2016
DOI: 10.4324/9781315609560
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Social Networks and Travel Behaviour

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Cited by 10 publications
(4 citation statements)
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References 91 publications
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“…The two identified various forms of visual data and their collection methods, including ‘found data’, ‘researcher-created data’ and ‘respondent-created data’. Looking first at ‘found data’, several spatial-related studies have used personal items such as old photo albums or calendars (e.g., Kowald & Axhausen, 2016) to support interviewees’ ability to reconstruct, for example, how and where they previously lived.…”
Section: Participatory Visual Methodsmentioning
confidence: 99%
“…The two identified various forms of visual data and their collection methods, including ‘found data’, ‘researcher-created data’ and ‘respondent-created data’. Looking first at ‘found data’, several spatial-related studies have used personal items such as old photo albums or calendars (e.g., Kowald & Axhausen, 2016) to support interviewees’ ability to reconstruct, for example, how and where they previously lived.…”
Section: Participatory Visual Methodsmentioning
confidence: 99%
“…Visiting friends, going to a sports club, or having a business meeting appear to be common motives for travel, and in each of these situations, there is a relation between an ego and a network partner to analyze. There seems to be clear evidence that social networks are a reason to travel (9,10). However, travel behavior research in the realm of social network analysis is mainly focused on leisure networks.…”
Section: Analyzing Relationshipsmentioning
confidence: 99%
“…Recognizing that travelers may have differing preferences regarding the balance of in-person versus electronic communication they wish to engage in, Roy et al used social network analysis to identify clusters of travelers on the basis of this balance (17). Kowald and Axhausen provided an overview of contemporary research on the topic (18). They noted, in particular, that the emergence of disaggregate travel models provides a stronger foundation on which to model the effects of social networks on travel, because individual networks can be simulated in a way that is impossible in aggregate models.…”
Section: Extended Social and Professional Network Effectmentioning
confidence: 99%