An Enterprise-ontology based Conceptual-modeling Grammar
for Representing Value Chain and Supply Chain Scripts
Wim Laurier
1
and Geert Poels
2
1
SMASH, Faculté ESPO, Université Saint-Louis, Boulevard du Jardin Botanique 43, 1000 Bruxelles, Belgique
2
Department of Management Information Systems and Operations Management,
Faculty of Economics and Business Administration, Ghent University, Tweekerkenstraat 2, 9000 Gent, Belgium
Keywords: Enterprise Ontology, Business Modeling, Information System Integration, Conceptual-modeling Grammar.
Abstract: In business modeling the focus is shifting from the enterprise to the supply chain as the prime context.
Contemporary business modeling grammars should allow each enterprise taking part in a supply chain to
develop its own information system and at the same time support the creation of system interoperability and
information sharing amongst business partners in the supply chain. This paper presents a conceptual
modeling grammar for representing business scripts in a way that is observer-independent. That is, rather
than presenting value chain information from the perspective of any partner in the supply chain (e.g.,
enterprise, supplier, customer, customer’s customer, supplier’s supplier) or from a completely neutral third
party. This observer-independent conceptual-modeling grammar, which is given strength by grounding it in
the mature Resource-Event-Agent model, is shown to represent information about business phenomena of
diverse supply chain partners such that it can be integrated across enterprise boundaries.
1 INTRODUCTION
Conceptual modeling in information systems (i.e.,
the creation of an conceptual-modeling grammar for
the purpose of designing information systems (Wand
et al., 1995)) is a challenging task, especially
because - in practice - enterprise information
systems form a small part of a much larger
information processing environment. Consequently,
conceptual-modeling grammars, which provide sets
of constructs and rules to model real-world domains
(Wand and Weber, 2002), for the purpose of
designing information systems cannot be considered
standalone artifacts. Moody and Shanks (2003) show
that significant benefits can be achieved through
integration of information systems, and argue that
considering individual systems in the context of an
overall architecture is critical for developing quality
information systems. Within conceptual modeling,
the choice of an appropriate representation of data is
one of the most crucial tasks in information systems
development, as it is a major determinant of an
information system’s ability to integrate with other
systems (Moody and Simsion, 1995).
Where the enterprise and its value adding
processes could be considered the prime conceptual
modeling context, which is the setting in which
conceptual modeling occurs and conceptual-
modeling scripts are used (Wand and Weber, 2002),
in the past, the supply chain is becoming more and
more important as a modeling context. A
continuously faster globalizing world economy and
increasing cooperation among supply chain partners
increases the need to model the entire supply chain
and not just individual players within it.
In some cases the conceptual-modeling context
consists of both the supply chain and the enterprise
(e.g., strategic alliances, joint ventures). As with all
other forms of collaboration, a fair distribution of the
added value among the collaborators is primordial.
This issue receives a lot of attention with joint
ventures, where each parent company expects to
receive a fair part of the joint venture’s added value,
although this added value can be very diverse in
nature (e.g., knowledge acquisition, financial
returns, cost reduction) (Ariño and Ring, 2010),
(Kumar, 2010). Fair distribution of added value
between supply chain partners is also essential for
closed-loop supply chains, where the reprocessing of
end-of-life products needs to be profitable too
(Kumar and Malegeant, 2006). To convince
collaborators that added value is distributed
103
Laurier W. and Poels G..
An Enterprise-ontology based Conceptual-modeling Grammar for Representing Value Chain and Supply Chain Scripts.
DOI: 10.5220/0004411901030111
In Proceedings of the 15th International Conference on Enterprise Information Systems (ICEIS-2013), pages 103-111
ISBN: 978-989-8565-59-4
Copyright
c
2013 SCITEPRESS (Science and Technology Publications, Lda.)
correctly, collaborating supply chain partners and
parent companies of a joint venture need to make
data about their transactions with other supply chain
partners or the joint venture available to their
collaborators, cofounders or a trusted third party that
certifies a fair distribution of added value between
supply chain partners or parent companies. Such a
certifying body would require an information system
that takes the independent-observer view on the data
that each trading partner generates about
transactions, where the joint venture or the supply
chain partner itself needs an information system that
takes the trading-partner view on the transactions it
participates in. The independent-observer view is a
supply-chain-centric conceptual modeling context
that looks at business from an independent observer
perspective or ‘helicopter’ view (e.g., business seen
as flows of goods, services and money between
parties that are caused by business events initiated
by these parties). The trading partner view, on the
other hand, is an enterprise-centric conceptual
modeling context that covers conceptual modeling
scripts for enterprise information systems from the
sole perspective of one particular party involved in
business, called the ‘trading partner’ (e.g., an
enterprise doing business in its role of customer,
producer or supplier).
Although the concept of supply-chain-centric
information systems is not new (Curran, 1991) and a
lot of work has been attributed to the standardization
and formalization of the information that is
exchanged between trading partners for a transaction
to take place (e.g., ebXML, UBL), supply chains and
enterprises are still considered distinct conceptual
modeling contexts when modeling information
systems (ISO/IEC, 2007) and most enterprises rely
on enterprise-centric information systems.
What is needed is a conceptual modeling
grammar that allows each enterprise in a supply
chain to develop its own private enterprise
information system and at the same time support the
creation of supply chain information systems (Tan et
al., 2010).
This paper presents a conceptual modelling
grammar that elaborates a reference model, which is
based on the Resource-Event-Agent (REA) ontology
(Geerts and McCarthy, 2002), and can be used for
both the trading-partner and independent-observer
view (Laurier et al., 2010) This conceptual
modelling grammar for the business domain
overarches the supply chain and enterprise domains
of business information systems and provides a
conceptual basis for both information systems
development and integration.
Section 2 reviews the REA ontology, on which
the conceptual-modeling grammar is based. Section
3 presents the conceptual-modeling grammar and
shows how it is built from the primitives that occur
in REA ontology (Geerts and McCarthy, 2002).
Subsequently, section 4 presents archetypal
conceptual-modeling scripts that demonstrate how
this conceptual-modeling grammar can be used to
integrate both conceptual modeling contexts (i.e.,
enterprise-centric and supply-chain centric) Next,
section 5 compares the conceptual-modeling
grammar to related conceptualizations used in
enterprise modeling and supply chain modeling.
Finally, section 6 concludes the paper and proposes
ideas for future research.
2 INTRODUCTION TO REA
The original REA generalized accounting
framework (McCarthy, 1982) was developed to
create an environment in which accountants and
non-accountants can share data about the same set of
business phenomena. Based on ideas taken from
Chen’s Entity-Relationship model (Chen, 1976), an
accounting conceptual modeling grammar was
proposed in which concepts were given real-world
business semantics (i.e., resources, events, agents)
instead of the usual debit-credit-account semantics
(e.g., accounts receivable, revenues deferred) which
code operational information such that it is hard to
decode for most non-accountants. The REA
framework includes procedural mechanisms for
taking different mutually compatible views on the
same business reality. For instance, an REA
conceptual modeling script, which is a product of a
conceptual modeling process given a conceptual
modeling grammar (Wand and Weber, 2002), would
still contain a representation of all data required to
restore the accounting view on business (e.g.,
calculate accounts receivable, revenues deferred,
etc.), but would at the same time also support the
data requirements of other kinds of operational and
managerial business applications (e.g., stock control,
policy setting, planning, management control, etc.).
Economic Resources (e.g., goods and services)
represent objects that are scarce, have utility and are
under the control of an economic agent (e.g.,
enterprise, household) (Ijiri, 1975), (McCarthy,
1982). The scarceness means that not every
economic agent can control such resources at a
certain point in time and indicates that for some
economic agents trade is required to gain control
over particular resources. The utility motivates why
ICEIS2013-15thInternationalConferenceonEnterpriseInformationSystems
104
certain economic agents want to gain control over
particular resources. Economic Events (e.g.,
produce, exchange, consume, distribute) result in
changes (i.e., increases and decreases) of resource
stocks (Yu, 1976), whereas Economic Agents
represent legal or natural persons that participate in
economic events (e.g., performing a task, enacting a
process) or have custody over resources (i.e., having
physical control over resource or controlling the
access to resources)(ISO/IEC, 2007).
Later, the constructs from the data modeling
grammar were augmented with axioms to create the
actual REA ontology (Geerts and McCarthy, 2004).
These axioms address the rules that govern business
seen from the perspective of a single trading partner
and describe the set of models intended by the
ontology (Guarino, 1998).
The first REA axiom stipulates that at least one
inflow event and one outflow event exist for each
economic resource and that inflow and outflow
events must affect identifiable resources (Geerts and
McCarthy, 2004). Consequently, this axiom requires
that every economic resource has its origin in an
inflow event (i.e., increment) and a purpose (i.e.,
being used in an outflow/decrement event).
The second REA axiom addresses the economic
rational by requiring that all events effecting an
outflow must be eventually paired in duality
relationships with events effecting an inflow and
vice- versa (Geerts and McCarthy, 2004). Together,
these two axioms define a healthy metabolism for an
enterprise. The first axiom requires that all resources
are useful and no resources will be stored
perpetually. The second axiom requires that the
enterprise is rewarded for its efforts, preventing that
its resources drain away. The second REA axiom is
also called the duality axiom. Duality balances
changes in resources due to economic activity (Ijiri,
1975) and relates back to REA’s accounting
background. For instance, duality in market
transactions dictates that when a company sells
products to a customer (i.e., an economic event that
decreases the value of the company’s inventory of
products), a requiting event like a payment or
delivery of equally or higher valued goods (e.g., as
in barter trade) by the customer must follow,
meaning that there is a dual economic event that
balances the decrease in value caused by the sale.
The third REA axiom then specifies that each
exchange needs an instance of both the inside and
outside subsets, requiring that each business
transaction involves at least two trading partners
(i.e., the enterprise that defines the viewpoint and an
outside agent (e.g., supplier, customer)).
Additionally, this axiom specifies that there is
always an agent inside the enterprise (e.g.,
salesperson) that is accountable for the transaction.
Most recently, REA’s trading-partner view on
the economic reality was complemented with an
independent-observer view. This independent-
observer view was developed for the purpose of
developing an ISO standard for open-edi (i.e.,
electronic data interchange) that is specific for
business transactions (ISO/IEC, 2007).
3 THE REA CONCEPTUAL
MODELING GRAMMAR
This section presents the conceptual-modeling
grammar that is based on the REA ontology and is
meant to be used for representing business
transactions in a modeling context that requires both
a trading-partner view and an independent-observer
view. Committing a conceptual-modeling grammar
to the conceptualization specified by a domain
ontology (like REA is) ensures that relevant domain
knowledge is captured (Guarino and Giaretta, 1995).
This knowledge includes conditions that specify the
configurations in the domain that are possible and
those that are not (Evermann and Wand, 2005).
Fig. 1 shows the conceptual-modeling grammar
that presents the trading-partner and independent-
observer views as mutually compatible views on the
same business reality. The model contains three
REA primitives (i.e. economic resource, economic
event, and economic agent) and a new concept (i.e.
organizational unit) that allows us to integrate the
mutually compatible views.
The Organizational Unit concept is used to
model that certain economic agents (i.e.,
organizational units) have control over economic
resources (i.e., ownership of the right to derive
economic benefit from a resource), which entails the
discretionary power to use or dispose of these
resources via economic events in a legal way, where
other (ordinary) economic agents can only have
physical access (i.e., custody) to economic
resources. Organizational units represent the entities
that experience the effect of economic events,
whereas agents represent the entities that engage in
events (e.g., an employee performs an event that
affects his employer’s resources). So agents may
have or control physical access to economic
resources of which they are not the owner (i.e.,
having custody (ISO/IEC, 2007) but not economic
control over the resources), which means that in that
case the agents act on behalf of organizational units.
AnEnterprise-ontologybasedConceptual-modelingGrammarforRepresentingValueChainandSupplyChainScripts
105
Figure 1: The REA Conceptual-Modeling Grammar.
For example, an employee is an agent for its
employer (i.e., the employee performs tasks from
which the employer reaps the full benefits). The
effect of economic events that economic units
experience is change of control (i.e., ownership).
The O
N
_
BEHALF
_
OF
association (fig. 1) can also
represent that an organizational unit, which is a kind
of economic agent, acts on behalf of another
organizational unit (e.g., a subsidiary on behalf of a
parent company).
In fig. 1, the T
RANSACTION
V
IEW
class models
the duality principle embedded in the second REA
axiom from the perspective of a single
organizational unit (i.e. trading-partner view), which
judges whether the increments and decrements it
experiences in its perception of a transaction are
well-balanced. The I
NFLOW
and O
UTFLOW
classes
were added to show the trading-partner view of
organizational units that respectively gain or lose
control (e.g., ownership) over resources and how the
resource stocks they control respectively increase or
decrease in value. The E
CONOMIC
E
VENT
class was
added to represent the independent-observer view on
each economic event. The independent-observer and
trading-partner view were made mutually
compatible by linking the I
NFLOW
and O
UTFLOW
classes to the E
CONOMIC
E
VENT
class, which
contains their perspective independent attributes
(e.g. date). Subjective (i.e., related to the view of an
organizational unit) attributes (e.g. value) need to be
represented inside the I
NFLOW
and O
UTFLOW
classes
as they relate to the perspective of a single trading
partner, which is represented by the
T
RANSACTION
V
IEW
class.
The first REA axiom requires that in conceptual
modeling scripts every economic event relates to one
or more economic resources through at least one
inflow and one outflow, and that every economic
resource relates to one economic event through and
inflow and another economic event through an
outflow.
The third REA axiom exclusively describes
conceptual modeling scripts for exchanges, requiring
that in these scripts the increment perception of an
economic event is modeled by relating an
organization unit to the economic event through an
inflow and a transaction view and that the decrement
perception of an economic event is modeled by
relating another organization to the same economic
event through an outflow and another transaction
view. The third REA axiom also stipulates that there
must always be an economic agent that participates
in an economic event. The participation association
between an economic agent and an economic event
indicates that this economic agent engages in
economic events for which it is accountable on
behalf of this organizational unit.
REA also explicitly recognizes E
CONOMIC
_
C
OMMITMENTS
, which are promises to perform
economic events in the future as specified by a
schedule or contract. As commitments represent
planned events, the commitment side of the
conceptual modeling grammar mirrors the event side
of the model. Resembling events, commitments can
be viewed as increment, decrement or both by an
organizational unit. For instance, one clause in a
contract may involve a future loss of resources (i.e.,
sale and delivery) for one organizational unit and a
future gain of these resources (i.e., acquisition and
receipt) for its opponent, whereas another clause in
the same contract specifies the amount of money to
be paid by the latter to the former. The R
ESERVE
relationships then indicates which resources are
reserved for the fulfillment of which commitments
and what the result of this fulfillment will be, where
the similar I
NCREMENT
and
D
ECREMENT
relationships shows which resources are involved in
an economic event and how the value of their stocks
are affected.
Like events, commitments are dual in nature and
such commitments are said to be reciprocal (Geerts
and McCarthy, 2002). In fig. 1, reciprocities, like
ICEIS2013-15thInternationalConferenceonEnterpriseInformationSystems
106
dualities, are represented by the TRANSACTIONVIEW
class, which shows that the appreciation of balanced
increment and decrement commitments is subjective
since it is related to the viewpoint of exactly one
organizational unit (e.g., the price paid or
installment plan for a car is deemed fair by the
buyer, the remuneration received for a car is deemed
fair by the seller). In addition, increment
(decrement) commitments can be fulfilled by one or
more inflow (outflow) events.
To improve graph readability, the association
primitives between the E
CONOMICAGENT class and
the ECONOMICRESOURCE (i.e. custody), ECONOMIC_
EVENT (i.e. participation), ECONOMICCOMMITMENT
(i.e. specify) classes are not shown in fig. 1.
4 ARCHETYPAL CONCEPTUAL
MODELING SCRIPTS
This section presents archetypal conceptual
modeling scripts exemplifying a number of concept
patterns (and variants) that apply when using the
conceptual-modeling grammar introduced above.
Additionally, this section demonstrates how the new
grammar allows integrating the features of trading-
partner and independent-observer view conceptual
modeling scripts.
Figure 2: The Economic Agreement script.
The conceptual modeling script, which is
represented as a UML object diagram, in fig. 2
exemplifies the use of the conceptual-modeling
grammar to model an economic agreement, which is
an arrangement of reciprocated economic
commitments between two trading partners
(ISO/IEC, 2007), representing the independent-
observer view and both trading-partner views of the
modeled transaction. To model the agreement, this
economic agreement model applies the view
integration principles introduced by (Laurier et al.,
2010 ) at the level of economic commitments instead
of economic events.
In the economic agreement script (fig. 2) models
two opposing views of a transaction. The transaction
will involve exchanging pizza for money from an
independent-observer perspective. From Pizza
Luigi’s (i.e. seller) perspective, the exchange will
involve giving pizza in return for cash. From John
Doe’s (i.e. buyer) perspective, the exchange will
involve giving cash in return for pizza. From the
independent-observer perspective, the opposing
views can be distinguished easily as the pizza
transfer commitment is perceived as a decrement
commitment (i.e. future outflow) by the seller and an
increment commitment (i.e. future inflow) by the
buyer. On the other hand, the cash transfer is
perceived as a future inflow by Pizza Luigi and a
future outflow by John Doe. The agreement in fig. 2
also specifies that Pizza boy Tom will participate in
both transfers on behalf of Pizza Luigi.
Figure 3: The Transfer Fulfillment script.
Fig. 3 shows from the independent-observer
perspective and both trading-partner views how the
T
RANSFER PIZZA economic commitment is fulfilled
by a P
IZZA TRANSFER economic event.
Consequently, the upper half of fig. 3 is identical to
the upper half of fig. 2. The lower half of fig 2 was
omitted because the fulfillment of the T
RANSFER
CASH economic commitment is almost identical to
the fulfillment of the T
RANSFER PIZZA economic
commitment displayed in fig. 3. Therefore, it should
AnEnterprise-ontologybasedConceptual-modelingGrammarforRepresentingValueChainandSupplyChainScripts
107
be feasible for the reader to complete the model
given the example in fig. 3.
As committed the P
IZZA TRANSFER economic
event, which fulfills the TRANSFER PIZZA economic
commitment, is perceive as a resource outflow by
Pizza Luigi and as a resource inflow by John Doe.
As specified by the commitment, Pizza boy Tom
participates in the event on behalf of Pizza Luigi and
the reserved resource (i.e. the P
IZZA) transferred
from Pizza Luigi’s to John Doe’s.
Fig. 4 shows from John Doe’s trading-partner
view how an agreement or contract can be settled.
Consequently, the left-hand side of fig. 4 is identical
to the left-hand side of fig. 2. The right-hand side of
fig. 2 was omitted as the settlement of John Doe’s
perspective on the agreement mirrors Pizza Luigi’s
perspective. Therefore, it should be feasible for the
reader to complete the model given the example in
fig. 4. As agreed, the T
AKE PIZZA increment
commitment, which is known as the T
RANSFER
PIZZA economic commitment in the independent-
observer view, is fulfilled by the T
AKE PIZZA inflow
and the GIVE CASH decrement commitment, which
is known as the TRANSFER CASH economic
commitment in the independent-observer view, is
fulfilled by the G
IVE CASH outflow. In the
independent-observer view, the TAKE PIZZA inflow
is known as the T
RANSFER PIZZA economic event
and the GIVE CASH outflow is known as the
TRANSFER CASH economic event. As specified by
the commitments, Pizza boy Tom participates in the
commitment fulfilling inflow and outflow.
Figure 4: The Settlement script.
Claims can be modeled as incomplete settlement
scripts. A positive claim is the expectation of a
trading partner to receive a future inflow that fulfills
an increment commitment that is enforceable due to
a reciprocal decrement commitment that has been
fulfilled by an outflow (.e.g. John Doe paid Pizza
boy Tom and expects to receive his pizza). A
negative claim is the obligation of a trading partner
to deliver a future outflow that fulfills a decrement
commitment that is enforceable due to a reciprocal
increment commitment that has been fulfilled by an
inflow (e.g. John Doe received his pizza and is
obliged to pay).
Next to modeling the components of an
exchange transaction between two trading-partners,
as shown in fig. 2, 3 and 4, the conceptual-modeling
grammar can be used to represent the components of
a production process, including its planning and
execution. In the REA terminology, such a model of
a production process is called a conversion model, as
it represents the conversion of one or more inputs
into one or more outputs. For a more detailed
analysis of conversion models, we refer to (Laurier
and Poels, 2012).
Figure 5: The Conversion Fulfillment script.
Fig. 5 shows the main components of a conversion
script. First, it should be noted that a conversion
script always refers the perspective of a single
trading-partner (i.e. the organizational unit that has
the conversion script as part of its business
processes). Like the transfer fulfillment script (fig.
3), which is its exchange equivalent, the conversion
fulfillment script consists of a planning layer and an
execution layer. The planning layer consists of the
economic commitment to make pizza; the execution
layer consists of the economic event that actually
produces the pizza. In fig. 5, the planned pizza
production process involves using flour to make
pizza. When additional planned in- and outputs need
to be modeled, decrement and increment
commitments can be added to the script. The script
also reveals that the economic commitment specifies
ICEIS2013-15thInternationalConferenceonEnterpriseInformationSystems
108
that “Baker Chet” will be responsible for the
execution. The execution layer, shows that Baker
Chet executed the actual pizza baking process
exactly as planned, consuming the inputs that were
reserved and producing the pizza’s that were
expected.
5 COMPARATIVE ANALYSIS
In this section, the REA conceptual-modeling
grammar for representing business transactions in an
integrated enterprise-centric and supply-chain-
centric conceptual modeling context is compared
with well-known related conceptualizations that are
used for modeling business transactions. First, the
merits of the new REA grammar vis-à-vis more
traditional independent-observer and trading-partner
view REA models are discussed.
In the new REA-based grammar, the ‘from’ and
‘to’ semantics that are typical for independent-
observer view models can be derived from the
inflow and outflow semantics. In the independent-
observer perspective, an event as perceived by an
independent observer makes resources flow from the
organizational unit that perceives it as an outflow to
the organizational unit that perceives it as an inflow.
In the fulfill script (fig. 3), pizza is transferred from
Pizza Luigi to John. Table 1 summarizes how the
inflow and outflow semantics of the conceptual-
modeling grammar can be translated to more
traditional trading-partner and independent view
model semantics.
Table 1: Inflow and Outflow Semantics Summary.
New
grammar
Trading-partner
view
Independent
view
Inflow Increment event To
Outflow Decrement event From
Due to the exchange focus and the implicit trading-
partner view it is possible to register one and the
same transfer event as an increment event (i.e.,
receipt) in one system and a decrement event in
another system. The REA conceptual-modeling
grammar, on the other hand, makes it also possible
to model business from both the trading-partner and
independent-observer point of view, meaning that
goods and money transfers are recognized only once
in the independent-observer view but may be
observed and registered twice or more (i.e., once in
the view of each trading partner (e.g., as increment
for one party and as decrement for the other party)).
Trading-partner models like the settlement script
(fig. 4) mirror each other and conform to the
semantics in the earlier REA trading-partner view
models. For example, McCarthy (1982) identifies
inside and outside parties, which are roles for
economic agents. In McCarthy’s models, the inside
party is the person (i.e., economic agent) that is
accountable for the transaction, the outside party the
trading partner. In the example conceptual-modeling
scripts presented above, the outside party can be
recognized as the agent that does not act on behalf of
the organizational unit that defines the transaction
view. The settlement script (fig. 4) models John
Doe’s transaction perspective. John acts on behalf of
himself, which means he also plays the inside party
role. If another person would act on behalf of John,
that other person would play the inside party role. In
the settlement script, the outside party role is played
by Pizza Luigi. Pizza boy Tom would be the inside
party from the perspective of Pizza Luigi. A more
detailed analysis of the inside and outside party roles
can be found in (Laurier et al., 2010 ).
In the new grammar the trading partner that
defines the view is explicitly modeled as the
organizational unit that is related to the transaction
view, where this view defining unit is implicit in
McCarthy’s, and also Hruby’s (2006), trading-
partner view models. In the example trading partner
conceptual-modeling scripts, the Pizza transfer is
perceived as an inflow by John and a outflow by
Pizza Luigi, where the money transfer is perceived
as an inflow by Pizza Luigi and an outflow by John.
For John acquiring the pizza is dual to paying for it,
where for Pizza Luigi delivering the pizza is dual to
getting paid for it.
Next to models that document the current state
and history of an organizational unit, the new REA
conceptual modeling grammar can also be used to
generate models that project planned future states.
Of all potential future organizational unit states,
such models include those that are desired and
documented (e.g., contracts and agreements). Those
contracts consist of increment and decrement
commitments that are paired in reciprocity with each
other and that mimic the economic agreement script
exemplified in fig. 2.
6 CONCLUSIONS
This paper presented a new conceptual modeling
grammar for the business domain that can be used
for the modeling of business transactions from the
perspective of trading partners as well as third
parties. The conceptual basis for this model is the
AnEnterprise-ontologybasedConceptual-modelingGrammarforRepresentingValueChainandSupplyChainScripts
109
REA ontology. The paper also presented archetypal
conceptual-modeling scripts that instantiate the
conceptual-modeling grammar. Via these scripts,
exemplifying typical transaction patterns, it was
demonstrated that the proposed model enables
taking both an independent-observer view and a
trading-partner view on business reality. This is
undoubtedly the most distinctive feature of our
proposal because it allows modelers to construct
business models that provide a basis for developing
information systems for each enterprise taking part
in a supply chain and at the same time for
facilitating system interoperability and information
sharing amongst business partners.
The introduction of the organizational unit
concept as business semantics viewpoint
determining entity is a key feature of our model.
Where previously, the perspective on business
reality of each enterprise was represented in a
separate script, the views of different enterprises that
are part of a supply chain can now be jointly
represented in a single script via the organizational
unit concept and its relations with events and agents.
This explicit representation of enterprise viewpoints
allows for a central administration of independent-
view transaction information and a federated
administration of transaction information, which
should help preserve their autonomy and isolation by
sharing only information that is registered in their
trading-partner view information systems that is
relevant for the independent-observer view. Since
both types of systems can now be based on the same
conceptual modeling script, data interoperability is
also expected to be facilitated when the integrated
enterprises reach agreement about a minimal set of
attributes (e.g., identifiers).
A limitation, though the result of a deliberate
choice, is that the new REA-based grammar
abstracts from application specific inferences like
the sequencing of events or other process control
flow aspects that are, for instance, key to workflow
modeling. Another limitation is that only a
descriptive evaluation of the presented conceptual
modeling grammar was presented here. Another type
of descriptive evaluation has been presented in
(Laurier and Poels, 2012), where a conceptual
modeling script for traceability is presented as a
proof of concept for this conceptual modeling
grammar.
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