A Framework for Performance Measurement in Service
Oriented Virtual Organizations
A Value Network Approach to Collaborative Performance Measurement
S. M. Amin Kamali, Greg Richards, Mohammad H. Danesh and Bijan Raahemi
Telfer School of Management, IBM Center for Business Analytics and Performance, University of Ottawa,
55 Laurier Ave. East, K1N 6N5, Ottawa, ON, Canada
Keywords: Virtual Organizations, Performance Measurement, Service Oriented Architecture, Value Networks.
Abstract: Management of Virtual Organizations faces unique challenges which traditional approaches cannot address.
Based on service oriented architecture, this paper proposes a performance measurement framework that
aligns the work of partners in a virtual organization at three different layers. The first layer is designed for
partners’ strategic alignment through coordination of the value creation network. In the second layer, five
performance dimensions of partners’ collaboration are defined which can be mapped onto the service
choreography model. The third layer focuses on assessing effectiveness and efficiency of partners’ domain
specific services which is designed based on ITIL V3 service level management guidelines. In order to
consolidate the proposed framework, these three layers are integrated using a procedure for extracting
service choreography and SLA aggregation patterns from the value network. We propose an integrated
solution for decentralized performance measurement without the need for a central authority. The proposed
framework provides flexibility, scalability, and interoperability and enhances transparency of partners’
performance information at an agreed-upon level as a basis for mutual trust.
1 INTRODUCTION
In a developing global economy, business is
becoming more competitive as a result of
worldwide, boundary less markets. Therefore
organizations must operate with great flexibility and
rapid adaptation to new demands. To survive this
intense competition, companies need to improve
competencies in terms of dealing with new business
models, strategies, organizational and governance
principles, processes and technological capabilities
(L. M. Camarinha-Matos et al., 2009).
As a result organizations started to share their
resources and skills by cooperation and outsourcing
some components of their products and services.
This cooperation was originally formed in relatively
stable, static and classic associations like supply
chains with well-defined roles and responsibilities.
But facing further complicated and more dynamic
markets, legally independent organizations started to
collaborate and share their resources and skills to
better respond to opportunities and form Virtual
Organizations (VOs) (L. M. Camarinha-Matos et al.,
2009).
Nevertheless collaboration does not guarantee
the VO’s success. Deficit in collaborative
management is an identified reason of VO’s failure
(Westphal et al., 2007). An essential pre-requisite
for an effective VO management is a sound
information basis. Therefore performance
measurement, as an important source for this
information, plays a critical role in success of VOs.
Furthermore traditional PM approaches do not meet
specific requirements and characteristics of VOs
(Westphal et al., 2007).
The purpose of this research project is to develop
a performance measurement framework for virtual
organizations that extracts key performance
indicators from their SOA-based collaboration
infrastructure. In the next section of this paper we
define the concepts of Collaborative Networked
Organization (CNO), Virtual Organization (VO),
Performance Measurement (PM), and Service
Oriented Architecture (SOA). This is followed by
proposing a PM framework for service oriented VO
and discussing structure and procedure for such a
framework in Section 3. The characteristics of the
proposed framework will be discussed in Section 4,
263
M. Amin Kamali S., Richards G., H. Danesh M. and Raahemi B..
A Framework for Performance Measurement in Service Oriented Virtual Organizations - A Value Network Approach to Collaborative Performance
Measurement.
DOI: 10.5220/0004054702630271
In Proceedings of the International Conference on Data Communication Networking, e-Business and Optical Communication Systems (ICE-B-2012),
pages 263-271
ISBN: 978-989-8565-23-5
Copyright
c
2012 SCITEPRESS (Science and Technology Publications, Lda.)
followed by a conclusion in Section 5.
2 BACKGROUND
2.1 Virtual Organizations
A collaborative network (CN) is a network
consisting of a variety of entities (e.g. organizations,
people, and even machines) that are largely
autonomous, geographically distributed, and
heterogeneous in terms of their operating
environment, culture, social capital and goals, but
collaborate to better achieve common or compatible
goals, and whose interactions are supported by
computer networks (L. M. Camarinha-Matos and
Afsarmanesh, 2008). Most forms of collaborative
networks imply some kind of organization of the
activities of their constituents, such as identification
of roles and governance rules among their
participants. Therefore, these can be called
manifestations of collaborative networked
organizations (CNOs) (L. M. Camarinha-Matos et
al., 2009).
Virtual Enterprises (VEs) are specific types of
goal oriented CNOs. A VE represents a temporary
alliance of enterprises that come together to share
skills or core competencies and resources in order to
better respond to business opportunities.
Cooporation among partners in the VE is supported
by computer networks. However, in this paper we
focus on goal-oriented, opportunity driven CNO
called a Virtual Organization (VO). A VO is similar
to a VE with the difference that it is comprised of
legally independent organizations which are not
limited to for-profit alliances. (L. M. Camarinha-
Matos et al., 2009).
A VO goes through different phases in its life-
cycle, including Creation, Operation, Evolution and
Dissolution or Metamorphosis (L. M. Camarinha-
Matos and Afsarmanesh, 2008).
Figure 1: Various phases of VO’s Life-Cycle.
Figure 1 shows the sequence of the phases in the
VO’s life-cycle. In contrast with traditional
organizations, creation and dissolution phases of VO
are complex and require considerable effort (L. M.
Camarinha-Matos et al., 2009). In this research, we
mainly focus on operation and evolution phases. In
fact, we provide a mechanism to derive evolution
and maintain operation of VO through performance
measurement and improvement.
2.2 Service Oriented Architecture
Service Oriented Architecture (SOA) builds
applications as a set of service components,
orchestrated to deliver a well-defined level of
service. SOA services are loosely coupled which
means the interdependencies in their relationship are
minimized, and they have to interact just at the
interface layer. This feature of SOA will boost
interoperability and agility needed for VO formation
and management. In SOA, services can be seen as
black boxes. That means their context and inner
logic is hidden from the outside world. This feature
is called service abstraction which facilitates
partners’ security of business advantages. Services
are also reusable which means the whole application
can be decomposed into units (services) which may
be used to compose other functionalities. Autonomy
of services provides control over the logic they
encapsulate, to their provider. As a flexible and
extensible architectural framework, SOA reduces
cost, increases revenue, and enables rapid
application delivery and integration across
organizations (Hurwitz et al., 2006).
2.3 Performance Measurement System
Performance Measurement (PM) is defined as the
systematic approach to planning and collection of
data regarding the accomplishment of tasks and
corresponding objectives (L. Camarinha-Matos et
al., 2008, p.239). PM has evolved through different
sections as is shown in Figure 2. The initial building
blocks of all PM initiatives are recommendations
related to discipline of PM. The accumulation of
these recommendations forms the PM frameworks
which can be categorized as structural and
procedural ones.
A structural framework specifies the typology
and structure of performance indicators. This can be
a hierarchy of performance indicators.
On the other hand a procedural framework
introduces a step-by-step process for developing
performance indicators from strategy (Folan and
Browne, 2005).
Using a procedural framework to develop a
specific structure of performance indicators, along
Evolution
Creation Operation Dissolution
ICE-B 2012 - International Conference on e-Business
264
with other performance management tools and
techniques is called a PM system.
Figure 2: Performance Measurement Evolution – Toward
Performance Management.
Finally using PM systems to provide information
in order to make positive change in organizational
culture, systems and processes is called Performance
Management. Inter-Organizational PM system is a
fast growing facet of the PM literature (Folan and
Browne, 2005).
2.4 SOA based Infrastructure for VOs
Virtual organizations are usually highly dependent
on computer networks to perform their day-to-day
activities (Karvonen et al., 2005). Managing the
interactions and collaborations of multiple
organizations participating in a VO faces specific
difficulties such as partners’ autonomy, privacy
concerns and interdependencies. In addition, VOs
tend to be extremely dynamic and in most cases
temporal in their nature (Drissen-Silva and Rabelo,
2009; Karvonen et al., 2004).
One of the best ways to implement dynamic
business process management solutions is with a
service oriented approach. In SOA-based BPM
systems, processes are defined in three different
layers. The first layer is collaborative processes,
which include high level business processes defined
between enterprises. The second layer is public
services which are processes inside an enterprise
composed of different business components and
orchestrated accordingly. The third layer, private
services which are internal business activities within
a business component. At each layer, processes are
built using the underlying level of services (Marc
Fiammante, 2009). In a service oriented virtual
organization (SOVO) the focus is on sharing
services between organizations and building
collaborative processes on top of the organizational
services. We use BPMN V2 notation and
recommendations to model business processes in all
three levels. The collaborative interaction of
processes is modelled with service choreographies.
Figure 3: Virtual ESB Facilitating a Distributed SOA
Infrastructure (Danesh et al., 2011).
In this research we have proposed a service zone
interaction model that was first presented in (Danesh
et al., 2011). “The service zone acts as an abstraction
layer for partners and facilitates policy and security
enforcement for every autonomous partner. This
service zone provides a gateway for the VO to the
partners’ services enabling it to choreograph and
manage VO collaborative processes, rules and
events, as if the VO is the owner of the services,
while at the same time, preserves organizations’
privacy and their control over services”. The service
zones are implemented as part of every
organizations’ SOA infrastructure. The federation of
multiple service zones will build a virtual service
bus that acts as the heart of a distributed SOA
infrastructure for the VO. This virtual bus can
support any of the common VO topologies known as
supply chain, star and peer-to-peer. This will
facilitate a dynamic and flexible infrastructure for
VOs.
As the interaction model is shown in Figure 3,
each partner has a SOA infrastructure with an
Enterprise Service Bus (ESB) and a service registry.
The service zone resides in these two components.
The implementation of this infrastructure is done by
IBM SOA infrastructure known as Websphere.
3 PROPOSED FRAMEWORKS
FOR SOVO PM
Based on the classification provided in section 2.3
we provide an inter-organizational PM system which
is specifically tailored to the requirements of service
oriented virtual organizations. This system includes
a structure of performance indicators and the
procedure for developing performance measures
A Framework for Performance Measurement in Service Oriented Virtual Organizations - A Value Network Approach to
Collaborative Performance Measurement
265
from strategy. These frameworks are discussed in
the following sections:
3.1 Structural Framework
Performance measurement of SOVOs needs a
specific framework which can address the
characteristics of SOVO that make it different from
traditional organizations (Wenan Tan et al., 2008).
The ECOLEAD project divides Performance
indicators in CNs into three different categories: (1)
The performance of the management approach and
management methods, (2) The performance of the
partners’ collaboration, (3) The performance in
fulfilling the given tasks and the contributing
performance of the partners (Graser et al., 2005).
We have used this classification as the base to
develop structural framework for SOVO. Based on
the specific requirements of SOVO, we have
proposed a structural framework as is shown in
Figure 4. In the following sections three layers of
performance indicators are introduced.
Figure 4: SOVO Performance Indicators Pyramid.
3.1.1 Value Network
The first layer copes with the strategic long term
performance of the alliance. However in the case of
a VO, due to the temporary nature of the alliance, it
does not seem rational to focus on the indicators of
long term performance like strategic goals and
objectives. A better approach is instead to measure
the high level performance of the VO by considering
its success in creating value for the client. This can
be measured considering the mechanism of creating
value in a set of multidimensional chains, which is
called a Value Network (VN).
Value networks are ways in which organisations
interact with each other forming complex chains
including multiple providers/ administrative
domains to drive increased business value (SAP AG,
2008). The most familiar value networks are supply
chains which are the simplest form in terms of the
interaction topology. Different topologies of value
networks are discussed in Wang et al. (2010). The
most general topology is peer-to-peer in which each
partner is capable of interaction with all of the other
partners. The values exchanged among SOVO
partners may be of any kind of product, service,
money, and information.
Figure 5: e3value model for supply chain (Carol Kort and
Jaap Gordijn, 2007).
A comprehensive method for modelling a
business as a value network is e3value (Gordijn et
al., 2000). The e3value ontology provides modelling
constructs for representing and analysing a network
of enterprises exchanging things of economic value
with each other. This method provides a UML based
notation for modelling value segments, actors,
activities, interfaces, and transactions. Figure 5
shows a sample of e3value model for a supply chain.
3.1.2 Collaboration Performance
The characteristic that makes VOs different from
traditional organizations is “collaboration”.
Collaboration is interacting in an incompletely
determined and non-hierarchic manner in order to
enable joint processes with other independent
organizations and human actors that are performed
to reach common goals (Westphal et al., 2010).
Collaboration is a kind of “lubrication” or “catalyst”
for the value creation and supporting processes in
the VO (L. Camarinha-Matos et al., 2008, p.250).
The indicators at this layer are necessary to
assess the effectiveness and efficiency of how
partners work together in joint processes for a
common goal. This layer of performance
measurement is the key for coordination among
partners and the success of SOVO (L. Camarinha-
Matos et al., 2006).
Meeting the performance targets at this layer
enables effective merging of the processes to
accomplish a common task in a non-hierarchic way
(Graser et al., 2005).
SCOR model (Supply Chain Council, 2010) and
ECOLEAD project (L. Camarinha-Matos et al.,
2008, p.250) are considered as reference for this
Value
Network
Collaboration
Performance
Service
Performance
Performance Measurement
Strategic
Operational
ICE-B 2012 - International Conference on e-Business
266
layer. Five dimensions are considered to measure
collaboration performance including: Reliability,
Flexibility, Responsiveness, Communication, and
Commitment. Reliability is defined as the ability to
deliver material, information, and services within
agreed upon quality, quantity, time and cost.
Flexibility describes the ability to respond to
external influences and the ability to adapt to new
situation. External influences may include non-
forecasted increases or decreases in demand,
suppliers or partners going out of business, natural
disasters, etc. Responsiveness describes the speed at
which collaborative tasks are performed such as
cycle-time metrics. Communication dimension
represents the ability to communicate, which
includes the aspect of using ICT as a means of
communication (Westphal et al., 2010). This
includes two sub-dimensions of re-active and active
commitment. Re-active aspect describes how the VO
members react on critical situations or problems.
The active aspect describes the intention of partners
to actively collaborate to avoid critical situations (L.
Camarinha-Matos et al., 2008, p.250).
These five dimensions of collaborative
performance can be mapped directly on the service
choreography model. Each component of the
choreography model represents an interaction
between two or more partners and the messages
which are transacted. All of the characteristics of
each interaction can be defined under the five
dimensions of collaboration performance.
3.1.3 Service Performance
The third layer of performance indicators in a VO is
related to fulfilling given tasks and contributing to
performance of the partners. Based on the
supporting infrastructure which is service oriented,
the tasks are done by executing different services of
partner organizations. Therefore, the low-level
performance indicators in a SOVO would be used to
assess the effectiveness and efficiency of services
shared by a specific partner in a collaborative
process. These indicators are mostly domain
specific, however they must be agreed upon by
related partners. This layer of indicators can be
considered as the most operational one. The
specification of each service, their target level and
the responsibilities of service provider must be
agreed upon among partners and be documented in
the form of Service Level Agreement (SLA) (Long,
2008). SLA guarantees the expected quality of
service to different stakeholders. The structure of an
SLA contains three parts of name, context and
terms. Basically each contract needs an official
name. The context indicates the initiator, responder,
provider and timeframe. Service terms define the
functional attributes of agreement whereas the
guarantee terms indicate non-functional ones.
3.2 Procedural Framework
The procedure for extracting performance indicators
from strategy (procedural framework) along with the
structural framework forms the PM system. The
basic assumption is that the business model is
derived from an opportunity in the market and
represented as value network. This opportunity may
be a growing demand for a new product or service
which can be addressed by putting together the
capabilities of different organizations. Next steps are
about linking the value network to two other layers
of performance indicators.
3.2.1 Extracting Service Choreography from
Value Network
There have been different attempts to derive
business choreographies from value networks.
Among these attempts authors in (Wang et al., 2010)
and (Wieringa and Gordijn, 2005) developed the
service choreography description and dependencies
based on inter-dependencies among values in the
value network. Wang et al. (2010) start this by
decoupling the value network into value chains with
loose or no relation to each other. The service
choreographies are then extracted from sets of
values and finally they connect different sets of
service choreography together. The downside in this
method is when we have a peer-to-peer network
where decoupling will not be an option because of
inter-dependencies between values. In this research
we use a similar approach based on value
dependencies, however we do not develop our
choreographies based on sets of decoupled value
chains. Instead we propose the following steps for
extracting Choreographies from value networks:
1. Note that information and service values in the
value network need to be broken down to the
smallest unit possible. Now we assign every
value in the network an ID as result we will
have a set of values which can be defined as
V={
.
2. At the next step the following matrix must be
formed. In the presented matrix
’s are values
of the set V.

is 1 if
has a dependency on
in a sense that
cannot be performed as it
should, unless
is performed otherwise

is
A Framework for Performance Measurement in Service Oriented Virtual Organizations - A Value Network Approach to
Collaborative Performance Measurement
267
0. Note that this dependency needs to be a
direct dependency which means if

and

but there is no direct relation between
and
then

.
3. For each value in V, count its successive
values (
) : 


4. For each value in V, Calculate its depth of
influence (
) which is equal to the
following formula (note the best way to
calculate this formula is to start from the
values with 
= 0) :


= 0
5. Rank the values based on 
6. Start modeling service choreographies from the
two top values (service choreography is
defined based on dependency between two or
more values) and continue until no dependency
is left.
In following lines we discuss an example of
implementing this method. Figure 6 shows a
hypothetical value network consisting of three value
actors and one market segment.
Figure 6: Value Network Model of a VO.
The client submits an order for Service3 which is
a composition of Service1 and Service2 provided by
the Supplier and Outsource. The order information
needed by outsource needs to be processed by the
supplier. Each payment is made based on the bill
provided by the payment recipient. V will be defined
as the set of above values. V= {v
1
,
v
2
,…, v
12
}. Matrix
M will be formed as follows:







Dependencies between pairs of value instances are
shown in Figure 7.
Figure 7: Value Dependencies.
Submit Initial
Order
Client
Supplier
Order Info
Service
Delivery and
Tracking
Outsource
Client
Order
Client
Supplier
Provide
Initial Service
Supplier
Outsource
Supplier
Outsource
Payment Info
Supplier Service Info
Client
Outsource
1
2
4
4
3
3
7,8
9
Client
Outsource
Supplier
Request
Initial
Billing
Supplier
Outsource
Order Info
Initial Bill
Supplier
Client
Initial Bill
Outsource
Client
Figure 8: Service Choreography Model.
The nodes are representing value transactions. The
numbers on top of each node are depicting that
specific value’s depth of influence. The numbers on

=

+ 
=0


     1
ICE-B 2012 - International Conference on e-Business
268
the edges of the graph are depicting choreography
modelling steps. Following the sequence of steps we
come up with the service choreography model which
is shown in Figure 8.
3.2.2 Extracting SLA Aggregation Pattern
from Value Network
The final step is to extract SLA aggregation pattern
from the value network. Within a business network,
services can be composed together to make a value
added service for the client. This implies some form
of aggregation pattern of SLAs for business partners,
which is discussed by Ul Haq and Schikuta (2010).
For each partner, a zone is defined as that partner’s
view. For each partner, this zone is defined as a set
including consumer oriented SLAs, provider
oriented SLAs, and dependencies to those SLAs.
The views show the level of access to the SLA
information for each partner.
Figure 9: SLA aggregation in VOs (Ul Haq and Schikuta
2010).
In this research, performance indicators of VO
partners’ contributing services are defined based on
this structure. With focusing on the value network
(Figure 6), we can extract the SLA aggregation
pattern using this method as shown in Figure 10.
Client
SLA
ap-VO
ap-Supplierap-Outsource
Client
Client’s SLA View
Outsource SLA View Supplier’s SLA View
SLA
SLA
Figure 10: SLA Aggregation Pattern.
VO’s view is shared with partners based on the
management topology which enables the partners to
access final SLA. In this simple example supplier
and outsource share the same view as they occupy
the same level in VO.
4 CHARACTERISTICS OF THE
PROPOSED FRAMEWORK
Strategic alignment of partners in CNOs generally,
and VOs specifically, is one of the most important
challenges in managing such alliances. The proposed
PM framework addresses this important issue
through coordination of partners’ value creation
network. Consequently, partner’s values will be
compatible following a common goal, i.e. providing
value added services to the customer. The core
characteristic of a VO is collaboration, and the way
to tackle this issue is by identifying attributes and
providing performance dimensions to measure their
effectiveness and efficiency. The proposed
framework also addresses interdependencies among
partners’ services by mapping the collaboration
performance on the service choreography model.
The dynamic nature and rapid changes
characteristics of a VO, calls for flexibility. These
changes can be handled based on their scope by
referring to the related layer of the performance
structure. Realizing distributed performance
measurement of the SOVO with no necessity of a
central authority is enabled by defining SLA
aggregation pattern, and independent SLA views.
This also provides transparency at an agreed-upon
level which is the basis for mutual trust. On the other
hand, privacy and security which are important
concerns for autonomous partners are realized by
implementing service zones in partners’ SOA
infrastructure layer.
5 CONCLUSIONS
To keep pace with the growth of global economy
and the intense hyper-competition, organizations
tend to form strategic alliances to better deliver
value to customers. These alliances, formed with the
main purpose of collaborative value creation, have
evolved to form today’s well known Virtual
Organizations. The literature on performance
measurement has not addressed inter-organizational
relationships in much detail. As such, the need to
conceptualize such interactions exists. This research
A Framework for Performance Measurement in Service Oriented Virtual Organizations - A Value Network Approach to
Collaborative Performance Measurement
269
focuses on meeting this demand, and providing a
base for aligning VO partners at their strategic
levels, as well as their operational activities. Our
work on value network analysis along with service
choreography and SLA aggregation enables such a
pervasive multi-level alignment within a VO. In the
infrastructure layer, Service Oriented Architecture is
used to maintain agility and scalability of partner’s
collaboration, and at the same time, provide an
agreed upon level of privacy and security. The
proposed solution provides a base for collaborative
performance measurement. We are expanding this
work to include guidelines about performance
monitoring, evaluation, and improvement in
collaborative environments. This will realize inter-
organizational performance management.
ACKNOWLEDGEMENTS
This project is jointly supported by IBM Centre for
Business Analytics and Performance (CBAP) and
MITACS-Accelerate program.
REFERENCES
Camarinha-Matos, L., Afsarmanesh, H. and Ollus, M.,
2008. Methods and Tools for Collaborative Networked
Organizations, Springer.
Camarinha-Matos, L., Afsarmanesh, H. and Ollus, M.,
2006. Network-centric collaboration and supporting
frameworks: IFIP TC 5 WG 5.5, seventh IFIP
Working Conference on Virtual Enterprises,
September 25-27, 2006, Helsinki, Finland, Springer.
Camarinha-Matos, L. M. et al., 2009. Collaborative
networked organizations - Concepts and practice in
manufacturing enterprises. Computers and Industrial
Engineering, 57(1), pp.46–60.
Camarinha-Matos, L. M. and Afsarmanesh, H., 2008. On
reference models for collaborative networked
organizations. International Journal of Production
Research, 46(9), pp.2453–2469.
Carol Kort and Jaap Gordijn, 2007. Handbook of
Ontologies for Business Interaction P. Rittgen, ed.,
IGI Global.
Danesh, M. H., Raahemi, B. and Kamali, M. A., 2011. A
framework for process management in service oriented
virtual organizations. In 2011 7th International
Conference on Next Generation Web Services
Practices (NWeSP). 2011 7th International Conference
on Next Generation Web Services Practices (NWeSP).
IEEE, pp. 12–17.
Drissen-Silva, M. V. and Rabelo, R. J., 2009. Managing
Decisions on Changes in the Virtual Enterprise
Evolution. In L. M. Camarinha-Matos, I. Paraskakis,
and H. Afsarmanesh, eds. Leveraging Knowledge for
Innovation in Collaborative Networks. Berlin,
Heidelberg: Springer Berlin Heidelberg, pp. 463–475.
Folan, P. and Browne, J., 2005. A review of performance
measurement: Towards performance management.
Computers in Industry, 56(7), pp.663–680.
Gordijn, J., Akkermans, H. and Vliet, H., 2000. What’s in
an Electronic Business Model? In R. Dieng and O.
Corby, eds. Knowledge Engineering and Knowledge
Management Methods, Models, and Tools. Berlin,
Heidelberg: Springer Berlin Heidelberg, pp. 257–273.
Graser, F., Westphal, I. and Eschenbaecher, J., 2005.
Roadmap on VOPM challenges on operational and
strategic level.
Hurwitz, J. et al., 2006. Service oriented architecture for
dummies, Wiley.
Karvonen, I. et al., 2004. Challenges in the Management
of Virtual Organizations. In L. M. Camarinha-Matos,
ed. Virtual Enterprises and Collaborative Networks.
Boston: Kluwer Academic Publishers, pp. 255–264.
Karvonen, I., Salkari, I. and Ollus, M., 2005.
Characterizing Virtual Organizations and Their
Management. In L. M. Camarinha-Matos, H.
Afsarmanesh, and A. Ortiz, eds. Collaborative
Networks and Their Breeding Environments. New
York: Springer-Verlag, pp. 193–204.
Long, J. O., 2008. ITIL® VERSION 3 AT A GLANCE,
New York: Springer.
Marc Fiammante, 2009. Dynamic SOA and BPM: Best
Practices for Business Process Management and SOA
Agility 1st ed., IBM Press.
SAP AG, 2008. NESSI Grid Vision and Strategic
Research Agenda.
Supply Chain Council, 2010. Supply Chain Operations
Reference (SCOR®) modelOverview - Version 10.0.
Ul Haq, I. and Schikuta, E., 2010. Aggregation patterns of
service level agreements. In Proceedings of the 8th
International Conference on Frontiers of Information
Technology. FIT ’10. New York, NY, USA: ACM,
pp. 40:1–40:6.
Wang, Z., Chu, D. and Xu, X., 2010. Value Network
Based Service Choreography Design and Evolution. In
E-Business Engineering, IEEE International
Conference on. Los Alamitos, CA, USA: IEEE
Computer Society, pp. 495–500.
Wenan Tan et al., 2008. The Differences and Conjunctions
on Performance Management between Entity
Enterprise and Virtual Enterprise. In Third
International Conference on Pervasive Computing and
Applications, 2008. ICPCA 2008. Third International
Conference on Pervasive Computing and
Applications, 2008. ICPCA 2008. IEEE, pp. 65–69.
Westphal, I., Thoben, K.-D. and Seifert, M., 2010.
Managing collaboration performance to govern Virtual
Organizations. Journal of Intelligent Manufacturing,
21(3), pp.311–320.
Westphal, I., Thoben, K.-D. and Seifert, M., 2007.
Measuring Collaboration Performance In Virtual
Organizations. In L. Camarinha-Matos et al., eds.
Establishing The Foundation Of Collaborative
ICE-B 2012 - International Conference on e-Business
270
Networks. IFIP Advances in Information and
Communication Technology. Springer Boston, pp. 33–
42.
Wieringa, R. J. and Gordijn, J., 2005. Value-oriented
design of service coordination processes: correctness
and trust. In Proceedings of the 2005 ACM symposium
on Applied computing. SAC ’05. New York, NY,
USA: ACM, pp. 1320–1327.
A Framework for Performance Measurement in Service Oriented Virtual Organizations - A Value Network Approach to
Collaborative Performance Measurement
271