Validating Value Network Business Models by Ontologies
José Granjo
1,
Marzieh Bakhshandeh
1,2
, João Pombinho
1
,
Miguel Mira da Silva
1
and Artur Caetano
1,2
1
Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal
2
Information Systems Group, INESC-ID,Rua Alves Redol 9, 1000-029 Lisboa, Portugal
{jose.granjo, marzieh.bakhshandeh, jpmp, mms, artur.caetano}@tecnico.ulisboa.pt
Keywords: Business Model Canvas, e3value, ArchiMate, Ontology Integration, Meta-model, OWL, SPARQL.
Abstract: Different meta-models allow modeling the business of an organization from different perspectives. The
Business Model Canvas focus is close to the strategy of the organization. E3value allows modeling of value
networks and ArchiMate allows alignment from business models to IT infrastructure. When models of these
three meta-models coexist for a certain value network, they must be consistent. Currently, there is no way to
validate such consistency automatically. We propose a solution, using ontologies and ontology mapping
techniques (OWL, OWL.DL, SPARQL) that helps to validate instantiated models automatically, based on a
set of mapping rules between the three meta-models. In this work, the mappings between Business Model
Canvas, e3value and ArchiMate are identified and formalized through ontologies. The formalized mapping
is then applied to a case study and exploited, together with reasoning techniques.
1 INTRODUCTION
Innovative business models challenge the
traditionally established ways of generating value,
resulting in advantage to a company. We have seen,
over time, that innovative business models can dare
the subsistence of other established companies or
even create complete new markets.
Having a shared understanding of what is the
business model of a company, by representing it,
eliminates possible interpretation ambiguities.
The Business Model Canvas (BMC)
(Osterwalder & Pigneur, 2010) is a tool for
representing the business model of a company.
When a company is executing its business, it is part
of a network of companies that exchange value with
the final goal of delivering value to customers.
e3value (Gordijn & Akkermans, 2003) allows
modeling of value networks: the value exchanges
between actors in the network.
BMC allows representing the business model of
an organization on a higher-level (or strategic)
perspective. e3value is closer to operationalization
of business, by showing value transactions of the
value network. On a lower-level, business processes
can be modeled with ArchiMate (The Open Group,
2012), a service-oriented enterprise architecture
modeling language, which considers three different
layers: business, application and technology.
Toghether, these three meta-models allow the
alignment from business models to information
technology and infrastructure.
When modeling the business of an organization
and its value network, several of these models can
be instantiated. If theys coexist for a value network,
they must be consistent and there is no way to
automatically validate such consistency between
model components. We aim to analyze the
possibility to perform this validation between
models by using ontologies. An ontology is a
formal, explicit specification of a shared
conceptualization (Gruber & others, 1993). Such
search for inconsistencies helps business to IT
alignment.
In section 2, the research proposal is presented,
and next, in section 3, we reference each meta-
model. Afterwards (section 4), the mapping rules
between the three meta-models are presented. In
section 5, a validation has been done with an
example case study. Finally, conclusions and future
work are discussed.
2 RESEARCH PROPOSAL
As depicted in figure 1, a validation method for
models of BMC, e3value and ArchiMate is
proposed, based on a set of mapping rules between
142
Granjo J., Bakhshandeh M., Pombinho J., da Silva M. and Caetano A.
Validating Value Network Business Models by Ontologies.
DOI: 10.5220/0005425201420147
In Proceedings of the Fourth International Symposium on Business Modeling and Software Design (BMSD 2014), pages 142-147
ISBN: 978-989-758-032-1
Copyright
c
2014 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
the thre
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Validating Value Network Business Models by Ontologies
143
which is different from the viewpoint adopted in
another ontology.
For mapping BMC, e3value and ArchiMate, there
were two kinds of mismatches: lexical mismatch,
where the same entity is represented by two different
names, such as, Customer Segments and Business
Actor; and coverage mismatch, where from the same
point of view, in the same context and with
comparable vocabulary, part of the domain that is
described differs and there are only overlapping
parts (Value Proposition and Goal). Most ontology
mapping approaches focus on automating the
discovery of a mappings. This case, requires an
exact mapping, so the mappings were done manually
using (Zivkovic, et al., 2007).
4.2 Mapping BMC to e3value
Previous work (Gordijn, et al., 2005) shows
connections between concepts of BMC and e3value
to understand similarities and differences between
both ontologies to possibly integrate them in order to
improve representation, design and analysis of
business models. The defined mapping rules (table
1) are inspired on previous work.
4.3 Mapping BMC to ArchiMate
Another work (Meertens, et al., 2012) explored the
connection between BMC an ArchiMate, where the
concepts of BMC were successfully mapped to
e3value. The defined mapping rules (table 2) are
inspired on previous work. We do not consider any
mapping between Customer Relationships (CR) and
Business Collaboration because CR refers to the
types of relationships an organization maintains with
its customers. Key Partners is only a list of partners,
so the mapping is simplified to Business Actor. Cost
Structure is not mapped to Value because it is only
the cost of performing Key Activities and
maintaining Key Resources.
4.4 Mapping e3value to ArchiMate
Direct transformation from e3value to ArchiMate is
inhibited by different levels of abstraction between
the economic transactions modeled in e3value and
ArchiMate (de Kinderen, et al., 2012). The same
authors use DEMO (Dietz, 2006) as a bridge for the
different levels of abstraction of e3value and
ArchiMate (de Kinderen, et al., 2012). Another work
(Pombinho J. A., 2014) defines the mapping
between e3value and DEMO in a more grounded,
formal and thorough way. Namely, it specifies a
detailed mapping based on the coordination acts and
facts of the transactional pattern and the
corresponding competences by the value actors.
Additionally, the authors define a Value-oriented
Solution Development Process in (Pombinho, 2013)
that specifies a process for incrementally developing
value networks by alternating coherent value and
construction models. Table 3 shows the defined
mapping rules.
Table 1: BMC-e3value meta-model concepts mapping.
BMC concept E3value concept Mapping rationale
Customer
Segment
Actor
Equivalence. The Customer Segments are groups of people that a
company aims to reach, while Actor is an independent economic entity
that generates profit or increases its utility. (1:1)
Market Segment Analogous to Actor. Market Segment is a specialization of Actor.
Key Partner Actor
Equivalence. Key Partners is the group of partners that help the
businesses execution. Analogous mapping to Customer Segment. (1:1)
Channel Value Transmission
Aggregation. A value transmission can be the delivery of value to
customers through a certain channel. (many:1)
Key Activity
Value Activity
Equivalence. Key Activities are the most important things a company
must do to make its business model work, while an actor performs a
Value Activity for profit or to increase its utility. (1:many)
Value Transmission
Aggregation. A Key Activity can involve a value exchange (to obtain a
needed resource) with a Key Partner. (many:1)
Key Resources Value Object Equivalence. A Key Resource acquired from a Key Partner. (1:1)
Revenue Stream Value Transmission Equivalence to inbound and monetary value exchange. (1:1)
Value
Proposition
Value Interface
Equivalence. A value interface defines the group of value objects the
company is willing to provide. Those value objects are also defined in
the outbound value ports belonging to the value interface. (1:1)
Actor Actor Equivalence. The Actor concept is the owner of a BMC. (1:1)
Fourth International Symposium on Business Modeling and Software Design
144
Table 2: BMC-e3value meta-model concepts mapping.
BMC concept ArchiMate concept Mapping rationale
Customer
Segment
Business Actor
Equivalence. Customer Segments are groups of people that a
company aims to reach, while Business Actor is an organizational
entity that is capable of performing behavior. (1:1)
Key Partner Business Actor
Equivalence. Key Partners is the group of partners that help the
business model execution. Analogous to Customer Segments. (1:1)
Channel Business Interface
Equivalence. Channels describe how a company communicates with
and reaches its Customer Segments to deliver Value Propositions. A
Business Interface is a point of access where a business service is
made available to the environment. (1:1)
Revenue Stream Value
Equivalence. Value may apply to what a party gets by selling or
making available some product or service, or it may apply to what a
party gets by buying or obtaining access to it. (1:1)
Value Proposition
Business Service
Aggregation. A Value proposition is a Business Service or a Product
(1:many)
Product
Value Aggregation. The worth of the Service/Product for the Customer.
Goal (Motivation
Extension)
Aggregation. Why the Service/Product is useful for the Customer.
Key Activity
Business Interaction Equivalence. The performed Key Activities may be represented as
high-level Business Processes or Business Functions, or by Business
Interactions between internal Business Actors. (1:many)
Business Function
Business Process
Actor Business Actor Equivalence. Analogous to Customer Segments, for example. (1:1)
Table 3: e3value-Archimate meta-model concepts mapping.
E3value concept ArchiMate concept Mapping rationale
Actor Business Actor
Equivalence. Actor is an independent economic entity that generates
profit or increases its utility. Business actor is an organizational entity
that is capable of performing behavior. (1:1)
Market Segment Business Actor Equivalence. Market Segment is a specialization of Actor. (1:1)
Value Interface Product
Equivalence. A value interface groups the value objects offering
provided by one actor. Such value offering in concretized by business
services and a Product is a coherent grouping of business services. (1:1)
Value
Transmission
Business Service
Equivalence. The utilization of a business service by an external actor is
concretizes a value transmission. (1:1)
Value Activity Business Process
Equivalence. High-level business processes that support business
services offered to external business actors. Business process
choreography is only present in lower levels.
Value Object
Business Object
Equivalence. A value object is a business object transmitted to some
other actor. A business object is tangible. (1:many)
Value
Equivalence. Value is the worth of a business service or product to some
business actor. Value can represent intangible value objects. (1:many)
5 VALIDATION
This proposal has a unified meta-model for the
purpose of integration. It was required to transform
the three meta-models into ontology (OWL). The
BMC OWL representation was obtained from other
authors (Pigneur, 2004). The ArchiMate
transformation process uses (1) an OWL
representation of the ArchiMate meta-model and (2)
OWL representations of ArchiMate models
(Bakhshadeh, et al., 2014) (Antunes, et al., 2013)
(Bakhshandeh, et al., 2013). An e3value OWL
representation was implemented with inspiration on
the meta-model presented in (Pombinho J. A., 2014).
Figure 2, shows a partial of the integrated
ontology, along with relationships with other
concepts and some constrains. It was required to
instantiate the models inside the integrated ontology
as individuals (OWL). A transformation was made
from BMC, e3value and ArchiMate example models
to individuals.
Validating Value Network Business Models by Ontologies
145
Figure 2
:
ontology.
5.1
C
ArchiSu
r
study t
o
models
2012) (
e3value,
designe
d
The
OWL t
o
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used to
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Gruning
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In the re
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ase Study
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illustrate th
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egrated ontol
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Fourth International Symposium on Business Modeling and Software Design
146
ACKNOWLEDGEMENTS
This project is partially supported by the European
Commission under the 7th Framework Programme
(FP7/2007-2013) under grant agreement 269940,
TIMBUS project (http://timbusproject.net). Also, by
national funds through FCT – Fundação para a
Ciência e a Tecnologia, under project PEst-
OE/EEI/LA0021/2013.
REFERENCES
Amrouch, S. & Mostefai, S., 2012. Survey on the
literature of ontology mapping, alignment and
merging. s.l., s.n., pp. 1-5.
Antunes, G. et al., 2013. Using ontologies for enterprise
architecture model alignment. s.l., s.n.
Baader, F., Horrocks, I. & Sattler, U., 2008. Description
logics. Foundations of Artificial Intelligence, Volume
3, pp. 135-179.
Bakhshadeh, M., Morais, A., Caetano, A. & Borbinha, J.,
2014. Ontology Transformation of Enterprise
Architecture Models. In: Technological Innovation for
Collective Awareness Systems. s.l.:Springer, pp. 55-62.
Bakhshandeh, M. et al., 2013. A Modular Ontology for the
Enterprise Architecture Domain. s.l., s.n., pp. 5-12.
Bouquet, P. et al., 2004. D2. 2.1 Specification of a
common framework for characterizing alignment.
Corcho, O., Fernández-López, M. & Gómez-Pérez, A.,
2006. Ontological engineering: principles, methods,
tools and languages. In: Ontologies for software
engineering and software technology. s.l.:Springer, pp.
1-48.
Davies, J., Studer, R. & Warren, P., 2006. Semantic Web
technologies: trends and research in ontology-based
systems. s.l.:Wiley. com.
de Kinderen, S., Gaaloul, K. & Proper, H. A., 2012.
Bridging value modelling to ArchiMate via transaction
modelling. Software & Systems Modeling, pp. 1-15.
de Kinderen, S., Gaaloul, K. & Proper, H. E., 2012.
Integrating value modelling into archimate. In:
Exploring Services Science. s.l.:Springer, pp. 125-139.
Dietz, J. L. G., 2006. Enterprise Ontology: Theory and
Methodology. s.l.:Springer.
Euzenat, J., Euzenat, J., Shvaiko, P. & others, 2007.
Ontology matching. s.l.:Springer.
Fox, M. S. & Gruninger, M., 1998. Enterprise modeling.
AI magazine, 19(3), p. 109.
Gordijn, J. & Akkermans, J., 2003. Value-based
requirements engineering: exploring innovative e-
commerce ideas. Requirements engineering, 8(2), pp.
114-134.
Gordijn, J., Osterwalder, A. & Pigneur, Y., 2005.
Comparing two business model ontologies for
designing e-business models and value constellations.
Proceedings of the 18th Bled eConference, Bled,
Slovenia, pp. 6-8.
Gruber, T. R. & others, 1993. A translation approach to
portable ontology specifications. Knowledge
acquisition, 5(2), pp. 199-220.
Kotis, K., Vouros, G. A. & Stergiou, K., 2006. Towards
automatic merging of domain ontologies: The
HCONE-merge approach. Web Semantics: Science,
Services and Agents on the World Wide Web, 4(1), pp.
60-79.
Lenzerini, M., Milano, D. & Poggi, A., 2004. Ontology
representation & reasoning. Universit di Roma La
Sapienza, Roma, Italy, Tech. Rep. NoE InterOp (IST-
508011).
Meertens, L. O. et al., 2012. Mapping the business model
canvas to ArchiMate. s.l., s.n., pp. 1694-1701.
Osterwalder, A. & others, 2004. The business model
ontology: A proposition in a design science approach.
Institut d'Informatique et Organisation. Lausanne,
Switzerland, University of Lausanne, Ecole des Hautes
Etudes Commerciales HEC, Volume 173.
Osterwalder, A. & Pigneur, Y., 2010. Business model
generation: a handbook for visionaries, game
changers, and challengers. s.l.:John Wiley & Sons.
Pigneur, Y., 2004. Modeling the business model ontology
with Protégé and OWL, s.l.: s.n.
Pombinho, J. A. D., T. J., 2013. Value-oriented Solution
Development Process - uncovering the rationale
behind organization components.. s.l., s.n.
Pombinho, J. A. D., T. J., 2014. Linking Value Chains –
Combining e3Value and DEMO for specifying Value
Networks. s.l., s.n.
Sofia, A. G.-P. P. H. & Martins, J. P., 1999. Some issues
on ontology integration. s.l., s.n.
The Open Group, 2012. ArchiMate 2.0 Specification.
s.l.:s.n.
Zivkovic, S., Kuhn, H. & Karagiannis, D., 2007. Facilitate
Modelling Using Method Integration: An Approach
Using Mappings and Integration Rules. s.l., s.n., pp.
2038-2049.
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