IDEAS home Printed from https://ideas.repec.org/p/diw/diwwpp/dp1529.html
   My bibliography  Save this paper

Does Transport Behavior Influence Preferences for Elektromobility? An Analysis Based on Person- and Alternative-Specific Error Components

Author

Listed:
  • Francisco J. Bahamonde-Birke

Abstract

The interconnection among different choices by the same decision-maker is fairly well established in the literature. Along this line, this paper aims to identify how preferences for electromobility are affected by mode choices for regular trips. With this purpose in mind, a framework based on person- and alternative-specific error components (covariances) is proposed. The method aims to include individual-specific error components associated with the alternatives of a given experiment into another, and to analyze how the preference for a certain alternative in a given choice situation affects the individual’s preferences in another choice situation. The data for the analysis originates from two discrete choice experiment conducted in Austria during February 2013 (representative sample). Here, individuals were asked to state their preferences in the contexts of transport mode choice and vehicle purchase situations. The results indicate the existenceof a strong correlation between the individuals’ preferences in both experiments. This way, individuals favoring private transport also favor conventional vehicles over electric alternatives, while individuals preferring public or non-motorized modes ascribe a higher utility to electric vehicles, especially to pure battery electric vehicles.

Suggested Citation

  • Francisco J. Bahamonde-Birke, 2015. "Does Transport Behavior Influence Preferences for Elektromobility? An Analysis Based on Person- and Alternative-Specific Error Components," Discussion Papers of DIW Berlin 1529, DIW Berlin, German Institute for Economic Research.
    • Handle: RePEc:diw:diwwpp:dp1529
    as

    Download full text from publisher

    File URL: https://www.diw.de/documents/publikationen/73/diw_01.c.521086.de/dp1529.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Golob, Thomas F., 1990. "The Dynamics of Household Travel Time Expenditures and Car Ownership Decisions," University of California Transportation Center, Working Papers qt1676t0bp, University of California Transportation Center.
    2. Jenn, Alan & Azevedo, Inês L. & Ferreira, Pedro, 2013. "The impact of federal incentives on the adoption of hybrid electric vehicles in the United States," Energy Economics, Elsevier, vol. 40(C), pages 936-942.
    3. Francisco J. Bahamonde-Birke & Uwe Kunert & Heike Link & Juan de Dios Ortúzar, 2017. "About attitudes and perceptions: finding the proper way to consider latent variables in discrete choice models," Transportation, Springer, vol. 44(3), pages 475-493, May.
    4. Vredin Johansson, Maria & Heldt, Tobias & Johansson, Per, 2006. "The effects of attitudes and personality traits on mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(6), pages 507-525, July.
    5. Anders Jensen & Elisabetta Cherchi & Juan Dios Ortúzar, 2014. "A long panel survey to elicit variation in preferences and attitudes in the choice of electric vehicles," Transportation, Springer, vol. 41(5), pages 973-993, September.
    6. Daniel McFadden, 1986. "The Choice Theory Approach to Market Research," Marketing Science, INFORMS, vol. 5(4), pages 275-297.
    7. Golob, Thomas F., 1990. "The Dynamics of Household Travel Time Expenditures and Car Ownership Decisions," University of California Transportation Center, Working Papers qt2t18b4q9, University of California Transportation Center.
    8. Bhat, Chandra R. & Gossen, Rachel, 2004. "A mixed multinomial logit model analysis of weekend recreational episode type choice," Transportation Research Part B: Methodological, Elsevier, vol. 38(9), pages 767-787, November.
    9. Kim, Jinhee & Rasouli, Soora & Timmermans, Harry, 2014. "Expanding scope of hybrid choice models allowing for mixture of social influences and latent attitudes: Application to intended purchase of electric cars," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 71-85.
    10. Francisco J. Bahamonde-Birke & Tibor Hanappi, 2015. "The Potential of Electromobility in Austria: An Analysis Based on Hybrid Choice Models," Discussion Papers of DIW Berlin 1472, DIW Berlin, German Institute for Economic Research.
    11. Joan L. Walker & Moshe Ben-Akiva & Denis Bolduc, 2007. "Identification of parameters in normal error component logit-mixture (NECLM) models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(6), pages 1095-1125.
    12. Caussade, Sebastián & Ortúzar, Juan de Dios & Rizzi, Luis I. & Hensher, David A., 2005. "Assessing the influence of design dimensions on stated choice experiment estimates," Transportation Research Part B: Methodological, Elsevier, vol. 39(7), pages 621-640, August.
    13. 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).
    14. Train, Kenneth E & McFadden, Daniel L & Goett, Andrew A, 1987. "Consumer Attitudes and Voluntary Rate Schedules for Public Utilities," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 383-391, August.
    15. Van Acker, Veronique & Witlox, Frank, 2010. "Car ownership as a mediating variable in car travel behaviour research using a structural equation modelling approach to identify its dual relationship," Journal of Transport Geography, Elsevier, vol. 18(1), pages 65-74.
    16. Offer, G.J. & Howey, D. & Contestabile, M. & Clague, R. & Brandon, N.P., 2010. "Comparative analysis of battery electric, hydrogen fuel cell and hybrid vehicles in a future sustainable road transport system," Energy Policy, Elsevier, vol. 38(1), pages 24-29, January.
    17. Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
    18. Eppstein, Margaret J. & Grover, David K. & Marshall, Jeffrey S. & Rizzo, Donna M., 2011. "An agent-based model to study market penetration of plug-in hybrid electric vehicles," Energy Policy, Elsevier, vol. 39(6), pages 3789-3802, June.
    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. Bahamonde-Birke, Francisco J. & Hanappi, Tibor, 2016. "The potential of electromobility in Austria: Evidence from hybrid choice models under the presence of unreported information," Transportation Research Part A: Policy and Practice, Elsevier, vol. 83(C), pages 30-41.
    2. Francisco J. Bahamonde-Birke & Juan de Dios Ortúzar, 2015. "About the Categorization of Latent Variables in Hybrid Choice Models," Discussion Papers of DIW Berlin 1527, DIW Berlin, German Institute for Economic Research.
    3. Francisco J. Bahamonde-Birke & Tibor Hanappi, 2015. "The Potential of Electromobility in Austria: An Analysis Based on Hybrid Choice Models," Discussion Papers of DIW Berlin 1472, DIW Berlin, German Institute for Economic Research.
    4. Francisco J. Bahamonde-Birke & Juan de Dios Ortúzar, 2015. "Analyzing the Continuity of Attitudinal and Perceptional Indicators in Hybrid Choice Models," Discussion Papers of DIW Berlin 1528, DIW Berlin, German Institute for Economic Research.
    5. Bahamonde-Birke, Francisco J. & Ortúzar, Juan de Dios, 2017. "Analyzing the continuity of attitudinal and perceptual indicators in hybrid choice models," Journal of choice modelling, Elsevier, vol. 25(C), pages 28-39.
    6. Weibo Li & Maria Kamargianni, 2020. "An Integrated Choice and Latent Variable Model to Explore the Influence of Attitudinal and Perceptual Factors on Shared Mobility Choices and Their Value of Time Estimation," Transportation Science, INFORMS, vol. 54(1), pages 62-83, January.
    7. Luis Márquez & Víctor Cantillo & Julián Arellana, 2020. "Assessing the influence of indicators’ complexity on hybrid discrete choice model estimates," Transportation, Springer, vol. 47(1), pages 373-396, February.
    8. Antonio Borriello & John M. Rose, 2021. "Global versus localised attitudinal responses in discrete choice," Transportation, Springer, vol. 48(1), pages 131-165, February.
    9. Soto, Jose J. & Márquez, Luis & Macea, Luis F., 2018. "Accounting for attitudes on parking choice: An integrated choice and latent variable approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 65-77.
    10. Wang, Tingting & Chen, Cynthia, 2012. "Attitudes, mode switching behavior, and the built environment: A longitudinal study in the Puget Sound Region," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1594-1607.
    11. Danielis, Romeo & Scorrano, Mariangela & Giansoldati, Marco & Rotaris, Lucia, 2019. "A meta-analysis of the importance of the driving range in consumers’ preference studies for battery electric vehicles," Working Papers 19_2, SIET Società Italiana di Economia dei Trasporti e della Logistica.
    12. Francisco J. Bahamonde-Birke & Uwe Kunert & Heike Link & Juan de Dios Ortúzar, 2017. "About attitudes and perceptions: finding the proper way to consider latent variables in discrete choice models," Transportation, Springer, vol. 44(3), pages 475-493, May.
    13. Joan L. Walker & Moshe Ben-Akiva, 2011. "Advances in Discrete Choice: Mixture Models," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 8, Edward Elgar Publishing.
    14. Dea van Lierop & Francisco J. Bahamonde-Birke, 2023. "Commuting to the future: Assessing the relationship between individuals’ usage of information and communications technology, personal attitudes, characteristics and mode choice," Networks and Spatial Economics, Springer, vol. 23(2), pages 353-371, June.
    15. Guevara, C. Angelo & Figueroa, Esteban & Munizaga, Marcela A., 2021. "Paving the road for electric vehicles: Lessons from a randomized experiment in an introduction stage market," Transportation Research Part A: Policy and Practice, Elsevier, vol. 153(C), pages 326-340.
    16. 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).
    17. Jie Song & Ruoniu Wang, 2017. "Measuring the Spatial Dimension of Automobile Ownership and Its Associations with Household Characteristics and Land Use Patterns: A Case Study in Three Counties, South Florida (USA)," Sustainability, MDPI, vol. 9(4), pages 1-19, April.
    18. Ferdous, Nazneen & Eluru, Naveen & Bhat, Chandra R. & Meloni, Italo, 2010. "A multivariate ordered-response model system for adults' weekday activity episode generation by activity purpose and social context," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 922-943, September.
    19. Palma, David & Ortúzar, Juan de Dios & Rizzi, Luis Ignacio & Guevara, Cristian Angelo & Casaubon, Gerard & Ma, Huiqin, 2016. "Modelling choice when price is a cue for quality: a case study with Chinese consumers," Journal of choice modelling, Elsevier, vol. 19(C), pages 24-39.
    20. Samira Ramezani & Barbara Pizzo & Elizabeth Deakin, 2018. "An integrated assessment of factors affecting modal choice: towards a better understanding of the causal effects of built environment," Transportation, Springer, vol. 45(5), pages 1351-1387, September.

    More about this item

    Keywords

    Electric Vehicles; Travel Behavior; Modal Choice; Correlation; Panel Structure; Error Components;
    All these keywords.

    JEL classification:

    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:diw:diwwpp:dp1529. 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: Bibliothek (email available below). General contact details of provider: https://edirc.repec.org/data/diwbede.html .

    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.