Guido L. Geerts

An ontological analysis of the economic primitives of the extended-REA enterprise information architecture

Abstract The resource–event–agent (REA) model for enterprise economic phenomena was first published in The Accounting Review in 1982. Since that time, its concepts and use have been extended far beyond its original accountability infrastructure to a framework for enterprise information architectures. The granularity of the model has been extended both up (to enterprise value chains) and down (to workflow or task specification) in the aggregation plane, and additional conceptual type-images and commitment-images have been proposed as well. The REA model actually fits the notion of domain ontology well, a notion that is becoming increasingly important in the era of E-commerce and virtual companies. However, its present and future components have never been analyzed formally from an ontological perspective. This paper intends to do just that, relying primarily on the conceptual terminology of John Sowa. The economic primitives of the original REA model (economic resources, economic events, economic agents, duality relationships, stock–flow relationships, control relationships, and responsibility relationships) plus some newer components (commitments, types, custody, reciprocal, etc.) will be analyzed individually and collectively as a specific domain ontology. Such a review can be used to guide further conceptual development of REA extensions.

Expert opinion [accounting]

The infrastructure of a corporate enterprise information system is concerned with acquiring, transferring, converting, and selling economic resources such as cash, inventory, and supplies. Accounting systems with individual computerized modules, such as: payroll, accounts payable and receivable, job costing, order entry, and general ledgers, have traditionally tracked such data, and accounting system designers usually have had a preemptive call on the basic schemes used to type economic data. This is because of a need to meet either statutory reporting requirements for governmental agencies, or private reporting requirements for creditors and shareholders. If accountants use these preemptive privileges to force traditional account coding onto the organization database as its fundamental classification architecture (that is, to require early bookkeeper filtering of transaction data), then many dysfunctional effects arise. Our remedy for these deficiencies is to apply the REA (economic resources, events, and agents) conceptual model when analyzing, designing, implementing, and operating an enterprise information system. REA specifically incorporates the semantics of economic objects into a firms information architecture. Such embedding facilitates an information systems initial design, as well as couples its production use with knowledge based decision support systems.

A design science research methodology and its application to accounting information systems research

Natural science research follows a stereotypical pattern and such uniformity makes it easier to recognize and evaluate the results of such research. A similar format has been lacking for design science research. This issue was addressed by Peffers et al. (2008) who defined such a template for design science research for information systems: the design science research methodology (DSRM). In this paper, we first discuss design science research and the DSRM. Then, we illustrate the application of the DSRM to AIS research through retroactive analysis. Finally, we integrate the DSRM into the operational specification of artifact networks and use the REA literature for illustration purposes.

Policy‐Level Specifications in REA Enterprise Information Systems

The Resource‐Event‐Agent (REA) enterprise model is a widely accepted framework for the design of the accountability infrastructure of enterprise information systems. Policy‐level specifications define constraints and guidelines under which an enterprise operates, and they are an extension to the REA enterprise model, adding the “what should, could, or must be” to the “what is.” This paper aims both at comprehensive understanding of policy‐level definitions as part of REA enterprise systems and at understanding of the semantic constructs that enable such definitions. We first explore two distinctive semantic abstractions essential to policy‐level specifications: typification and grouping. The typification abstraction links instances of an object class to concepts for which they are concrete realizations, while the grouping abstraction aggregates objects into collections. We next present a number of patterns for the semantic modeling of policies. Following, we look at policy‐level applications for REA enter...

Augmented Intensional Reasoning in Knowledge‐Based Accounting Systems

A limitation of existing accounting systems is their lack of knowledge sharing and knowledge reuse, which makes the design and implementation of new accounting systems time‐consuming and expensive. An important requirement for knowledge sharing and reuse is the existence of a common semantic infrastructure. In this article we use McCarthys (1982) Resource‐Event‐Agent (REA) model as a common semantic infrastructure in an accounting context. The objective is to make knowledge‐intensive use of REA to share accounting concepts across functional boundaries and to reuse these concepts in different applications and different systems, an approach we call augmented intensional reasoning. Intensional reasoning is the active use of conceptual structures in information systems operations such as design and information retrieval. For augmented intensional reasoning, the conceptual structures are extended with domain‐specific REA knowledge. Sections II and III describe different dimensions of augmented intensional rea...

Modeling Business Enterprises as Value-Added Process Hierarchies with Resource-Event-Agent Object Templates

Applying object orientation to the task of modeling the value-added processes of a business enterprise is a task that should be examined both conceptually and practically. This paper does both, but its main theme is a conceptual reliance on a standardized object template — the REA (resource-event-agent) model — at various levels of abstraction as that template is used to model the economic activities of an enterprise. Deployment of REA concepts in business object design and implementation is a semantic strategy for increasing reusability and interoperability. We explain the components and use of REA models in the context of a simple example, and we discuss also its predictable patterns of implementation compromise. The paper finishes with a discussion of the adaptation of various object-oriented analysis and design techniques to the task of REA modeling of enterprises.

A supply chain of things: The EAGLET ontology for highly visible supply chains

Recently, technological developments, such as radio frequency identification (RFID), have facilitated the identification of individual things and information sharing regarding their behavior throughout the supply chain. Such developments have generated the capabilities of a highly visible supply chain (HVSC): a supply chain where the location of arbitrary individual things can be determined at any point in time by all appropriate supply chain partners, made possible by an “Internet of Things” for the supply chain, referred to as a “Supply Chain of Things.” A critical component of a Supply Chain of Things is an ontology to facilitate the visibility and interoperability of things along the supply chain. As a result, the objective of this paper is to define an ontology that leverages the availability of an individual thing’s (object) identification information within the context of a standard set of economic phenomena that support multiple views in a range of data architectures. Our design science approach begins with a set of ontological primitives and gradually defines structuring principles that provide guidance for the design of supply chain systems that are characterized by increased visibility and interoperability and which facilitate management of and collaborative decision making about supply chain activities. The EAGLET ontology is named after its five primitives: Event, AGent, Location, Equipment, and Thing. The following are some of its unique characteristics: location and equipment are recognized as ontological primitives, and creating and destroying of containment structures is explicitly modeled; the economic phenomena underlying the supply chain are defined from an independent view, as opposed to a trading-partner view; the supply chain is defined from three different perspectives: the physical flow, the chain of custody, and the chain of ownership; event sequences that resemble the economic scripts underlying the supply chain are defined.

Stevie: A Dynamic, Between‐Instructor Collaborative Internet Tool for Learning Cardinalities

Instructors increasingly use a data modeling approach to teach accounting information systems (AIS). An important part of data modeling is the specification of cardinalities. Cardinalities represent constraints on the participation of entities in a relationship and are used to express business practices. Stevie is an Internet tool that helps students learn cardinalities. Stevie has a number of unique features. First, Stevie is a collaborative effort; its content is created by a number of instructors. Second, Stevie is a dynamic Internet application. Dynamic Internet technology enables instructors to manage student accounts, add exercises, and create customized assignments. Further, customized assignments make it easy for instructors to adapt Stevies content to specific learning objectives for their AIS course. For example, instructors can create assignments where students have to define stereotypical cardinality patterns or heuristics for REA relationships. Finally, Stevie supports accounting‐specific cl...

The Belgian Chocolate Company: A Dynamic Data Modeling and Database Design Case for the Accounting Information Systems Class

The Belgian Chocolate Company (BCC) case was designed to be used in an accounting information systems (AIS) class with strong emphasis on the Resource‐Event‐Agent (REA) model, data modeling, and database design. Students are asked to design, implement, and use an accounting database. A unique feature of the case is its delivery through the Internet by means of a dynamic web site. Instructors are able to adapt the content of the case to their specific needs and to create individualized assignments for students.

Automated Integration of Enterprise Accounting Models Throughout the Systems Development Life Cycle

This paper summarizes and projects research in the field of automated software engineering as that work has been applied to the domain of accounting-centered enterprise models. In particular, we review the basic concepts and goals of the REA (Resource–Event–Agent) accounting model and speculate on its past, present, and future use as an embedded domain theory of enterprise economic activity within computer-aided systems engineering (CASE) tools. The REA CASE tools reviewed here include ones like REAVIEWS, CREASY, and REAtool that have already been built plus others like REACH, FREACC, and REAVERSE that have been specified only in theory. The entire systems development life cycle is used as a discussion vehicle to treat these tools and projected future work in an integrated way.