Title: The most common issues in development of causal-loop diagrams and stock-and-flow diagrams

Authors: Vladimír Bureš; Tereza Otčenášková; Marek Zanker; Martin Nehéz

Addresses: Faculty of Informatics and Management, University of Hradec Kralove, 50003 Hradec Kralove, Czech Republic ' Faculty of Informatics and Management, University of Hradec Kralove, 50003 Hradec Kralove, Czech Republic ' Faculty of Informatics and Management, University of Hradec Kralove, 50003 Hradec Kralove, Czech Republic ' Faculty of Electrical Engineering and Information Technology, Slovak University of Technology in Bratislava, Bratislava, Slovakia

Abstract: System dynamics, and the modelling of system dynamics in particular, represent a current as well as a relevant issue. If this modelling is appropriately managed and correspondingly interpreted, it might be efficiently used in decision making. Nevertheless, it is usually quite hard to identify as well as describe and set all the relationships between and among the system elements suitably. During the modelling process, which starts with problem formulation and system boundary definition and ends with policy and scenario propositions, various mistakes occur. This paper presents the most common mistakes identified by four-group model-based single-blind experiment that modellers make during a specific stage of the overall modelling process: development of both causal-loop diagrams and stock-and-flow diagrams. Identification of these issues contributes to their minimisation or even elimination. Consequently, this improves the efficiency of the systems thinking and decision making performed within complex systems.

Keywords: causal-loop diagrams; decision making; modelling mistakes; modelling process; patterns; simulation; single-blind experiment; stock-and-flow diagrams; system dynamics; system thinking.

DOI: 10.1504/IJIEI.2020.115722

International Journal of Intelligent Engineering Informatics, 2020 Vol.8 No.5/6, pp.419 - 438

Received: 17 Apr 2020
Accepted: 07 Sep 2020

Published online: 18 Jun 2021 *

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