IDEAS home Printed from https://ideas.repec.org/a/eee/ecolec/v68y2008i1-2p504-516.html
   My bibliography  Save this article

The 'neighbor effect': Simulating dynamics in consumer preferences for new vehicle technologies

Author

Listed:
  • Mau, Paulus
  • Eyzaguirre, Jimena
  • Jaccard, Mark
  • Collins-Dodd, Colleen
  • Tiedemann, Kenneth

Abstract

Understanding consumer behaviour is essential in designing policies that efficiently increase the uptake of clean technologies over the long-run. Expert opinion or qualitative market analyses have tended to be the sources of this information. However, greater scrutiny on governments increasingly demands the use of reliable and credible evidence to support policy decisions. While discrete choice research and modeling techniques have been applied to estimate consumer preferences for technologies, these methods often assume static preferences. This study builds on the application of discrete choice research and modeling to capture dynamics in consumer preferences. We estimate Canadians' preferences for new vehicle technologies under different market assumptions, using responses from two national surveys focused on hybrid gas-electric vehicles and hydrogen fuel cell vehicles. The results support the relevance of a range of vehicle attributes beyond the purchase price in shaping consumer preferences towards clean vehicle technologies. They also corroborate our hypothesis that the degree of market penetration of clean vehicle technologies is an influence on people's preferences ('the neighbor effect'). Finally, our results provide behavioural parameters for the energy-economy model CIMS, which we use here to show the importance of including consumer preference dynamics when setting policies to encourage the uptake of clean technologies.

Suggested Citation

  • Mau, Paulus & Eyzaguirre, Jimena & Jaccard, Mark & Collins-Dodd, Colleen & Tiedemann, Kenneth, 2008. "The 'neighbor effect': Simulating dynamics in consumer preferences for new vehicle technologies," Ecological Economics, Elsevier, vol. 68(1-2), pages 504-516, December.
  • Handle: RePEc:eee:ecolec:v:68:y:2008:i:1-2:p:504-516
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0921-8009(08)00214-0
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Bunch, David S. & Bradley, Mark & Golob, Thomas F. & Kitamura, Ryuichi & Occhiuzzo, Gareth P., 1993. "Demand for clean-fuel vehicles in California: A discrete-choice stated preference pilot project," Transportation Research Part A: Policy and Practice, Elsevier, vol. 27(3), pages 237-253, May.
    2. DeShazo, J. R. & Fermo, German, 2002. "Designing Choice Sets for Stated Preference Methods: The Effects of Complexity on Choice Consistency," Journal of Environmental Economics and Management, Elsevier, vol. 44(1), pages 123-143, July.
    3. Brownstone, David & Train, Kenneth, 1999. "Forecasting new product penetration with flexible substitution patterns," Department of Economics, Working Paper Series qt3tb6j874, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    4. Brownstone, David & Bunch, David S & Train, Kenneth, 1999. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Department of Economics, Working Paper Series qt45f996hh, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    5. Horne, Matt & Jaccard, Mark & Tiedemann, Ken, 2005. "Improving behavioral realism in hybrid energy-economy models using discrete choice studies of personal transportation decisions," Energy Economics, Elsevier, vol. 27(1), pages 59-77, January.
    6. Nic Rivers & Mark Jaccard, 2005. "Combining Top-Down and Bottom-Up Approaches to Energy-Economy Modeling Using Discrete Choice Methods," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 83-106.
    7. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
    8. Brownstone, David & Train, Kenneth, 1998. "Forecasting new product penetration with flexible substitution patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 109-129, November.
    9. 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.
    10. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, September.
    11. Roberts, James A. & Bacon, Donald R., 1997. "Exploring the Subtle Relationships between Environmental Concern and Ecologically Conscious Consumer Behavior," Journal of Business Research, Elsevier, vol. 40(1), pages 79-89, September.
    12. Hensher, David & Louviere, Jordan & Swait, Joffre, 1998. "Combining sources of preference data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 197-221, November.
    13. Jaccard, Mark & Murphy, Rose & Rivers, Nic, 2004. "Energy-environment policy modeling of endogenous technological change with personal vehicles: combining top-down and bottom-up methods," Ecological Economics, Elsevier, vol. 51(1-2), pages 31-46, November.
    14. Mark K. Jaccard & John Nyboer & Crhis Bataille & Bryn Sadownik, 2003. "Modeling the Cost of Climate Policy: Distinguishing Between Alternative Cost Definitions and Long-Run Cost Dynamics," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 49-73.
    15. Train, Kenneth, 1985. "Discount rates in consumers' energy-related decisions: A review of the literature," Energy, Elsevier, vol. 10(12), pages 1243-1253.
    16. Hensher, David A. & Stopher, Peter R. & Louviere, Jordan J., 2001. "An exploratory analysis of the effect of numbers of choice sets in designed choice experiments: an airline choice application," Journal of Air Transport Management, Elsevier, vol. 7(6), pages 373-379.
    17. Fujii, Satoshi & Gärling, Tommy, 2003. "Application of attitude theory for improved predictive accuracy of stated preference methods in travel demand analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(4), pages 389-402, May.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. 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.
    3. Martin Achtnicht, 2012. "German car buyers’ willingness to pay to reduce CO 2 emissions," Climatic Change, Springer, vol. 113(3), pages 679-697, August.
    4. 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.
    5. 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.
    6. 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).
    7. Ahn, Jiwoon & Jeong, Gicheol & Kim, Yeonbae, 2008. "A forecast of household ownership and use of alternative fuel vehicles: A multiple discrete-continuous choice approach," Energy Economics, Elsevier, vol. 30(5), pages 2091-2104, September.
    8. 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).
    9. 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.
    10. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    11. Andreas Ziegler, 2010. "Individual Characteristics and Stated Preferences for Alternative Energy Sources and Propulsion Technologies in Vehicles: A Discrete Choice Analysis," CER-ETH Economics working paper series 10/125, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    12. Karsten Kieckhäfer & Thomas Volling & Thomas Stefan Spengler, 2014. "A Hybrid Simulation Approach for Estimating the Market Share Evolution of Electric Vehicles," Transportation Science, INFORMS, vol. 48(4), pages 651-670, November.
    13. Hidrue, Michael K. & Parsons, George R. & Kempton, Willett & Gardner, Meryl P., 2011. "Willingness to pay for electric vehicles and their attributes," Resource and Energy Economics, Elsevier, vol. 33(3), pages 686-705, September.
    14. Nobuyuki Ito & Kenji Takeuchi & Shunsuke Managi, 2012. "Willingness to pay for the infrastructure investments for alternative fuel vehicles," Discussion Papers 1207, Graduate School of Economics, Kobe University.
    15. Hu, Wuyang & Adamowicz, Wiktor L. & Veeman, Michele M., 2004. "Decomposing Unobserved Choice Variability In The Presence Of Consumers' Taste Heterogeneity," 2004 Annual meeting, August 1-4, Denver, CO 19954, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    16. Aurélie Glerum & Lidija Stankovikj & Michaël Thémans & Michel Bierlaire, 2014. "Forecasting the Demand for Electric Vehicles: Accounting for Attitudes and Perceptions," Transportation Science, INFORMS, vol. 48(4), pages 483-499, November.
    17. Parsons, George R. & Hidrue, Michael K. & Kempton, Willett & Gardner, Meryl P., 2014. "Willingness to pay for vehicle-to-grid (V2G) electric vehicles and their contract terms," Energy Economics, Elsevier, vol. 42(C), pages 313-324.
    18. Dimitropoulos, Alexandros & Rietveld, Piet & van Ommeren, Jos N., 2013. "Consumer valuation of changes in driving range: A meta-analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 55(C), pages 27-45.
    19. 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.
    20. 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.

    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:ecolec:v:68:y:2008:i:1-2:p:504-516. 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/locate/ecolecon .

    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.