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Focusing on Connected Personal Leisure Networks: Selected Results from a Snowball Sample

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  • Matthias Kowald
  • Kay W Axhausen

Abstract

Explanations of leisure travel must take the influence of participants' social contacts into account. To analyze this influence, transport planning uses social network analysis methods. While most past projects have focused on isolated network components, this paper presents a study collecting data on connected personal networks by taking a snowball sample. The paper explains difficulties for transport planning in approaching and explaining leisure travel and then introduces both the survey methodology and the instrument in detail. Advantages and disadvantages of snowball sampling are addressed, and the question why this strategy is important for approaching leisure travel, followed by experiences from the field about response rate, the fit between survey and target population, and sources of bias are given. Descriptive analyses highlight the potential of the data to produce new empirical insights.

Suggested Citation

  • Matthias Kowald & Kay W Axhausen, 2012. "Focusing on Connected Personal Leisure Networks: Selected Results from a Snowball Sample," Environment and Planning A, , vol. 44(5), pages 1085-1100, May.
    • Handle: RePEc:sae:envira:v:44:y:2012:i:5:p:1085-1100
    DOI: 10.1068/a43458
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    Citations

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    Cited by:

    1. Maness, Michael, 2017. "Comparison of social capital indicators from position generators and name generators in predicting activity selection," Transportation Research Part A: Policy and Practice, Elsevier, vol. 106(C), pages 374-395.
    2. Holz-Rau, Christian & Scheiner, Joachim, 2019. "Land-use and transport planning – A field of complex cause-impact relationships. Thoughts on transport growth, greenhouse gas emissions and the built environment," Transport Policy, Elsevier, vol. 74(C), pages 127-137.
    3. Maness, Michael & Cirillo, Cinzia & Dugundji, Elenna R., 2015. "Generalized behavioral framework for choice models of social influence: Behavioral and data concerns in travel behavior," Journal of Transport Geography, Elsevier, vol. 46(C), pages 137-150.
    4. Kowald, Matthias & van den Berg, Pauline & Frei, Andreas & Carrasco, Juan-Antonio & Arentze, Theo & Axhausen, Kay & Mok, Diana & Timmermans, Harry & Wellman, Barry, 2013. "Distance patterns of personal networks in four countries: a comparative study," Journal of Transport Geography, Elsevier, vol. 31(C), pages 236-248.
    5. Xiao, Yu & Lo, Hong K., 2016. "Day-to-day departure time modeling under social network influence," Transportation Research Part B: Methodological, Elsevier, vol. 92(PA), pages 54-72.

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