Development of methods for the simplification of complex group built causal loop diagrams: a case study of the Rechna doab

Asif, M; Inam, A; Adamowski, J; Shoaib, M; Tariq, H; Ahmad, S; Alizadeh, M; Nazeer, A

Abstract

Complex systems are generally challenging to model due to many variables whose relationships and dependencies are often difficult and time-consuming to comprehend. Simplifying complex systems can remove barriers to adaptation and application by marginalized stakeholders. The main aim of the proposed research is to compare two simplification methods, i.e., Endogenisation, Encapsulation and Order-Oriented Reduction (EEOR) and Thematic Maps Development (TMD), in terms of maintaining system integrity. A case study was conducted in the Rechna Doab region of Pakistan. This was a qualitative system dynamics model study, which included 79 variables, 32 duplicate or ghost variables and 15 loops. EEOR simplifies Causal Loop Diagrams (CLDs) by removing exogenous variables and adjusting loops in successive steps. In this study, EEOR eliminated 46 variables and 6 critical feedback loops during the simplification of the complex case study CLD and did not maintain the system's integrity. The main risk of this technique is eliminating variables without understanding their significance. Accordingly, despite the goal of a better understanding, EEOR led to a loss of 60% of the final merged CLD. TMD divided the final integrated case study CLD into four thematic sub-modules: agriculture, environmental, social and industrial, and government subsidies. Each variable and loop were placed in their respective thematic sub-modules. This separation enhanced the understanding and evaluation of individual thematic sub-modules. When recombined into a single diagram, these sub-modules were able to represent the entire system without losing any information. This research can help to simplify complex system models to help system understanding by novice stakeholders, while maintaining the integrity of the system. Consequently, this simplification approach can help further increase stakeholder engagement in participatory modelling exercises.

• Journal Article Type: Article
• Acceptance Date: Oct 30, 2022
• Online Publication Date: Dec 6, 2022
• Publication Date: Dec 6, 2022
• Deposit Date: Jan 26, 2023
• Journal: Ecological Modelling
• Print ISSN: 0304-3800
• Publisher: Elsevier
• Volume: 476
• Pages: 110192
• DOI: https://doi.org/10.1016/j.ecolmodel.2022.110192
• Publisher URL: http://doi.org/10.1016/j.ecolmodel.2022.110192