Using Systems Thinking and System Dynamics Modeling to Understand Rebound Effects

Abstract

Processes leading to an increase of demand for a resource as a consequence of increasing the efficiency of using this resource in production or consumption are known as (direct) rebound effects. Rebound effects at micro and macro levels tend to offset the reduction in resource consumption enabled by progress in efficiency. Systems thinking and modeling instruments such as causal loop diagrams and System Dynamics can be used to conceptualize the structure of this complex phenomenon and also to communicate model-based insights. In passenger transport, the rebound effect can be invoked by increased cost efficiency (direct economic rebound) and/or increase in speed (time rebound). In this paper we review and compare two existing models on passenger transportincluding a model on the role of information and communication technologywith regard to the feedback loops used to conceptualize rebound effects.

Consequences of Future Data Center Deployment in Canada on Electricity Generation and Environmental Impacts: A 2015–2030 Prospective Study

“…Additionally, several researchers investigated the unwanted effects of ICT usage that can equal or even offset the positive effects expected by improving human activities with ICT (Takahashi et al. ; Ahmadi Achachlouei and Hilty ; Börjesson Rivera et al. ).…”

“…Ong and colleagues (2014) and Borggren and colleagues (2013) compared face-to-face meetings with videoconference meetings and concluded that the latter are not always better than the former. Additionally, several researchers investigated the unwanted effects of ICT usage that can equal or even offset the positive effects expected by improving human activities with ICT (Takahashi et al 2006;Ahmadi Achachlouei and Hilty 2016;Börjesson Rivera et al 2014). If such unwanted effects were to occur, the impacts of each scenario would be more significant.…”

Optimising the Use of National CORS Data in the Context of Thailand

“…SD provides aggregate perspectives (top-down), whereas AB perceives a system from the interactions of different units (bottom-up) (Macal, 2010). Compared to SD, AB requires more resources and data to use in modelling (Ahmadi Achachlouei & Hilty, 2015). AB focuses on the modelling of individual elements of a system, whereas SD is a more appropriate holistic modelling approach.…”

“…This research seeks to provide policy scenarios that serve the research aim. System Dynamics (SD) and Agent-Based modelling (AB) are two simulationbased modelling techniques to address social systems (Macal, 2010;Sokolova & Fernández-Caballero, 2012;Ahmadi Achachlouei & Hilty, 2015). SD provides aggregate perspectives (top-down), whereas AB perceives a system from the interactions of different units (bottom-up) (Macal, 2010).…”

Towards a Systemic View on Rebound Effects: Modelling the Feedback Loops of Rebound Mechanisms

“…In some cases, RE was investigated as a type of unintended consequence (Laurenti et al, 2016) or leading to policy resistance in sustainability transitions (de Gooyert et al, 2016). RE has also been the primary phenomenon of interest in a few studies (Achachlouei and Hilty, 2016;Freeman, 2018;Freeman et al, 2016). Qualitative SD modelling helped indicate the specific structures leading to RE, such as decreased cost of driving leading to additional driving (Stepp et al, 2009), additional recycling minimising costs and leading to increased demand for materials (Dace et al, 2014), or the build-up of social norms reinforcing the amount of transportation (Freeman et al, 2016).…”