Social Networks and Travel Behaviour by Matthias Kowald & Kay W. Axhausen

Author:Matthias Kowald & Kay W. Axhausen [Kowald, Matthias & Axhausen, Kay W.]
Language: eng
Format: epub
Tags: Regional Planning, Public Policy, Social Science, Political Science, Research
ISBN: 9781317053644
Google: g0urCwAAQBAJ
Goodreads: 29443210
Publisher: Routledge
Published: 2016-03-03T00:00:00+00:00

Matthias Kowald

Investigating the influence of social contacts on leisure travel patterns was the aim of the study by Frei and Axhausen (see Chapter 3) and numerous other survey projects in transport planning in recent years. Many of these studies used social network analysis (SNA) methods. They identified leisure travel as being primarily undertaken to join others in leisure activities; it is also referred to as ‘social’ or ‘activity’ travel. In focusing mainly on network topology statistics (i.e., number of personal contacts, geographical distances between tied persons, and contact modes and frequencies used to maintain relationships), these projects confirmed SNA-methods productivity, producing new empirical insights and results (Larsen et al. 2006; Carrasco et al. 2008; van den Berg et al. 2009; also see Chapter 3). However, one issue was ignored by previous studies: topology of a population-wide ‘global’ leisure network.

Focussing on personal networks means that respondents’ personal networks (usually) do not overlap in terms of shared social contacts. Surveyed network structures are isolated components of the global social network. However, in social reality people are connected to many others by direct, but to most others by chains of indirect relationships. In other words: People have a limited number of relatives, friends and acquaintances but when also accounting for friends of friends, or even higher orders of interconnectivity, they are linked to many others. Their personal networks are embedded in a population-wide network structure. This underlying network allows feelings (Christakis and Fowler 2009), styles and behaviours (Gladwell 2002), as well as contagious diseases (Mossong et al. 2008; Smieszek et al. 2011) to spread within a given population. Information on this population-wide network is needed to allow analyses of its structure and an implementation of a ‘global’ leisure network in agent-based travel demand simulations.

The Institute for Transport Planning and Systems (IVT) of ETH Zurich and the Institute for Sea- and Land-Transport (ILS) of TU Berlin conducted a joint survey study between January 2009 and March 2011 to investigate this population-wide leisure network topology. The survey is presented in detail here. Starting with an introduction of the survey design, the chosen methodology to collect information on personal networks as well as a population-wide network structure is presented. This is followed by a discussion on the survey instrument. Survey protocol, closely linked to bias-decreasing measures developed for this project, is presented next. Accompanied by an analysis of people’s response behaviour a fieldwork report is provided. It also includes information on relevant ethical and data protection issues. Discussing the fit between survey and target population and providing information on non-response behaviour aims to analyse the data in terms of data quality (most of this work was previously published in Kowald and Axhausen 2014). Finally, selected results from the survey are presented. This includes, on the one side, information on personal networks. However, instead of repeating the analysis from Chapter 3, additional aspects of personal networks are analysed, including issues of homophily and tie strength. On the other side, results about the population-wide network structure are presented.

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