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It was predicted that trained observers would detect deception more accurately than untrained observers. More specifically, it was predicted that the highest deception detection accuracy would be found among trained observers judging the veracity of low self-monitors and unrehearsed liars, whereas the lowest detection accuracy would be found among untrained observers judging the veracity of high self-monitors and rehearsed deceivers. It also was hypothesized that the discrepancy between observers‘actual ability to detect deception and their certainty in the accuracy of their judgments would be smaller for trained observers than for untrained observers. Observers trained to detect deception used six behavioral cues based on research by deTurck and Miller (1985): (a) message duration, (b) response latency, (c) adaptors, (d) pauses, (e) nonfluencies, and (f) hand gestures. Results confirmed both hypotheses. 相似文献
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Yefim Roth 《决策行为杂志》2020,33(5):643-656
Given the rapid proliferation of smartphone applications and data aggregation websites, in many situations people can use decision aids to guide their choices. For example, they may consider whether to use a navigation device to check the fastest route or whether to use a price comparison website to find the cheapest deal. In what circumstances will subjects use a costly comparison decision aid (which I refer to as “checking”) to choose for them? In six studies, I investigate the impact of the number of available alternatives and checking's attractiveness on the decision to check. While at first increasing the attractiveness of checking led to higher checking rates, a further increase in the number of available alternatives (and thus checking's attractiveness) did not increase the checking rate. Surprisingly, even when checking had a 40% higher expected value compared with not checking, the observed checking rate was below 45%, contrary to risk and ambiguity aversion predictions. Furthermore, labeling the checking alternative as the default had no impact on its choice rate. I find large individual differences in decisions to check. Surprisingly, subjects' initial decisions had high predictive power over their subsequent checking rates, even after 100 trials with full feedback. I propose two simple learning models that capture well the aggregated results. 相似文献