Invariant conditions in value system simulation models

• Published in: Decision Support Systems Vol. 56; pp. 275 - 287
• Main Authors: Laurier, Wim, Poels, Geert
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01-12-2013; Elsevier; Elsevier Sequoia S.A
• Subjects: Applied sciences; Axioms; Business; Business process; Computer science; control theory; systems; Computer simulation; Construction; Construction costs; Exact sciences and technology; Financial performance; Firm modelling; Information systems. Data bases; Integrated approach; Integration; Invariants; Logistics; Mathematical models; Memory organisation. Data processing; Ontology; Operational research and scientific management; Operational research. Management science; Resource-event-agent ontology; Simulation; Software; Studies; Supply chain; Supply chain management; Supply chains; Value chain; Value system; Virtual organization; Supply chain; Business process; Integration; Resource-event-agent ontology; Value chain; Virtual organization; Value system; Ontology; Accounting; Modeling; User interface; User assistance; Integrated system; Invarying system; Production process; Firm strategy; Discrete event system; Computer simulation; Reuse; Integrated management; Logistic distribution; Manufacturing process; Virtual enterprise; Firm management; Added value; Logistics
• ISSN: 0167-9236; 1873-5797
• DOI: 10.1016/j.dss.2013.06.009

This paper presents a framework for the integration of supply chain (or logistics/distribution), value chain (or financial), and business process (or operational/manufacturing) simulation models, which should facilitate assessing the impact of supply chain and operational changes on an enterprise's financial performance. A Design Science approach is taken to demonstrate that the REA ontology, which provides a shared conceptual ground for these three model types, and its axioms, which describe invariant conditions for value systems, can help to build conceptually sound simulation models and identify the integration points between these models. It is further shown how these three types of simulation models can be integrated into one value system model for discrete event simulation, making use of the ExSpecT simulation tool. With this ontology-based framework, simulation model builders should be able to scope their models better and define integration points with other models, which is expected to promote the (re)use of simulation models for different purposes (e.g., simulating logistical, operational and financial performance).
•Defining the scope of business process, supply and value chain simulation models•Rephrasing the REA modeling axioms for each of these types of simulation models•Identifying integration points between these models through the REA ontology•Integrating these three types of models into a hierarchic value system model•First application of the REA ontology for building discrete-event simulation models