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University of Nebraska - Lincoln
DigitalCommons@University of Nebraska - Lincoln
Library Philosophy and Practice (e-journal) Libraries at University of Nebraska-Lincoln
1-1-2013
Knowledge-sharing behavior in dairy sector of
Pakistan
Syed Rahmatullah Shah
University of the Punjab, rahmatgee@yahoo.com
Khalid Mahmood Dr.
University of the Punjab, Lahore, Pakistan, khalid.dlis@pu.edu.pk
Follow this and additional works at: hp://digitalcommons.unl.edu/libphilprac
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Shah, Syed Rahmatullah and Mahmood, Khalid Dr., "Knowledge-sharing behavior in dairy sector of Pakistan" (2013). Library
Philosophy and Practice (e-journal). Paper 917.
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1
Knowledge
KnowledgeKnowledge
Knowledge-
--
-sharing behavior in dairy sector of Pakistan
sharing behavior in dairy sector of Pakistansharing behavior in dairy sector of Pakistan
sharing behavior in dairy sector of Pakistan
Syed Rahmatullah Shah
Syed Rahmatullah ShahSyed Rahmatullah Shah
Syed Rahmatullah Shah
Librarian, Sohail Iftikhar Research Institute, Department of Special Education, University of the
Punjab, Lahore, Pakistan
rahmatgee@yahoo.com
Khalid Mahmood
Khalid MahmoodKhalid Mahmood
Khalid Mahmood
Professor, Library and Information Science, University of the Punjab, Lahore, Pakistan
khalid.dlis@pu.edu.pk
Abstract
AbstractAbstract
Abstract
This study is about knowledge sharing behavior in dairy sector. Two-hundred middle
managers (with professional qualifications) from five industrial units in Pakistan were selected
for study. Fifty-seven managers participated in the study (29 percent of the sample). Research
model and hypotheses were based on behavioral theories, i.e., TRA, TPB, and TAM. Data were
collected through a questionnaire using Likert scale. Spearman’s and Pearson’s correlation
coefficients and structural equation model among different variables tested hypotheses of the
research modal. The study proved that attitude, intention, and behavior had accepted mutual
positive direct effects for knowledge sharing in dairy sector. Conversely, subjective norms and
perceived behavioral control had non-significant values but weak positive direct effects toward
knowledge sharing. Findings of this study are useful for better understanding about behavioral
influences for knowledge sharing. Furthermore, it is of practical use for the organizational
administration involved in knowledge management initiatives in geographical circumstances of
Pakistan.
Introduction
IntroductionIntroduction
Introduction
Knowledge has become an accepted resource for organizational sustainability in present
age (Robinson, 2012). That’s why; knowledge management has been prioritized in all sectors.
Apex management considers knowledge management as a tool (Martensson, 2000), initiative /
system (Wong & Aspinwall, 2006), or as a business strategy (Drew, 1999) for organizational
goals of improved performance (Fugate, Stank, & Mentzer, 2009), competitive advantage
(Gupta & McDaniel, 2002), and innovation (Kamath, Rodrigues, & Desi, 2011). Existence of
embodied and embedded knowledge is an accepted reality but its flow, in the form of knowledge
sharing, changes the overall context (Decarolis & Deeds, 1999). Therefore, knowledge sharing
has been identified as the major segment of knowledge management. In broader perspective,
information and communication technologies (ICTs) facilitate knowledge sharing (Fei, 2011).
Despite all ICTs, individuals are chief actors for sharing knowledge and information (Elmholdt,
2004). It is one’s behavior that counts for knowledge sharing in an organization (Lam &
Lambermont-Ford, 2010).
Many researchers have gone through the various aspects of k-sharing and human
behavior. Hsu et al. (2007) proposed their social cognitive theory based model in their
quantitative study of 39 societies comprising nine types of virtual communities in different
sectors. Bock and Kim (2002) discussed organizational reward systems, Michailova and
Hutchings (2006) elaborated cultural influences, Hsu and Lin (2008), and Quigley et al. (2007)
explained motivation, and Chow and Chan (2008) illustrated trust, with special reference to
knowledge sharing behavior. Similarly, knowledge sharing in different sectors was focal point in
recent researches. Lawson et al. (2009) discussed industrial sector, Hooff and Huysman (2009)
2
concentrated on services sector, Rowley et al. (2012) brightened government sector, and many
others focused on knowledge sharing in some specific sector organization.
Some researchers discussed knowledge sharing behavior in Pakistan from different
angles (Ellahi & Mushtaq, 2011; Lodhi & Ahmad, 2010; Rehman, et al., 2011). Just a few
researches, in general, encircled knowledge sharing in industrial or corporate sector of Pakistan
(Bano, Rehman, & Khan, 2010). There is hardly any research on knowledge sharing behavior in
dairy industry, in general, and dairy sector of Pakistan, in particular.
Problem statement
Problem statementProblem statement
Problem statement
Main center of attention behind this research work is knowledge sharing behavior with
special reference to dairy sector in Pakistan. This study highlights and clarifies the role of
behavioral aspect in knowledge sharing in organizational settings of Pakistan. Similarly, this
research has examined knowledge sharing behavior in the light of widely accepted
psychological concepts explained by theory of reasoned action (TRA), theory of planned
behavior (TPB), and technology acceptance model (TAM). Additionally, it presents a scenario
that boosts interest and awareness of middle management for understanding and encouraging
knowledge sharing behavior in their organization. Moreover, this research contributes for the
promotion of knowledge management research culture in Pakistan.
Literature
Literature Literature
Literature r
rr
review
evieweview
eview
Knowledge is well accepted resource and asset of routine life in present age. Ownership
of knowledge is a complex phenomenon, either it lies with individuals who possess knowledge
or is from the belongings of organization that hires the knowledge based individuals. Wide
spread knowledge management literature promotes the idea that frequent access, control, and
ownership of knowledge goes to conventional management rather than individuals (Elmholdt,
2004). Some studies support the view that individuals are actual owners of all knowledge they
possess (Bock et al., 2005). Bock (2002) and Goh (2002) illustrate that organizations do heavy
investments on employees for their motivation for knowledge sharing and announce attractive
incentives on it. On the other side, Dalkir (2005) emphasizes that organizations reward
individuals for what they know and not for what they share in organizational settings.
Research reveals that knowledge is the outcome of cognition and learning (Csibra &
Gergely, 2006). Literature on distributed cognition makes it clear that knowledge and
competence reside in person and its environment, not only in person (Cools, Broeck, &
Bouckenooghe, 2009). In addition, cognition, learning, and knowledge are distributed in
interpersonal relations and are the upshot of social practice (Przemyslaw & Magdalena, 2009).
Thus knowledge is an activity rather than entity, object, or a thing (Polanyi, 1961). So, as an
activity, knowledge is context bound and is seen as constructed in individual-environment
interaction. In the words of Elmholdt (2004), “it becomes a contradiction in terms to search for a
location of knowledge in employees’ heads or in companies’ databases - knowledge is in
practice.” Despite all controversies, researchers have unanimous opinion that usability and
importance of knowledge sharing is a reality in routine business (Alavi & Liedner, 2001).
Knowledge sharing is the most important segment and a hectic challenge of knowledge
management. There is no single accepted definition for knowledge sharing (Earl & Scott, 1999).
Anyhow, some researchers attempted to define knowledge sharing for better understanding.
Hansen (1999) declares knowledge sharing to be the provision or receipt of task, information,
know-how, and a feedback regarding a product or procedure. Similarly, according to the
definition by Lee (2001), knowledge sharing is a “set of activities of transferring or disseminating
knowledge from one person, group or organization to another.” So, knowledge sharing is
something more than communication, and information distribution. In the words of Lasswell
(1948), communication is just to answer who? says what? in which channel? to whom? with
what effect? Similarly, information distribution is just “distribution of information” (Schement &
Curtis, 1995). Cognitive factor lacks in both notions of communication and information
3
distribution. Conversely, in knowledge sharing, there is involvement of learning something from
someone. In other words the process of re-enactment takes place in knowledge sharing
(Hendriks, 1999). As knowledge sharing involves cognition, so, human behavior counts as the
most active contributor for knowledge sharing. Many attempts, models, and designs have been
introduced from different horizons, to share knowledge capital, at both individual and
organizational level. But the research, so far, could not finalize any general formula or model
that could be adopted by all organizations for sharing their knowledge capital (Riege, 2005).
Model and
Model and Model and
Model and h
hh
hypotheses
ypothesesypotheses
ypotheses
The Theory of Reasoned Action (TRA) developed and further extended by Martin
Fishbein and Icek Ajzen (1975, 1980), and the Theory of Planned Behavior (TPB) developed by
Icek Ajzen (1985) are widely accepted theories that deeply explains attitude and behavior in
social psychology research. Another extension of TRA is in the form of Technology Acceptance
Model (TAM), introduced by Davis (1989) and Bagozzi and Warshaw (1992).
In TRA, major constructs for human action are behavioral intentions, attitudes, and
subjective norms in such a relation that behavioral intentions are the outcome of one’s attitude
toward behavior and subjective norms (Fishbein & Ajzen, 1975, 1980). While in TPB, the
phenomenon of Perceived Behavioral Control (PBC) was introduced to cover non-volitional
behaviors, as TRA covered only volitional behaviors. It indicated that behavioral intentions were
the sum of attitude toward behavior, subjective norm, and perceived behavior control (Ajzen,
1985). The concept of PBC got its roots from Bandura’s self-efficacy theory that was evolved
from social cognitive theory (Bandura, 1977, 1980). PBC gives a touch of human feelings to the
TRA. Summarizing above, TPB promotes the view that individuals who have better behavioral
attitude, have supporting subjective norms, and have greater perceived behavioral control, they
have strong behavioral intentions for the subject in question. Obviously, individuals with strong
behavioral intentions have better attitude toward the subject under investigation.
Furthermore, Bandura (1977) described that self-efficacy was positively related to human
behavior and Ajzen (2002) proclaimed that self-efficacy and perceived behavioral control, were
the same in his theory of planned behavior. Thus, behavioral intentions and perceived
behavioral control both have positive correlation with human behavior in theory of planned
behavior.
Both TRA and TAM have same behavioral descriptions, “if somebody has intentions to
do anything then he can do that without any limitations.” But contrary to TRA, TAM presents
technology perspective with measures of ‘usefulness’ and ‘ease of use’. TAM describes a
positive relation between technology acceptance and human behavior. On the basis of above
assumptions, following research hypotheses were inked for this study:
H1: A person, who has better attitude toward knowledge sharing, has positive behavioral
intentions for knowledge sharing.
H2: A person having supporting subjective norms for knowledge sharing has good
behavioral intentions to share knowledge.
H3: Someone, with good perceived behavioral control (PBC) for knowledge sharing, has
strong behavioral intentions to share knowledge
H4: An individual, with strong behavioral intentions to share knowledge, has better
knowledge sharing behavior.
H5: Somebody, having strong perceived behavioral control (PBC) over sharing
knowledge, has better knowledge sharing behavior.
H6: Anyone, with improved information technology acceptance for sharing knowledge,
has enhanced knowledge sharing behavior.
Method
MethodMethod
Method
The research instrument in this study was a questionnaire. This questionnaire was
already used by Chatzoglou and Vraimaki (2009) in their research on knowledge-sharing
4
behavior of bank employees in Greece. They also ensured its validity and reliability. The
questionnaire was reshaped for present study. In a new format, the questionnaire comprised of
29 statements covering six different aspect regarding knowledge sharing, i.e., behavior, level of
information technology usage, intention to share knowledge, attitude toward knowledge sharing,
subjective norms about knowledge sharing, and perceived behavioral control to knowledge
sharing. There were four to six structured questions under each heading with a 5-point Likert
scale. The participants were asked to mark their response from 1 to 5 against each statement, 1
= Not at all and 5 = Very high level. Some demographic details were also included in the
questionnaire at the end consisting on gender, age, experience, and designation with
organizational affiliations.
Population of this study was comprised of five independent industrial units producing
dairy products. Each industrial unit had one or more branches but the common factor under
consideration was – they should have strength of at least 200 professional middle managers.
Professional staff means those employees who had professional qualifications in their
respective discipline like Masters in Business Administration (MBA), Masters in Commerce (M.
Com), a university degree in computer science, and graduates of different disciplines of
engineering. Forty respondents were selected in each industrial unit of the said population using
random sampling technique. Two-hundred questionnaires were administered by ‘in person drop-
off method.’ Just a few respondents filled questionnaire and returned it back at the spot.
Remaining asked to fill the questionnaire on a later time or demanded soft copy to send them by
e-mail. Some responses were collected on first and second follow up round on weekly basis.
Some respondents filled questionnaires after telephonic reminders. A very small number of
responses received via e-mail. Fifty seven usable questionnaires received that were 29 percent
of total sample.
Results and discussion
Results and discussionResults and discussion
Results and discussion
Descriptive statistics for demographic characteristics revealed that majority of
respondents in gender were male (51, 90%), of age between 36 and 45 years (28, 49%), with
experience between six and 10 years (26, 46%) (table 1).
Table 1. Demographic characteristics of respondents
Measure
Item
Frequency
Percent
Gender
Male
51
90
Female
6
1
1
Age
Up
to 25
years
9
1
6
2
6
-
35
years
16
28
3
6
-
45
years
28
49
4
6
years
and above
4
7
Experience
Up to 5 years
14
2
5
6
-
10 years
26
46
1
1
-
15 years
7
12
1
6
-
20 years
8
14
2
1
years
and above
2
4
Normality of data was checked. Shapiro-Wilk test results showed significance values for
behavior (0.027), intention (0.021), attitude (0.004), subjective norms (0.008), and perceived
behavior control (0.012) for knowledge sharing in dairy sector. These variables are not
significant (
p
< .05). It supported the view that non-parametric tests or their conditions better fit
the data of these variables. Conversely, data for level of IT usage (0.050) is normally distributed
that satisfied the condition for parametric analysis.
5
Table 2 showed the Spearman’s correlation coefficients values for intention to share
knowledge and perceived behavioral control toward behavior, attitude toward intention and
subjective norms for knowledge sharing in dairy sector. Similarly, parametric test of correlation –
Pearson’s coefficient (.266) was found significant between behavior and level of IT usage (.046)
at p < .05.
Table 2. Spearman’s correlation coefficients for variables of research model
Behavior
Intention
Attitude
Subjective
Behavior
Intention to share knowledge
.
369
**
Attitude toward k
-
sharing
.
252
.
268
*
Subjective norms about k
-
sharing
.
171
.1
76
.
313
*
PBC towards k
-
sharing
.
285
*
.
056
.
167
.
0
60
*Values are significant at p < .05
* *Values are significant at p < .01
The research model was tested by using Structural Equation Modeling (SEM) software
package to examine the relationships between latent variables. Figure 1 presents the structural
model along with path coefficients and factor loading, produced by LISREL 9.10.
Figure 1. Structural Model of Research along with path coefficients and factor loading
On the basis of above analysis, hypotheses testing results were concluded in the form of
table 3.
H1 was accepted as it proposed that a person, who has better attitude toward knowledge
sharing, has positive behavioral intentions for knowledge sharing. Research results proved a
strong positive direct effect of attitude toward knowledge sharing (path coefficient = 0.59) and a
statistical significant value 0.04 in their relationship at
p
< .05. This result is similar to the
descriptions of Ajzen’s TPB and TRA. This is also consistent with other recent researches (Hooft
& Jong, 2009; Pradeep, 2012).
H2 was rejected as it emphasized that a person having supporting subjective norms for
knowledge sharing has good behavioral intentions to share knowledge. It did not happen in all
circumstances. Research outcome revealed that subjective norms had moderate positive direct
effect (path coefficient = 0.32) toward intentions to share knowledge with an insignificant value
6
at
p
< .05 level. Therefore, subjective norms were not always the contributor for setting
behavioral intentions. These results were contrary to the well established behavioral theories –
TPB and TRA. In a recent research, conducted by Pradeep (2012), subjective norms had
insignificant influences toward behavioral intentions. These insignificant values were, most
probably, due to small sample size.
Table 3. Hypothesis testing results
Hypothesis
Path
Path
coefficient
Remarks
H1
Attitude
Intention
0.59
Strong positive direct effect
that is
significant
H2
Subjective norms
Intentions
0.32
Moderate positive direct effect
that is insignificant
H3
PBC
Intention
0.17
Weak positive direct effect
that is
insignificance
H4
Intention
Behavior
0.19
Weak positive direct effect
that is
significant
H5
P
BC
Behavior
0.02
Weak positive direct effect
significant
H6
Level of IT
u
sage
Behavior
0.34
Moderate positive direct effect
that is significant
H3 was rejected as it was not always the case; it supported the view that someone, with
good perceived behavioral control (PBC) for knowledge sharing, has strong behavioral
intentions to share knowledge. Perceived behavioral control had weak positive direct effect
(path coefficient = 0.02) and insignificant relational value at 0.05 level toward intention to share
knowledge. These results were contrary to the descriptions by Ajzen and Fishbein (1980), and
Ajzen (1985) about PBC and intention relationship, but were identical to the research conducted
by Hooft and Jong (2009). They also calculated that PBC was positively correlated with intention
with a small and non-significant variance in intention. They also described both sample size and
sample type as the reason of these results.
H4 was accepted. It stated that individual, with strong behavioral intentions to share
knowledge, has better attitude toward knowledge sharing. The study results presented weak
positive direct effect (path coefficient = 0.19) but with significant relational value 0.005 at level
0.05 for behavioral intentions for knowledge sharing to actual behavior of knowledge sharing.
Scholz et al. (2012) research study supported this research by illustrating that intentions were
the most important predictor of behavior in line with the assumptions of the planned behavior.
H5 was accepted. It recommended that somebody, having strong perceived behavioral
control (PBC) over sharing knowledge, has better knowledge sharing behavior. Perceived
behavioral control had weak positive direct effect (path coefficient = 0.02) but a significant
relational value of 0.03 (
p
< .05) for personal behavior toward knowledge sharing. These results
strengthened the views of Ajzen (1991) regarding perceived behavioral control contributions for
behavioral intentions and for ultimate behavioral achievements. It was similar to the Chatzoglou
and Vraimaki’s (2009) findings.
H6 was also accepted. It proposed that anyone, with improved information technology
acceptance for sharing knowledge, has enhanced knowledge sharing behavior. The results
supported the hypothesis as a moderate positive direct effect of level of information technology
usage (path coefficient = 0.34) toward personal behavior for knowledge sharing with a
significant value (0.567) at .01 level. Ajzen and Fishbein (1980) considered the effects of
external variables on behavior at the time of behavioral intention. Yaobin, Tao and Bin (2009)
7
supported this notion in their research study that level of IT usage contributes for individual’s
behavior to perform specific task.
Conclusion
ConclusionConclusion
Conclusion
Research model for this study was based on behavioral theories preferably the theory of
planned behavior. This model has limitations of sample in terms of size and type for its accuracy
and validity in research. Further, it discussed behavior internally in the form of individualistic
behavior. External factors like culture, overall environment, and demographic aspects affecting
on human behavior have been put aside. Research results in a small sample just point out
positive trends rather than verifying some hypotheses. Like in this research, subjective norms
and perceived behavioral control for knowledge sharing in dairy sector had moderate and weak
positive direct effect but with non-significant values toward intentions for knowledge sharing in
dairy sector. These relational values for subjective norms and perceived behavioral control may
be significant in a large sample size and in a cross-sectional generalized study. Information
technology usage was external factor in the research model. Behavioral research for external
factors is mostly context bound that showed mixed trends in different studies. Therefore, it is not
compulsory that positive correlation of IT usage in dairy sector with knowledge sharing behavior
in dairy sector will always be significant in all circumstances. No doubt, IT contributes a lot for
improvement of organizational structure, processes, and overall performance. But human
interactions, coordination and connections have their own role particularly for knowledge sharing
in organizations. In short, in behavioral study, both internal factors like motivation and external
factors like demographic, cultural, and social aspects present a comprehensive scenario that
affect individual’s behavior, in general, and for knowledge sharing, in particular.
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