Abstract
This paper presents a decision tool intended to help achieve the goal of reduction in Green House Gas (GHG) emissions in the greater Philadelphia region by the year 2050. The goal is to explore and build a pre-prototype to evaluate the value of the role for agents, alternative data sources (Census, energy reports, surveys, etc.), GIS modeling, and various social science theories of human behavior. Section 2 explains our initial research on an Agent Based Model (ABM) built upon the Theory of Planned Behavior (TPB) and the Discrete Decision Choice model (DDC) to model consumer technology adoption. The users can utilize the proposed ABM to investigate the role of attitude, social networks, and economics upon consumer choice of vehicle and transportation mode. Finally, we conclude with results on agent decisions for which transit mode to use and whether to adopt greener technologies.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Khansari, N., et al.: An agent-based decision tool to explore urban climate & smart city possibilities. In: 11th Annual IEEE International Systems Conference (SysCon) 2017 (2017)
Moss, S., Pahl-Wostl, C., Downing, T.: Agent-based integrated assessment modelling: the example of climate change. Integr. Assess. 2(1), 17–30 (2001)
Robinson, S.A., Rai, V.: Determinants of spatio-temporal patterns of energy technology adoption: an agent-based modeling approach. Appl. Energy 151, 273–284 (2015)
Sopha, B.M., Klöckner, C.A., Hertwich, E.G.: Adoption and diffusion of heating systems in Norway: coupling agent-based modeling with empirical research. Environ. Innovation Societal Transitions 8, 42–61 (2013)
Rai, V., Henry, A.D.: Agent-based modelling of consumer energy choices. Nat. Clim. Change 6(6), 556–562 (2016)
Ma, T., Nakamori, Y.: Modeling technological change in energy systems–from optimization to agent-based modeling. Energy 34(7), 873–879 (2009)
Roozmand, O., Ghasem-Aghaee, N., Hofstede, G.J., Nematbakhsh, M.A., Baraani, A., Verwaart, T.: Agent-based modeling of consumer decision making process based on power distance and personality. Knowl.-Based Syst. 24(7), 1075–1095 (2011)
Silverman, B.G., Hanrahan, N., Bharathy, G., Gordon, K., Johnson, D.: A systems approach to healthcare: agent-based modeling, community mental health, and population well-being. Artif. Intell. Med. 63(2), 61–71 (2015)
Rai, V., Robinson, S.A.: Agent-based modeling of energy technology adoption: empirical integration of social, behavioral, economic, and environmental factors. Environ. Model Softw. 70, 163–177 (2015)
McCright, A.M., Dunlap, R.E., Xiao, C.: Perceived scientific agreement and support for government action on climate change in the USA. Clim. Change 119(2), 511–518 (2013)
Circella, G., Handy, S., Boarnet, M.: Impacts of Gas Price on Passenger Vehicle Use and Greenhouse Gas Emissions, 30 September 2014. http://arb.ca.gov/cc/sb375/policies/policies.htm
De Vries, B.J., Petersen, A.C.: Conceptualizing sustainable development: an assessment methodology connecting values, knowledge, worldviews and scenarios. Ecol. Econ. 68(4), 1006–1019 (2009)
Khansari, N., Vesaghi, A., Mansouri, M., Mostashari, A.: The multiagent analysis of social progress in energy behavior: the system dynamics methodology. IEEE Syst. J. PP(99), 1–10 (2015)
Dunlap, R.E.: At 40, environmental movement endures, with less consensus. Gallup Poll. (2010)
Acknowledgements
We thank Kleinman Center for Energy Policy, the Mellon Foundation: Humanities, Urbanism, and Design Initiative, and the Delaware Valley Regional Planning Commission for supporting us in this research. Any opinions or errors are those of the authors alone.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Khansari, N., Waldt, J.B., Silverman, B.G., Braham, W.W., Shen, K., Lee, J.M. (2017). Simulating Population Behavior: Transportation Mode, Green Technology, and Climate Change. In: Lee, D., Lin, YR., Osgood, N., Thomson, R. (eds) Social, Cultural, and Behavioral Modeling. SBP-BRiMS 2017. Lecture Notes in Computer Science(), vol 10354. Springer, Cham. https://doi.org/10.1007/978-3-319-60240-0_21
Download citation
DOI: https://doi.org/10.1007/978-3-319-60240-0_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-60239-4
Online ISBN: 978-3-319-60240-0
eBook Packages: Computer ScienceComputer Science (R0)