IDEAS home Printed from https://ideas.repec.org/a/eee/trapol/v52y2016icp113-120.html
   My bibliography  Save this article

How may incentives for electric cars affect purchase decisions?

Author

Listed:
  • Rudolph, Christian

Abstract

In this paper, the impact of five different incentives for buyers of zero emission vehicles (ZEV) is investigated with a stated choice experiment. The tested incentives are direct subsidies, free parking, a separate CO2 tax, an increase of fuel costs by tax elevation, and an increase of available charging infrastructure. By implementing the mobility patterns of the respondents, it was possible to simulate estimations of ecological impact and modal shift with a random utility model (mixed logit). Based on 875 complete questionnaires, the simulation results show that giving incentives to these buyers ecological rebound effects are expected: Mostly people with a low CO2-emission rate regarding their daily transportation routines (cyclists and public transport users) will exploit these incentives. They show a significantly higher likelihood of choosing alternatively propelled cars than conventional car users. Consumers that usually use a passenger car for their daily mobility routines are mostly unwilling to change to ZEV even when incentives are given.

Suggested Citation

  • Rudolph, Christian, 2016. "How may incentives for electric cars affect purchase decisions?," Transport Policy, Elsevier, vol. 52(C), pages 113-120.
  • Handle: RePEc:eee:trapol:v:52:y:2016:i:c:p:113-120
    DOI: 10.1016/j.tranpol.2016.07.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0967070X16300877
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tranpol.2016.07.014?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Daziano, Ricardo A. & Achtnicht, Martin, 2012. "Forecasting adoption of ultra-low-emission vehicles using the GHK simulator and Bayes estimates of a multinomial probit model," ZEW Discussion Papers 12-017, ZEW - Leibniz Centre for European Economic Research.
    2. Yan Zhou & Michael Wang & Han Hao & Larry Johnson & Hewu Wang & Han Hao, 2015. "Plug-in electric vehicle market penetration and incentives: a global review," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 20(5), pages 777-795, June.
    3. Kenneth Train, 1980. "A Structured Logit Model of Auto Ownership and Mode Choice," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(2), pages 357-370.
    4. Achtnicht, Martin & Bühler, Georg & Hermeling, Claudia, 2008. "Impact of Service Station Networks on Purchase Decisions of Alternative-fuel Vehicles," ZEW Discussion Papers 08-088, ZEW - Leibniz Centre for European Economic Research.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, September.
    6. Green, Paul E & Srinivasan, V, 1978. "Conjoint Analysis in Consumer Research: Issues and Outlook," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 5(2), pages 103-123, Se.
    7. Kenneth A. Small & Clifford Winston & Jia Yan, 2005. "Uncovering the Distribution of Motorists' Preferences for Travel Time and Reliability," Econometrica, Econometric Society, vol. 73(4), pages 1367-1382, July.
    8. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    9. Arne Risa Hole, 2007. "Fitting mixed logit models by using maximum simulated likelihood," Stata Journal, StataCorp LP, vol. 7(3), pages 388-401, September.
    10. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
    11. Kenneth E. Train, 1998. "Recreation Demand Models with Taste Differences over People," Land Economics, University of Wisconsin Press, vol. 74(2), pages 230-239.
    12. Martin Achtnicht, 2012. "German car buyers’ willingness to pay to reduce CO 2 emissions," Climatic Change, Springer, vol. 113(3), pages 679-697, August.
    13. Dagsvik, John K. & Wennemo, Tom & Wetterwald, Dag G. & Aaberge, Rolf, 2002. "Potential demand for alternative fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 36(4), pages 361-384, May.
    14. Sophia Rabe-Hesketh & Anders Skrondal, 2012. "Multilevel and Longitudinal Modeling Using Stata, 3rd Edition," Stata Press books, StataCorp LP, edition 3, number mimus2, March.
    15. Axsen, Jonn & Mountain, Dean C. & Jaccard, Mark, 2009. "Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles," Institute of Transportation Studies, Working Paper Series qt02n9j6cv, Institute of Transportation Studies, UC Davis.
    16. Ziegler, Andreas, 2012. "Individual characteristics and stated preferences for alternative energy sources and propulsion technologies in vehicles: A discrete choice analysis for Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1372-1385.
    17. Hensher, David A. & Rose, John M. & Greene, William H., 2008. "Combining RP and SP data: biases in using the nested logit ‘trick’ – contrasts with flexible mixed logit incorporating panel and scale effects," Journal of Transport Geography, Elsevier, vol. 16(2), pages 126-133.
    18. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    19. Brownston, David & Bunch, David S. & Train, Kenneth, 1999. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," University of California Transportation Center, Working Papers qt7rf7s3nx, University of California Transportation Center.
    20. Axsen, Jonn & Mountain, Dean C. & Jaccard, Mark, 2009. "Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles," Resource and Energy Economics, Elsevier, vol. 31(3), pages 221-238, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Rodrigues Teixeira, Ana Carolina & Machado, Pedro Gerber & Borges, Raquel Rocha & Felipe Brito, Thiago Luis & Moutinho dos Santos, Edmilson & Mouette, Dominique, 2021. "The use of liquefied natural gas as an alternative fuel in freight transport – Evidence from a driver's point of view," Energy Policy, Elsevier, vol. 149(C).
    2. Mirzadeh Phirouzabadi, Amir & Savage, David & Blackmore, Karen & Juniper, James, 2020. "The evolution of dynamic interactions between the knowledge development of powertrain systems," Transport Policy, Elsevier, vol. 93(C), pages 1-16.
    3. Zhuge, Chengxiang & Wei, Binru & Shao, Chunfu & Shan, Yuli & Dong, Chunjiao, 2020. "The role of the license plate lottery policy in the adoption of Electric Vehicles: A case study of Beijing," Energy Policy, Elsevier, vol. 139(C).
    4. Kim, Ga-Eun & Kim, Ju-Hee & Yoo, Seung-Hoon, 2019. "South Korean consumers’ preferences for eco-friendly gasoline sedans: Results from a choice experiment survey," Transport Policy, Elsevier, vol. 77(C), pages 1-7.
    5. Sousa, Nuno & Almeida, Arminda & Coutinho-Rodrigues, João, 2020. "A multicriteria methodology for estimating consumer acceptance of alternative powertrain technologies," Transport Policy, Elsevier, vol. 85(C), pages 18-32.
    6. Raj Kumar & Yuan Chun & Tanjia Binte Zafar & Nora Ahmed Mothafar, 2019. "Building Sustainable Green Environment by Reducing Traffic Jam: The Role of Sharing Economy as Ride-sharing An Overview of Dhaka Metropolitan City," International Journal of Science and Business, IJSAB International, vol. 3(6), pages 164-173.
    7. Wang, Zhuowei & Yu, Jiangbo (Gabe) & Chen, Anthony & Fu, Xiaowen, 2024. "Subsidy policies towards zero-emission bus fleets: A systematic technical-economic analysis," Transport Policy, Elsevier, vol. 150(C), pages 1-13.
    8. Jiali Yu & Peng Yang & Kai Zhang & Faping Wang & Lixin Miao, 2018. "Evaluating the Effect of Policies and the Development of Charging Infrastructure on Electric Vehicle Diffusion in China," Sustainability, MDPI, vol. 10(10), pages 1-25, September.
    9. Flávia Mendes de Almeida Collaço & Ana Carolina Rodrigues Teixeira & Pedro Gerber Machado & Raquel Rocha Borges & Thiago Luis Felipe Brito & Dominique Mouette, 2022. "Road Freight Transport Literature and the Achievements of the Sustainable Development Goals—A Systematic Review," Sustainability, MDPI, vol. 14(6), pages 1-18, March.
    10. Teixeira, Ana Carolina Rodrigues & Machado, Pedro Gerber & Borges, Raquel Rocha & Mouette, Dominique, 2020. "Public policies to implement alternative fuels in the road transport sector," Transport Policy, Elsevier, vol. 99(C), pages 345-361.
    11. Kowalska-Pyzalska, Anna & Michalski, Rafał & Kott, Marek & Skowrońska-Szmer, Anna & Kott, Joanna, 2022. "Consumer preferences towards alternative fuel vehicles. Results from the conjoint analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    12. Squalli, Jay, 2024. "Environmental hypocrisy? Electric and hybrid vehicle adoption and pro-environmental attitudes in the United States," Energy, Elsevier, vol. 293(C).
    13. Edwaren Liun & Suparman Suparman & Sriyana Sriyana & Dharu Dewi & Jupiter Sitorus Pane, 2022. "Indonesia s Energy Demand Projection Until 2060," International Journal of Energy Economics and Policy, Econjournals, vol. 12(2), pages 467-473, March.
    14. Mariano Gallo & Mario Marinelli, 2020. "Sustainable Mobility: A Review of Possible Actions and Policies," Sustainability, MDPI, vol. 12(18), pages 1-39, September.
    15. Falcão, Eduardo Aparecido Moreira & Teixeira, Ana Carolina Rodrigues & Sodré, José Ricardo, 2017. "Analysis of CO2 emissions and techno-economic feasibility of an electric commercial vehicle," Applied Energy, Elsevier, vol. 193(C), pages 297-307.
    16. Loría, Luis Enrique & Watson, Verity & Kiso, Takahiko & Phimister, Euan, 2019. "Investigating users' preferences for Low Emission Buses: Experiences from Europe's largest hydrogen bus fleet," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    17. Gabriela D. Oliveira & Luis C. Dias, 2019. "Influence of Demographics on Consumer Preferences for Alternative Fuel Vehicles: A Review of Choice Modelling Studies and a Study in Portugal," Energies, MDPI, vol. 12(2), pages 1-33, January.
    18. Park, Soyeong & Maeng, Kyuho & Shin, Jungwoo, 2023. "Efficient subsidy distribution for hydrogen fuel cell vehicles based on demand segmentation," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    19. Yujin Beak & Kayoung Kim & Kyuho Maeng & Youngsang Cho, 2020. "Is the environment‐friendly factor attractive to customers when purchasing electric vehicles? Evidence from South Korea," Business Strategy and the Environment, Wiley Blackwell, vol. 29(3), pages 996-1006, March.
    20. Rostad Sæther, Simen, 2022. "Mobility at the crossroads – Electric mobility policy and charging infrastructure lessons from across Europe," Transportation Research Part A: Policy and Practice, Elsevier, vol. 157(C), pages 144-159.
    21. Hackbarth, André & Madlener, Reinhard, 2018. "Combined Vehicle Type and Fuel Type Choices of Private Households: An Empirical Analysis for Germany," FCN Working Papers 17/2018, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN), revised May 2019.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hackbarth, André & Madlener, Reinhard, 2016. "Willingness-to-pay for alternative fuel vehicle characteristics: A stated choice study for Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 89-111.
    2. Tanaka, Makoto & Ida, Takanori & Murakami, Kayo & Friedman, Lee, 2014. "Consumers’ willingness to pay for alternative fuel vehicles: A comparative discrete choice analysis between the US and Japan," Transportation Research Part A: Policy and Practice, Elsevier, vol. 70(C), pages 194-209.
    3. Hackbarth, André & Madlener, Reinhard, 2011. "Consumer Preferences for Alternative Fuel Vehicles: A Discrete Choice Analysis," FCN Working Papers 20/2011, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    4. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    5. Takanori Ida & Kayo Murakami & Makoto Tanaka, 2012. "Keys to Smart Home Diffusion: A Stated Preference Analysis of Smart Meters, Photovoltaic Generation, and Electric/Hybrid Vehicles," Discussion papers e-11-011, Graduate School of Economics Project Center, Kyoto University.
    6. Bigerna, S. & Bollino, C.A. & Micheli, S. & Polinori, P., 2017. "Revealed and stated preferences for CO2 emissions reduction: The missing link," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P2), pages 1213-1221.
    7. Martin Achtnicht, 2012. "German car buyers’ willingness to pay to reduce CO 2 emissions," Climatic Change, Springer, vol. 113(3), pages 679-697, August.
    8. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
    9. J�r�me Massiani, 2013. "The use of Stated Preferences to forecast alternative fuel vehicles market diffusion: Comparisons with other methods and proposal for a Synthetic Utility Function," Working Papers 2013:12, Department of Economics, University of Venice "Ca' Foscari".
    10. J�r�me Massiani, 2013. "SP surveys for electric and alternative fuel vehicles: are we doing the right thing?," Working Papers 2013_01, Department of Economics, University of Venice "Ca' Foscari".
    11. Helveston, John Paul & Liu, Yimin & Feit, Elea McDonnell & Fuchs, Erica & Klampfl, Erica & Michalek, Jeremy J., 2015. "Will subsidies drive electric vehicle adoption? Measuring consumer preferences in the U.S. and China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 73(C), pages 96-112.
    12. Oliveira, Gabriela D. & Roth, Richard & Dias, Luis C., 2019. "Diffusion of alternative fuel vehicles considering dynamic preferences," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 83-99.
    13. Alexandros Dimitropoulos & Piet Rietveld & Jos N. van Ommeren, 2011. "Consumer Valuation of Driving Range: A Meta-Analysis," Tinbergen Institute Discussion Papers 11-133/3, Tinbergen Institute.
    14. Bera, Reema & Maitra, Bhargab, 2021. "Assessing consumer preferences for Plug-in Hybrid Electric Vehicle (PHEV): An Indian perspective," Research in Transportation Economics, Elsevier, vol. 90(C).
    15. Frick, Bernd & Barros, Carlos Pestana & Prinz, Joachim, 2010. "Analysing head coach dismissals in the German "Bundesliga" with a mixed logit approach," European Journal of Operational Research, Elsevier, vol. 200(1), pages 151-159, January.
    16. Schuster, Monica & Vranken, Liesbet & Maertens, Miet, 2017. "You Can(’t) Always Get the Job You Want: Stated versus Revealed Employment Preferences in the Peruvian Agro-industry," Working Papers 254076, Katholieke Universiteit Leuven, Centre for Agricultural and Food Economics.
    17. Stephane Hess & John W. Polak, 2004. "An analysis of parking behaviour using discrete choice models calibrated on SP datasets," ERSA conference papers ersa04p60, European Regional Science Association.
    18. Michael P. Keane & Nada Wasi, 2013. "The Structure of Consumer Taste Heterogeneity in Revealed vs. Stated Preference Data," Economics Papers 2013-W10, Economics Group, Nuffield College, University of Oxford.
    19. Ricardo A. Daziano & Martin Achtnicht, 2014. "Forecasting Adoption of Ultra-Low-Emission Vehicles Using Bayes Estimates of a Multinomial Probit Model and the GHK Simulator," Transportation Science, INFORMS, vol. 48(4), pages 671-683, November.
    20. Haghani, Milad & Sarvi, Majid & Shahhoseini, Zahra, 2015. "Accommodating taste heterogeneity and desired substitution pattern in exit choices of pedestrian crowd evacuees using a mixed nested logit model," Journal of choice modelling, Elsevier, vol. 16(C), pages 58-68.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:trapol:v:52:y:2016:i:c:p:113-120. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/30473/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.