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Bicycle Use in Germany: Explaining Differences between Municipalities with Social Network Effects

Author

Listed:
  • Frank Goetzke

    (Frank Goetzke is in the Department of Urban and Public Affairs, University of Louisville, 426 West Bloom Street, Louisville, Kentucky, 40208, USA, f0goet01@louisville.edu)

  • Tilmann Rave

    (IFO Institute for Economic Research, Poschingerstr. 5, Munich, 81679, Germany, rave@ifo.de)

Abstract

This paper aims to account for important factors influencing bicycle use and focuses in particular on differences between 20 selected German municipalities with considerable variation in their bicycle mode share. Using data from the nation-wide survey Mobility in Germany 2002, a mode choice model for bicycling is developed. In an extension to previous research, social network or spillover effects as a measure of the city’s bicycling culture are also taken into account. These effects are modelled using an instrumental variable approach. It is shown that social network effects increase the probability of cycling for shopping and recreational trip purposes, but not for school, work or errands. Furthermore, it is found that cycling infrastructure matters only for shopping and errand trips. Finally, commuting trips by bicycle seem to be largely independent of any policy variables.

Suggested Citation

  • Frank Goetzke & Tilmann Rave, 2011. "Bicycle Use in Germany: Explaining Differences between Municipalities with Social Network Effects," Urban Studies, Urban Studies Journal Limited, vol. 48(2), pages 427-437, February.
  • Handle: RePEc:sae:urbstu:v:48:y:2011:i:2:p:427-437
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    Cited by:

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    2. Walker, Joan L. & Ehlers, Emily & Banerjee, Ipsita & Dugundji, Elenna R., 2011. "Correcting for endogeneity in behavioral choice models with social influence variables," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(4), pages 362-374, May.
    3. Lanzendorf, Martin & Busch-Geertsema, Annika, 2014. "The cycling boom in large German cities—Empirical evidence for successful cycling campaigns," Transport Policy, Elsevier, vol. 36(C), pages 26-33.
    4. Mahsa Ghandehari & Vahid Hamidi Pouyandeh & Mohammad Hossein Moshref Javadi, 2013. "Locating of Bicycle Stations in the City of Isfahan Using Mathematical Programming and Multi-Criteria Decision Making Techniques," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 3(4), pages 18-26, October.
    5. repec:eee:transa:v:104:y:2017:i:c:p:21-31 is not listed on IDEAS
    6. Axsen, Jonn & Orlebar, Caroline & Skippon, Stephen, 2013. "Social influence and consumer preference formation for pro-environmental technology: The case of a U.K. workplace electric-vehicle study," Ecological Economics, Elsevier, vol. 95(C), pages 96-107.
    7. repec:eee:jotrge:v:31:y:2013:i:c:p:296-308 is not listed on IDEAS
    8. repec:eee:jotrge:v:31:y:2013:i:c:p:18-29 is not listed on IDEAS
    9. José I. Castillo-Manzano & Mercedes Castro-Nuño & Lourdes Lopez-Valpuesta, 2015. "The relationship between public and private bicycle use: the case of Seville," ERSA conference papers ersa15p206, European Regional Science Association.
    10. Carlos Carrion & Nebiyou Tilahun & David Levinson, 2011. "Monte Carlo Simulation of Adaptive Stated Preference Survey with a case study: Effects of Aggregate Mode Shares on Individual Mode Choice," Working Papers 000093, University of Minnesota: Nexus Research Group.
    11. repec:eee:jotrge:v:46:y:2015:i:c:p:137-150 is not listed on IDEAS
    12. repec:eee:jotrge:v:57:y:2016:i:c:p:184-193 is not listed on IDEAS
    13. Frondel, Manuel & Vance, Colin, 2017. "Cycling on the extensive and intensive margin: The role of paths and prices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 104(C), pages 21-31.
    14. Páez, Antonio & López, Fernando A. & Ruiz, Manuel & Morency, Catherine, 2013. "Development of an indicator to assess the spatial fit of discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 56(C), pages 217-233.
    15. Sharmeen, Fariya & Arentze, Theo & Timmermans, Harry, 2014. "An analysis of the dynamics of activity and travel needs in response to social network evolution and life-cycle events: A structural equation model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 159-171.
    16. Jan-Dirk Schmöcker & Tsuyoshi Hatori & David Watling, 2014. "Dynamic process model of mass effects on travel demand," Transportation, Springer, vol. 41(2), pages 279-304, March.
    17. Frank Goetzke & Tilmann Rave, 2015. "Automobile access, peer effects and happiness," Transportation, Springer, vol. 42(5), pages 791-805, September.
    18. Kroesen, Maarten, 2015. "Do partners influence each other’s travel patterns? A new approach to study the role of social norms," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 489-505.
    19. Maness, Michael & Cirillo, Cinzia, 2016. "An indirect latent informational conformity social influence choice model: Formulation and case study," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 75-101.
    20. repec:eee:jotrge:v:30:y:2013:i:c:p:202-207 is not listed on IDEAS
    21. repec:eee:jotrge:v:42:y:2015:i:c:p:122-130 is not listed on IDEAS
    22. Frank Goetzke & Regine Gerike & Antonio Páez & Elenna Dugundji, 2015. "Social interactions in transportation: analyzing groups and spatial networks," Transportation, Springer, vol. 42(5), pages 723-731, September.
    23. repec:gam:jsusta:v:9:y:2017:i:4:p:558-:d:95081 is not listed on IDEAS
    24. Thomas Klinger & Martin Lanzendorf, 2016. "Moving between mobility cultures: what affects the travel behavior of new residents?," Transportation, Springer, vol. 43(2), pages 243-271, March.

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