Doctoral Degrees (Logistics)

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Browsing Doctoral Degrees (Logistics) by browse.metadata.advisor "Nel, Hannelie"

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    Designing travel behaviour change interventions: a spatiotemporal perspective
    (Stellenbosch : Stellenbosch University, 2017-12) Van Dijk, Justin Tycho; Krygsman, Stephan; Nel, Hannelie; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Logistics. Logistics.
    ENGLISH SUMMARY : Against the background of unprecedented growth in private vehicle ownership and the entrenchment of the private car in everyday life, the past decades have seen a growing and ongoing academic and policy debate on how to encourage individuals to change to more sustainable ways of travelling; for instance, with voluntary travel behaviour change (VTBC) interventions. VTBC interventions aim to alter travel behaviour by providing information. In recent years, a large body of research has focused on the evaluation of the effectiveness of these programmes. However, no consensus has been reached on the question of whether a broad implementation of VTBC programmes is effective in stimulating people to use more sustainable ways of travelling. This dissertation argues that location-aware technologies, particularly GPSenabled smartphones, could potentially augment the research on VTBC interventions. Smartphones can not only source data (such as place and time of travel or activity) but can also provide individuals with real-time information, feedback, and suggestions for alternative behaviour or travel options.. However, between sourcing the data and relaying feedback to individual commuters, significant research is required on how to obtain, clean, and interpret the data, as well as on how to account for individual spatiotemporal accessibility. GPS data need to be collected and analysed systematically; especially in the context of evaluating the effectiveness of VTBC interventions in which effect sizes are known to be small and inconspicuous. As such, the translation of raw GPS trajectories into activity episodes and the best estimation of a travelled route are pivotal. Methods of activity recognition were explored with advanced machine learning algorithms, and two approaches for identifying travelled routes were proposed. Furthermore, it was demonstrated how spatiotemporal measurements could aid the design of VTBC interventions. Attention was drawn to the time-geographical concepts of activity spaces and potential path areas. Based on the examination of GPS tracks with different two-dimensional operationalisations of activity spaces, it was found that the density of opportunities within an activity space is related to the size of the activity space: larger activity spaces have lower densities of opportunities than smaller activity spaces. This may suggest that individuals who have a low opportunity density are less likely to respond to external stimuli and/or awareness programmes than individuals who have a high opportunity density. In turn, potential path areas were used to establish to what extent individuals have different spatiotemporal opportunities that will enable behavioural change in travel and activity. The findings indicate that location-aware technologies hold great potential to supplement transport geographical-research. Moreover, the results show that the incorporation of spatiotemporal measurements is crucial to consider for the design, implementation, and evaluation of VTBC interventions. The added value of seemingly new technologies, such as GPS, is that they can be easily integrated into a larger spatiotemporal framework of analysis. However, one has to be careful not to consider GPS as a panacea, because GPS data and technology also have some drawbacks. Careful consideration should go into application development, sample selection, site selection, and data imputation.