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Participants' perceptions of smartphone travel surveys
Affiliation:1. Consultant, Bastrop, TX, USA;2. Institute of Transport and Logistics Studies, The University of Sydney Sydney, Australia
Abstract:Smartphone travel surveys are becoming of central importance in collecting detailed, accurate data of people’s travel activities. As with their conventional survey counterparts, the quality of data collected through these surveys is adversely affected by participants’ non-response and resulting biases. However, little is known about the factors affecting people’s perceptions and intentions to continue participating in such surveys. Although literature has investigated the associations between individuals’ socio-demographic attributes and their likelihood of survey participation, the impact of their subjective perceptions and attitudes on their survey participation intentions and behaviour is underexplored. Hence, through a model of participants’ perceptions of smartphone travel survey applications (survey apps), this study aims to reveal such impacts and how they affect the participants’ intentions to continue participating in these surveys. In this study, a survey is designed and used to collect data in a smartphone travel survey before the participants are asked about their personal perceptions and attitudes. Partial least squares path modelling (PLS-PM) is applied to analyse the data, as it allows simultaneous estimation of the relationships between multiple latent constructs as well as the indicators of each construct. The results showed a significant, positive impact of the perceived “ease of use” and “usefulness” of the survey app as the technological medium of data collection on the participants’ “satisfaction” and “intention” to continue participating in the corresponding survey. The study also found that participants’ perceived “risk” associated with privacy concerns did not have any significant impact on their intention to continue participating in the survey.
Keywords:Smartphone travel survey  Survey participation  Technology acceptance model  Perceived risk  Partial least squares path model (PLS-PM)
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