Knowledge Management in Value Creation Networks: Establishing a New Business Model through the Role of a Knowledge-Intermediary

Abstract

The spatial distribution and growing granularity of value chains within manufacturing networks increase the complexity of inter-organizational value creation processes and pose new challenges for their coordination and a common innovation development. “Knowledge” is the essential resource to cope with this complexity. However, in an inter-organizational context conflicts between knowledge management objectives and general management objectives can arise, which have to be compensated. The presented article describes the role of a knowledge intermediary, which represents a support function within value creation networks. The intermediary supports value creation structures, processes and the artifact, which ensure an appropriate symbiosis between knowledge management objectives and general management objectives.

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2212-8271 © 2014 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/3.0/).
Selection and peer-review under responsibility of the International Scientific Committee of “The 6th CIRP Conference on Industrial
Product-Service Systems” in the person of the Conference Chair Professor Hoda ElMaraghy”
doi: 10.1016/j.procir.2014.01.006
Procedia CIRP 16 ( 2014 ) 38 – 43
ScienceDirect
Product Services Systems and Value Creation. Proceedings of the 6th CIRP Conference on Industrial
Product-Service Systems
Knowledge Management in Value Creation Networks: Establishing a New
Business Model through the Role of a Knowledge-Intermediary
Krenz, P.a*; Basmer, S. a; Buxbaum-Conradi, S. a; Redlich, T. a; Wulfsberg, J.-P. a
aHelmut-Schmidt-Universität, Holstenhofweg 85, 22043 Hamburg, Germany
* Tel: +49 40 6541 2490; fax: 40 6541 2839. E-mail address: pascal.krenz@hsu-hh.de
Abstract
The spatial distribution and growing granularity of value chains within manufacturing networks increase the complexity of inter-organizational
value creation processes and pose new challenges for their coordination and a common innovation development. “Knowledge” is the essential
resource to cope with this complexity. However, in an inter-organizational context conflicts between knowledge management objectives and
general management objectives can arise, which have to be compensated. The presented article describes the role of a knowledge intermediary,
which represents a support function within value creation networks. The intermediary supports value creation structures, processes and the
artifact, which ensure an appropriate symbiosis between knowledge management objectives and general management objectives.
Keywords: Knowledge Management; Co-operation Networks; Value Co-Creation; Innovation and Value Creation; Distributed Manufacturing
1. Introduction
The success and competitive ability of value creation
networks depend on the ‘productive knowledge’ that is
available during the inter-organizational value creation
processes [1,2]. Productive knowledge refers to the cognitive
ability of transferring knowledge into actions (or using
knowledge appropriately in a specific context) [3]. The single
actors within a network have only a limited capacity to
accumulate productive knowledge due to the complexity and
diversity of knowledge stocks [4]. Thus, the single actor (or
enterprise) focuses on his core competencies and outsources
secondary and tertiary business processes [5]. Knowledge,
which has been created in the company over years and
decades, is distributed to autonomous partners and becomes
intransparent and often not directly accessible. This results in
a spatial distribution of knowledge carriers and value creation
processes [6].
The increasing granularity of value chains does not only
result in a growing intransparency, it also reflects the
increasing complexity of the product development process.
This complexity poses new challenges for the design and
coordination of inter-organizational value chains [7,8].
Knowledge Management (KM) sets the preconditions for
the solution of complex problems evolving in the context of
the (re-)integration of distributed, single operations into
efficient inter-organizational business processes within the
network [9]. The common potential of the actors can be best
exploited through a (re-)aggregation of the spatially
distributed knowledge resp. the relevant experts [10,11].
2. Knowledge Management within the regional
aeronautical cluster Hamburg Aviation
The actors of the aeronautical cluster in Hamburg
(Hamburg Aviation) are currently facing that exact
challenges. The exceptional density of factors of production
within the cluster offers great potentials for collaborative
problem-solving and innovation. Although cluster initiatives
are established to actually meet the growing complexity of
inter-organizational value creation, the inter-organizational
cooperation activities are assessed as insufficient by many of
the aeronautical clusters’ actors. Even though the potentials of
an efficient management of the common resource
‘knowledge’ [12] are recognized, there seems to be a lack of
ability to put them into practice.

39
P. Krenz et al. / Procedia CIRP 16 ( 2014 ) 38 – 43
knowledge management tasks
identification of
knowledge
distribution of
knowledge
development of
knowledge
application of
knowledge
general management tasks
normative mgmt
cohesion
strategic mgmt
changeability
operative mgmt
coordination
impact factors
participating
actors
relations between the
actors
sectoral
environment
global
environment
Fig. 1 Schematic illustration of the interdependencies between different areas of influence, KM tasks and GM tasks
Within the framework of a BMBF (Federal Ministry of
Education and Research) sponsored research project a
Knowledge Management Systems (KMS) has been developed
for the aeronautical cluster in Hamburg. Correspondingly, the
developed KMS supports the cooperation of the clusters’
actors by enabling them to manage the common resource
‘knowledge’ efficiently following the overall aim of
optimizing the harmonization of value chains as well as
fostering collaborative innovation in the cluster.
The regional cluster initiative Hamburg Aviation (HA)
consists of the core companies AIRBUS and LUFTHANSA
Technik, Hamburg Airport, several associations, research
institutes and universities, as well as 300 small and medium-
sized enterprises (SMEs), which are linked both vertically and
horizontally with one another.
Grasping and mastering the complexity of the various and
constantly changing forms of cooperation within a value
creation network (i.e. HA) cannot be achieved through a
constructivist approach, which aims at a rather static system.
Instead of order, determinism, deduction and stasis, the
analytical framework has to focus on indeterminism, sense-
making and the openness towards change [13]. That also
means that the solution is not necessarily linked to a series of
mathematical conditions, but rather to patterns of emergence,
which provoke further changes.
„Theory in turn becomes not the discovery of theorems of
undying generality, but the deep understanding of
mechanisms that create these patterns and propagations of
change.“ [14]
3. Requirements for inter-organizational KM
Based on the exposed premises, a systemic analysis for a
deeper analytical understanding of the interdependencies
between the single elements of the system Hamburg Aviation
is required [15]. This analysis serves as a fundament for the
subsequent deriving procedure of the KMS. In a first step, the
effects of context-specific impact factors (e.g. level of trust,
power asymmetries along the value chain) on the realization
of the KM tasks as well as the realization of the general
management tasks (GM tasks) in the course of cooperation are
detected (see figure 1). Major tasks of the KMS are composed
of the identification, distribution, development and
application of knowledge [16]. The organization and
regulation of the system (GM tasks) can be divided into the
domains of operational management (coordination of the
value creation processes), strategic management (securing the
changeability) and normative management (ensuring
cohesion) [17,18].
Within interdisciplinary workshops a qualitative model has
been developed based on a method by NEUMANN/ GRIMM
that describes the interdependencies between context-specific
impacts on the realization of the KM as well as the GM tasks
in detail [19]. The development of the model is based on a
qualitative interview study, which has been carried out with
experts of the different sectors of the aeronautical cluster
[20,21].
The qualitative model allows us to identify key impacts on
the realization of KM and GM tasks [22]. Moreover
conflicting factors can be extracted that have an opposing
impact (i.e. positive impact on KM tasks; negative impact on
objectives of the GM tasks). Figure 2 shows an extract of the
key impacts on ‘knowledge development’ and the ‘ensuring
of cohesion’ as an objective of the normative management as
well as the identified conflicting factors “autonomy” and
“heterogeneity”.
(+) intensity of collaboration
(+) level of agglomeration
(+) fulfillment of purpose
(+) level of form al networ king
(+) level of comm on go als
(+) systemic trust
(+) common identity
(-) autonomy
(-) hetero genei ty
cohesion
norm ative manage ment
(+) r elation ship of dependency
(+) culture of openness
(+) knowledge transparency
(+) reflexive communication
(+) error tolerance
(+) autonomy
(+) he te roge neity
(+) aggregation
development of knowledge
knowledge management
(-) relation ship of depe ndency
(- ) hi er arc hic al s tr uct ures
(-) power asymmetries
conflicting factors
Fig. 2: Conflicting factors between ‘development of knowledge’ and
‘cohesion’
Based on a comprehensive analysis of the key impacts
within these two fields (KM and GM tasks) three central
conflicts have been identified between KM and GM tasks.
Though an entire resolution of these conflicts is never
possible and also not aspirated, it is necessary to establish an
appropriate, context-specific compensation (see figure 3).
Accordingly, three major requirements for the knowledge
management were derived:
(1) Compensation between cognitive proximity and
distance: Cognitive distance (resp. proximity) refers to the
degree of similarity of mental models, i.e. their structure and
content. A high degree of autonomy and heterogeneity usually
comes along with a certain cognitive distance between the
actors and is the fundament for high problem solving skills of

40 P. Krenz et al. / Procedia CIRP 16 ( 2014 ) 38 – 43
cooperating actors that are not blocked through group
thinking and conformity. However, these exact factors have a
strong negative impact on the cohesion of the system (resp.
sub-system), whereas cognitive proximity facilitates an
efficient communication and the establishment of a common
identity in the long run [23].
General Mgmt Knowledge Mgmt
identification of
know ledge
changeability
(strategic mgmt)
conflic ting fact or:
dynamics of structures und processes
distr ibution of
know ledge
coordin atio n
(operative mgmt)
conflict ing factor:
know ledge tran sparen cy
development of
know ledge
cohesio n
(norm ativ e mgmt)
conflic ting factors:
autonomy, diversity
Requirements for KM
proximity distance
bal ance b etween ...
dynamics stability
bal ance b etween ...
trans par enc y
non-
disclos ure
bal ance b etween ...
Fig. 3 The three major conflicts of objectives and the need for their
compensation
First requirement: During the cooperation a dynamic
compensation between cognitive distance and proximity has
to be assured, which fosters the innovation potential and
prevents conformity and group thinking without affecting the
cohesion of the whole cooperation system.
(2) Compensation between dynamics and stability:
Dynamic structures and processes within the value creation
system (VCS) are the basis for its changeability and the
precondition for the adaptation to changing environments
(market conditions, political framework). However, this
strongly affects the process of knowledge identification.
Stable structures and well-established processes as well as
generally accepted standards facilitate the identification of
knowledge significantly.
Second requirement: Consequently, there is a need for
compensating constant long-term structures as well as
dynamic system features in a way that the identification of
knowledge can be realized without affecting the dynamic of
the whole system.
(3) Compensation between knowledge transparency and
non-disclosure: The availability of internal expert knowledge
and knowledge of internal operations is crucial to the
coordination of value creating activities and the emergence of
synergies. However, a high level of transparency increases the
risk of inadvertent knowledge drain (or industrial espionage),
which in turn strongly affects the willingness to share
knowledge – an essential precondition for the distribution of
knowledge within the system.
Third requirement: There is a need to regulate the
availability of knowledge (transparency) in a way that the
necessary willingness to share can be raised and competitive
knowledge can be protected (i.e. loss risks can be minimized).
During our empirical research we found these conflicts of
objectives in different areas and on different levels of the
value creation system. A very heterogeneous, interdisciplinary
task force composed of actors having a high cognitive
distance (due to different professional, institutional and
cultural backgrounds) may serve the problem solving
performance of the team (i.e. changeability, ability to
innovate), but also highly complicates their communication
and coordination (i.e. viability). The emergence of synergies
as well as an efficient coordination demands for a certain
amount of knowledge transparency and the willingness to
share knowledge, which in turn strongly contradicts to the
single actor’s need to protect intellectual property. These
problems on the micro-level of the task force are also
reflected on the macro-level of the whole value creation
network (i.e. the cluster).
Consequently, there is a constant need for the
compensation between cognitive proximity and distance,
dynamics and stability, transparency and non-disclosure in
order to assure the viability of the value creation system on its
different levels and in its different stages. KM should thus
regulate the knowledge flows in a way that ensures the
cohesion, changeability and cordination of the VCN.
Therefore, the design of the value creation artifact, its system
structure and the related processes as well as their
interdependencies have to be taken into account. KM is often
misunderstood as another add-on in management activities,
but it cannot be considered isolated from general management
activities. There is still a lack of management models for an
appropriate symbiosis of the KM and GM objectives
especially in an inter-organizational context. In the following
section, the hitherto missing super-ordinated knowledge
function in inter-organizational value creation systems is
presented.
4. Operational principles of a knowledge function in value
creation systems
The basic task of the knowledge function is to achieve an
accurate compensation between the conflicts of objectives in
order to realize the tasks of KM and GM successfully (see
previous section). In this sense, the knowledge function
performs a contribution to the regulation of value creation
systems and is conducive to its goal-oriented design. In the
following section the regulating mechanism of the knowledge
function is explained in three steps (figure 4). Using a
qualitative approach it is worthy to note that system variables
are fuzzy in nature and not quantifiable, we therefore focus on
the peculiarity of a system variable (i.e. a high vs. a low level
of heterogeneity).
controlled system: value creation system
controller: knowledge function
input: fuzzy
pro c ess fa cto rs
out put: v ariatio n
impact variables
assessment of the system
status
assessment of the system
varia bl es
varia tion of the impact
factors
Fig. 4: Schematic figure of the steps of regulation
(1) Assessment and transformation of the system variables:
Within the first step of regulation the qualitative system

41
P. Krenz et al. / Procedia CIRP 16 ( 2014 ) 38 – 43
variables (fuzzy system input) are assessed with regard to
their peculiarity and transformed into a standardized linguistic
description (i.e. high – medium – low). Corresponding to
figure 1 these are: (a) the relevant impact factors (e.g. power
asymmetries alongside the value chain, common basis of
trust), (b) the level of realization of the tasks of KM as well as
(c) the tasks of GM (cohesion, changeability, coordination).
After assessing the peculiarities of the system variables, a
further evaluation is carried out that focusses on the current
stage (actual context) in which the system is located
(initiation, constitution, operation, transition) since each stage
demands for different degrees of cognitive distance, systems
dynamic and transparency.
(2) Assessment of the system status: In order to fulfill the
system’s purpose it is inevitable to ensure the viability of the
system. According to Stafford Beer [24] a system will be
viable, if appropriate degrees of cohesion, changeability as
well as coordination skills are highly developed. Thus, as part
of the second step of regulation the peculiarity of these
necessary system characteristics is assessed with regard to the
current system stage: Is the peculiarity of the system
characteristics (cohesion, changeability and coordination)
suitable to the particular development stage of the value
creation system and is an appropriate compensation achieved
between tasks of KM and GM? Whereas in step 1 of the
regulation only not related data (single variables) were
assessed, step 2 is based on a holistic perspective that takes
the interdependencies of the different elements into account.
low
mediu m
high
intended level of
cohe sion (qu al.)
stag es o f deve lopme nt of
the value creation system
intitiation constitution operation transition
Fig. 5: Development of a suitable level of cohesion with regard to different
stages of development
Figure 5 shows for example the demand for cohesion
according to the particular stage of development. During the
early stages of the system development (initiation and
constitution) a higher cognitive distance between the actors
should be aspired which is usually correlating with a low level
of cohesion. The intention is to unlock the hidden innovation
potential of the actors by an appropriate configuration of
heterogeneous and specialized partners and to develop the
common value creation structures, processes and artifacts
within a controversial and open process. In contrast, the stage
of operation is characterized by the actual realization of the
common artifact. The definition of the task is already known,
the necessary operational processes are defined and an
efficient processing of subtasks is needed. Because of the
complexity of the task standardized processes and common
structures are established to coordinate the single tasks of the
common value creation. If the cognitive proximity of the
actors increases in this stage, the level of cohesion is
simultaneously rising. Nevertheless, if the surrounding
environmental conditions change, common structures and
processes or the artifact itself need to be adapted so the
distance between the actors needs to be raised again leading to
a medium level of cohesion in the stage of transition.
On the basis of the information on the peculiarity of the
systems’ cohesion, changeability and coordination
performance and the current development stage of the system,
the assessment of the system state is now possible. For
example: a high level of cohesion within the stage of
transition would block the process of transformation of the
system. Accordingly, there is a need for compensation
between cognitive proximity and distance in order to induce a
higher distance between the actors through the variation of the
conflict-causing variables (impact variables).
(3) Variation of the impact variables: During this step of
regulation, the knowledge function needs to modify those
impact variables that cause the imbalances between KM and
GM objectives with regard to the specific stage of the value
creation system. Those impact variables have been identified
already in the qualitative interdependency model developed
within this research project (see section 2). Table 1 shows an
extract of the identified variables. They are categorized based
on the following spheres: value creation system, artifact and
process. By varying the peculiarities of these impact
variables, the structure, process and artifact can be modified
in order to achieve the compensation appropriate to a specific
context.
scop e of service
process struct ure
proxi mit y and distanc e dyna mics and stability t rans parenc y and non-
disclosur e
gra nular ity of the
comm on task
comm on obj ectives
power asymmetries,
leve l of depend enc y
width and depth of
cooperation activities
reg ional agglomer ation
of the actors
inter-organi zati onal
coordin atio n
coop eration st ruc ture
modular ity
technological
changeability
culture of error
tolerance
leve l of depend enc y
adaptability
inter-organi zationa l
coordin atio n
coop eration st ruc ture
prop erty right s stru cture
granular ity
trust
conflict culture
depth of coop erati on
activities
informal network
form al net wor k
comm unicati on culture
art ifact
Tab.1: Impact variables to compensate the three conflicts of objectives
5. Realization of the knowledge function in value creation
networks (VCNs) by the role of a knowledge intermediary
The knowledge function is a systemic approach to explain
a necessary super-ordinated mechanism within a value
creation system that establishes an adequate symbiosis of the
objectives of the tasks of KM and GM. In the following, the
role of the knowledge intermediary is presented, whose
central task is to implement the knowledge function within the
organizational structure of the value creation network. In
other words the knowledge intermediary is the institutional
realization of the knowledge function within a value creation
network. The intermediary analyzes the network continuously
(regulation: 1. Step), assesses the cooperation according to the
compensation of conflicting factors (regulation: 2. step) and
finally develops concrete courses of action to realize the

42 P. Krenz et al. / Procedia CIRP 16 ( 2014 ) 38 – 43
necessary variation of the relevant impact variables
(regulation: 3. Step). In doing so, the intermediary supports to
design the value creation structure, process and artifact of the
network in a goal-oriented way (compensation between an
efficient regulation of the resource ‘knowledge’ and securing
the viability of the network).
If the overall aim of inter-organizational KM is to increase
the realized added value of the whole system (thereby also
implying a satisfaction of individual needs), a broad
participation of the different knowledge carriers needs to be
assured [25,26]. This implies that the knowledge intermediary
has to fulfill two fundamental attributes for a successful
realization of the knowledge function:
Taking a holistic perspective (on the VCN): A holistic
perspective takes the needs of the various actors of the value
chain into account and enables the compensation of the three
conflicts of objectives between the KM and the GM tasks that
may occur on very different levels of the VCN.
Neutral and objective realization of the knowledge
function: The intermediary needs to realize the knowledge
function objectively and independent from particular interests
of the actors. Courses of action have to be developed on the
basis of an objective assessment of the respective context.
However, these characteristics lead to special requirements
regarding the realization of the role inside the network. The
primary value-adding activities consist of product
development, manufacturing and marketing. Actors involved
in a VCN are usually experts for a single section of the value
chain and they focus their efforts on optimizing their part of
the value creation process in order to enforce their
competitiveness. They are guided by particular interests
within a limited point of view. In other words, they lack an
objective, holistic point of view [27,28]. However, the
knowledge intermediary needs to take a neutral, holistic
perspective to fulfill the requirements for an inter-
organizational KM within the network. Consequently, the
realization of the knowledge function through the role of an
intermediary needs to be realized by actors that are not part of
the primary value creating processes. Otherwise the
acceptance would be low due to an insufficient neutrality of
the actors (e.g. fear of opportunistic behavior) or a low quality
of the courses of action on account of an insufficient holistic
perspective. These specific attributes, which the knowledge
intermediary is required to fulfill within value creation
networks, open up the field for new business models.
The business model [29] of the knowledge intermediary is
based on enabling the actors of the primary value-adding
processes to realize the requirements of inter-organizational
KM within the frame of their cooperation, while effectively
compensating the conflicts of objectives. They collect
information affecting the realization of the KM tasks in the
network. Furthermore, they analyze the arrangement of
balances in the system and check to what extent adjustments
have to be made. Finally, the identified adjustments are
realized through a collaborative development of courses of
action that aim at a variation of the conflicting factors.
As a matter of fact, the intermediary and the derived
business model should not be understood as an institution that
develops the KMS for the network in a top-down manner. Nor
does it mean that the intermediary is represented through one
single actor in the network. This role needs to be implemented
on different levels of cooperation inside the value creation
network and all segments of the value chain. A variety of
intermediaries is needed, which fulfill the role for single
segments in the network and develop a holistic view.
6. Implementing the role of a knowledge intermediary in
Hamburg Aviation
The presented research results have been realized in the
aeronautical cluster Hamburg Aviation by implementing the
role of a knowledge intermediary at the Centre of Applied
Aeronautical Research (ZAL GmbH). The ZAL offers a
platform for scientific-technological cooperation in Hamburg.
It is a company consisting of a heterogeneous number of
shareholders (i.e. core companies, public sector, universities).
We were so far able to institutionalize the inter-organizational
task force (TF) ‘Aerospace Production’ which aims at
orienting the regional research activities stronger to the needs
of the local industry and identifying and exploiting synergies.
structure
coope rat ion structu re
formless aggregation of autonomous actors
(common de mand)
esta blish an open c ommunity struct ure,
coop erat ion contra ct
inter-organi zatio nal co ordina tion
avoid anc e of top-do wn coo rdina tion by a
neutral instance instead of a focal actor
desig nation of projec t leade rs,
coordin atio n by a neut ral insta nce
aggl omer ati on of the ac tor s
local aggregation through meetings,
decentralized operations based on a virtual
coll abor ati on system
shortening of meeting periods,
participation of the operational level by
means of an IT-syst em
width of coo perat ion ac tivi ties
meet ings as open f ora
red ucti on of th e amount of par tner s
acco rding to the requir ed number for the
implementation of defined tasks
common aims and expectation, common identity
definition of s trategic o bject ives, name of
the gr oup, guidi ng principl e
differentiated milestones related to the
tasks, common public image
powe r asymm etry
demo crat ic principl es (participation), coor din atio n by a neut ral act or (ZAL)
level of de pendency
facilitate access to common knowledge ressources by means of a virtual cooperation
plat form
granul ari ty
differentiated portfolio of themes concentration on extracts of the portfolio
of themes
scope of service
development of portfolios of themes as interdisciplinary R&D (cons iderati on of as pects
of tec hnol ogy, proce sses and systems)
hig h cognitive proximity
betw een th e cooper ating acto rs
hig h cognitive dis tance
betw een th e cooper ating acto rs
initiation constitution operation
processart ifact
Tab. 2: Phase-dependent courses of action to balance proximity and distance
of the cooperating actors within the task force ‘Aerospace Production’
As a neutral actor the ZAL realizes its role as an
intermediary in so far that it supports the TF passing the
stages of idea management, business model architecture, and
project management. Table 2 shows an extract of the courses
of action, which have been implemented by the ZAL in its
role as intermediary. For example, the table can display that
the autonomous actors have been aggregated within the
structure of an open community in the earlier stages of the
cooperation (impact factor: cooperation structure). A
hierarchical coordination of the inter-organizational
cooperation has not been waived during the meetings. Rather,
an accompanying moderation by the ZAL as a neutral
instance was utilized (impact factor: inter-organizational
coordination). After the stage of the idea generation a

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P. Krenz et al. / Procedia CIRP 16 ( 2014 ) 38 – 43
common business model has been defined and realized within
concrete single projects. In this course, the cooperation has
been institutionalized, cooperation contracts were signed and
the project leaders were chosen within each subproject
(impact factor: cooperation structure / inter-organizational
coordination). This example shows the goal-oriented design
of the value creation structure of the ZAL in cooperation with
the participating actors of the cluster to achieve a context-
oriented compensation between cognitive proximity and
distance of the actors. In this way, the common potential to
develop knowledge in the stage of idea generation could be
fully exploited and furthermore, the viability of the
cooperation was ensured during the stage of operation.
7 Conclusion and Outlook
Knowledge Management has to be considered against the
backdrop of changing paradigms of value creation - from the
traditional firm in the industrial era to mass collaboration in a
globalized networked world - focusing on its integrative
function. As we have pointed out in the previous sections,
KM in value creation networks needs to regulate the
knowledge flows in a way that ensures the viability as well as
the adaptability/ changeability of the VCN. Therefore, the
design of the value creation artifact, its system structure and
the related processes as well as their interdependencies have
to be taken into account. Following such an integrative
systemic approach, one has to analyze the interweaving of
GM and KM objectives.
Existing theories and models according KM are not
recognizing the presented holistic view and the embedding of
KM inside the overall network management. In contrast to
other understandings of the role of a broker respective
intermediary the understanding of the presented knowledge
intermediary differs. In contrast to a knowledge broker the
central task of a knowledge intermediary is not to support the
realization of the knowledge tasks. He does not transfer
knowledge between the different actors of the network or
identifies the knowledge resources within the network.
Instead the intermediary designs value creation structures,
processes and the artifact in cooperation with the network
actors. The relevant objective is to ensure a symbiosis
between tasks of the knowledge management and tasks of the
general management. Concluding, knowledge management
represents not only an add-on in management activities in a
network, but rather it is grounded in the value creation
structures, processes and the artifact. This holistic perspective
ensures its embedding in the overall network management.
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