Abstract
In this digital economy, customers' handwriting, such as signatures and related characteristics, can be easily collected and quantitatively analyzed. From the perspective of decision-making, obtaining information from signature characteristics is an important data-driven business leverage. In this regard, can we infer individual preferences from signatures? Through a large-scale laboratory experiment, this study measured the participants’ risk and time preferences and collected their signature information in order to determine the influence of behavioral preferences on their signatures. Based on the empirical results, the higher the risk and ambiguity aversion of the participants, the smaller were their signature sizes. Moreover, the greater their level of patience, the more likely their signatures showed a trend of increasing size. Overall, this study fills a research gap in signature-related behavior by highlighting the application of text mining in digital handwriting, especially in broad business settings such as the insurance industry.
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