Abstract
The most likely responses of humans in emergency escape scenarios is not perfectly understood and many of the current behavioural assumptions are speculative. Because of the insufficiency of empirical evidence, certain assumptions and terminologies in this area have been derived from analogical experiments with non-human crowds (e.g. ants or mice, as models of humans) or from purely numerical analyses. Some have suggested that stressful collective escape situations trigger an increased tendency to imitate the decision of the majority, the so-called ‘herd-behaviour’ assumption. Here, we empirically test this assumption using a series of novel experiments with human crowds. Individual-level observations of direction choice were gathered and analysed using econometric modelling methods. Results showed that humans do not tend to imitate direction choices of the majority. To the contrary, they tend to avoid the direction chosen by the majority, and the bigger the majority is, the less likely they are to follow it. The high-urgency treatment (assumed to be associated with higher degrees of stress) did not reverse, nor did it decrease this avoid-the-majority tendency. If anything, it even amplified it in certain choice situations. We also found out that the general level of crowding (i.e. the total number of people in the choice-maker’s vicinity) is another factor that can moderate the reaction to peers’ decision. Higher levels of crowding also amplified the avoid-the-crowd tendency in certain direction choice scenarios. The results overall suggested that escaping humans, when not facing substantial degrees of information uncertainty, tend to avoid the direction chosen by the majority (opposite the ‘herding’ assumption); and they do so more distinctly when they perceive higher urgency or greater number of people in their vicinity. An implication of our finding is that strong parallels between escape behaviour of humans and animals/insects may not exist. Such analogies (particularly on decision-making aspects) need to be drawn with great caution. They might misguide modelling assumptions and lead to unrealistic predictions.
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