Journal of Service Science and Management, 2011, 4, 59-65
doi:10.4236/jssm.2011.41009 Published Online March 2011 (http://www.SciRP.org/journal/jssm)
59
A Factorial Validation of Knowledge-Sharing
Motivation Construct*
Qinxuan Gu, Yingting Gu
Antai School of Management, Shanghai Jiao Tong University, Shanghai, China.
Received November 14th, 2010; revised December 17th, 2010; accepted December 20th, 2010.
ABSTRACT
While there is increasingly strategic impo rtance in kno wledge, it is facing new challenges to manage kno wledge effec-
tively. The paper studies the motivationa l construct model for knowledge sharing from the perspective o f content theo-
ries and social motivation theories. The data collected by using the questionnaire survey from a variety of industries
was analyzed on the basis of interviews and pretest. The results of exploratory factor analysis (EFA) and confirm atory
factor analysis (CFA) showed the motivational construct model for knowledge sharing was comprised of existence mo-
tivation, relatedness motivation, growth motivation and norm motivation. The results extended the perspectives for
knowledge sharing mo tivation and provided theoretical evidences for facilitating knowledge sharing b ehavior.
Keywords: Knowledge Sharing, Motivation, Norm, Content Theory, Factor Analysis
1. Introduction
With the continuous development of knowledge econ-
omy and economy globalization, competitive advantages
and sustainable development of enterprises are increas-
ingly dependent on knowledge and knowledge manage-
ment. [1] As a key component of knowledge manage-
ment, knowledge sharing is a force which facilitates
knowledge exchange and transfer. It not only facilitates
knowledge creation but also avoid the creation overlap.
Therefore, knowledge sharing makes full use of spillover
effect of knowledge, and then enhances organizational
competitive advantages. In addition, knowledge is closely
related to innovation [2].
People who are the carriers of knowledge share and
create knowledge. On the other hand, knowledge sharing
is not a spontaneous process. Those who master knowl-
edge usually tend not to transfer and diffuse their know-
ledge. Considering protecting their own special status,
the employees who have unique skills do not easily share
their knowledge with others, especially when the knowl-
edge come so uneasily and is so beneficial to him.
Knowledge sharing has become a challenge for organiza-
tions in knowledge management (Grant, 1996) [3]. Evi-
dences showed that contrary to the importance of know-
ledge sharing, ways to facilitate knowledge sharing at
many organizations didn’t achieve the expected results.
Knowledge sharing, is becoming a difficult practice, af-
fects the effective knowledge management in enterprises
to a great extent [4-6]. Motivational factor is the key to
knowledge sharing behavior [8,9]. Much literature con-
tributed to individual knowledge sharing motivation from
the perspective of content theories of motivation, how-
ever few of them focus on the social motivation of know-
ledge sharing [10]. Considering the complexity and so-
ciability of knowledge sharing behavior, the purpose of
this study is to explore the construct dimensions of shar-
ing motivation systematically from the perspective of
combining content theories and social motivation theo-
ries. To identify the knowledge-sharing construct, firstly,
we conducted pre-research, then adopted two types of
analyses—Exploratory Factor Analysis (EFA) and Con-
firmatory Factor Analysis (CFA) to establish four-com-
ponent model of knowledge sharing. Moreover, theoreti-
cal contributions and practical implications of the find-
ings have been discussed.
2. Theoretical Background of Knowledge
Sharing Motivation
Motivation is the result of interaction of individuals and
the situation (Robbins, 1992). It’s the intention to make
*This article is based on research sponsored by National Natural Sci-
ence Foundation of China Grant 70771064.

A Factorial Validation of Knowledge-Sharing Motivation Construct 60
efforts for the organizational goal. But this kind of inten-
tion is subject to whether the efforts meet individuals’
needs [11]. Scott and Walker claimed that motivation
explains why people do something and why people be-
have, it’s the source of driving continuous efforts [7].
For a long time, theorists used to study motivation
theories from psychology, management. The typical ex-
amples are content theories of motivation. One of them is
Maslow’s Hierarchy of Needs Theory (physiological,
safety, love/belonging, esteem, and self-actualization)
[11], according to that, only when the lower needs are
met, the higher needs can be met. However, this hierar-
chy theory wasn’t fully support by subsequent empirical
researches. Another theory is ERG theory, presented by
Alderfer, which merged and developed Maslow’s Hier-
archy of Needs Theory. Existence is composed of phy-
siological needs and safety; Relatedness refers to the
desire of interaction and harmonious relationship with
others, composed of belonging and esteem. Growth re-
fers to the internal desire of development in career and
work, composed of self-actualization. Alderfer proposed
there is no hierarchy among these three kinds of needs. In
other words, to meet the higher needs doesn’t require that
lower needs have been met [12]. Similar to ERG theory,
another three-factor theory of needs was presented by
McClelland. The theory includes need for affiliation,
need for achievement and need for power, excluding
economic, physiological and safety needs and dividing
relationship needs and growth needs into need for affilia-
tion, need for achievement and need for power [13].
Herzberg proposed Motivator-Hygiene Theory, which
distinguishes hygiene factors that can eliminate dissatis-
faction and motivators that can lead to satisfaction. Hy-
giene factors are composed of salary, status, interper-
sonal relationship, company policy, safety and security,
etc. Motivators are composed of achievement, responsi-
bility, recognition, advance and growth. Hygiene factors
are the basic conditions to drive people to work. How-
ever, motivators are the factors to satisfy people’s growth
needs. These content theories of motivation can be ap-
plied to the research of motivation of knowledge sharing.
In fact, these theories have been enriched and developed
in the practices of manage knowledge workers’ behavior
[14].
Stott and Walker (1995) argued that according to
Maslow’s theory, knowledge worker do not tend to share
knowledge for money or improving the relations with
colleagues. Their motivations of knowledge sharing are
to satisfy the three higher levels of needs: belonging,
esteem and self-actualization [7]. In another word, they
argued the motivations of knowledge sharing are not
from the external or visible factors, but from the recep-
tive or internal factors. Because belonging and esteem
are reflected by relations and self-actualization is re-
flected by self-growth and development, the three kinds
of motivations involve relationship and self-growth. Us-
ing Motivator-Hygiene Theory, Hendricks (1999) found
that for knowledge workers at IT industry, motivations of
knowledge sharing include achievement, responsibility,
recognition and growth, instead of hygiene factors such
as salary and status [15]. Hall (2001) found that invisible
rewards such as enhancing reputation and satisfaction are
the driving factors of knowledge sharing [8]. In addition,
Hall (2001), Bartol & Srivastava (2002) suggested that
effective reward systems not only provide staff with visi-
ble reward, e.g. salary, stock, bonus, etc., but also en-
courages employees to share knowledge with other em-
ployees [8,9]. Prior research showed that visible eco-
nomic rewards can also encourage knowledge sharing.
Davenport & Prusak (1998) pointed out knowledge
sharing means a market where knowledge holders share
their knowledge for rewards such as reciprocity, reputa-
tion, altruism [16]. Reciprocity refers to the probability
by which the seller of knowledge expect the buyer to
give him a hand when necessary. The higher the prob-
ability, the more time and money the seller will spend on
knowledge sharing. Although reputation is invisible, it
brings visible benefits. Having a reputation of knowledge
sharing is helpful to reciprocal behavior. And the reputa-
tion as a knowledge seller makes a person a more effi-
cient knowledge buyer or enhances the possibility of
promotion. Altruists have no expectations on repayment,
but they hope that their knowledge can be diffused.
When the knowledge holders don’t believe that the
knowledge sharing get the expected results, the sharing
will be hindered. Therefore, the motivations of reciproc-
ity, reputation and altruism are related to the interper-
sonal relationship [18].
The existing research stressed on content theories of
motivation, that is to say they focused on rewards and
incentives, ranging from visible rewards to invisible re-
wards, from external return to internal feeling, involving
economic return (the direct or indirect), relationship and
achievement or growth, etc.
However, some researchers argued that content theo-
ries of motivation explain how the knowledge exchange
is encouraged, but the theories fail adequately to explain
the knowledge sharing [10]. Knowledge sharing includes
knowledge exchange and transfer, meaning receiving
others’ knowledge while transferring their knowledge.
Moorman & Miner (1998) suggested knowledge sharing
is collective belief and code of conduct about learning
among individuals or between departments in organiza-
tions [17]. Knowledge sharing, fundamentally, is a social
process [9,10]. Knowledge lies in different levels of or-
ganization, including individual level, group level and

A Factorial Validation of Knowledge-Sharing Motivation Construct 61
organizational level. Among these levels, knowledge
sharing among individuals is the key to shaping organ-
izational knowledge. The social factors that facilitate
knowledge provider and receiver are necessary to streng-
then sharing motivation. Social motivation theory origi-
nated from the research in peer influences [10]. Norms
that come from interpersonal interaction are group agree-
ments and social motivation mechanisms. The norms in-
fluence individual motivations indirectly by acknowledge
the existing influencing mechanism of motivation [10,20].
Norms represent the consistency of cognition and judg-
ment people have towards behavior in a social system
[20]. Feldman suggested norms are used to restrain im-
portant behaviors in organizations. When people feel
some special behavior can bring them more outcomes,
they will put forward and define the norms [20]. There-
fore, norms make people’s behaviors meet the group’s or
organization’s expectations. Studies showed that norms
of knowledge sharing are playing an important role in
encouraging knowledge providers to share their knowl-
edge [20,23].
Thus, we found that among the prior research, more
studies on the knowledge sharing motivation from the
traditional content theories, whereas fewer studies from
social motivation, less study from the combination of two
different perspectives. Knowledge sharing among indi-
viduals is a complex process, is driving by different mo-
tivations. This present study combines the content theo-
ries and social motivation theories to discuss the dimen-
sions of knowledge sharing motivation.
3. Development of Knowledge-Sharing
Motivation Construct
3.1. Pre-Research
Pre-research explored the construct model of knowledge
sharing motivation with the original questionnaire by
following three steps.
Step 1: semi-structured interview. The process was, 1)
by analyzing existing literatures, determined the major
interview questions on aspects of direct economic reward
and indirect economic reward, relationship, growth and
norm, and design the open questions; 2) discussed with
the interviewees about the types of behavior motivations,
the definition of knowledge sharing, motivations of
knowledge sharing behavior and the main features; 3)
asked the interviewees in details according to the de-
signed questions, and ask the interviewees to illustrate
and give more supplementary questions. Eight persons
were interviewed, including three HR managers, two
R&D professionals, one technician and two project ma-
nagers from six enterprises, three foreign-owned enter-
prises, two state-owned enterprises and one private en-
terprise. The interview time was ranged from 45 minutes
to 60 minutes for per person.
Step 2: code of interview transcripts and design of
questionnaire. The process was, 1) analyzing the inter-
view transcripts and extracting the content that influence
the knowledge sharing behavior; 2) classifying the con-
tent extracted into the four aspects of semi--structured
interview; 3) conducting statistics & analysis of the fre-
quency of all kinds of the content, discussing the over-
lapped, 15 items on knowledge sharing motivations con-
cluded 4) three professors and two senior managers were
invited to appraise and amend the reasonableness and the
expression of the 15 items, and 1 ambiguous item deleted
and 14 items kept which consist of the initiative ques-
tionnaire.
Step 3: pre-test and determination of the questionnaire.
pretest using the samples from MBA students at one
university in Shanghai. 53 questionnaires collected were
valid. Conducting exploratory factor analysis and item
analysis, one item cross loading was deleted, 13 items
were retained for next survey.
3.2. Data Collection and Sample Description
Using the pre-tested questionnaire to conduct large-scale
survey for exploring and test the construct of knowledge
sharing. The variables included contextual variables,
independent variable and dependent variables. Contex-
tual variables referred to personal information such as
gender, age, education. Independent variable was know-
ledge sharing motivation. Dependent variables were know-
ledge sharing behavior. Independent variable and de-
pendent variables used 5-point Likert scales. The re-
spondents were the knowledge employees graduated
from college or above, from over 200 enterprises in
Shanghai, Jiangsu, Anhui, Zhejiang, Fujian, Guangdong,
and Shenzhen. Of the 600 questionnaires distributed, 451
were returned, and 419 were valid, the valid rate was
69.8%. Among the 419 valid questionnaires, 62.8% male,
35.7% female, 1.5% NA; 3.0% between the age of 21-25,
27.6% between 26-30, 32.5% between 31-35, 29.1%
between 36-45, 7.9% over 46; 11.3% graduated from
college, 42.1% from university, 33.7% with master de-
gree, 12.3% with PhD degree, 0.5% NA.
Due to the collection of all measures from the same
source, there might be common method variance influ-
encing the research conclusions. Thus, we used the Har-
man one-factor test to examine the potential problem of
common method variance. Significant common method
variance would result if one general factor accounts for
the majority of variance in the variables [21]. A principle
factor analysis on the measurement items of this study
yielded six factors with eigenvalues greater than one that
accounts for 68.126% of the total variance, and the first

A Factorial Validation of Knowledge-Sharing Motivation Construct 62
factor accounted for 17.497% for the variance. Since a
single factor does not emerge and one general factor does
not account for most of the variance, common method
bias is unlikely to be a serious problem in the data [21].
3.3. The Construct of Knowledge Sharing
Motivation
To explore and construct knowledge sharing motivations,
we used SPSS15.0 to analyze the data and principal
components factor analysis with varimax rotation. This
samples collected had a larger scale (N = 419). in terms
of 13 items from previous research according to 1:10
ratio. We divided the samples into two groups, one used
for exploratory factor analysis (N = 210), the other used
for confirmatory factor analysis (N = 209), in order to get
results with cross validation.
The exploratory factor analysis yielded four factors, as
shown in Table 1. The factors with eigenvalues greater
than one that accounts for 69.254% of the total variance
and each factor accounted from 14.084% to 19.409 for
the variance. The load coefficient of each factor was
greater than 0.6. According to the content theories and
social norm theories, we explained and defined the four
factors as follows:
The first factor contains three items: salary, bonus and
job security. It reflects knowledge sharing player’s needs
for physiological and safety corresponds to the existence
needs of Alderfer’s ERG theory [12]. Thus, we defined it
as existence motivation.
The second factor contains four items: group mem-
bership, recognition of expertise, professionalism and
reputation & esteem. It reflects that knowledge sharing
player’s expectations to maintain his or her membership
and positive interpersonal or social relationship. Thus,
we defined it as relationship motivation.
The third factor contains three items: growth and de-
velopment, achievement and good self-feeling. It reflects
knowledge sharing player’s needs for feeling and growth.
Thus, we defined it as growth motivation.
The fourth factor contains three items: responsibility to
knowledge sharing as an organizational member; know-
ledge as a public good shared by people; knowledge be-
longs to organizations rather than individuals. It reflects
that knowledge sharing player’s desires to engage agree-
ments of the interacted group or organization. Thus, we
defined it as norm motivation.
By exploratory factor analysis, we found that the mo-
tivations to share knowledge are composed of four fac-
tors consisting of existence, relationship, growth and
norm.
Table 1. Results of exploratory factor analysis (N = 210).
Factor loading
Item
1 2 3 4
1. Salary/ bonus to be increased 0.835 0.096 −0.077 −0.046
2. Reword to be received 0.764 0.27 0.208 −0.002
3.Job security to be enhanced 0.615 0.237 0.035 0.344
4.Group Membership To Be Held 0.014 0.65 0.061 0.357
5. Expertise to be recognized 0.143 0.783 0.187 0.106
6. Status as expert to be got 0.26 0.799 0.124 0.022
7. Reputation and esteem 0.252 0.766 0.219 0.013
8.Learning more knowledge and growth & development 0.105 0.141 0.721 0.169
9. Achievement 0.034 0.178 0.856 0.176
10. Good self-feeling from knowledge sharing −0.014 0.153 0.819 0.17
11. Responsibility to share 0.049 0.153 0.366
0.721
12. Knowledge as a public goods, shared by people 0.065 0.067 0.269 0.837
13. Knowledge belonged to organizations rather than individuals0.039 0.072 0.045 0.892
Eigenvalues 1.831 2.523 2.285 2.364
The rate of variance explained % 14.084 19.409 17.575 18.186

A Factorial Validation of Knowledge-Sharing Motivation Construct 63
3.4. Confirmation of Knowledge-Sharing
Motivation Construct
On the basis of exploratory factor analysis, we used
AMOS 7.0 to conduct confirmatory factor analysis for
the construct of knowledge sharing motivation. To con-
firm whether the four-factor model is the optimization
model, according to the literature review above, we pro-
posed two candidate models including a two-component
model and a three-component model. Then, we compared
the three models to decide which one is the optimization
model. A two-component model was proposed according
to content theories of motivation and social motivation
theories. Existence, relationship and growth, each of
them is part of content theories, are integrated into one
component, norm is the other component which is in-
volved in social influence mechanisms. A three-compo-
nent model is to put the content motivations into two
categories: existence and relationship are involved in
external motivations and integrated into one component;
whereas growth is involved in internal motivation and
belongs to another component.
We used the other half of data to conduct confirmatory
factor analysis by AMOS 7.0, and got fit indices of the
three models, as shown in Tab le 2. Expectation value of
X2/df is 1, the more close to 1, the fitter the model is. If
X2/df < 3, the whole model is good [22]. If RMSEA <
0.05, the fitness is good; and if RMSEA < 0.08, the fit-
ness is acceptable [23]. There are other fit indices, such
as NFI, NNFI, GFI, CFI, IFI, the values between 0 and 1,
the bigger the value, the good the fitness. The usual re-
quirement is that these indices are bigger than 0.90.
Compared with these fitness requirements, the 4-com-
ponent model was the optimization model. The fit indices
showed the construct model fits the observed data very
well. Furthermore, we tested the reliability of four com-
ponents, and found the Cronbach α are 0.661, 0.804,
0.794 and 0.836, respectively. Except the reliability of
existence was a little low, the other components’ Cron-
bach α were bigger than 0.70. The whole Cronbach α is
0.831, indicating that the reliability of the four compo-
nents was good.
Finally, we used second-order CFA to test convergent
validity of dimensions of knowledge sharing motivation,
taking knowledge sharing motivation as second-order
factor, four dimensions as first-order factor. The conclu-
sion showed that the fitness is good (2

= 1.766, df = 1,
2

/df= 1.766, RMSEA = 0 .044, GFI = 0.998, CFI =
0.997, IFI = 0.997, NFI = 0.993, NNFI = 0.982). And the
factor loadings of second-order factors (relationship,
growth and norm) were over 0.50 with 0.001 in signifi-
cance. The factor loading of existence was a little low,
0.21, with 0.001 in significance. The model showed that
there is a common latent variable behind the four dimen-
sions, which is knowledge sharing motivation variable.
4. Discussion and Implications
4.1. Discussion
This paper studied conceptualization of knowledge shar-
ing motivation by using samples of knowledge workers
from the perspectives of combining content theories of
motivation and social motivation theories. This present
study suggested a four-component model of knowledge
sharing motivation which consists of existence, relation-
ship, growth and norm. This result showed that knowl-
edge sharing is a complex social process. Knowledge
workers have mastered knowledge, skills and expertise,
thus, they become important knowledge sharing players.
As most people, they may care about the economic re-
ward, job security or stability. However, to some extent,
knowledge workers are different from most people, they
pay more attention to the internal gratification and
growth from knowledge sharing, focusing on the realiza-
tion of self-value and desire for recognitions from the
group, organization and others. In addition, knowledge
workers are typically members of a society, an organiza-
tion or a group, so, their knowledge sharing behavior is
under some social situation. If an organization or group
has shaped knowledge sharing norms, the norms will be
a driving force to facilitate knowledge sharing among
individuals in organizations or groups.
4.2. Theoretical Contributions and Practical
Implications
4.2.1. Theoretical Contributions
First, this present study enlarged the view of knowledge
sharing motivation through combination of content theo-
ries of motivations and social motivation theories. Tradi-
tional content theories of motivations tend to encourage
Table 2. Resulis of confirmatory factor analysis (N = 209).
Model 2

df 2

/df RMSEA GFI CFI IFI NFI NNFI
2-component Model 662.079 64 10.345 0.152 0.778 0.739 0.741 0.721 0.682
3-component Model 332.454 62 5.362 0.104 0.89 0.882 0.883 0.86 0.851
4-component Model 98.43 46 2.139 0.053 0.965 0.977 0.977 0.958 0.961

A Factorial Validation of Knowledge-Sharing Motivation Construct 64
knowledge exchange behavior, but they fail adequately
to explain knowledge sharing behavior, that is to say
while receiving others’ knowledge, people transfer their
knowledge to others. Social motivation theories make up
the deficiency of content theories in knowledge sharing.
Knowledge sharing is complex process in which indi-
viduals behave under specific social situations, with in-
terpersonal relationship and interaction. Social motiva-
tion theory argues that social influence mechanisms such
as norms can influence behaviors by serving to intensify
or strengthen to motivational tendencies of structural
features such as incentives [10]. Specifically, norms that
support knowledge sharing may accentuate the influence.
In other words, the norms which come from interpersonal
interaction significantly influence or strengthen knowl-
edge sharing behavior. The four-component construct of
knowledge sharing motivation concluded in basis of the
combination of content theories and social motivation
theories enriched the theoretical views about individual
motivation to share knowledge. Our findings suggested
knowledge sharing is a complex process involving in
individual behaviors under the particular social context.
4.2.2. Prac ti ca l Implications
The study provided a few practical implications. First,
when facilitating employees to share knowledge, manag-
ers should pay attention to the individual’s motivation
factors, especially to relationship and growth, recognition,
expert status and esteem, and encourage employees to
learn from each other in an organization, to respect each
other; to grow and develop, to realize their values. Man-
agers also should highlight social motivation factors by
setting up knowledge sharing norms in an organization
and having individuals aware of the organizational norms.
The cognitions of knowledge as a public good and be-
longings to organizations should be strengthen, and make
knowledge workers recognize responsibility to share
knowledge with others.
4.3. Limitations
There were several limitations in this study that should
be taken into account in the further study. First, the study
of social motivation was limited to norm motivation,
didn’t involve other types of social motivations, like in-
terpersonal trust motivation. Further research should be
expanded on shared social motivations. Second, the data
was collected from the coastal areas in China, which
didn’t cover the central and western regions in China.
The geographical limitation may affect the ecological
validity
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