The potential of electromobility in Austria: Evidence from hybrid choice models under the presence of unreported information

This paper analyses the impact of the introduction of electromobility in Austria, focusing specifically on the potential demand for electric vehicles in the automotive market. We estimate discrete choice behavioral mixture models considering latent variables; these allows us to deal with this potential demand as well as to analyze the effect of different attributes of the alternatives over the potential market penetration. We find out that some usual assumptions regarding electromobility also hold for the Austrian market (e.g. proclivity of green-minded people and reluctance of older individuals), while others are only partially valid (e.g. the power of the engine is not relevant for purely electric vehicles). Along the same line, it is established that some policy incentives would have a positive effect for the demand for electrical cars, while others – such as an annual Park and Ride subscription or a one-year-ticket for public transportation – would not increase the willingness-to-pay for electromobility. Our work suggests the existence of reliability thresholds concerning the availability of charging stations.

[1]  A. Skonhoft,et al.  The Norwegian support and subsidy policy of electric cars. Should it be adopted by other countries , 2014 .

[2]  Joan L. Walker,et al.  Integration of Choice and Latent Variable Models , 1999 .

[3]  Denis Bolduc,et al.  Hybrid Choice Modeling of New Technologies for Car Choice in Canada , 2008 .

[4]  Ricardo A. Daziano,et al.  Conditional-logit Bayes estimators for consumer valuation of electric vehicle driving range , 2013 .

[5]  D. Diamond.  The impact of government incentives for hybrid-electric vehicles: Evidence from US states , 2009 .

[6]  C. Bhat,et al.  A Mixed Multinomial Logit Model Analysis of Weekend Recreational Episode Type Choice , 2004 .

[7]  Juliane Stark,et al.  Modeling Demand for Electric Cars - A Methodical Approach , 2012 .

[8]  Georgios Fontaras,et al.  The evolution of European passenger car characteristics 2000–2010 and its effects on real-world CO2 emissions and CO2 reduction policy , 2012 .

[9]  Clemens Gerbaulet,et al.  Power System Impacts of Electric Vehicles in Germany: Charging with Coal or Renewables? , 2015 .

[10]  Erwin Schmid,et al.  Cost and well-to-wheel implications of the vehicle fleet CO2 emission regulation in the European Union , 2014 .

[11]  Jianqiu Li,et al.  A review on the key issues for lithium-ion battery management in electric vehicles , 2013 .

[12]  Moshe Ben-Akiva,et al.  Advances in Discrete Choice: Mixture Models , 2011 .

[13]  Margaret J. Eppstein,et al.  An agent-based model to study market penetration of plug-in hybrid electric vehicles , 2011 .

[14]  Pavlos S. Kanaroglou,et al.  Household demand and willingness to pay for clean vehicles , 2007 .

[15]  Denzil G Fiebig,et al.  What influences participation in genetic carrier testing? Results from a discrete choice experiment. , 2006, Journal of health economics.

[16]  C. E. Thomas.  How green are electric vehicles , 2012 .

[17]  P Frías,et al.  Assessment of the Impact of Plug-in Electric Vehicles on Distribution Networks , 2011, IEEE Transactions on Power Systems.

[18]  Kenneth Lebeau,et al.  The market potential for plug-in hybrid and battery electric vehicles in Flanders: A choice-based conjoint analysis , 2012 .

[19]  M. Raberto,et al.  An agent-based modeling approach to predict the evolution of market share of electric vehicles: A case study from Iceland , 2012 .

[20]  Ricardo A. Daziano,et al.  Incorporating pro-environmental preferences towards green automobile technologies through a Bayesian hybrid choice model , 2013 .

[21]  Meryl P. Gardner,et al.  Willingness to pay for electric vehicles and their attributes , 2011 .

[22]  Steven E. Sexton,et al.  Conspicuous conservation: The Prius halo and willingness to pay for environmental bona fides , 2014 .

[23]  Francisco J. Bahamonde-Birke,et al.  Is Sequential Estimation a Suitable Second Best for Estimation of Hybrid Choice Models? , 2014 .

[24]  Zissis Samaras,et al.  A quantitative analysis of the European Automakers’ voluntary commitment to reduce CO2 emissions from new passenger cars based on independent experimental data , 2007 .

[25]  Kenneth A. Bollen,et al.  Structural Equations with Latent Variables , 1989 .

[26]  Suzanna Long,et al.  Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions , 2012 .

[27]  D. McFadden.  Conditional logit analysis of qualitative choice behavior , 1972 .

[28]  M. Bierlaire,et al.  Discrete choice models with multiplicative error terms , 2009 .

[29]  Elisabetta Cherchi,et al.  On the stability of preferences and attitudes before and after experiencing an electric vehicle , 2013 .

[30]  Stephane Hess,et al.  On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice , 2006 .

[31]  William S. Breffle,et al.  A Joint Latent-Class Model: Combining Likert-Scale Preference Statements With Choice Data to Harvest Preference Heterogeneity , 2011 .

[32]  Gavin Turrell,et al.  Income non-reporting: implications for health inequalities research , 2000, Journal of epidemiology and community health.

[33]  Juan de Dios Ortúzar,et al.  About attitudes and perceptions: finding the proper way to consider latent variables in discrete choice models , 2017 .

[34]  Piet Rietveld,et al.  Consumer valuation of changes in driving range: A meta-analysis , 2013 .

[35]  Joan L. Walker,et al.  Identification of parameters in normal error component logit-mixture (NECLM) models , 2007 .

[36]  Andrew Daly,et al.  Contrasting imputation with a latent variable approach to dealing with missing income in choice models , 2014 .

[37]  A. Zellner.  Estimation of Regression Relationships Containing Unobservable Independent Variables , 1970 .

[38]  Elisabetta Cherchi,et al.  A long panel survey to elicit variation in preferences and attitudes in the choice of electric vehicles , 2014 .

[39]  Zissis Samaras,et al.  On the way to 130 g CO2/km—Estimating the future characteristics of the average European passenger car , 2010 .

[40]  Reinhard Madlener,et al.  Consumer Preferences for Alternative Fuel Vehicles: A Discrete Choice Analysis , 2012 .

[41]  Michel Bierlaire,et al.  BIOGEME: a free package for the estimation of discrete choice models , 2003 .

[42]  L. Thurstone.  A law of comparative judgment. , 1994 .

[43]  Max Åhman,et al.  Government policy and the development of electric vehicles in Japan , 2006 .

[44]  Cathy Macharis,et al.  A decision analysis framework for intermodal transport: Comparing fuel price increases and the internalisation of external costs , 2010 .

[45]  Martin Wietschel,et al.  Evaluation of European electric vehicle support schemes , 2010 .

[46]  W. Shaw,et al.  The Distributional Impacts of Recreational Fees: A Discrete Choice Model with Incomplete Data , 2007, Land Economics.

[47]  Juan de Dios Ortúzar,et al.  Bewertung der Angebotsmerkmale des Personenfernverkehrs vor dem Hintergrund der Liberalisierung des Fernbusmarktes , 2014 .

[48]  Juan de Dios Ortúzar,et al.  On the variability of hybrid discrete choice models , 2014 .

[49]  Maria Johansson,et al.  The effects of attitudes and personality traits on mode choice , 2006 .

[50]  J. Xie,et al.  Policy Incentives for the Adoption of Electric Vehicles across Countries , 2014 .

[51]  Inês L. Azevedo,et al.  The impact of federal incentives on the adoption of hybrid electric vehicles in the United States , 2013 .