Clearing the path to transcend barriers to walking: Analysis of associations between perceptions and walking behaviour

Walkability is much studied, but the relative importance of perceptions and motivations is still not consensual. This study took a holistic approach to examine the comparative importance of a range of possible perceptions, motivations and individual characteristics on walking levels.Data from Auckland Transport's Active Modes online survey (AT survey, N = 4,114) captured environmental perceptions and travel behaviour. Machine learning (gradient boosting) was used to predict walking levels from perceptual data and individual characteristics and determine the relative importance of each variable. Strong predictors of walking included the use of public transport, walking perceived as saving money and avoiding parking hassle, age group, and overall satisfaction with walking. Surprisingly, the importance of expected dimensions such as perceived availability of destinations or internal motivations was null in the general model.These findings suggest a more holistic view of walking behaviour is needed, one that moves beyond the pure availability of destinations.


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  • Accession Number: 01767781
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Feb 3 2021 3:10PM