Abstract
The values of security documents such as banknotes depend on the subjective confidence in those security documents by their users. We tried to elucidate what factors are affecting the perceived genuineness of security documents. In the first experiment, we investigated how people's awareness to security features influences the perceived resistance of banknotes against counterfeiting. Nine banknotes actually circulated on the market were sampled and presented to sixteen observers. The observers reported as many security features found on each banknote as possible and ranked the perceived resistance of those banknotes against counterfeiting. The interval scale of perceived resistance was estimated from the rank order data. A highly significant correlation between the perceived resistance against counterfeiting and the average number of security features found by the observers on each banknote, but no correlations were found with other metrics. This suggests that security features on security documents should be designed self-explanatory. In the second experiment, we tried to investigate what factors of the portraits in banknotes are affecting the perceived genuineness of the banknotes. Each of seventeen banknotes was enclosed in an envelope with a hole so that only the portrait area was presented to twenty-one observers. The observers judged the genuineness of each portrait as a part of a banknote according to a 5-category Likert scale. At the same time, observers reported the criteria in rating the genuineness of banknotes and features mentioned by the observers were recorded during the sessions. The interval scales of the genuineness of the banknotes judged from their portraits were constructed with Torgerson's law of category judgement. By comparing highly-rated notes in genuineness with lowly-rated notes, it was suggested that the lack of complexity in design makes banknotes look less genuine and that reasonable and plausible wear and tear make banknotes look more genuine.
Meeting abstract presented at VSS 2016