Encouraging Sustainable Transport Choices in American Households: Results from an Empirically Grounded Agent-Based Model
by
Davide Natalini 1,* and Giangiacomo Bravo 2
Davide Natalini 1,* and Giangiacomo Bravo 2
1
Global Sustainability Institute, Anglia Ruskin University, East Road, Cambridge CB1 1PT, UK
2
Department of Social Studies, Linnaeus University, and Collegio Carlo Alberto, Universitetsplatsen 1, 35252 Växjö, Sweden
*
Author to whom correspondence should be addressed.
Sustainability 2014, 6(1), 50-69; https://doi.org/10.3390/su6010050
Received: 3 September 2013 / Revised: 5 December 2013 / Accepted: 9 December 2013 / Published: 20 December 2013
(This article belongs to the Special Issue Creative Solutions to Big Challenges)
The transport sector needs to go through an extended process of decarbonisation to counter the threat of climate change. Unfortunately, the International Energy Agency forecasts an enormous growth in the number of cars and greenhouse gas emissions by 2050. Two issues can thus be identified: (1) the need for a new methodology that could evaluate the policy performances ex-ante and (2) the need for more effective policies. To help address these issues, we developed an Agent-Based Model called Mobility USA aimed at: (1) testing whether this could be an effective approach in analysing ex-ante policy implementation in the transport sector; and (2) evaluating the effects of alternative policy scenarios on commuting behaviours in the USA. Particularly, we tested the effects of two sets of policies, namely market-based and preference-change ones. The model results suggest that this type of agent-based approach will provide a useful tool for testing policy interventions and their effectiveness.
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Keywords:
Agent-Based Model; environmental policies; price-based policies; preference-based policies; sustainability; transports
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MDPI and ACS Style
Natalini, D.; Bravo, G. Encouraging Sustainable Transport Choices in American Households: Results from an Empirically Grounded Agent-Based Model. Sustainability 2014, 6, 50-69.
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