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◇ Open MIND2026-07-31· Recall

Memory biases in commuting decisions

Lai Yan Tung Tiffany, Nicharee Suwantip, Elliot Ludvig, Xiaomu Guo

原始摘要(英文原文)· Original abstract
This research investigates how memory biases influence risky commuting decision-making. Everyday travel decisions are often made based on memories of previous experiences rather than complete or objective information. However, memories are not always accurate and may disproportionately emphasise particularly severe or salient events. Such memory distortions may influence how people perceive travel reliability and subsequently affect their transport choices. To examine this, the study compares experience-based and description-based decision-making. Participants will complete commuting tasks involving two routes with equivalent total delay but different delay distributions: one route contains a rare but severe delay, whereas the other contains frequent but mild delays. In the experience-based condition, participants observe commuting outcomes over multiple days, whereas in the description-based condition, the same information is presented as a written summary. Participants then complete memory recall tasks and make subsequent commuting decisions, including route choice and departure-time buffer decisions under both low- and high-stakes scenarios. The study aims to determine whether acquiring information through direct experience produces greater memory distortion than acquiring equivalent information through description, and whether these memory distortions influence subsequent commuting decisions. Specifically, the project examines distortions in the perceived severity and frequency of delays, their relationship with route choice, and their influence on the amount of extra travel time participants allow before departing. The findings will contribute to the literature on decisions from experience, memory biases, and transport behaviour by providing evidence on how memory shapes risk preferences in everyday commuting contexts. The results may also offer practical insights into how commuters respond to different patterns of travel delays and how transport information could be presented to support more informed decision-making.
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