SYSDYM

Preliminary study on system dynamics modelling including an application test to analyse implementation obstacles regarding climate protection and climate adaptation measures

Background

The transformation of society towards a sustainable future is very complex due to multiple influences, interactions and pathways and thus difficult to capture, predict or control. The method of systems dynamics (SD) modelling is appropriate to analyse the behaviour of dynamic, complex systems by analysing the system structure that triggers the system behaviour. Examples of such systems are the implementation of climate adaptation and mitigation measures, the dynamics of the Covid-19 pandemic or the evolution towards a sustainable society. Qualitative system dynamics attempts to analyse the interdependencies as well as the prevailing paradigms and structures of a system through participatory processes such as group model building (1). In this process, the system knowledge of actors from different disciplines is summarised in a causal loopdiagram in order to achieve the most holistic understanding possible. In these diagrams, the interactions of influencing factors are represented by connectors (arrows with polarities), which lead to the non-linear, complex behaviour of the system in reinforcingand balancing feedback loops. Quantitative system dynamics aims to resolve the effects of these system interrelationships and the complexity of dynamic processes in time by means of simulations. Scenarios are used to analyse which social factors and policy instruments have an influence on the dynamics of the system and how this can be influenced in a positive sense (2). This is illustrated in Figure 1.

Figure 1: System dynamics modelling is divided into two parts: the qualitative part, which attempts to capture the structure of the system under consideration by integrating the mental models or system understandings of individual actors in an causal loop diagram, and the quantitative part, which aims to analyse the leverage points and dynamics of the system more precisely through simulations and, for example, to test the effectiveness of policy instruments. The simulation model is always a simplification of the mental model (existing system understanding) and this in turn of the complex system under consideration.

Aim

The overall objective of the project was to explore the methods of SD modelling as an inter- and transdisciplinary method for future application at the Institute in order to better understand complex systems and dynamic processes of sustainable development. Such an understanding of complex processes at different spatial scales is also of central importance as a basis for the successful sustainability transformation of socio-ecological-technical systems. In the one-year SYSDYM project, both the possibilities and limitations of SD modelling for the research questions of the IOER were compiled through a screening of the literature. A central aim of the project was also to test first applications of qualitative and quantitative SD modelling for use at the IOER.

Research Questions

To what extent can SD modelling reproduce a holistic system understanding of complex and dynamic processes regarding sustainability developments?

Is the joint generation of causal loop diagrams with different actors in practice effective in order to develop a common understanding of implementation obstacles, new insights and corresponding approaches to solutions? If so, how high is the effort?

Can SD modelling strengthen the interdisciplinary cooperation and mutual understanding of different research disciplines regarding sustainability transformation using qualitative and quantitative SD approaches?

Which scale levels of spatial development can be mapped by SD modelling?

Project results

  • Extensive literature research on the methodology of system dynamics modelling with a focus on sustainable developments of socio-ecological-technical system
  • Conducting workshops to test the applicability and usefulness of qualitative system dynamics (participatory system dynamics modelling/group model building) with actors from academia (IOER and TU Dresden)
  • Conducting workshops to test the applicability and usefulness of qualitative system dynamics with actors from practice (housing associations EWG Dresden and WBG Zukunft Erfurt)
  • Analysis of suitable fields of application for system dynamics modelling at the IOER via surveys, workshops and literature research
  • Creation of a first aggregated SD simulation model (quantitative SD), which illuminates the low implementation dynamics of energetic refurbishment (3)
  • Synthesis of the project findings in a final workshop for interdisciplinary discussion on how system dynamics modelling at the IOER can be used in the future to address the research questions.

Literature

 Recommended literature as introduction into the basics of System Dynamics and System Thinking

  • Donella H. Meadows: „Thinking in Systems: A Primer“, 2008 (ISBN: 9781603580557)
    - Basics in System Thinking and System Dynamics Modeling - 
  • David Peter Stroh: „Systems Thinking for Social Change: A Practical Guide to Solving Complex Problems, Avoiding Unintended Consequences, and Achieving Lasting Results”, 2015 (ISBN: 9781603585804)
    - Basics in (qualitative) System Thinking -
  • Peter S. Hovmand: “Community Based System Dynamics”, 2014 (ISBN: 978-1-4614-8763-0)
    - Basics in participatory modeling (Group Model Building) -
  • Andrew Ford: “Modeling the Environment, Second Edition: An Introduction To System Dynamics Modeling Of Environmental Systems Andrew Ford”, 1999 (ISBN 1559636017)
    - Basics in quantative (and qualitative) System Dynamics Modeling -

Literature
(1) Doylea, J.K., Ford, D.N.: Mental models concepts for system dynamics research, System Dynamics Review 14, 3-29, (1998)

(2) Honti, G., Dörgő, G., Abonyi, J.: Review and structural analysis of system dynamics models in sustainability science, Journal of Cleaner Production, Volume 240, (2019)

(3) Schünemann, C.; Sidorova, A.; Gkini, C.; Kopainsky, B.: Using system dynamics modelling to analyse the interplay of policies and societal motivation for promoting energetic renovation. In: Proceedings of the 2021 System Dynamics Conference, Virtually Chicago, USA, July 26-30 2021. System Dynamic Society, 1-30, 2021.

The Leibniz Institute of Ecological Urban and Regional Development is jointly funded by the federal government and the federal states.

FS Sachsen

This institute is co-financed by tax funds on the basis of the budget approved by the Saxon State Parliament.