Determinants of Knowledge Transfer in Egocentric Networks.
Comparative Analysis of Professions
MARZENA FRYCZYŃSKA
Collegium of Business Administration
Warsaw School of Economics
Al. Niepodległości 162, 02-554 Warsaw
POLAND
Abstract: - This paper investigates determinants of knowledge transfer in egocentric networks of knowledge
recipient and knowledge provider, what is crucial to knowledge management in organisations. Knowledge
transfer is assumed to depend on knowledge work, networking competence, and the subject’s profession:
teacher, Information Technology (IT) professional, or physician. The paper reports result of a quantitative study
among samples of mentioned professionalists. Regression models testing, including mediation and moderation,
were performed. The findings indicate that knowledge transfer in the egocentric network of the knowledge
recipient increases along with knowledge work, but only when it is mediated by networking competence.
Analyses in each profession support a partial mediation in the case of IT professionals and teachers. Knowledge
transfer in egocentric network of the knowledge provider increases along with knowledge work of the provider.
In the case of physicians, knowledge transfer in the providers’ and recipients’ knowledge networks is affected
neither by knowledge work nor by networking competence.
Key-Words: - knowledge transfer, egocentric network, knowledge network, knowledge provider, knowledge
recipient, knowledge work, networking competence
Received: May 23, 2021. Revised: December 14, 2021. Accepted: January 2, 2022. Published: January 3, 2022.
1 Introduction
Companies and economies are faced with a
challenge of knowledge transfer necessary to run
business, achieve goals and develop communities.
Knowledge transfer appears among and between
organizations, network organizations and its
employees. An aim of the present paper is to
elaborate knowledge transferred by highly
competent professionals in their egocentric
networks.
In egocentric networks, predefined ego-an
employee, provides or receives flows of knowledge
to or from others [55]. This kind of egocentric
knowledge networks are differed based on the ego’s
roles as - a knowledge recipient i.e., receiving others
knowledge or - a knowledge provider delivering
own knowledge to others. Literature provides
numerous examples of factors that affect knowledge
transfer dynamics between knowledge providers and
recipients e.g., motivation, learning process, existing
relationship, level and kind of expertise, trust, or
status [33; 67; 35; 34]. In the context of egocentric
knowledge network, knowledge work is a prominent
variable which characterise knowledge recipients
and providers, which affects their network size what
in turn determine knowledge transfer. According to
literature reports, the extent of knowledge transfer
between individuals depends on their degree of
acquaintance and access to the other person, all of
which is supported by their networking competence,
understood as the establishment and maintenance of
contacts required for one’s work.
Despite knowledge workers are active at labour
market for decades [19; 20; 3], nowadays
knowledge intensive companies as well as
developing economies are in a need of them. The
present paper provides a comparative analysis of
three selected professions: physicians, IT
professionals, and teachers, typically considered as
knowledge workers [16; 42], with a view to
identifying the differences in knowledge transfer in
egocentric knowledge networks based on
knowledge work and networking competence.
The research problem can therefore be formulated in
the following question: How does knowledge
transfer in egocentric networks of knowledge
providers and recipients who work as physicians, IT
professionals, or teachers change based on their
knowledge work and networking competence
levels? This question is answered in the main body
of the paper. The analyses are supported by three
detailed questions:
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How does knowledge transfer occur in egocentric
networks?
How do knowledge work and networking
competence differentiate knowledge transfer in the
egocentric networks of the knowledge provider and
the recipient?
How does knowledge transfer differ in egocentric
networks of physicians, IT professionals, and
teachers?
Based on these reflections, two research models and
hypotheses were developed to illustrate the
associations between independent variables that
affect the egocentric networks of knowledge
providers and recipients who are physicians, IT
professionals, or teachers. In the following study,
these research questions and hypotheses are
explored and explained based on the analysis of data
collected in the quantitative study. Finally,
conclusions from the analysis are presented, and the
resulting scientific contribution is described, along
with possible limitations and indications for future
research.
2 Problem Formulation
2.1 Knowledge Transfer in Egocentric
Knowledge Networks
In a broad sense, a network is a „set of actors and
ties among them” [64], where actors are human or
nonhuman. The ties are the result of a relationship
which emerges from an exchange between the
actors. Network types include knowledge networks
and exchange networks [7; 29]. A knowledge
network is defined as an organisational system
responsible for work processes and the maintenance
of organisational knowledge [62; 54]; a structural
representation of accumulated resources of rules,
procedures, practices, or documents produced by the
joint efforts of former and current employees [63],
connected by a network of relationships [51]. In the
present paper, knowledge networks are analysed
from an egocentric [43] and personal [25]
perspective. This means that the main focus of the
investigation is an egocentric knowledge network in
which an individual employee and their ties to
others with whom they transfer knowledge.
In knowledge management people rely on other
people when they need to obtain knowledge [8],
necessary for quick problem-solving and ongoing
work-related task performance [52; 12]. To perform
their work-related tasks, individuals exchange high-
quality, innovative [41], diverse and unique
knowledge, solve problems and seek innovative
solutions [9; 27] They exchange knowledge with
colleagues from departments of the same
organisation [17; 35; 9], with other organisations in
the network [15], and with other individuals in their
own contact network, some of whom are boundary
spanners [38].
Knowledge transfer, rather than knowledge sharing
[45], is assumed here, considering that “transfer”
involves a purposeful exchange and a recipient
capable of utilising the obtained knowledge [30].
Knowledge is transferred when the knowledge
provider decides to share their knowledge, and the
recipient accepts it [60]. which is especially likely to
occur when the recipient needs the knowledge —
and such circumstances exist in advice networks
[56]. The purposeful nature of knowledge exchange
results from organisational standards and workflows
or from short-term needs, which can arise when
individuals solve problems and challenges in their
work.
Knowledge transfer between two individuals
exposes two roles: that of a recipient and that of a
provider. The recipient is the target node of the
relationship, receiving the object of exchange (i.e.
knowledge), while the provider is the source node of
the relationship, sharing the object of exchange.
Networks of associations are seldom evenly
distributed [49], which also applies to the egocentric
networks of knowledge providers and recipients,
even when the same individual alternates between
the roles of a provider and a recipient.
Those who need knowledge i.e., potential recipients,
first reach out to contacts perceived as able to
provide knowledge and inform about other sources
of knowledge in a way suited to the recipient’s
knowledge absorbing capacity [9]. Individuals from
whom one seeks knowledge are not chosen at
random [5], but rather based on a combination of
opportunities, pre-existing relationship, proximity,
trust, or familiarity with the advisor [35; 28; 9; 57].
Basically, to provide knowledge, one must have it
[13]. Knowledge resources increase along with
individuals’ education level and professional
experience [24]. Involvement in provision of advice
increases if one is recognised by a specific
community as an expert [17] with a high status [33],
which the knowledge provider can achieve through
networking.
Therefore, knowledge transfer occurs in the
egocentric network of the knowledge recipient when
the individual (ego) obtains knowledge from others
(providers), and in the egocentric network of the
knowledge provider when the employee (ego)
provides knowledge to others.
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2.2 Determinants of Knowledge Transfer in
the Egocentric Networks of Knowledge
Providers and Recipients
Knowledge transfer increases as the egocentric
networks of knowledge providers and recipients
grow. The more contacts the ego has and exchanges
knowledge resources with, the more intense the
knowledge transfer. Knowledge transfer in the
egocentric networks of knowledge providers and
recipients grows depending on knowledge work and
networking competence, but the impact of these two
variables differs between these two types of
networks.
The main determinant of intensive knowledge
transfer in networks is the performance of
knowledge work [10], i.e., work that requires
diverse knowledge which is not readily available.
Through this work, performed under conditions of
autonomy, knowledge workers create innovative
solutions that increase their knowledge resources.
Nonetheless, the impact of knowledge work differs
depending on whether the individual obtains
knowledge from others or provides knowledge to
them.
The need to perform knowledge work increases the
demand for super-networks of contact networks,
especially ones that enable access to knowledge that
is in short supply [31]. Research by Gargiulo et al.
[23] indicates that being a recipient and obtaining
knowledge is more beneficial, as knowledge
acquisition in close networks increases the value of
financial bonuses, while knowledge provision to
others decreases this value. As indicated by
Brennecke and Rank [9], Research and
Development department employees who hold the
most patents and have unique knowledge, i.e. those
who perform the most knowledge work, seek
knowledge from others more often than provide it to
them. Thus, having knowledge and creating new
knowledge in the innovation process, which is a
component of knowledge work, is associated with
seeking knowledge from others and acting as a
recipient in knowledge networks. Knowledge
seeking is intensified by the need to continuously
update one’s knowledge, especially among
individuals working in knowledge-intensive sectors
and/or performing knowledge work.
Available research suggests that knowledge transfer
towards an individual is possible and indeed
desirable even if that individual performs
knowledge work, though it is not necessarily strong,
as knowledge acquisition also depends on
characteristics and competences enabling the
employee to successfully reach sources of
knowledge.
Another variable that affects egocentric networks is
networking competence, understood as the
establishment and maintenance of contacts required
for one’s work. It is a set of workers’ behaviours
which are stable at a given moment and allow them
to gather contacts who can support them with
resources. Specific behaviours (or the lack thereof)
determine whether a relationship can be established,
and how it is developed, maintained, or terminated
[22; 66]. Activity in this area, undertaken in
personal on remote contact, directly affects the
extent and type of one’s direct and dual
relationships with each of one’s alters. Networking
competence is assumed to intensify networks of any
type, and its impact on egocentric knowledge
networks is based on the assumption that behaviours
shape the structure of networks [1], including
knowledge networks. Strong networking
competence is developed through interactions with
others and through the exchange of resources, which
over time builds trust and further increases
exchange between partners.
Firstly, networking competence helps grow the
egocentric network of the knowledge recipient.
Through specific behaviours, one establishes and
maintains contact with those who can provide
access to resources or to other actors. And as it is
knowledge that constitutes the object of exchange,
networking competence also has an indirect impact,
mediated through knowledge work.
Secondly, networking competence helps grow the
provider’s network as well, and consequently
increases the scope of knowledge that is being
provided. Even if the establishment of contacts for
the provision of knowledge is secondary, the
maintenance of contacts is of primary importance.
The latter involves behaviours that allow for
maintaining a network through exchange between
partners, i.e. providing advice and knowledge to
others, as well as exchanges understood in the
broader context of the social exchange theory [33].
The strength of knowledge transfer from the
individual playing the role of a provider largely
depends on the quality of their knowledge work.
Those who have and create knowledge, and thus
perform high-quality knowledge work, are very
good contacts for knowledge seekers [17] and hold a
valuable transferable resource. In contrast to the
model developed for the egocentric networks of
knowledge recipients, in the providers’ egocentric
networks, the impact of networking competence is
weaker. Top knowledge workers are not always
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interested in establishing contacts and undertaking
networking behaviours [16], and they prefer task-
centred contact networks to social ones [53],
consistently with the weaker role of networking
competence, which does include socialising [22].
Establishing and maintaining contacts increases
one’s ability to reach potential knowledge
recipients, but only if one has knowledge that is in
demand.
For both knowledge transfer models, in the
egocentric network of the knowledge recipient or
provider, knowledge work is assumed to positively
affect networking competence, as knowledge
workers are required to regularly participate in
knowledge networks [61] and develop relationships
that allow network actors to use one another’s
knowledge resources [5].
The performance of knowledge work enhances
networking competence, as the increasing
specificity of knowledge work entails the need to
establish and maintain contacts with individuals
capable of providing support in this work. Greater
networking competence also enables the
implementation of the personalisation strategy,
which is preferred by knowledge workers [26]. The
association between knowledge work and
networking competence is particularly relevant for
contract workers, as going beyond their immediate
surroundings allows them to access more diverse
knowledge resources and build their identity, based
on knowledge, in a variety of contacts [21].
In the present study, the first assumption is that
knowledge transfer in the egocentric networks of
knowledge recipients and providers is positively
correlated with knowledge work and networking
competence, as described above. Another
assumption is that each of the three studied
professions moderates the strength of the
hypothesised dependencies, as shown below.
Personal egocentric knowledge networks, their
variability, and their impact have been studied in
various areas, e.g., Research and Development units
[9; 28], and in various professions, e.g., judges [33]
physicians [35; 17; 11] school principals [48],
teachers [40], or IT professionals [41].
Okkonen et al. [40] reported that physicians
benefited from being in a broad network. Still, the
study by Mascia et al. [35] demonstrated that
physicians tend to be involved in exchange
networks with other physicians who have similar
knowledge and work in their close environment,
with relationships based on reciprocity. Considering
a broader range of medical professions, empirical
evidence indicates that they are more likely to
provide knowledge if they have more social capital
[67], but on the other hand, an ego’s egocentric
network may include alters who will exchange
virtually any resource with the ego, or ones who will
only exchange selected resources, including
knowledge and advice [11]. For teachers, broad
networks that allow them to provide and obtain
information are the most beneficial [40]. School
principals seek advice in their closest environment,
among individuals with a similar status, and ones
they personally value, regardless of the performance
of the schools they manage. They are also more
likely to respond to requests for advice than share
knowledge unprompted [48]. IT professionals obtain
valuable knowledge in strong knowledge networks,
through face-to-face communication, and in diverse
knowledge networks involving remote
communication. The form of communication is not
relevant for obtaining diverse knowledge from
diverse knowledge networks — if an IT professional
belongs to one, they immediately gain more diverse
knowledge, and increase their own innovativeness
[41].
The cited findings demonstrate specific
characteristics of certain professions in terms of
knowledge provider and recipient networks. There
is, however, no research using the same
methodology to compare knowledge networks and
their variability between three selected professions,
which makes it difficult to formulate specific
hypotheses. One could expect that IT professionals
have the broadest capabilities of providing and
obtaining knowledge in networks. Nonetheless,
further studies are needed.
Assuming the potential variation of physicians’, IT
professionals’, and teachers’ knowledge networks,
the main hypotheses were formulated regarding
knowledge transfer in their egocentric networks of
knowledge recipient (HI) and provider (HII).
HI Knowledge transfer in the egocentric network of
the knowledge recipient increases along with the
level of knowledge work they perform, with a
strong impact of the mediating networking
competence, and is moderated by profession.
HII Knowledge transfer in the egocentric network of
the knowledge provider increases along with the
level of knowledge work they perform, with a weak
impact of the mediating networking competence,
and is moderated by profession.
The dependency model with the main and
supporting hypotheses of model I and II is shown in
Figure 1.
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Research model II
Fig.1: Research models: knowledge transfer in the
egocentric networks of the knowledge recipient (I)
and the knowledge provider (II)
Research model I
HI is detailed by supporting hypotheses assuming
impacts of knowledge work on networking
competence (strong) HI (1), on the size of the
egocentric network of the knowledge recipient
(moderate) HI (2), and of networking competence
on the size of this egocentric network (strong) HI
(3). Another supporting hypothesis states that the
size of the egocentric network of the knowledge
recipient increases along with the level of
knowledge work, partially mediated by networking
competence HI (4). HII is also detailed by
supporting hypotheses assuming impacts of
knowledge work: on networking competence
(moderate) HII (1), on the size of the egocentric
network of the recipient of knowledge (strong) HII
(2), and of networking competence on the size of
this egocentric network (moderate) HII (3). The
final supporting hypothesis assumes that the size of
the egocentric network of the knowledge provider
increases along with the level of knowledge work,
partially mediated by networking competence HII
(4). All supporting hypothesis of model I and II
indicate moderations of each profession i.e., (a)
physicians, (b) IT professionals, (c) teachers.
3 Problem Solution
The empirical part of the research included an
explanatory quantitative study in order to test the
dependencies from the research models. To gather
the required data, a survey was performed in a group
of physicians, IT professionals, and teachers, using
the computer-assisted web interviewing (CAWI)
technique in the first quarter of 2017.
3.1 Setting and Data
The sample was selected in a purposive manner and
was limited to knowledge workers working in
Poland, initially defined as ones with a higher
education degree and at least 10 years of working
experience in their profession. Sample was divided
in three subgroups of physicians, IT professionals
and teachers. It was assumed that each subgroup
should have the same characteristics due to the
demographic variables demographic (age, sex),
employment-related (work experience), and
organisational characteristics (size, sector) in order
to gather data allowing comparisons between
professions. This was due to the lack of information
on employment structure in all three professions,
and simultaneously, it allowed for making inter-
group comparisons.
The invitation to participate in the study was sent to
4.543 organizations from the medical, IT and
educational sectors, assuming that the research
respondents constitute the core staff in these
organizations. In return, response rate was 8.8% of
organizations, but there could not be more than
three respondents from one organisation.
Ultimately, data were gathered on 1189 subjects
performing work at various levels of knowledge
work, divided as follows: physicians N=411, IT
professionals N=427, teachers N=351.
Nearly all respondents held non-management
positions (N=1131) and most were employed as
specialists (N=905, 76%). In the three groups, this
percentage ranged between 85.6% (physicians) and
70.1% (teachers). Most respondents worked
“overtime”, i.e. more than 40 hours per week. This
did not, however, apply to teachers, of whom 324
(92.3%) worked the exact full time equivalent.
Physicians worked the longest hours, with as many
as 250 respondents (60%) spending between 51 and
70 hours weekly at work. Roughly one in two
physicians worked in multiple places (N=226, 55%),
similarly to IT professionals (N=250, 58.5%).
Nearly all physicians (N=400, 97%) and all teachers
worked under employment contracts. Among IT
professionals, more than half (N=250, 58.5%)
worked under civil law contracts, and the remaining
HII(4)
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ones (N=177, 41.5%) worked under employment
contracts (see details in Table 1).
3.2 Variables and Measures
Knowledge transfer increases along with the number
of individuals with whom one exchanges
knowledge. In the research methodology applying
network paradigm [6; 14] used here, the egocentric
knowledge networks are measured by their in-
degree centrality, i.e., the number of ties to a node,
and out-degree centrality, i.e., the number of ties
from a node [1; 37; 64]. This reflects the egocentric
knowledge network and role of the recipient, and
that of the provider, respectively.
The egocentric network of the knowledge recipient
(ENKR) is measured by the numbers provided in
response to the question: (1) How many people
typically give you advice or valuable guidance when
you do not know how to perform a new or difficult
work-related task? (a measure of in-degree
centrality). The egocentric network of the
knowledge provider (ENKP) is measured by
responses to the question: (2) How many people do
you typically give advice or valuable guidance to
when they do not know how to perform a new or
difficult work-related task? (a measure of out-degree
centrality).
Knowledge work (KW) and networking competence
(NC) are latent variables, measured using reflective
indicators — eight each for networking competence
and knowledge work. For example, two reflective
indicators of networking competence are: When I
start a new task or project, I meet in person with
everyone involved, When I am looking for a new or
additional job, I call my acquaintances to ask if they
know about any interesting offers for me. Final
eight indicators were established as a measuring
model based on confirmatory factor analysis
(CFI=,902, RMSEA=,057, NFI=,878). Another two
example indicators for knowledge work are: I
perform routine tasks (reversed), When I work, I
learn new things. Also analysing measurement
model of knowledge work scale by confirmatory
factor analysis brought results as follow: CFI=,905,
RMSEA=,058, NFI =,885. Achieved results confirm
the scales reliability [2; 32].
Responses on NC and KW were collected using a 7-
item scale, where 1 = minimum at 7 maximum
range. In the present analyses, mean reflective
indicator values for each variable were used.
3.3 Analysis and Results
The collected quantitative data were used to test
research models I and II and the associated
hypotheses. IBM SPSS v. 25 software was used,
with the PROCESS extension by F. Hayes. Model
59 was applied, as it is appropriate for the mediation
and moderation strength and relationships between
all the variables, i.e. knowledge work, networking
competence, egocentric network of the knowledge
provider, and egocentric network of the knowledge
recipient.
In both knowledge transfer models, for the
egocentric networks of the knowledge recipient
(ENKR) and provider (ENKP), the association
between knowledge work (KW) and networking
competence (NC) moderated by profession has a
good fit to data (F (3,1185), p<.0001) and explains
nearly half of the variance (R2 =.4930) with a beta
regression coefficient of .3462. Other associations
differ between the two models, and therefore,
statistical analysis results will be provided
separately for models I and II.
In the model for knowledge transfer in the
egocentric network of the knowledge recipient, the
direct impact of networking competence on the
egocentric networks of the knowledge recipient is
significant (p<.0001) and rather strong (beta=.5624).
In turn, the impact of knowledge work on the
egocentric networks of the knowledge recipient size
is not significant (p=.060) despite the regression
coefficient value (beta=.2426). One may therefore
assume that full mediation occurs in the model,
consistently with hypothesis HI (1). Still, the
moderation analyses for each profession indicate
that dependencies in the model are strongly
determined by profession (Table 1).
Table 1. Regression model I testing results,
including mediation and moderation, for the
egocentric network of the knowledge recipient
Analysis of direct and indirect impact on the
egocentric network of the knowledge recipient
among physicians showed that none of the analysed
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variables has a significant impact. The result for the
direct impact of knowledge work on networking
competence was .081 (p=.0853), and on the
egocentric networks of the knowledge recipient —
.0050 (p=.9764). No significance (p=.1383) was
found for the indirect effect (.2950) of networking
competence on the egocentric network of the
knowledge recipient. Considering mediation, the
indirect impact of knowledge work on the
egocentric network of the knowledge recipient is
also insignificant due to the confidence interval
found (–.0044–.0705). Thus, hypotheses HI (1a), HI
(2a), HI (3a), and HI (4a) are all rejected.
In the studied group of IT professionals, the direct
and indirect impact of all the analysed variables on
knowledge transfer in the egocentric network of the
knowledge recipient is significant, with differences
in terms of strength. The strongest impact on the
egocentric networks of the knowledge recipient was
found in the case of networking competence
(beta=.8574, p=.0001). The impact of knowledge
work was significant, but much weaker (beta=.2476,
p=.010). The indirect impact of knowledge work on
the egocentric networks of the knowledge recipient,
mediated by networking competence, is rather weak
(indirect effect=.372, LLCI–ULCI = .2760–.4553),
though stronger than the direct impact of knowledge
work. The egocentric networks of the knowledge
recipient growth among IT professionals depends
mainly on their networking competence, with a
much smaller impact of knowledge work. This
supports hypotheses HI (1b), HI (2b), HI (3b), and
HI (4b), indicating that IT professionals performing
knowledge work must demonstrate networking
competence to obtain knowledge from their
contacts, as networking competence is the most
significant factor in obtaining knowledge.
The system of dependencies among teachers is
similar to that found among IT professionals, though
the impact of knowledge work and networking
competence is stronger: NC->ENKR: beta= 1.4199,
p<.0001) and KW->ENKR: beta=.4902, p=.001.
The mediation of networking competence between
knowledge work and the egocentric networks of the
knowledge recipient is also significant and strong
among teachers (indirect effect=1.0995, LLCI–
ULCI=.8290–1.3749), but less so than the direct
impact of networking competence on the egocentric
networks of the knowledge recipient. Thus,
hypotheses HI(1c), HI(2c), HI(3c), and HI(4c) are
confirmed, and the results indicate that the partial
mediation model I of knowledge transfer is the
strongest among teachers, compared to the other
professions. Therefore, knowledge transfer to
teachers from their contacts strongly depends on
both their networking competence and knowledge
work.
The mediation model does not apply to knowledge
transfer in the egocentric network of the knowledge
provider. The intermediate variable, networking
competence, does not significantly affect the
egocentric network of the knowledge provider
(beta=.2981, p=.105), undermining the assumption
regarding mediation. The direct impacts of
knowledge work on the egocentric network of the
knowledge provider (beta=.3981, p=.012) and on
networking competence (beta=.3462, p<.0001) are
confirmed. As a result, hypothesis H II is partially
confirmed, as it referred to a weak mediation of
networking competence in knowledge transfer from
the provider to other nodes of the egocentric
network among all professionals in the sample.
Further analyses regarding differences between the
professions with regard to the relevant dependencies
indicate that no variables in model II are significant
in the case of physicians. This means that no
significant impact on knowledge transfer through
the egocentric network of the knowledge provider
growth was found either for knowledge work
(beta=.2643, p=.204) or for networking competence,
which was overall insignificant in model II, with no
mediation (indirect effect=.3124, CI –.0081–.1094).
Thus, hypotheses HII (1a), HII (2a), HII (3a), and
HII (4a), regarding determinants of knowledge
transfer from physicians to others, are all rejected.
IT professionals provide knowledge more as their
knowledge work intensifies (beta=.6625, p<.0001).
Knowledge work also enhances networking
competence (beta=.4282, p<.0001). Networking
competence does not intensify knowledge transfer,
neither directly nor through mediation with
knowledge work (indirect effect=.3124, LLCI–
ULCI=.2029–.4280), as its impact is weaker than
the direct impact of knowledge work on the
egocentric network of the knowledge provider size
and knowledge transfer increase. So firstly, IT
professionals provide more knowledge if their work
has more characteristics of knowledge work, and
secondly, networking competence is significant, but
it limits knowledge transfer compared to the direct
effect of knowledge work. This means that
hypotheses HII (1b) and HII (2b) were fully
confirmed, and hypothesis HII (4b) was partially
confirmed.
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Table 2. Regression model testing results, including
mediation and moderation, for the egocentric
network of the knowledge provider
Knowledge work increases teachers’ networking
competence (beta=.7744, p<.0001), confirming
hypothesis HII (1c). The direct impact of knowledge
work on knowledge transfer in the egocentric
network of the knowledge provider among teachers
is much stronger (1.0606, p<.0001) than among IT
professionals, which confirms HII (2c) and further
explains the differences in knowledge transfer
between professions. The mediating role of
networking competence in knowledge transfer in the
egocentric network of the knowledge provider
among teachers is significant (indirect effect=.7957,
LLCI–ULCI=.7067–.8420) but lower than direct
effect. As to networking competence, it can also be
involved in the transfer, but the resulting knowledge
transfer is less intense than with the direct impact of
knowledge work, which means that hypotheses HII
(3c) and HII (4c) cannot be fully confirmed.
4 Discussion
4.1 Scientific Contribution
The above research procedure has provided the
basis for answering the research questions and
drawing conclusions that make up the scientific
contribution of the present paper. These are as
follows:
1. Knowledge transfer differs based on whether one
obtains knowledge from others or provides it to
them, as well as based on the quality of one’s
knowledge work and networking competence.
Knowledge transfer in the egocentric network of the
knowledge recipient is determined by knowledge
work, with mediation by networking competence.
To obtain knowledge from others, the individual
(ego) should perform knowledge work, i.e. use
knowledge and create new knowledge within a
diverse, autonomous, and creative work process.
This is however not sufficient — they must also
establish and maintain contacts required for their
work. On the other hand, regardless of the quality of
knowledge work performed, if an individual needs
to acquire new knowledge, they cannot do this
without networking competence, which is thus
prerequisite for knowledge transfer. These findings
emphasise the importance of relationships and
proximity for obtaining knowledge and advice,
consistently with recent reports by Mascia et al.
[35], Kang, Kim [28], and Brennecke, Rank [9].
As to knowledge transfer in the egocentric network
of the knowledge provider, it only depends on
knowledge work. The establishment and
maintenance of contacts with people who can assist
one in performing knowledge work is not significant
for the provision of one’s knowledge to others.
Knowledge transfer from the provider (ego) to
recipients is possible whenever the provider has
knowledge that is needed by others. Simply put, one
cannot give what one does not have. Knowledge
transfer from the provider tends to be responsive
rather than proactive [68], as the latter would
require seeking and keeping touch with individuals
to whom one could provide knowledge. Though
providers do perform high-quality knowledge work
and share their knowledge with others, they do not
apply their networking competence as a mechanism
for maintaining reciprocity in the knowledge
exchange network [12]. On the other hand, if they
are willing to provide knowledge, they receive other
benefits consistent with their values, in line with the
social exchange theory [33].
2. Knowledge work and networking competence
affect knowledge transfer in the egocentric
networks of knowledge providers and recipients
differently in each of the studied professions, i.e.
physicians, IT professionals, and teachers.
Neither models were found significant for
physicians. Thus, knowledge transfer, both in
knowledge recipient and knowledge provider
networks, is not determined by knowledge work or
networking competence of physicians. Physicians
obtain knowledge from their contacts and provide it
to them, but without interrelations to knowledge
work or networking competence. This is puzzling,
considering that knowledge transfer in networks had
been a major theme in previous research [35; 67; 17;
11]. This discrepancy might result from the broader
context of health care system and physicians’
working conditions in Poland, namely, labour
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shortages [59], excessively long working hours [36],
and the fact that physicians do not tend to
proactively establish new professional contacts in
their networks and rather appreciate relations with
closest co-workers: other physicians, supervisors,
nurses and patients [4;18]. Work satisfaction
assessed in various studies indicates that Polish
physicians are at most moderately satisfied [18],
which significantly decreases if they work for the
public sector [47] but increases if they work abroad
[4]. Relatively low level of work satisfaction might
weaken the level of knowledge work which also
covers organizational context which is said to be
one of the biggest maladies of Polish healthcare
system. Researched sample (55%), as well as other
studies and institutional statistic (53.1%) [58]
indicate that physicians perform multiple jobs which
increases their work time even more. This fact
might limit networking competence which, in order
to be on a high level, requires additional time [65].
Conversely, work as a teacher entails stronger
effects of the studied variables. Knowledge transfer
in the egocentric networks of knowledge recipients
is intensified by knowledge work and networking
competence, both separately and in combination. In
contrast to the general model, the one for teachers
involves partial mediation. As in the general model
for knowledge provision, however, knowledge
transfer in the provider’s network increases along
with knowledge work. Teachers provide knowledge
to more recipients when they work under conditions
of autonomy, use advanced knowledge, solve
complex tasks, and create new knowledge and
innovations. Importantly, though, the direct and
indirect effects of the studied variables in the case of
teachers are very strong — stronger than in the
entire group and the strongest among the three
professions, which had not been expected at the
design stage. This is even more interesting
considering that the mean results for the three
variables in the models, i.e. knowledge work,
networking competence, and knowledge network,
are lower than in the two other studied professions.
Strong impact of knowledge work and networking
competence on knowledge transfer in the teachers’
egocentric network of the knowledge might be an
effect of structure of in-degree centrality measure.
As many as two fifths teachers (40.2%) acquire
knowledge from one person. Thus, each respondent,
who acquires knowledge from more than one person
works as a leverage effect for correlations between
variable, hence do increasing impact of knowledge
work and networking competence on knowledge
transfer directed to teachers. That is why there are
teachers, even though there were not many of them
in the study sample, who represent key priorities for
contemporary professional teachers implement
“team leadership, instruction, networking and
effective communication with parents and other
stakeholders, improve their skills, collaborating with
colleagues and parents, and thinking creatively
about the challenges they face” [39], increase the
levels of examined variables, as well as
dependencies of the examined variables on the
knowledge transfer.
Knowledge transfer in the egocentric networks of IT
professionals has a similar structure to that found in
the case of teachers, though with weaker effects.
Still, IT professionals obtain knowledge from others
through knowledge work and networking
competence, both separately and in combination. As
to knowledge transfer from IT professionals to
others, it depends on knowledge work, but not on
networking competence. Networking competence,
knowledge work and egocentric knowledge
networks among IT professionals are significantly
higher than among physicians and teachers. IT
professionals more often than representatives of
other professions are satisfied with their job [47].
They declare the will as well for further training and
development, which is usually realized using
Internet; blogs and thematic portals are used by 80%
of IT professionals, Internet forums by 54%, on –
line courses by 48% and through the contact with co
– workers (64%) [46]. Therefore, they give
involvement in gaining knowledge on every level of
their knowledge work, as well as through
establishing and maintaining contacts.
Teachers and IT professionals obtain more
knowledge from others if they establish and
maintain more contacts, and if they perform more
knowledge work. In other words, they obtain new
knowledge owing to their well-developed
networking competence, their advanced knowledge
work, or both.
4.2 Implications
In this article, the key problem in knowledge
management, therefore, the knowledge transfer is
analysed with the use of egocentric networks
method.
This study investigates knowledge transfer in
general sample as well in three different professions.
A significant stake is the presentation of various
dynamics of knowledge transfer, depending on
whether knowledge is received from or provided to
others.
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Knowledge needed for one’s work can be obtained
from others, especially if one actively establishes
and maintains useful contacts. By developing
networking competence, either on the initiative of
the individual or of their employer, one can increase
the knowledge resources available to fulfil one’s
needs in the egocentric network of knowledge
recipient.
On the other hand, knowledge transfer to others in
the egocentric network of knowledge providers
develops as knowledge work increases.
Knowledgeable professionals are not focused on
networking in order to spread their knowledge.
Thus, it is recommended for organisations to
establish solutions for identifying key sources of
knowledge in order to moderate the knowledge
transfer. Otherwise knowledge flows would might
be close up to clique of well introduced to
knowledge provider. For example, knowledge
centres can emerge wherever employees are allowed
to autonomously tackle difficult tasks and seek
innovative solutions which both require knowledge
and create new knowledge resources. Those
working there can then provide this knowledge to
others, increasing access to knowledge resources.
One important consideration is the need to protect
organisational knowledge resources against
unauthorised access. Employees’ egocentric
knowledge networks may span organisational
boundaries, increasing the risk of knowledge leaks.
It is therefore recommended that organisations
establish practices regulating the extent of
organisational knowledge that is shared.
Individuals who need to obtain knowledge from
others find sources of this knowledge especially
well when they have a high level of networking
competence. If networking competence is not
sufficiently developed, the creation of organisational
or social knowledge centres or expert databases is
worth considering. This could facilitate access to
knowledge sources regardless of an employee’s
work characteristics or networking competence
level.
Knowledge transfer in both directions requires trust,
cooperation, and reciprocity. Therefore, it is
recommended to develop a broader system of social
exchange, so as to balance the roles of recipients
and providers. An individual remaining in one role
for an extended time may experience an imbalance
in the exchange, which may result in termination of
some contacts, especially those involving
knowledge provision to others. Seeking the same
advice from the same expert by multiple individuals
should also be avoided, as the repetition of the same
content to a number of recipients could be
discouraging. This is why it is a good idea to create
knowledge bases or to share relevant knowledge
with a broader community when a new work-related
challenge arises.
Presented recommendations might be applied to
teachers and school principals as well as IT
professionals and their employers but not directly
for physicians. In case of physicians, and employing
them organisations, the major recommendation is
focused on improving work conditions building
decent work and supporting socialisation with co-
workers.
4.3 Limitations and Indications for Future
Research
The reported findings have certain limitations,
which on the one hand may prompt a discussion
regarding their reliability, but on the other, could
motivate further research.
The size of knowledge recipient and provider
egocentric networks was declared by the
respondents, as in the study by Halgin and Borgatti
[25]. This means that the number of contacts with
whom one exchanges knowledge was not verified
by the alters — i.e. the other party in the knowledge
transfer was not asked to confirm that they have
actually taken part in said transfer.
Further studies could investigate knowledge transfer
in both directions, though this would require a
closed study population. Another potential area of
research could involve the characteristics of alters
the respondents transfer knowledge to or from. In
the context of protecting organisational knowledge,
it would be particularly interesting to investigate the
extent to which knowledge transfer spans
organisational boundaries.
Furthermore, the findings from the qualitative study
only allowed for formulating general
recommendations regarding the variability of
egocentric networks in the studied professional
groups. Though they supported the separate
analyses performed in the three selected professions,
a more in-depth exploration of knowledge transfer
determinants in egocentric networks would be
warranted.
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Marzena Fryczyns a - full contribution
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2015/17/B/HS4/02039.
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