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Electrifying Choices: How Electric Bicycles Impact on Mode Choice and CO2 Emissions

Author

Listed:
  • Thomas Hagedorn

    (Institute of Transport Economics, Muenster)

  • Jan Wessel

    (Institute of Transport Economics, Muenster)

  • Marlena Meier

    (Institute of Transport Economics, Muenster)

Abstract

This paper analyzes (i) the influence of electric bicycle (“e-bike†) ownership on transport mode choice and (ii) how a change in e-bike ownership affects carbon dioxide (CO2) emissions in Germany. Using longitudinal data from household surveys from 2016 to 2022, we first conduct a trip-level analysis with a mixed multinomial logit model (MMNL model) to estimate mode choice probabilities. The results show that the change in e-bike ownership significantly affects travel behavior, by increasing the likelihood of choosing an e-bike as means of transportation by 14.6 percentage points (p.p.), while correspondingly decreasing the likelihood of choosing other modes, especially conventional bicycles by 5.6 p.p., as well as car and public transportation by about 4 p.p. each. Second, by using observed changes in individual distances traveled and transport-mode-specific emissions values, we calculate net emissions savings per person after acquiring an e-bike. These savings amount to 526.9kg CO2 per person and year.

Suggested Citation

  • Thomas Hagedorn & Jan Wessel & Marlena Meier, 2024. "Electrifying Choices: How Electric Bicycles Impact on Mode Choice and CO2 Emissions," Working Papers 40, Institute of Transport Economics, University of Muenster.
    • Handle: RePEc:mut:wpaper:40
    as

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    References listed on IDEAS

    as
    1. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, January.
    2. Philips, Ian & Anable, Jillian & Chatterton, Tim, 2022. "E-bikes and their capability to reduce car CO2 emissions," Transport Policy, Elsevier, vol. 116(C), pages 11-23.
    3. Mathijs Haas & Maarten Kroesen & Caspar Chorus & Sascha Hoogendoorn-Lanser & Serge Hoogendoorn, 2022. "E-bike user groups and substitution effects: evidence from longitudinal travel data in the Netherlands," Transportation, Springer, vol. 49(3), pages 815-840, June.
    4. Richard Williams, 2012. "Using the margins command to estimate and interpret adjusted predictions and marginal effects," Stata Journal, StataCorp LP, vol. 12(2), pages 308-331, June.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    E-Bikes; transport mode choice; CO2 emissions; longitudinal data; mixed multinominal logit model;
    All these keywords.

    JEL classification:

    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • Q59 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Other

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