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A Multilevel Path Analysis of Social Networks and Social Interaction in Neighbourhood

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  • Pauline van den Berg
  • Harry J.P. Timmermans

Abstract

In urban renewal policies in the Netherlands, great importance is attached to housing diversification and social mix in neighbourhoods. The assumption that housing diversification will lead to more neighbourhood-based social interaction and social cohesion has been taken for granted, although empirical evidence supporting this assumption is scarce and inconclusive. It is therefore important to improve our understanding of the effects of neighbourhood characteristics on neighbourhood-based social contacts, based on empirical results. This paper aims to contribute to this line of research by studying the role of socio-demographics and neighbourhood characteristics in the formation of social network ties and social interactions with neighbours. These relationships are analysed using a multi-level path analysis approach. The analyses are based on data collected in 2011 in 70 different neighbourhoods in Eindhoven, the Netherlands in a survey among 751 respondents. The results indicate that neighbourhood-based contacts are influenced by socio-demographic characteristics. People who spend more time at home (people with children and people who do not work) and who have been living longer at the current address have a larger share of neighbours in their social network and higher contact frequencies with their neighbours. Immigrants have a smaller share of neighbours in their social network. Education is found to have a negative effect, whereas income is found to have a positive effect on social interaction with neighbours. Neighbourhood characteristics are not found to affect social network size, the share of neighbours in the network or the frequency of interaction with neighbours. This finding is at variance with the assumption that an adaptation of neighbourhood characteristics (through urban renewal) can lead to increasing social interaction among neighbours.

Suggested Citation

  • Pauline van den Berg & Harry J.P. Timmermans, 2013. "A Multilevel Path Analysis of Social Networks and Social Interaction in Neighbourhood," ERES eres2013_4, European Real Estate Society (ERES).
    • Handle: RePEc:arz:wpaper:eres2013_4
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    References listed on IDEAS

    as
    1. Golob, Thomas F., 2001. "Structural Equation Modeling For Travel Behavior Research," University of California Transportation Center, Working Papers qt8pb2m1pk, University of California Transportation Center.
    2. George Galster, 2007. "Neighbourhood Social Mix as a Goal of Housing Policy: A Theoretical Analysis," International Journal of Housing Policy, Taylor & Francis Journals, vol. 7(1), pages 19-43.
    3. Pauline Berg & Theo Arentze & Harry Timmermans, 2012. "Involvement in clubs or voluntary associations, social networks and activity generation: a path analysis," Transportation, Springer, vol. 39(4), pages 843-856, July.
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    Cited by:

    1. Bojing Liao & Pauline E. W. van den Berg & Pieter J. V. van Wesemael & Theo A. Arentze, 2020. "How Does Walkability Change Behavior? A Comparison between Different Age Groups in the Netherlands," IJERPH, MDPI, vol. 17(2), pages 1-14, January.
    2. Parady, Giancarlos & Frei, Andreas & Kowald, Matthias & Guidon, Sergio & Wicki, Michael & van den Berg, Pauline & Carrasco, Juan-Antonio & Arentze, Theo & Timmermans, Harry & Wellman, Barry & Takami, , 2021. "A comparative study of social interaction frequencies among social network members in five countries," Journal of Transport Geography, Elsevier, vol. 90(C).
    3. Pauline Berg & Theo Arentze & Harry Timmermans, 2015. "A multilevel analysis of factors influencing local social interaction," Transportation, Springer, vol. 42(5), pages 807-826, September.
    4. Chiara Calastri & Romain Crastes dit Sourd & Stephane Hess, 2020. "We want it all: experiences from a survey seeking to capture social network structures, lifetime events and short-term travel and activity planning," Transportation, Springer, vol. 47(1), pages 175-201, February.

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    JEL classification:

    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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