Crowdsourcing as a Method for the Collection of Revealed Preferences Data

摘要

Crowdsourcing has been used widely for the collection of stated preference data (e.g., responses in a survey) by researchers. However, the use of crowdsourcing for collection of revealed preference data (e.g., real-life data collected in natural experiments) is much less common. The study reported in this short (research-in-progress) paper shows how crowdsourcing can be used as a method for the collection of revealed preference data in the context of transport studies. In transport studies, data is traditionally collected through surveys, diaries or simulations. Here, crowdsourcing could provide an alternative method that provides real-life data very fast and very cheap to researchers. To generate insights on crowdsourcing as an alternative data collection method, we use an open call on a crowdsourcing platform (Amazon Mechanical Turk - AMT), a mobile application (Advanced Travel Logging Application for Smartphones II - ATLAS II) and a participant survey to practically perform such a crowdsourced data collection and evaluate the effectiveness of the method. While the full study is still in progress, the initial results reported in this paper are promising and support the idea that crowdsourcing can indeed be used as an effective method for the collection of revealed preference data.