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The determinants of travel mode choice: the case of Łódź, Poland

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  • Wójcik Szymon

    (University of Łódź, Department of Econometrics)

Abstract

In this study, potential factors influencing the decisions made by citizens of the city of Łódź, Poland, regarding the choice of transportation mode used in their daily travel activities were examined. In addition to a brief literature review, an empirical study was performed. Data from a previous quality-of-life study were used to enhance the scope of explanatory variables in a regression model. In order to identify the determinants of travel behaviour, binary logistic regression models were used. The results show that socio-demographic characteristics of respondents and household access to a car most influenced transport mode choices. Also, the relationship between geographic distances and subjective opinions regarding public transport were found to be statistically significant. The determinants for choosing either public or private transportation varied.

Suggested Citation

  • Wójcik Szymon, 2019. "The determinants of travel mode choice: the case of Łódź, Poland," Bulletin of Geography. Socio-economic Series, Sciendo, vol. 44(44), pages 93-101, June.
  • Handle: RePEc:vrs:buogeo:v:44:y:2019:i:44:p:93-101:n:8
    DOI: 10.2478/bog-2019-0018
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    1. Van, Hong Tan & Choocharukul, Kasem & Fujii, Satoshi, 2014. "The effect of attitudes toward cars and public transportation on behavioral intention in commuting mode choice—A comparison across six Asian countries," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 36-44.
    2. De Witte, Astrid & Hollevoet, Joachim & Dobruszkes, Frédéric & Hubert, Michel & Macharis, Cathy, 2013. "Linking modal choice to motility: A comprehensive review," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 329-341.
    3. Javier Asensio, 2002. "Transport Mode Choice by Commuters to Barcelona's CBD," Urban Studies, Urban Studies Journal Limited, vol. 39(10), pages 1881-1895, September.
    4. Astrid De Witte & Joachim Hollevoet & Frédéric Dobruszkes & Michel Hubert & Cathy Macharis, 2013. "Linking modal choice to motility: a comprehensive review," ULB Institutional Repository 2013/138176, ULB -- Universite Libre de Bruxelles.
    5. McFadden, Daniel, 1974. "The measurement of urban travel demand," Journal of Public Economics, Elsevier, vol. 3(4), pages 303-328, November.
    6. Schwanen, Tim & Mokhtarian, Patricia L., 2005. "What Affects Commute Mode Choice: Neighborhood Physical Structure or Preferences Toward Neighborhoods?," University of California Transportation Center, Working Papers qt4nq9r1c9, University of California Transportation Center.
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