Evaluating Task Knowledge as a Mediator in the Relationship
between Knowledge Sharing and Innovative Work Behaviour
Shahnawaz Muhammed
a
, Valmira Osmanaj
b
, Atik Kulakli
c
and Syed Faizan Hussain Zaidi
d
College of Business Administration, American University of the Middle East, Egaila, Kuwait
Keywords: Task Knowledge, Knowledge Sharing, Innovation, Mediation, Survey Methodology.
Abstract: It is widely recognized that knowledge sharing contributes to innovation in organizations. The implicit
assumption in the linkage between individual knowledge sharing and their innovative work behaviour is that
individuals gain certain qualities while being engaged in knowledge sharing that enable them to become more
innovative. In this paper, we explore employee task knowledge as a key mediator in the relationship between
knowledge sharing and their innovative work behaviour. Data collected from knowledge workers from several
manufacturing and service based organizations is used to test the mediation hypotheses. Results support our
mediation hypothesis and show that task knowledge partially mediates knowledge sharing’s impact on
innovative work behaviour. Knowledge sharing had a positive impact on innovative work behaviour even
after considering task knowledge as a mediator, suggesting other mechanisms at work in addition to their task
knowledge in how knowledge sharing contributes to innovation. Theoretical and practical implications of the
findings are also discussed.
1 INTRODUCTION
Driven by the need to introduce new products faster,
increased competition, changing global environment,
and to simply maximize the use of available
resources, organizations today are increasingly
focused on fostering innovation within their
workforce. As Kahn (2018) noted “innovation is
everywhere today” (p. 453). It is gaining increasing
presence in organizational mission and vision
statements, and in business school curriculums
(Kahn, 2018).
Though the debate as to what innovation really
means in an organizational context is still an on-going
concern (Fagerberg, Mowery, & Nelson, 2005), Kahn
(2108) suggests that it could be understood from an
outcome, process, and a mind-set perspective. From
each of these perspectives, as organizations focus on
producing innovative outputs related to their
products, process and other organizational outcomes,
focus on the innovation process itself, and develop an
innovation supportive culture in their organizations,
a
https://orcid.org/0000-0002-6031-5376
b
https://orcid.org/0000-0002-9864-8627
c
https://orcid.org/0000-0002-2368-3225
d
https://orcid.org/0000-0003-1931-1004
they have to do this firstly by enabling their
workforce to be innovative (West & Farr, 1989). In
addition to innovations occurring in business
functions focused on it, such as in R&D and in new
product development, researchers have emphasized
the importance of innovations arising from all
functions of the organization due to their potential to
come up with creative ideas and the impact it could
have on organizations (Amabile, 1996; Bäckström &
Bengtsson, 2019; Hoyrup, 2012; Kesting & Ulhoi,
2010; Oldham & Cummings, 1996; Smith et al.,
2012). We adopt such a broad perspective of
innovation and focus on innovative work behaviour
(IWB) of employees across the spectrum in this study.
Several authors have suggested that knowledge
sharing is an important element facilitating such
innovations in the workplace (Akram, Haider &
Hussain, 2019; Bontis, Bart, Sáenz, Aramburu, &
Rivera, 2009; Kamaşak & Bulutlar, 2010; Wang &
Wang, 2012; Ritala, Olander, Michailova, & Husted,
2015; Khan & Khan, 2019). While how knowledge
sharing facilitating development of intellectual
40
Muhammed, S., Osmanaj, V., Kulakli, A. and Zaidi, S.
Evaluating Task Knowledge as a Mediator in the Relationship between Knowledge Sharing and Innovative Work Behaviour.
DOI: 10.5220/0010015000400050
In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - Volume 3: KMIS, pages 40-50
ISBN: 978-989-758-474-9
Copyright
c
2020 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
capital that eventually leads to organizational
innovation is well documented in literature, a clear
understanding of how knowledge sharing may
contribute to innovation at the individual level is still
elusive. This research aims to contribute to a better
understanding of how such a contribution is possible
at the individual level. While studies have shown that
knowledge sharing impacts innovation at the
individual level (Akram et al., 2019; Ritala et al.,
2015; Khan & Khan, 2019), the tacit assumptions in
most of these studies have been that sharing
knowledge (both knowledge giving and knowledge
taking) bestows certain qualities in the individuals
that make them more innovative. However, very few
studies have empirically examined what these
qualities are in relation to knowledge sharing that
make employees more innovative. Similar to how
knowledge sharing at an organizational level
contributes to the organizational knowledge (Han,
Yoon, & Chae, 2020; Nonaka, 1994; Widén-Wulff &
Ginman, 2004; Yang, 2007), we present individual’s
task related knowledge as a key mediator in the
relationship between knowledge sharing and their
innovative work. In essence, the thesis of this article
is to empirically explore the contention that for
knowledge sharing to have an impact on workers
innovation, it does so by primarily enhancing their
task related knowledge.
2 LITERATURE REVIEW
2.1 Knowledge Sharing
Knowledge sharing in organizations has received
substantial attention in the management literature and
specifically in the literature related to knowledge
management. This is not surprising since it is one of
the important processes in an organization by which
information essential to the organizational
functioning becomes available to the organizational
entities, no matter how small or large the organization
is. Though individual level contributions to society
are important in many ways, organizations amplify
such impact. An essential aspect of these
organizations and its success is their ability to
communicate and coordinate the actions of its sub-
units, and more fundamentally of the individual
entities in it, for a larger common purpose (Thomas,
Thomas, Manrodt & Rutner, 2001; Greenberg &
Baron, 2002). Knowledge sharing is one such key
form of communication where provider and recipient
are engaged in transferring ones understanding to the
recipient of that knowledge (Muhammed, Doll &
Deng, 2011; Van den Hooff & de Ridder, 2004).
Ipe (2003) indicates that knowledge sharing is
“the act of making knowledge available to others
within the organization. Knowledge sharing between
individuals is the process by which knowledge held
by an individual is converted into a form that can be
understood, absorbed, and used by other individuals.”
(p.341). In an organizational context, Bartol and
Srivastava (2002) define knowledge sharing as
“individuals sharing organizationally relevant
information, ideas, suggestions, and expertise with
one another” (p. 65). Similarly, building on
Cummings (2004) and Pulakos, Dorsey and Borman
(2003), Wang and Noe (2010) note that individual
knowledge sharing in an organizational context
involves “provision of task information and know-
how to help others and to collaborate with others to
solve problems, develop new ideas, or implement
policies or procedures” (p. 117).
Individual knowledge sharing being the
fundamental aspect of knowledge sharing that takes
place at all other higher levels of abstraction. In this
paper, we focus on knowledge sharing at this level.
Further we focus on the knowledge outflow of
individual level knowledge (knowledge giving), and
define knowledge sharing as an act of making
individual knowledge available to others, similar to
the definition adopted by Ipe (2003). We adopted this
perspective of knowledge sharing in this research, to
evaluate the extent to which individual knowledge
sharing contributes to their innovative work
behaviour through their task related knowledge.
2.2 Task Knowledge
Based on various objectives, knowledge has been
categorized from many perspectives. One such
perspective is to view individual knowledge that is
relevant to their work as task knowledge. In the
service innovation perspective, task knowledge is the
accumulation of facts, comprehensions, skills, and
lessons learned from previous and emergent service
development activities and originate from different
functions within the company (Storey & Kahn, 2010).
Task knowledge structures are functionally
equivalent to the knowledge structures that people
have and use when they carry out any task at their
work (Johnson, Johnson, Waddington, & Shouls,
2001). The foundation of the task approach relies on
influential work which divides workplace’s activities
into tasks. Tasks are constructed on the activities
accomplished by organizations’ employees related to
Evaluating Task Knowledge as a Mediator in the Relationship between Knowledge Sharing and Innovative Work Behaviour
41
their particular occupations (Autor, Levy & Murnane,
2003).
Helfat and Peteraf (2003) describe organizational
capability as “the ability of an organization to
perform a coordinated set of tasks, utilizing
organizational resources, for the purpose of achieving
a particular end result” (p. 999). Therefore,
organizational knowledge plays a vital role to achieve
the successful completion of these set of tasks. Task
oriented knowledge is hence knowledge relevant for
organizational actions. Organizations are sustained
by acquiring knowledge relevant to its various tasks
and allocating these to right positions for
accomplishing the task. From this point, optimal level
of knowledge acquisition and talent is required to
determine the complexity of task knowledge.
Communication plays an important role in shaping
the relationship between individual talents and
administers the organizational process and structure
that integrates detached knowledge to perform tasks
more proficiently. The task based approach identifies
the organization process that optimizes the relations
between tasks and talents as the core of organizational
capital (Garicano & Wu, 2010).
Fonseca, de Faria and Lima (2017) explain the
firm innovation process from a task based viewpoint
and presented a view of human capital which is based
on the tasks that firms’ workers accomplish. Authors
proposed a measure of cognitive analytical and
interpersonal tasks as the degree of abstractism. They
content that “the level of abstractism of a firm not
only has an effect on a firm’s propensity to innovate,
but also on its product innovation performance” (p.
616). Further, authors propose measures of task
which allow the assessment of the optimal
organizational task structure to maximize the
inclination of a firm to innovate and subsequently
improve its product innovation performance. Thus,
innovation performance is exploited at transitional
value of the degree of abstractism in organizations.
Innovation management literature stresses this
relationship between human capital characteristics
and innovation performance (Faems & Subramanian,
2013).
While task knowledge can be viewed from many
perspectives in organizations, it is challenging to
measure it at the right level of abstraction that makes
it usable for substantive analysis. To be able to
maintain a generic abstraction that is required to
capture the full breadth of individual’s task
knowledge in differing contexts while at the same
time keeping the construct at a manageable level for
such research, we adopt the conceptualization
proposed by Muhammed, Doll and Deng (2009) and
view task knowledge comprising of conceptual,
contextual and operational knowledge. Conceptual
knowledge is the “deeper understanding of why a
person is engaged in a particular task” (p. 4) and it
provides the rationale for individuals for their actions
and addresses the ‘know-why’ aspect of a given task
(Garud, 1997; Hulme, 2014). It becomes easier to
assimilate other types of information when such
knowledge related to one’s organizational task is
present (Kim, 1993). Operational knowledge is the
knowledge individuals immediately need to
accomplish their task (such as know-what and know-
how) (Garud, 1997; Hulme, 2014). This is often
referred to as the declarative and procedural
knowledge that individuals carry (Schultze &
Leidner, 2002; Zack, 1999). Without a satisfactory
level of operational knowledge individuals may not
be able to even accomplish their routine tasks let
alone to be innovative in their work. Contextual
knowledge is what individuals know in addition to the
immediate knowledge required to complete the task
(operational knowledge) and may enrich the existing
knowledge with what may not be obvious (such as
know-who, know-where, and know-when) (Atherton,
2013; Howell & Boies, 2004). These three knowledge
components capture the breadth of knowledge that
employees bear on in accomplishing their
organizational tasks.
2.3 Innovative Work Behaviour
Increasing employees’ knowledge sharing, as a
means to generate new ideas, is considered vital for
the organizations which are striving to innovate
products and services, achieve competitive
advantages and attain a strong market position
(Masih, Sriratanaviriyakul, El-Den, & Azam, 2018;
Ologbo, Nor, & Okyere-Kwakye, 2015). “Creativity
and innovation at work are the process, outcomes, and
products of attempts to develop and introduce new
and improved ways of doing things.” (Anderson,
Potocnik & Zhou, 2014, p.4). According to Che, Wu,
Wang, & Yang (2019), innovation is a combination
of idea generation (generation of domain-specific,
novel and useful new ideas) and idea implementation
(implementing new ideas to practice).
While a substantial research investigates the
innovation process in organisations (Rothaermel &
Hess, 2007; Stalk, Evans, & Shulman, 1992), there is
an increasing focus on innovation at an individual
level and how it affects organizations (Grigoriou &
Rothaermel, 2014; Maqbool, Černe, & Bortoluzzi,
2019; Odetunde, 2019). Considering the fact that the
innovation capability of the organisations derives
KMIS 2020 - 12th International Conference on Knowledge Management and Information Systems
42
from their employees’ innovation capabilities,
employee innovative work behaviour (IWB) is
crucial to the organization success and innovation
(Arsawan, Kariati, Prayustika, & Wirga, 2019;
Odetunde, 2019; Scott & Bruce, 1994). IWB
indicates the intentional creation, introduction and
application of new ideas, processes, products or
services within their work-role, group or
organizational context (Janssen, 2000; Odetunde,
2019; Radaelli, Lettieri, Mura, & Spiller, 2014; Scott
& Bruce, 1994). According to a study conducted by
Janssen (2000), IWB encompasses three main tasks:
idea generation (developing novel ideas); idea
promotion (obtaining external support); and idea
application (producing a model or prototype of the
idea).
The employee’s ideas are nurtured through
communication and exchange of expertise that are
substantial for stimulating innovative ideas (Masih et
al., 2018). Both the knowledge denoting and
knowledge collecting play an important influence on
employee's innovative behaviour (Hassan et al.,
2018). Ability to elaborate, re-combine and
disseminate knowledge is skill-set required both for
knowledge sharing and innovation (Radaelli et al.,
2014). However, how such innovations occur has not
been sufficiently explored. Thus, the focus of this
study is to analyse the impact knowledge sharing
have on employee’s ability to be creative, by
generating domain-specific, novel and useful new
ideas and implementing these new ideas into their
work, and the role of task knowledge in this
relationship.
3 THEORY AND HYPOTHESES
The focus of this research is in understanding if and
how knowledge sharing contributes to employees
innovative work behaviour. A central theme in this
argument is that individuals become more innovative
when knowledge sharing helps them build knowledge
relevant to their work which we address in this paper
as ‘task knowledge’. In the next two sections we
develop this thesis further and propose the hypotheses
in the light of extant literature.
3.1 Knowledge Sharing and Innovative
Work Behaviour
Radaelli et al. (2014) claimed that employees who
share knowledge engage more in creating, promoting
and implementing innovations. According to Githii
(2014), exchanging ideas and information through
communication boost innovation. In a study
conducted by Arsawan et al. (2019), the authors
found out that employees who share knowledge can
improve self-quality by taking positive values in the
form of capability, competence, skill, and trust. Also,
Radaelli et al. (2014), found that knowledge sharing
enliven knowledge recombination and re-elaboration
that stimulates the generation, promotion and
application of new ideas.
Akram and Bokhari (2011) found in their study
that knowledge sharing is positively related to
individual performance. In addition, they argued that
successful knowledge transfer requires high level of
individual motivation so that knowledge seeker and
knowledge provider openly share and accept it. Based
on the review conducted by Githii, (2014), there is
overwhelming evidence showing that knowledge
management practices play a significant role in
innovation and suggest that employee innovation
should be supported by organizational systems and
structures that encourage their efforts to learn and
acquire new knowledge. Also, Masih et al. (2018)
content in their study that knowledge sharing
promotes employees’ innovation capabilities and the
employees should be given incentives by the
management in order to increase both their
knowledge sharing and innovative capabilities.
Phung, Hawryszkiewycz and Chandran (2019)
studied the impact of knowledge-sharing behaviour
on the innovative work behaviour in university
settings in developing countries, focusing on the
moderating role of transformational leadership. The
authors found that knowledge-sharing behaviour
positively affects innovative work behaviour, and
recommended leaders to focus on promoting
innovative behaviours of employees during their
daily work through encouraging knowledge sharing.
Several more studies point to the positive impact of
knowledge sharing on innovation (Bontis et al., 2009;
Jada Mukhopadhyay & Titiyal, 2019; Kamaşak &
Bulutlar, 2010; Kim & Park, 2017; Leonardi, 2014;
Radaelli et al., 2014).
H1: Knowledge sharing has a significant positive
effect on innovative work behaviour.
3.2 Task Knowledge as a Mediator
When organizations focus on knowledge
management, the emphasis is usually on the macro
elements, such as organizational level innovation,
improved performance, and competitive advantage.
While this is important from a strategic perspective,
such innovations are driven by amalgamation of
Evaluating Task Knowledge as a Mediator in the Relationship between Knowledge Sharing and Innovative Work Behaviour
43
innovations by individual employees in their day-to-
day work. Further, organizations innovate when
employees share their knowledge and innovations
widely across the organization. Knowledge sharing
thus is key focus area in organizational knowledge
management initiatives. It refers to the delivery of
task information in collaborative environment to
resolve problems. Developing new ideas for
accomplishing the task and implementing policies
and procedures are the important aspects of
knowledge sharing (Cummings, 2004). Creativity,
learning, and performance are viewed as most
common factors in this context that are affected by
knowledge sharing (Ahmad & Karim, 2019).
Knowledge sharing hence contributes to building the
social capital in organizations that can drive
innovation (Widén-Wulff & Ginman, 2004).
According to Storey and Kahn (2010), a positive
relationship exist between task knowledge and
innovation due to the fact that task knowledge
increases the company stock knowledge that is further
utilized to increase proficiency and boost innovation
of new service development. Similar results were
found in the study of Akgün, Dayan and Di Benedetto
(2008), where the authors analysed the impact of the
team knowledge in the new product development.
The authors found that both declarative and
procedural knowledge of the team affected positively
the team’s knowledge base which led to a positive
impact in the new products’ creativity and success.
Moreover, Afsar & Umrani (2019) suggested that the
task complexity has a significant effect on motivation
to learn and develop their work related knowledge,
which enhances the innovative work behaviour of the
employees.
While there is some research suggesting that
knowledge could sometimes impede innovation, as in
the case when employees become too comfortable
with the knowledge that they have in doing their work
and resist change and seeking new knowledge. For
example, Subramaniam & Youndt (2005) discovered
in their study that human capital negatively impacted
the radical innovative capability (to generate
innovations that significantly transform existing
products and services). The authors argue that
possessing viciously independent experts, who
hesitate to share their ideas with their colleagues, may
be counterproductive for organizations. However, in
a knowledge sharing context, people seek out new
knowledge and are willing to share what they know.
While it is important to understand what prompts the
employees to share knowledge and a substantial work
has been done in this regard (Bock, Zmud, Kim, and
Lee, 2005; Lin, 2007), our focus is in exploring how
knowledge sharing impacts their innovative
capability by building their task related knowledge.
As discussed earlier, knowledge in the
organizational context could be conceptualized as
conceptual, contextual and operational knowledge
(Muhammed et al., 2009). As individuals share their
knowledge among their colleagues and other online
and offline communities related to their work, they
build a network of connections on which they could
depend on when they face certain roadblocks in their
work, and hence directly contributing to their
operational knowledge. Such forums and
communities also act as a platform where they may
come across a broad range of information
contributing to their contextual knowledge. Engaging
in sharing knowledge requires individuals to think
about what they may tacitly know and consciously
turn it into a form that is understandable and
receivable by the audience (Muhammed et al., 2011).
This process can enhance the conceptual
understanding of what they may already know and
acquire in this process. Hence, sharing knowledge can
contribute to gaining further knowledge. In fact this
may be a more effective way to quickly gain and
broaden one’s task knowledge eventually, leading to
new ideas and further innovations.
It is widely recognized that innovation involves
more than creating new ideas, and may involve
selection, development implementation of those ideas
at the least (Backstrom & Bengtsson, 2019; Dodgson
2017). While contextual knowledge helps individuals
to connect disparate ideas thus contributing to
creating novel outcomes in their work (Howell &
Boies, 2004), conceptual knowledge helps
individuals to develop a broader and more critical
perspective of such creation and would help in
evaluating which of those creative ideas may be best
implemented. Since operational task knowledge is the
knowledge related to the actual skill and know-how
of one’s task, a higher level of such operational task
knowledge would also help individuals to implement
their novel productions contributing to a successful
innovation. Given together, we can safely suggest that
their task knowledge conceptualized as comprising of
conceptual, contextual and operational knowledge
contributes to all the phases of innovation (Nurulin et
al., 2019). Hence, as hypothesized in the previous
section while knowledge sharing may directly impact
employees innovative work behaviour, there is
compelling rationale suggesting that a large portion
of this impact may be due to the enhanced task
knowledge that knowledge sharing may help gain. In
other words it is highly likely that task knowledge is
a key mediator in this relationship between
KMIS 2020 - 12th International Conference on Knowledge Management and Information Systems
44
knowledge sharing and employee’s innovative work
behaviour.
H2: Task knowledge mediates the relationship
between knowledge sharing and innovative work
behaviour.
4 METHODS
This research uses a cross-sectional survey design to
collect the data used to test the hypothesized model.
Measures used in this study were developed based on
generally accepted psychometric principles
(Churchill, 1979). Face validity of the measures were
assessed in the pre-test stage by having five experts
and five target respondents examine the items against
the construct definition (Netemeyer, Bearden, &
Sharma, 2003). Measures were further refined based
on a pilot survey before using it in the large scale data
collection. After receiving the responses, the data was
evaluated for any potential problems and missing
values. Further it was assessed for any potential
biases, such as non-response bias and common
method bias. Next, before assessing the substantive
relationships, validity and reliability of the measures
were assessed. Once the measures were assessed to be
sound, substantive relationships and the related
hypotheses were tested using hierarchical linear
regression and mediation analysis.
4.1 Measures
Responses to all measures were anchored on a five-
point Likert type scale except for the outcome
variable innovative work behaviour, which was
measured on a seven-point Likert type scale.
Participants were asked to reflect on the past six
months at their work to answer the questionnaire. The
final measure for knowledge sharing included three
items such as “I have shared my insights with others”
“I have shared my knowledge with others” and “I
have shared my work-related knowledge with
others”. For task knowledge, a three dimensional
measure inclusive of conceptual, contextual and
operational knowledge as proposed by Muhammed et
al. (2009) was used. Items for knowledge sharing and
tasks knowledge were anchored from (1) none or to a
very little extent to and (5) to a very great extent. For
innovative work behaviour, a three item measure
similar to De Jong and Den Hartog (2010), and Afsar
and Umrani (2019) were used. It included items such
as “my work was creative”, “my work was original
and practical”, and “I was the first to use certain ideas
in my kind of work”. Respondents were asked to
indicate the level of their innovative output compared
to other individuals in similar position, and the items
were anchored from (1) Not at all to (7) To an
exceptionally high degree. Further, respondent’s
position in the organization, level of education, age
and gender are used as controls.
4.2 Data Collection
Data was collected using a web-based survey
targeting knowledge workers in various
manufacturing and related industries. Most of the
responses were from US firms. A total of 154 usable
responses were received for a response rate of 24%
based on the click-through. Responses were received
from knowledge workers in wide spectrum of
industries. 42% of the respondents worked in various
manufacturing and related firms, 39% were from
computer, information technology or software firms
and the remaining 19% indicated that they were from
firms other than these two sectors. The respondents
also represented firms of various sizes with most
number of responses from individuals working in
large organizations that employed more than 500
individuals (40%), 25% of the responses were from
individuals in small firms that employed fewer than
50 and the rest were from medium sized
organizations.
5 RESULTS
5.1 Measurement Assessment
A confirmatory factor analysis was done initially to
assess the overall measurement model. Before testing
for substantive analysis, it is imperative that we assess
the convergent validity and the discriminant validity
of the measures. A confirmatory factor analysis with
all items including the summated scales of the three
dimensions of task knowledge was constructed.
Factor loading for all items in this measurement
model were significantly loaded on their respective
constructs, and exceeded the minimum requirement.
The loadings ranged from 0.73 to 0.94. The resultant
measurement model showed excellent fit (χ2 = 36.8,
df = 24, p-value=0.045, RMSEA=0.046, GFI=0.97,
NNFI=0.99, CFI=0.99). The composite reliabilities
(CR) were 0.92 for knowledge sharing, 0.80 for task
knowledge, and 0.89 for innovative work behaviour.
Similarly, AVE ranged from 0.58 (task knowledge) to
0.79 (knowledge sharing) indicating good convergent
validity of the measurement instruments.
Evaluating Task Knowledge as a Mediator in the Relationship between Knowledge Sharing and Innovative Work Behaviour
45
Discriminant validity is the ability of the
constructs to differentiate from other unrelated
constructs and is assessed by evaluating the AVE for
each construct (Fornell & Larker, 1981; Kline, 2010).
The squared correlations for each construct were less
than its AVE, indicating sufficient discriminant
validity (Chin, 1998; Fornell & Larcker, 1981).
Highest correlation was 0.45 (between knowledge
sharing and task knowledge) and was below the
recommended 0.70 providing further evidence of
discrimination (Ping, 2004). The scales also
displayed good reliabilities as assessed using
Cronbach’s alpha () and range from 0.79 (Task
knowledge) to 0.91 (knowledge sharing).
5.2 Mediating Effect of Task
Knowledge
A three-step regression procedure was used to test the
mediating effect of task knowledge in the relationship
between knowledge sharing and innovative work
behaviour (Baron & Kenny, 1986). The procedure
include first for testing the direct effect of
independent variable (knowledge sharing) on
dependent variable (innovative work behaviour) as
hypothesized in H1. If this relationship is significant
then two other models are evaluated. The second one
with the independent variable and the moderator, and
in the third model, the outcome variable- innovative
work behaviour is regressed on both knowledge
sharing and task knowledge. In order to test the
mediation hypothesis using hierarchical regression
analysis summated scales of the measures where
used. Table 1 shows the results of the three regression
models. The first model is represented as Model 1 and
indicates that, after considering the effect of the
control variables, knowledge sharing had a significant
impact on innovative work behaviour (β = .39, p <
.001) thus supporting hypotheses H1. From the
control variables except for education in Model 1 and
2, and age in Model 3, they did not have any
significant impact on innovative work behaviour or
task knowledge.
Model 2 shows the regression result of knowledge
sharing and task knowledge on innovative work
behaviour. In this model, both knowledge sharing (p
< .05) and task knowledge (p < .001) had a significant
positive impact on innovative work behaviour and
showed a significant increase in the variance
explained (9.2%) compared to Model 1. In order to
fully establish mediation, it is also essential that we
test task knowledge as the criterion variable with
knowledge sharing as the predictor (Model 3). This
model showed a strong significant relationship
between knowledge sharing and task knowledge (β
=.23, p < .001). The above findings combined support
the hypotheses related to task knowledge as the
mediator (Hypotheses H2). Support for both
hypothesis H1 and H2 indicate a partial mediation of
task knowledge in the relationship between
knowledge sharing and innovative work behaviour.
Table 1: Results of regression analysis for testing mediation.
Model 1 Model 2 Model 3
Std. Error t Sig.
Std. Error t Sig.
Std. Error t Sig.
(Constant) 4.953 0.602 8.230 0.000 3.247 0.700 4.639 0.000 2.702 0.312 8.651 0.000
Control variables
Pois ition -0.060 0.061 -0.993 0.322 -0.077 0.058 -1.340 0.182 0.027 0.032 0.858 0.392
Education
-0.265
0.083 -3.201 0.002
-0.224
0.079 -2.831 0.005 -0.065 0.043 -1.515 0.132
Age 0.084 0.085 0.988 0.325 0.032 0.082 0.387 0.699
0.083
0.044 1.880 0.062
Gender -0.182 0.230 -0.789 0.431 -0.250 0.219 -1.144 0.255 0.109 0.119 0.910 0.364
Main effect
Knowledge Sharing
0.387
0.101 3.825 0.000
0.240
0.102 2.356 0.020
0.232
0.052 4.422 0.000
Mediating effect
Task Knolwedge
0.631
0.150 4.204 0.000
N 154 154 154
F-Value 4.834 7.427 6.214
R-sq 0.140 0.233 0.174
R-sq 0.092
Innovative Work Behavior Task Knowledge
Unstandardized
coefficients
Unstandardized
coefficients
Uns tandardized
coefficients
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6 DISCUSSION, IMPLICATIONS
AND LIMITATIONS
Knowledge sharing has been associated with
innovation in many different contexts but, how it may
contribute to innovation at an individual level has not
been investigated sufficiently well in the literature.
This research aimed to address this gap, and proposed
that one of the key mechanism by which individuals
can be more innovative by sharing knowledge is
when such knowledge sharing contributes to their
task related knowledge. As proposed in hypotheses
H1 and supported by results, this study confirms the
role knowledge sharing can play in helping
individuals to be more innovative in their workplace.
Managers looking for greater innovations from their
employees may take note of this and encourage
knowledge sharing within their organizations. They
should look at ways to motivate individuals to share
their knowledge and provide structural support
mechanisms such as technological platforms, and
incentives build into organizational reward systems
for this (Bartol & Srivastava, 2002; Le & Lei, 2019).
The results also supported our second hypotheses
related to the mediating role of task knowledge in the
relationship between knowledge sharing and
employee’s innovative work behaviour. This
provides important insights into how individuals can
become more innovative by sharing their knowledge.
As they engage in knowledge sharing, they should be
reflective of how it may improve their own
knowledge which could help them become more
innovative at work. Since knowledge sharing is one
of the main aspects of many knowledge management
initiatives, a better understanding of not only what
motivates employees to engage in knowledge sharing,
but also what impact it could have on individual’s
work and how such impact is manifested would be an
on-going concern for many managers. Findings are in
line with other studies that suggest that knowledge
sharing in organizations impacts its performance only
when employees utilize the knowledge that they gain
through knowledge sharing (Zaim, Muhammed &
Tarim, 2019).
While task knowledge is a significant mediator of
knowledge sharing’s impact on innovation, the
findings of this study show that it only partially
mediates this relationship. This opens up avenues for
future researchers to evaluate other aspects of
knowledge sharing’s impact on innovation. For
example, in a recent study Asurakkody and Hee
(2020) found self-leadership to be a mediator in this
relationship. While recognizing the limitation of
measuring individual knowledge in an organizational
context at a very broad scale and the varied
complexities that may be masked by such an
approach, this research shows the usefulness of
measuring task knowledge at such a scale and how
important substantive relations may be effected by it.
Future research could use similar measure of task
knowledge to evaluate other substantive
relationships, especially, the ones in the knowledge
management area since a better understanding of how
the various initiatives improve the knowledge stock
of individuals and organizations would be of interest
to researchers and practitioners in this field.
REFERENCES
Afsar, B. & Umrani, W.A. (2019). Transformational
leadership and innovative work behavior: The role of
motivation to learn, task complexity and innovation
climate. European Journal of Innovation Management,
23(3), 402-428.
Ahmad, F., & Karim, M. (2019). Impacts of knowledge
sharing: A review and directions for future
research. Journal of Workplace Learning, 31(3), 207-
230.
Akgün, A.E., Dayan, M., & Di Benedetto, A. (2008). New
product development team intelligence: Antecedents
and consequences. Information & Management, 45(4),
221-226.
Akram, F., & Bokhari, R. (2011). The role of knowledge
sharing on individual performance, considering the
factor of motivation-the conceptual framework.
International Journal of Multidisciplinary Sciences and
Engineering, 2 (9), 44-48.
Akram, T., Lei, S., Haider, M.J., & Hussain, S.T. (2019).
The impact of organizational justice on employee
innovative work behavior: Mediating role of
knowledge sharing. Journal of Innovation &
Knowledge, 5(2), 117-129.
Amabile, T. M. "Creativity and Innovation in
Organizations." Harvard Business School Background
Note 396-239, January 1996.
Anderson, N., Potocnik, K. & Zhou, J. (2014). Innovation
and creativity in organizations: a state-of-the-science
review, prospective commentary, and guiding
framework. Journal of Management, 40(5), 1297-1333.
Arsawan, I.W.E., Kariati, N.M., Prayustika, P.A., & Wirga,
I.W. (2019). Elucidating Knowledge Sharing on
Innovative Work Behavior: Multiperspective Analysis.
ICORE, 5(1), 670-686.
Asurakkody, T.A., & Hee, S. (2020). Effects of Knowledge
Sharing Behavior on Innovative work Behavior among
Nursing Students: Mediating role of Self-Leadership.
International Journal of Africa Nursing Sciences, 12, 1-
6.
Atherton, A. (2013). Organisational ‘know-where’and
‘know-when’: re-framing configurations and
Evaluating Task Knowledge as a Mediator in the Relationship between Knowledge Sharing and Innovative Work Behaviour
47
distributions of knowledge in organisations. Knowledge
Management Research & Practice, 11(4), 410-421.
Autor, D.H., Levy, F., & Murnane, R.J. (2003). The skill
content of recent technological change: An empirical
exploration. The Quarterly Journal of
Economics, 118(4), 1279-1333.
Backstrom, I., & Bengtsson, L. (2019). A mapping study of
employee innovation: proposing a research agenda.
European Journal of Innovation Management, 22 (3),
468-492.
Baron, R.M., & Kenny, D.A. (1986). The moderator–
mediator variable distinction in social psychological
research: Conceptual, strategic, and statistical
considerations. Journal of Personality and Social
Psychology, 51(6), 1173.
Bartol, K. M., & Srivastava, A. (2002). Encouraging
knowledge sharing: The role of organizational reward
systems. Journal of Leadership & Organizational
Studies, 9(1), 64-76.
Bock, G.W., Zmud, R.W., Kim, Y.G., & Lee, J.N. (2005).
Behavioral intention formation in knowledge sharing:
Examining the roles of extrinsic motivators, social-
psychological forces, and organizational climate. MIS
Quarterly, 87-111.
Bontis, N., Bart, C., Sáenz, J., Aramburu, N., & Rivera, O.
(2009). Knowledge sharing and innovation
performance. Journal of Intellectual Capital, 10(1),
22.36.
Che, T., Wu, Z., Wang, Y., & Yang, R. (2019). Impacts of
knowledge sourcing on employee innovation: the
moderating effect of information transparency. Journal
of Knowledge Management, 23(2), 221-239.
Chin, W.W. (1998). Issues and opinion on structural
equation modeling. MIS Quarterly, 22(1), vii-xv.
Churchill Jr, G.A. (1979). A paradigm for developing better
measures of marketing constructs. Journal of
Marketing Research, 16(1), 64-73.
Cummings, J.N. (2004). Work groups, structural diversity,
and knowledge sharing in a global
organization. Management Science, 50(3), 352-364.
De Jong, J., & Den Hartog, D. (2010). Measuring
innovative work behaviour. Creativity and innovation
management, 19(1), 23-36.
Dodgson, M. (2017). Innovation in firms. Oxford Review of
Economic Policy, 33(1), 85-100.
Faems, D., & Subramanian, A.M. (2013). R&D manpower
and technological performance: The impact of
demographic and task-related diversity. Research
Policy, 42(9), 1624–1633.
Fagerberg, J., Mowery, D. C., & Nelson, R.R. (Eds.).
(2005). The Oxford handbook of innovation. Oxford
University Press.
Fonseca, T., de Faria, P., & Lima, F. (2019). Human capital
and innovation: the importance of the optimal
organizational task structure. Research Policy, 48(3),
616-627.
Fornell, C., & Larker, D. (1981). Structural equation
modeling and regression: guidelines for research
practice. Journal of Marketing Research, 18(1), 39-50.
Garicano, L. & Wu, Y. (2010). A Task-Based Approach to
Organization: Knowledge, Communication and
Structure," CEP Discussion Papers dp1013, Centre for
Economic Performance, LSE.
Garud, R. (1997). On the distinction between know-how,
know-what, and know-why. Advances in Strategic
Management, 14, 81-102.
Githii, S. (2014), Knowledge management practices and
innovation performance: a literature review. Journal of
Business and Management (IOSR-JBM). 16(2), 89-94.
Greenberg, J. & Baron, R. A. (2002). Behavior in
organizations: Understanding and managing the human
side of work. Prentice Hall, NY.
Grigoriou, K. & Rothaermel, F.T. (2014). Structural
microfoundations of innovation: The role of relational
stars. Journal of Management, 40(2), 586-615.
Han, S.H., Yoon, S. W., & Chae, C. (2020). Building social
capital and learning relationships through knowledge
sharing: a social network approach of management
students’ cases. Journal of Knowledge
Management. https://doi.org/10.1108/JKM-11-2019-
0641
Hassan, H.A., Asif, J., Waqar, N., & Abbas, S.K. (2018).
The impact of knowledge sharing on innovative work
behaviour. Asian Journal of Multidisciplinary Studies,
6(5), 22-25.
Helfat, C.E., & Peteraf, M. (2003). The Dynamic Resource-
Based View: Capability Lifecycles. Strategic
Management Journal, 24, 997–1010.
Howell, J.M., & Boies, K. (2004). Champions of
technological innovation: The influence of contextual
knowledge, role orientation, idea generation, and idea
promotion on champion emergence. The Leadership
Quarterly, 15(1), 123-143.
Høyrup, S. (2012). Employee-driven innovation: A new
phenomenon, concept and mode of innovation.
In Employee-driven innovation (pp. 3-33). Palgrave
Macmillan, London.
Hulme, P.E. (2014). Bridging the knowing–doing gap:
know-who, know-what, know-why, know-how and
know-when. Journal of Applied Ecology, 51(5), 1131-
1136.
Ipe, M. (2003). Knowledge sharing in organizations: A
conceptual framework. Human Resource Development
Review, 2(4), 337-359.
Jada, U.R., Mukhopadhyay, S., & Titiyal, R. (2019).
Empowering leadership and innovative work behavior:
a moderated mediation examination. Journal of
Knowledge Management, 23(5), 915-930.
Janssen, O. (2000), Job demands, perceptions of effort
reward fairness and innovative work behaviour.
Journal of Occupational and Organizational
Psychology, 73(3), 287-302.
Johnson, P., Johnson, H, Waddington, R. & Shouls, A.
(2001). Task-Related Knowledge Structures: Analysis,
Modelling and Application, publication at:
https://www.researchgate.net/publication/2401134
Kahn, K.B. (2018). Understanding innovation. Business
Horizons, 61(3), 453-460.
KMIS 2020 - 12th International Conference on Knowledge Management and Information Systems
48
Kamaşak, R., & Bulutlar, F. (2010). The influence of
knowledge sharing on innovation. European Business
Review, 22(3), 306-317.
Kesting, P., & Ulhøi, J.P. (2010). Employeedriven
innovation: extending the license to foster
innovation. Management Decision, 48(1), 65-84.
Khan, N.A., & Khan, A.N. (2019). What followers are
saying about transformational leaders fostering
employee innovation via organisational learning,
knowledge sharing and social media use in public
organisations?. Government Information Quarterly,
36(4).
Kim, D.H. (1993). A framework and methodology for
linking individual and organizational learning:
Applications in TQM and product
development (Doctoral dissertation, Massachusetts
Institute of Technology).
Kim, W., & Park, J. (2017). Examining structural
relationships between work engagement, organizational
procedural justice, knowledge sharing, and innovative
work behavior for sustainable organizations.
Sustainability, 9(2), 205.
Kline, R.B. (2010). edition 3. Principles and practice of
structural equation modeling.
Le, P.B., & Lei, H. (2019). Determinants of innovation
capability: the roles of transformational leadership,
knowledge sharing and perceived organizational
support. Journal of Knowledge Management.
Leonardi, P.M. (2014). Social media, knowledge sharing,
and innovation: Toward a theory of communication
visibility. Information Systems Research, 25(4), 796-
816.
Lin, C.P. (2007). To share or not to share: Modeling
knowledge sharing using exchange ideology as a
moderator. Personnel Review, 36(3), 457-475.
Maqbool, S., Černe, M., & Bortoluzzi, G. (2019). Micro-
foundations of innovation. European Journal of
Innovation Management, 22(1), 125-145.
Masih, N., Sriratanaviriyakul, N., El-Den, J., & Azam, S.
(2018). The Role of Knowledge Sharing on Employees’
Innovation Initiatives. In 2018 8th International
Workshop on Computer Science and Engineering
(WCSE 2018), 697-704.
Muhammed, S., Doll, W.J., & Deng, X. (2009). A model of
interrelationship among individual level knowledge
management success measures. International Journal
of Knowledge Management, 5(1), 1 – 16.
DOI:104018/jkm.2009010101
Muhammed, S., Doll, W.J., & Deng, X. (2011). Impact of
knowledge management practices on task knowledge:
an individual level study. International Journal of
Knowledge Management, 7(4), 1–21.
doi.org/10.4018/jkm.2011100101
Netemeyer, R.G., Bearden, W.O., & Sharma, S.
(2003). Scaling procedures: Issues and applications.
Sage Publications.
Nonaka, I. (1994). A dynamic theory of organizational
knowledge creation. Organization Science, 5(1), 14-37.
Nurulin, Y., Skvortsova, I., Tukkel, I., & Torkkeli, M.
(2019). Role of Knowledge in Management of
Innovation. Resources, 8(2), 87.
Odetunde, O.J. (2019), Employee Innovation Process: An
Integrative Model, Journal of Innovation Management,
7(3), 15-40.
Oldham, G.R., & Cummings, A. (1996). Employee
creativity: Personal and contextual factors at
work. Academy of management Journal, 39(3), 607-
634.
Oliver, D., & Jacobs, C. (2007). Developing guiding
principles: an organizational learning perspective.
Journal of Organizational Change Management, 20(6),
813-828.
Ologbo, A.C., Nor, K.M., & Okyere-Kwakye, E. (2015).
The Influence of knowledge sharing on employee
innovation capabilities. International Journal of
Human Resource Studies, 5(3), 102-110.
Phung, V.D., Hawryszkiewycz, I., & Chandran, D. (2019),
How knowledge sharing leads to innovative work
behaviour: A moderating role of transformational
leadership. Journal of Systems and Information
Technology, 21(3), 277-303.
Ping Jr, R.A. (2004). On assuring valid measures for
theoretical models using survey data. Journal of
business research, 57(2), 125-141.
Pulakos, E. D., Dorsey, D. W. and Borman, W., (2003).
Hiring for Knowledge-Based Competition. In Jackson,
S. E., DeNisi, A., & Hitt, M. A. (Eds.). Managing
knowledge for sustained competitive advantage:
Designing strategies for effective human resource
management (Vol. 21). John Wiley & Sons, pp.155-
177.
Radaelli, G., Lettieri, E., Mura, M., & Spiller, N. (2014).
Knowledge sharing and innovative work behaviour in
healthcare: A microlevel investigation of direct and
indirect effects. Creativity and Innovation
Management, 23(4), 400-414.
Ritala, P., Olander, H., Michailova, S., & Husted, K.
(2015). Knowledge sharing, knowledge leaking and
relative innovation performance: An empirical study.
Technovation, 35, 22-31.
Rothaermel, F.T., & Hess, A.M. (2007). Building dynamic
capabilities: Innovation driven by individual-, firm-,
and network-level effects. Organization Science, 18(6),
898-921.
Schultze, U. & Leidner, D.E. (2002). Studying knowledge
management in information systems research:
discourses and theoretical assumptions. MIS Quarterly,
213-242.
Scott, S.G., & Bruce, R.A. (1994). Determinants of
innovative behavior: A path model of individual
innovation in the workplace, Academy of Management
Journal, 37(3), 580-607.
Smith, M., Busi, M., Ball, P., & Van der Meer, R. (2008).
Factors influencing an organisation's ability to manage
innovation: a structured literature review and
conceptual model. International Journal of Innovation
Management, 12(04), 655-676.
Evaluating Task Knowledge as a Mediator in the Relationship between Knowledge Sharing and Innovative Work Behaviour
49
Stalk, G., Evans, P., & Shulman, L.E. (1992). Competing
on capabilities: The new rules of corporate
strategy. Harvard Business Review, 70(2), 57-69.
Storey, C., & Kahn, K.B. (2010). The role of knowledge
management strategies and task knowledge in
stimulating service innovation. Journal of Service
Research, 13(4), 397-410.
Subramaniam, M., & Youndt, M.A. (2005). The influence
of intellectual capital on the types of innovative
capabilities. Academy of Management Journal, 48(3),
450-463.
Thomas, S.P., Thomas, R.W., Manrodt, K.B., & Rutner,
S.M. (2013). An experimental test of negotiation
strategy effects on knowledge sharing intentions in
buyer–supplier relationships. Journal of Supply Chain
Management, 49(2), 96-113.
Van Den Hooff, B., & De Ridder, J.A. (2004). Knowledge
sharing in context: the influence of organizational
commitment, communication climate and CMC use on
knowledge sharing. Journal of Knowledge
Management, 8(6), 117-130.
Wang, Z., & Wang, N. (2012). Knowledge sharing,
innovation and firm performance. Expert Systems with
Applications, 39(10), 8899-8908.
West, M.A., & Farr, J.L. (1989). Innovation at work:
Psychological perspectives. Social Behaviour, 4(1), 15-
30.
Widén-Wulff, G., & Ginman, M. (2004). Explaining
knowledge sharing in organizations through the
dimensions of social capital. Journal of Information
Science, 30(5), 448-458.
Yang, J.T. (2007). The impact of knowledge sharing on
organizational learning and effectiveness. Journal of
knowledge Management, 11(2), 83-90.
Zack, M.H. (1999). Managing codified knowledge. Sloan
Management Review, 40(4), 45-58.
Zaim, H., Muhammed, S., & Tarim, M. (2019).
Relationship between knowledge management
processes and performance: critical role of knowledge
utilization in organizations. Knowledge Management
Research & Practice, 17(1), 24-38.
KMIS 2020 - 12th International Conference on Knowledge Management and Information Systems
50