Capturing Hidden Attitudes: Introducing the Implicit Association Test to Transportation Planning

TitleCapturing Hidden Attitudes: Introducing the Implicit Association Test to Transportation Planning
Publication TypeJournal Article
Year of Publication2017
AuthorsJoanna Moody, jintai Li, Jinhua Zhao
JournalWorking paper
Abstract

Transportation planners routinely rely on surveys or other self-report measures (revealed preference or stated preference) to understand people’s travel preference and attitudes. This understanding is fundamental in designing policy interventions toward more sustainable travel choice. However, respondents may hold implicit attitudes that differ from their expressed answers to surveys because of social desirability bias, self-enhancement, or self-ignorance. This mismatch between attitudes measured through surveys and the actual preferences underlying behavior could have wide-ranging impacts on the shape and efficacy of policy interventions meant to influence people’s behavior.
We introduce the Implicit Association Test (IAT) – a series of computer-based matching exercises that record response time and capture subconscious associations – and evaluated it with specific reference to attitudinal and behavioral understanding for transportation planning. We motivate the use of IAT as a complement to traditional self-report methods, explain the IAT’s underlying modus operandi, and discuss its merits and limitations. We present a case study that explores the influence of social status bias on commuter’s mode choice between car and bus. We find that, in this case, the implicit attitude captured by the IAT better predicts user’s primary commute mode than the explicit measure captured by Likert scale questions. 
We demonstrate how the IAT can be applied to better understand the sustainability implications of social status bias on peoples travel behavior and we also discuss how the IAT could help planners capture perceptions of equity in transportation services and policies among different population segments. We conclude that the IAT is a viable and valuable tool that can offer unique diagnostic and predictive advantages to planners and policymakers and that further research is warranted to fully exploit IAT’s potential.