Greenhouse gas mitigation policies and the transportation sector: The role of feedback effects on policy effectiveness

Stepp, Matthew; Winebrake, James J.; Hawker, J. Scott; Skerlos, Steven J.

doi:10.1016/j.enpol.2009.03.013

Cited by 67 publications

(50 citation statements)

References 32 publications

(33 reference statements)

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“…Researchers have recognized that environmental regulations and emissions reduction initiatives can be frustrated, reinforced, and otherwise complicated by feedback effects, unanticipated consequences, and behavior which arise in response to regulation. (Stepp et al 2009) Environmental regulations have both direct and indirect effects, and the indirect effects are often difficult to predict or anticipate.…”

Section: Quantifying Environmental Impactmentioning

confidence: 99%

Panama Canal expansion: alleviating global climate change

Mulligan

Lombardo

2011

WMU J Marit Affairs

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This paper quantifies likely changes in greenhouse gas emissions which contribute to anthropogenic climate change, resulting from the expansion of the Panama Canal and the consequent increase in ship-borne commercial transportation from east Asia to the US east coast. Ocean transportation offers higher fuel economy and lower pollutant emissions compared with land transport. Additionally, truck and train transportation of cargo along the US land bridge threatens to overwhelm existing highway and rail systems and limit economic growth. The alternate transportation route for easterly transit of the Panama Canal will reduce overland traffic congestion and enhance economic development by maintaining freight flow efficiency.

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Section: Quantifying Environmental Impactmentioning

confidence: 99%

Panama Canal expansion: alleviating global climate change

Mulligan

Lombardo

2011

WMU J Marit Affairs

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“…As pointed out by Stepp et al (2009) qualitative casual models can be useful in identifying the unintended consequences of policies so that it is only through a set of related policies that the end goal could be met. Furthermore, these can be used to identify the complementarity between policies that together could lead to improved outcomes, what Stepp et al refer to as 'policy synergies'.…”

Section: Discussionmentioning

confidence: 99%

Exploring stability and change in transport systems: combining Delphi and system dynamics approaches

Rees¹,

Stephenson

Hopkins

et al. 2016

Transportation

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Transport is a vast and complex socio-technical system, and despite a clear need to reduce dependence on fossil fuels due to undesirable environmental impacts, it is largely locked into business-as-usual. Systems approaches are a useful way to help make sense of multiple competing influences which may be simultaneously driving change and supporting the status quo. This paper applies qualitative system dynamics modelling to help interpret the results of a Delphi study into global transport transitions, involving 22 international experts in various aspects of transport. The main contribution of the paper is its exploration of the use of system dynamics (SD) modelling to interpret the Delphi findings. SD modelling was used to reveal and elucidate the causal arguments put forward by the expert panel about the factors driving business-as-usual, the factors creating barriers to more sustainable transport systems, and the drivers of change. The SD model is used to explore and expose the key causal patterns at play, and how these interact to both support and hinder change. The resulting model shows the complex, interdependent dynamics involved in supporting the status quo. Even at the relatively high level of analysis reported here, the model is useful in revealing interdependencies between parts of the system, where change in one part may well have knock-on effects elsewhere in the system. In particular the model reveals the strong reinforcing loops that act to minimise the impact of change drivers and thus retain the dominance of automobility. The result is a system that is highly dependent on the continued existence of key reinforcements such as policies that subsidise fossil fuels. From a methodological perspective, the outcomes of the Delphi study provided a rich source of qualitative material which was highly suitable for developing a system dynamics model.

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“…Given the current knowledge about a system (in which a rebound effect occurs) and knowledge about historically and socially constructed influencing factors, a systems thinking and modeling approach assists in structuring a policy issue regarding rebound effects, conceptualizing and linking socio-economic causal relations, and communicating and enhancing such understanding of the system and its behavior over time in collaboration with stakeholders. Thereby, systems modeling provides a platform for testing various policy options and system intervention scenarios to mitigate rebound effects-For example, see the policy discussions in studies employing a systems approach and also addressing rebound effects: Hilty et al [12], Stepp et al [13], Peeters [14], and Dace et al [15].…”

Section: Contribution Of Systems Thinking and Modeling To Rebound Anamentioning

confidence: 99%

“…Hilty et al [12] used such tools (at a quantitative level) to include time rebound and direct economic rebound in their study of effects of information and communication technology (ICT) on environmental sustainability. Stepp et al [13] employed causal loop diagrams to highlight the potential unintended consequences and rebound effects when studying the role of feedback effects in GHG mitigation policies in the transport sector. Peeters [14] used causal loop diagrams to investigate the positive and negative role (and rebound effects) of technological progress in the context of GHG emissions from tourism transport.…”

Section: Introductionmentioning

confidence: 99%

Using Systems Thinking and System Dynamics Modeling to Understand Rebound Effects

Achachlouei

Hilty

2016

Progress in IS

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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.

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Greenhouse gas mitigation policies and the transportation sector: The role of feedback effects on policy effectiveness

Cited by 67 publications

References 32 publications

Panama Canal expansion: alleviating global climate change

Panama Canal expansion: alleviating global climate change

Exploring stability and change in transport systems: combining Delphi and system dynamics approaches

Using Systems Thinking and System Dynamics Modeling to Understand Rebound Effects

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