inputs and outputs are owned by the E
MPLOYER
,
without a transfer of ownership during the
conversion process. This representation is closer to
reality than Hruby’s implicit ownership transfer
during the conversion process. The template also
shows that an E
MPLOYEE
performs the
T
RANSFORMATION
event. For representing an entire
production process, subsequent events can be
modelled using the transformation template, creating
multiple events that are all related to the same
economic unit (i.e. the enterprise in which they take
place) and share one or more resources (i.e. the
output of one conversion process is the input for a
subsequent one). At the start of such a process
model we find one or more exchange templates (fig.
6) that represent the acquisition of the process inputs
and at the end we find one or more exchange
templates that represent how revenue is generated
from process outputs.
Figure 7: REA Transformation Event Model.
4 CONCLUSIONS
The consolidated reference model presented in this
paper supports inter-enterprise (e.g. for transaction
recording systems) and intra-enterprise (e.g. for
production process monitoring systems) data, as
both kinds of systems can now rely on the same
reference model.
Key to the integration of the existing REA
reference models was the partial redefinition of the
economic unit and agent concepts. The redefinition
of the economic unit concept allows models to
represent previously implicit semantics related to the
control over resources. Where previously the view
of every enterprise was represented in a separate
model, the scope of different enterprises can now be
represented in a single model via the economic unit
concept and its relations with resources, events and
agents. This explicit representation of enterprise
boundaries allows for a central administration of
transactions between and transformations within
enterprises.
Where the redefinition of the economic unit and
agent concepts facilitates the integration of data
across enterprise boundaries, the intuitive event
concept eases process modelling. Together, they can
help improve product traceability by identifying the
event chains (i.e. transfer and transformation events)
that lead to the products, irrespective of the number
of enterprises (and enterprise information systems)
in which products and their constituents have their
origin. Such product tracing infrastructure might
support product authentication in the battle on
counterfeit and other supply chain intrusions (e.g.
food safety scandals) (Bechini et al., 2008). It may
also help to trace the origin of money (e.g. drugs
money) in the battle against money laundering.
REFERENCES
Bechini, A., Cimino, M. G. C. A., Marcelloni, F. &
Tomasi, A. (2008) Patterns and technologies for
enabling supply chain traceability through
collaborative e-business. 50, 342-359.
Geerts, G. L. & Mccarthy, W. E. (2002) An ontological
analysis of the economic primitives of the extended-
REA enterprise information architecture. International
Journal of Accounting Information Systems, 3, 1-16.
Geerts, G. L. & Mccarthy, W. E. (2004) The Ontological
Foundation of REA Enterprise Information Systems.
Michigan State University.
Giachetti, R. E. (1999) A standard manufacturing
information model to support design for
manufacturing in virtual enterprises. Journal of
Intelligent Manufacturing, 10, 49-60.
Hruby, P. (2006) Model-driven design using business
patterns, Berlin, Springer.
ISO/IEC (2007) Information technology - Business
Operational View Part 4: Business transaction scenario
- Accounting and economic ontology. ISO/IEC FDIS
15944-4: 2007(E).
Jansen-Vullers, M. H., Van Dorp, C. A. & Beulens, A. J.
M. (2003) Managing traceability information in
manufacture. International Journal of Information
Management, 23, 395-413.
Mccarthy, W. E. (1982) The REA Accounting Model: A
Generalized Framework for Accounting Systems in a
Shared Data Environment. Accounting Review, 57,
554-578.
Mccarthy, W. E. (2003) The REA Modeling Approach to
Teaching Accounting Information Systems. Issues in
Accounting Education, 18, 427-441.
Porter, M. E. & Millar, V. E. (1985) How information
gives you competitive advantage. Harvard Business
Review, 63, 149-160.
Shin, K. & Leem, C. S. (2002) A reference system for
internet based inter-enterprise electronic commerce.
Journal of Systems and Software, 60, 195-209.
Weber, R. (1986) Data Models Research in Accounting:
An Evaluation of Wholesale Distribution Software.
Accounting Review, 61, 498.
ICEIS 2010 - 12th International Conference on Enterprise Information Systems
164