu đồng đến dưới 20 triệu đồng
Từ 20 triệu đồng trở lên
Xin chân thành cảm ơn Anh/Chị.
56

Appendix 3. Cronbach’s alpha results
Knowledge sharing Intension (KSI)
Cronbach's N of Items
Alpha
.651 3
Item-Total Statistics
Scale Mean if Scale Corrected Cronbach's
Item Deleted Variance if Item-Total Alpha if Item
Item Deleted Correlation Deleted
KSI1 6.64 4.282 .569 .499
KSI2 6.87 3.246 .332 .802
KSI3 7.16 3.141 .586 .373
Knowledge sharing
Intension (KSI) – after
delete KSI2
Alpha
.802 2
Scale Mean if Scale Corrected Cronbach's
Item Deleted Variance if Item-Total Alpha if Item
Item Deleted Correlation Deleted
KSI1 3.18 1.302 .712 .
KSI3 3.69 .643 .712 .
Reward
Alpha
.864 5
Item -Total Statistics
Scale Mean if Scale Variance Corrected Cronbach's
Item Deleted if Item Item-Total Alpha if
Delete
d Correlation Item
Deleted
REW1 17.08 6.871 .654 .843
REW2 17.10 6.618 .685 .835
REW3 17.15 6.241 .710 .828
REW4 17.12 6.253 .708 .829
REW5 17.11 6.676 .665 .840
57

Subjective norm
Alpha
.799 3
Item Deleted
if
Item Item-Total Alpha if Item
Deleted Correlation Deleted
SNO1 6.49 2.316 .664 .707
SNO2 6.54 2.347 .652 .719
SNO3 6.68 2.180 .621 .756
Image
Alpha
.886 5
Item Deleted if Item Item-Total Alpha if Item
IMG1 14.24 11.057 .706 .865
IMG2 14.03 11.403 .733 .860
IMG3 14.12 .851
11.083 .770
IMG4 14.04 11.384 .707 .865
IMG5 13.97 10.296 .720 .865
Individual culture
Alpha
.828 3
Item Deleted if Item Item-Total Alpha if Item
ICU1 8.70 1.737 .680 .769
ICU2 8.66 1.818 .676 .774
ICU3 8.66 1.650 .704 .745
58

Appendix 4. EFA results
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy
Approx. Chi-Square
Bartlett's Test of Sphericity df
Sig.
.793
2935.889
105
.000
Communalities
Initial Extraction
KSI1 .561 .699
KSI3 .542 .750
REW1 .448 .506
REW2 .489 .560
REW3 .537 .612
REW4 .524 .611
REW5 .458 .531
SNO1 .498 .648
SNO2 .459 .576
SNO3 .440 .531
IMG1 .545 .577
IMG2 .571 .619
IMG3 .635 .698
IMG4 .566 .587
IMG5 .560 .630
Extraction Method: Principal Axis
Factoring.
Total Variance Explained
Factor Initial Eigenvalues Extraction Sums of Squared Rotation
Loadings Sums of
Squared
Loadingsa
Total % of Cumulati Total % of Cumulati Total
Variance ve % Variance ve %
1 3.727 24.848 24.848 3.342 22.279 22.279 3.136
2 3.137 20.914 45.762 2.725 18.166 40.445 2.886
3 2.454 16.363 62.124 2.070 13.802 54.247 1.924
4 1.309 8.728 70.853 .996 6.637 60.884 1.820
5 .570 3.799 74.652
6 .538 3.589 78.241
7 .476 3.175 81.417
8 .461 3.070 84.487
9 .436 2.905 87.392
10 .387 2.580 89.972
11 .363 2.419 92.391
12 .352 2.348 94.738
59

13
14
15
.324
.238
.227
2.161
1.589
1.512
96.900
98.488
100.000
a. When factors are correlated, sums of squared loadings cannot be added to obtain a total
variance.
Factor Matrixa
Factor
1 2 3 4
IMG3 .698 -.435
IMG5 .671 -.407
IMG2 .652 -.431
IMG4 .613 -.448
IMG1 .599 -.464
REW2 .418 .601
REW3 .474 .595
REW4 .482 .579
REW5 .388 .575
REW1 .416 .548
SNO1 .698 .381
SNO2 .674 .331
SNO3 .666
KSI1 .381 .523 -.516
KSI3 .316 .471 -.621
a. Attempted to extract 4 factors. More than 25 iterations
required. (Convergence=.002). Extraction was terminated.
Pattern Matrixa
Factor
1 2 3 4
IMG3 .834
IMG2 .784
IMG5 .780
IMG4 .763
IMG1 .761
REW3 .781
REW4 .768
REW2 .746
REW5 .740
REW1 .708
SNO1 .823
SNO2 .766
SNO3 .681
KSI3 .885
KSI1 .805
60

a. Rotation converged in 5 iterations.
Structure Matrix
Factor
1 2 3 4
IMG3 .832
IMG2 .786
IMG5 .782
IMG4 .763
IMG1 .758
REW3 .782
REW4 .778
REW2 .747
REW5 .725
REW1 .711
SNO1 .802
SNO2 .758
SNO3 .719 .342
KSI3 .863
KSI1 .323 .832
Factor Correlation Matrix
Factor 1 2 3 4
1 1.000 .076 .007 .147
2 .076 1.000 .013 .197
3 .007 .013 1.000 .321
4 .147 .197 .321 1.000
61

Appendix 5. CFA results
Regression Weights: (Group number 1 - Default model)
IMG3 <--- IMG 1.000
IMG2 <--- IMG .915 .051 17.865 ***
IMG5 <--- IMG 1.119 .063 17.720 ***
IMG4 <--- IMG .935 .053 17.671 ***
IMG1 <--- IMG .975 .057 17.236 ***
REW3 <--- REW 1.000
REW4 <--- REW .997 .062 15.979 ***
REW2 <--- REW .879 .057 15.340 ***
REW5 <--- REW .850 .058 14.760 ***
REW1 <--- REW .795 .055 14.515 ***
SNO1 <--- SNO 1.000
SNO2 <--- SNO .965 .073 13.252 ***
SNO3 <--- SNO 1.027 .079 13.065 ***
KSI3 <--- KSI 1.000
KSI1 <--- KSI .944 .121 7.771 ***
Standardized Regression Weights: (Group number 1 - Default model)
Estimate
IMG3 <--- IMG .831
IMG2 <--- IMG .779
IMG5 <--- IMG .774
IMG4 <--- IMG .773
IMG1 <--- IMG .758
REW3 <--- REW .780
REW4 <--- REW .778
REW2 <--- REW .748
62

Estimate
REW5 <--- REW .722
REW1 <--- REW .711
SNO1 <--- SNO .783
SNO2 <--- SNO .759
SNO3 <--- SNO .732
KSI3 <--- KSI .728
KSI1 <--- KSI .978
Model Fit Summary
CMIN
Model NPAR CMIN DF P CMIN/DF
Default model 36 198.851 84 .000 2.367
Saturated model 120 .000 0
Independence model 15 2976.456 105 .000 28.347
RMR, GFI
Model RMR GFI AGFI PGFI
Default model .034 .945 .921 .661
Saturated model .000 1.000
Independence model .227 .450 .371 .394
Baseline Comparisons
Model
NFI RFI IFI TLI
CFI
Delta1 rho1 Delta2 rho2
Default model .933 .916 .960 .950 .960
Saturated model 1.000 1.000 1.000
Independence model .000 .000 .000 .000 .000
Parsimony-Adjusted Measures
Model PRATIO PNFI PCFI
Default model .800 .747 .768
Saturated model .000 .000 .000
63

Independence model 1.000 .000 .000
NCP
Model NCP LO 90 HI 90
Default model 114.851 77.449 159.963
Independence model 2871.456 2697.171 3053.066
FMIN
Model FMIN F0 LO 90 HI 90
Default model .465 .268 .181 .374
Saturated model .000 .000 .000 .000
Independence model 6.954 6.709 6.302 7.133
RMSEA
Model RMSEA LO 90 HI 90 PCLOSE
Default model .057 .046 .067 .140
AIC
Model AIC BCC BIC CAIC
Default model 270.851 273.647 417.064 453.064
Saturated model 240.000 249.320 727.375 847.375
ECVI
Model ECVI LO 90 HI 90 MECVI
Default model .633 .545 .738 .639
HOELTER
Model
HOELTER HOELTER
.05 .01
64

Model
HOELTER HOELTER
.05 .01
Default model 230 252
Independence model 19 21
65

Appendix 6. SEM results
Regression Weights: (iCU high - Default model)
KSI <--- IMG .172 .057 3.028 .002
KSI <--- REW .181 .068 2.646 .008
KSI <--- SNO .422 .086 4.898 ***
IMG3 <--- IMG 1.000
IMG2 <--- IMG .915 .051 17.865 ***
IMG5 <--- IMG 1.119 .063 17.720 ***
IMG4 <--- IMG .935 .053 17.671 ***
IMG1 <--- IMG .975 .057 17.236 ***
REW3 <--- REW 1.000
REW4 <--- REW .997 .062 15.979 ***
REW2 <--- REW .879 .057 15.340 ***
REW5 <--- REW .850 .058 14.760 ***
REW1 <--- REW .795 .055 14.515 ***
SNO1 <--- SNO 1.000
SNO2 <--- SNO .965 .073 13.252 ***
SNO3 <--- SNO 1.027 .079 13.065 ***
KSI3 <--- KSI 1.000
KSI1 <--- KSI .944 .121 7.771 ***
Standardized Regression Weights: (iCU high - Default model)
Estimate
KSI <--- IMG .162
KSI <--- REW .141
KSI <--- SNO .329
IMG3 <--- IMG .831
IMG2 <--- IMG .779
66

Estimate
IMG5 <--- IMG .774
IMG4 <--- IMG .773
IMG1 <--- IMG .758
REW3 <--- REW .780
REW4 <--- REW .778
REW2 <--- REW .748
REW5 <--- REW .722
REW1 <--- REW .711
SNO1 <--- SNO .783
SNO2 <--- SNO .759
SNO3 <--- SNO .732
KSI3 <--- KSI .728
KSI1 <--- KSI .978
Model Fit Summary
CMIN
Default model 36 198.851 84 .000 2.367
RMR, GFI
Default model .034 .945 .921 .661
Model
NFI RFI IFI TLI
CFI
Default model .933 .916 .960 .950 .960
67

Model
NFI RFI IFI TLI
CFI
NCP
Default model 114.851 77.449 159.963
FMIN
Default model .465 .268 .181 .374
RMSEA
Default model .057 .046 .067 .140
AIC
Default model 270.851 273.647 417.064 453.064
Saturated model 240.000 249.320 727.375 847.375
68

ECVI
Default model .633 .545 .738 .639
69

Appendix 7. Multi-group analysis results
Regression Weights: (high - Default model)
KSI <--- IMG .512 .065 7.906 ***
KSI <--- REW .219 .096 2.289 .022
KSI <--- SNO .446 .169 2.638 .008
IMG3 <--- IMG 1.000
IMG2 <--- IMG .794 .063 12.572 ***
IMG5 <--- IMG .853 .065 13.165 ***
IMG4 <--- IMG .932 .043 21.536 ***
IMG1 <--- IMG .752 .062 12.058 ***
REW3 <--- REW 1.000
REW4 <--- REW 1.060 .093 11.413 ***
REW2 <--- REW .934 .084 11.089 ***
REW5 <--- REW .828 .085 9.703 ***
70

REW1 <--- REW .773 .077 10.032 ***
SNO1 <--- SNO 1.000
SNO2 <--- SNO 1.286 .194 6.618 ***
SNO3 <--- SNO 1.149 .171 6.712 ***
KSI3 <--- KSI 1.000
KSI1 <--- KSI .602 .080 7.487 ***
Standardized Regression Weights: (high - Default model)
Estimate
KSI <--- IMG .557
KSI <--- REW .167
KSI <--- SNO .208
IMG3 <--- IMG .966
IMG2 <--- IMG .708
IMG5 <--- IMG .726
IMG4 <--- IMG .897
IMG1 <--- IMG .692
REW3 <--- REW .812
REW4 <--- REW .794
REW2 <--- REW .775
REW5 <--- REW .693
REW1 <--- REW .712
SNO1 <--- SNO .634
SNO2 <--- SNO .820
SNO3 <--- SNO .659
KSI3 <--- KSI .895
KSI1 <--- KSI .686
71

Model Fit Summary
CMIN
Default model 72 405.369 168 .000 2.413
RMR, GFI
Default model .048 .893 .848 .625
Model
NFI RFI IFI TLI
CFI
Default model .867 .833 .917 .895 .916
NCP
Default model 237.369 182.203 300.234
FMIN
72

Default model .949 .556 .427 .703
RMSEA
Default model .058 .050 .065 .041
AIC
Default model 549.369 561.316
Saturated model 480.000 519.825
Independence model 3099.937 3104.915
ECVI
Default model 1.287 1.157 1.434 1.315
Saturated model 1.124 1.124 1.124 1.217
HOELTER
Model
HOELTER HOELTER
.05 .01
Default model 211 226
Independence model 36 38
73

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