Improving the behavioral realism of global integrated assessment models: An application to consumers’ vehicle choices

David McCollum1, Charlie Wilson2, Hazel Pettifor2, Kalai Ramea3, Volker Krey1, Keywan Riahi1,4, Christoph Bertram5, Zhenhong Lin6, Oreane Edelenbosch7, Sei Fujisawa1
1Energy Program, International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, 2361 Laxenburg, Austria
2Tyndall Centre for Climate Change Research, University of East Anglia (UEA), Norwich NR4 7TJ, UK
3Institute of Transportation Studies, University of California, Davis, 1605, Tilia Street, Davis, CA 95616, USA
4Graz University of Technology, Inffeldgasse, 8010 Graz, Austria
5Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
6Oak Ridge National Laboratory, 2360 Cherahala Boulevard, Knoxville, TN 37932, USA
7PBL Netherlands Environmental Assessment Agency, Antonie van Leeuwenhoeklaan 9, 3721 MA Bilthoven, The Netherlands

Tóm tắt

Từ khóa


Tài liệu tham khảo

Allcott, 2014, Gasoline prices, fuel economy, and the energy paradox, Rev. Econ. Stat., 96, 779, 10.1162/REST_a_00419

Anable, 2012, Modelling transport energy demand: a socio-technical approach, Energy Policy, 41, 125, 10.1016/j.enpol.2010.08.020

Avineri, 2012, On the use and potential of behavioural economics from the perspective of transport and climate change, J. Transp. Geogr., 24, 512, 10.1016/j.jtrangeo.2012.03.003

Axsen, 2015, Preference and lifestyle heterogeneity among potential plug-in electric vehicle buyers, Energy Econ., 50, 190, 10.1016/j.eneco.2015.05.003

Axsen, 2012, Social influence, consumer behavior, and low-carbon energy transitions, Ann. Rev. Environ. Resour., 37, 311, 10.1146/annurev-environ-062111-145049

Ayres, 2009

Baltas, 2013, An empirical investigation of the impact of behavioural and psychographic consumer characteristics on car preferences: an integrated model of car type choice, Transport. Res. Part A Policy Pract., 54, 92, 10.1016/j.tra.2013.07.007

Beggs, 1980, Choice of smallest car by multi-vehicle households and the demand for electric vehicles, Transport. Res. Part A Gen., 14, 389, 10.1016/0191-2607(80)90057-6

Belgiawan, 2013, Effects of peer influence, satisfaction and regret on car purchase desire, Proc. Environ. Sci., 17, 485, 10.1016/j.proenv.2013.02.063

Bertram, 2015, Complementing carbon prices with technology policies to keep climate targets within reach, Nat. Clim. Change, 5, 235, 10.1038/nclimate2514

Bosetti, 2013, Light duty vehicle transportation and global climate policy: the importance of electric drive vehicles, Energy Policy, 58, 209, 10.1016/j.enpol.2013.03.008

Brand, 2012, The UK transport carbon model: an integrated life cycle approach to explore low carbon futures, Energy Policy, 41, 107, 10.1016/j.enpol.2010.08.019

Bunch, 2015

Camerer, 2004

Choo, 2004, What type of vehicle do people drive? The role of attitude and lifestyle in influencing vehicle type choice, Transport. Res. Part A Policy Pract., 38, 201, 10.1016/j.tra.2003.10.005

Conlisk, 1996, Why bounded rationality?, J. Econ. Lit., 34, 669

Creutzig, 2011, Climate policies for road transport revisited (I): evaluation of the current framework, Energy Policy, 39, 2396, 10.1016/j.enpol.2011.01.062

Darzianazizi, 2013, Investigation of the consumers preferences about effective criteria in brand positioning: conjoint analysis approach, Aust. J. Basic Appl. Sci., 7, 70

Dellavigna, 2009, Psychology and economics: evidence from the field, J. Econ. Lit., 47, 315, 10.1257/jel.47.2.315

Dijk, 2013, Incorporating social context and co-evolution in an innovation diffusion model—with an application to cleaner vehicles, J. Evolut. Econ., 23, 295, 10.1007/s00191-011-0241-5

Ekholm, 2010, Determinants of household energy consumption in India, Energy Policy, 38, 5696, 10.1016/j.enpol.2010.05.017

Element Energy, 2013. Pathways to high penetration of electric vehicles. Final Report for the Committee on Climate Change. Cambridge, UK.

Gaker, 2010, Experimental economics in transportation: focus on social influences and provision of information, Transp. Res. Rec., 10.3141/2156-06

Gillingham, 2009

Giraudet, L.-G., Guivarch, C., Quirion, P., 2011. Exploring the potential for energy conservation in French households through hybrid modelling. Report DT/WP No 2011-26. Centre International de Recherches sur l’Environnement et le Développement (CIRED).

Girod, 2013, Climate impact of transportation: a model comparison, Clim. Change, 118, 595, 10.1007/s10584-012-0663-6

Greene, 2011, Uncertainty, loss aversion, and markets for energy efficiency, Energy Econ., 33, 608, 10.1016/j.eneco.2010.08.009

Greene, 2013, Analyzing the sensitivity of hydrogen vehicle sales to consumers’ preferences, Int. J. Hydrogen Energy, 38, 15857, 10.1016/j.ijhydene.2013.08.099

Guerin, 2000, Occupant predictors of household energy behavior and consumption change as found in energy studies since 1975, Family Consum. Sci. Res. J., 29, 48, 10.1177/1077727X00291003

Gül, 2009, An energy-economic scenario analysis of alternative fuels for personal transport using the Global Multi-regional MARKAL model (GMM), Energy, 34, 1423, 10.1016/j.energy.2009.04.010

Hedenus, 2010, Cost-effective energy carriers for transport – the role of the energy supply system in a carbon-constrained world, Int. J. Hydrogen Energy, 35, 4638, 10.1016/j.ijhydene.2010.02.064

Heinrichs, 2014, Including road transport in the EU ETS (European Emissions Trading System): a model-based analysis of the German electricity and transport sector, Energy, 69, 708, 10.1016/j.energy.2014.03.061

Hocherman, 1983, Estimation and use of dynamic transaction models of automobile ownership, Transp. Res. Rec., 944, 134

IEA, 2015

IIASA, 2015. SSP Database (Shared Socioeconomic Pathways) – Version 1.0 [Online]. Available: <https://tntcat.iiasa.ac.at/SspDb/>.

IRGC, 2015

Jaccard, 2006, Estimating home energy decision parameters for a hybrid energy-economy policy model, Environ. Model. Assess., 11, 91, 10.1007/s10666-005-9036-0

Jaffe, 1994, The energy efficiency gap: what does it mean?, Energy Policy, 22, 804, 10.1016/0301-4215(94)90138-4

Jansson, 2010, Green consumer behavior: determinants of curtailment and eco-innovation adoption, J. Consum. Market., 27, 358, 10.1108/07363761011052396

Jenkins, 2014, Political economy constraints on carbon pricing policies: what are the implications for economic efficiency, environmental efficacy, and climate policy design?, Energy Policy, 69, 467, 10.1016/j.enpol.2014.02.003

Jiang, 2015, Global urbanization projections for the Shared Socioeconomic Pathways, Glob. Environ. Change

Kahneman, 2000

Kc, 2015, The human core of the shared socioeconomic pathways: population scenarios by age, sex and level of education for all countries to 2100, Glob. Environ. Change

Kirman, 1992, Whom or what does the representative individual represent?, J. Econ. Perspect., 6, 117, 10.1257/jep.6.2.117

Kitamura, R., Golob, T.F., Yamamoto, T., Wu, G., 2000. Accessibility and automobile use in a motorized metropolis. In: Number, T.R.B.I.D. (Ed.), 79th Transportation Research Board Annual Meeting. Washington, DC.

Krey, 2014, Global energy-climate scenarios and models: a review, Wiley Interdiscipl. Rev. Energy Environ., 3, 363

Krey, 2014, Getting from here to there – energy technology transformation pathways in the EMF27 scenarios, Climatic Change, 123, 369, 10.1007/s10584-013-0947-5

Kriegler, 2014, The role of technology for achieving climate policy objectives: overview of the EMF 27 study on global technology and climate policy strategies, Climatic Change, 123, 353, 10.1007/s10584-013-0953-7

Kyle, 2011, Long-term implications of alternative light-duty vehicle technologies for global greenhouse gas emissions and primary energy demands, Energy Policy, 39, 3012, 10.1016/j.enpol.2011.03.016

Laitner, 2003, Room for improvement: increasing the value of energy modeling for policy analysis, Utilities Policy, 11, 87, 10.1016/S0957-1787(03)00020-1

Laitner, 2000, Incorporating behavioural, social, and organizational phenomena in the assessment of climate change mitigation options

Levine, 2007, Residential and commercial buildings

Lin, 2013, Hydrogen vehicles: impacts of DOE technical targets on market acceptance and societal benefits, Int. J. Hydrogen Energy, 38, 7973, 10.1016/j.ijhydene.2013.04.120

Lin, 2009

Lin, 2011, Promoting the market for plug-in hybrid and battery electric vehicles, Transport. Res. Rec. J. Transport. Res. Board, 2252, 49, 10.3141/2252-07

Lin, 2013

Lin, Z., Li, J., Dong, J., 2014. Dynamic Wireless Charging: Potential Impact on Plug-in Electric Vehicle Adoption. SAE Technical Papers 2014-01-1965. Society of Automotive Engineers.

Lutzenhiser, 1993, Social and behavioral aspects of energy use, Annu. Rev. Energy Env., 18, 247, 10.1146/annurev.eg.18.110193.001335

Mannering, 1985, A dynamic empirical analysis of household vehicle ownership and utilization, RAND J. Econ., 16, 215, 10.2307/2555411

Mannering, 2002, An exploratory analysis of automobile leasing by US households, J. Urban Econ., 52, 154, 10.1016/S0094-1190(02)00009-8

Marletto, 2014, Car and the city: socio-technical transition pathways to 2030, Technol. Forecast. Soc. Chang., 87, 164, 10.1016/j.techfore.2013.12.013

Mattauch, 2015, Happy or liberal? Making sense of behavior in transport policy design, Transport. Res. Part D Transp. Environ.

McCarthy, 1998, New vehicle consumption and fuel efficiency: a nested logit approach, Transport. Res. Part E Log. Transport. Rev., 34, 39, 10.1016/S1366-5545(97)00042-2

McCollum, 2014, Transport electrification: a key element for energy system transformation and climate stabilization, Climatic Change, 123, 651, 10.1007/s10584-013-0969-z

Mercure, 2016, Modelling complex systems of heterogeneous agents to better design sustainability transitions policy, Glob. Environ. Change, 37, 102, 10.1016/j.gloenvcha.2016.02.003

Mock, 2014

Mundaca, 2010, Evaluating energy efficiency policies with energy-economy models, Ann. Rev. Environ. Resour., 35, 305, 10.1146/annurev-environ-052810-164840

O’Neill, 2015, The roads ahead: narratives for shared socioeconomic pathways describing world futures in the 21st century, Global Environ. Change

Peters, 2015, Understanding car-buying behavior: psychological determinants of energy efficiency and practical implications, Int. J. Sustain. Transport., 9, 59, 10.1080/15568318.2012.732672

Pietzcker, 2014, Long-term transport energy demand and climate policy: alternative visions on transport decarbonization in energy-economy models, Energy, 64, 95, 10.1016/j.energy.2013.08.059

Rausch, 2010, Computation of equilibria in OLG models with many heterogeneous households, Comput. Econ., 36, 171, 10.1007/s10614-010-9229-8

Riahi, 2012, Chapter 17 – energy pathways for sustainable development

Riahi, 2007, Scenarios of long-term socio-economic and environmental development under climate stabilization, Technol. Forecast. Soc. Chang., 74, 887, 10.1016/j.techfore.2006.05.026

Riahi, 2015, Locked into copenhagen pledges—implications of short-term emission targets for the cost and feasibility of long-term climate goals, Technol. Forecast. Soc. Chang., 90, 8, 10.1016/j.techfore.2013.09.016

Rivers, 2006, Useful models for simulating policies to induce technological change, Energy Policy, 34, 2038, 10.1016/j.enpol.2005.02.003

Rogers, 2003

Rösler, 2014, Electricity versus hydrogen for passenger cars under stringent climate change control, Sustain. Energy Technol. Assess., 5, 106

Sathaye, 2013, Methods and models for costing carbon mitigation, Ann. Rev. Environ. Resour., 38, 137, 10.1146/annurev-environ-083111-092115

Shogren, 2008, On behavioral-environmental economics, Rev. Environ. Econ. Policy, 2, 26, 10.1093/reep/rem027

Stern, 1992, What psychology knows about energy conservation, Am. Psychol., 47, 1224, 10.1037/0003-066X.47.10.1224

Strachan, N., Warren, P., 2011. Incorporating Behavioural Complexity in Energy-Economic Models. Oxford: Energy and People Conference.

Sun, 2007, Dynamic testing of wholesale power market designs: an open-source agent-based framework, Comput. Econ., 30, 291, 10.1007/s10614-007-9095-1

Tavoni, 2013, The distribution of the major economies’ effort in the Durban platform scenarios, Climate Change Econ., 4, 25, 10.1142/S2010007813400095

Tran, 2013, Simulating early adoption of alternative fuel vehicles for sustainability, Technol. Forecasting Social Change, 80, 865, 10.1016/j.techfore.2012.09.009

Turnheim, 2015, Evaluating sustainability transitions pathways: bridging analytical approaches to address governance challenges, Glob. Environ. Change, 35, 239, 10.1016/j.gloenvcha.2015.08.010

UCL, 2015. Energy Models at the UCL Energy Institute: BLUE [Online]. University College London. <www.ucl.ac.uk/energy-models/models/blue> (accessed 2015-07-23).

Urry, 2008, Governance, flows, and the end of the car system?, Global Environ. Change, 18, 343, 10.1016/j.gloenvcha.2008.04.007

van Bree, 2010, A multi-level perspective on the introduction of hydrogen and battery-electric vehicles, Technol. Forecasting Social Change, 77, 529, 10.1016/j.techfore.2009.12.005

van Vliet, 2012, Synergies in the Asian energy system: climate change, energy security, energy access and air pollution, Energy Econ., 34, S470, 10.1016/j.eneco.2012.02.001

Wilson, 2007, Models of decision making and residential energy use, Ann. Rev. Environ. Resour., 32, 169, 10.1146/annurev.energy.32.053006.141137

Wilson, C., Pettifor, H., Mccollum, D., 2014. Improving the Behavioural Realism of Integrated Assessment Models of Global Climate Change Mitigation: A Research Agenda (ADVANCE Project Deliverable No. 3.2), Available at: <www.fp7-advance.eu>. Tyndall Centre for Climate Change Research, Norwich, UK and International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria.

Wu, 2014, Applying conjoint analysis to evaluate consumer preferences toward subcompact cars, Expert Syst. Appl., 41, 2782, 10.1016/j.eswa.2013.10.011