Why is 1 out of 20 Riskier than 5%? Effect of Representing Unlikely Events as Frequency versus Percentage on Risk Perceptions

Consider two individuals contemplating the purchase of a new laptop computer. Both are interested in the same specific brand and model. While one individual comes across a product review stating that 5% of the brand’s laptops are expected to require repairs, the other individual reads a review reporting that 1 out of 20 of the brand’s laptops is expected to require repairs. Although the likelihood of failure is relatively low and objectively equivalent, the numeric representation of the probability information in the two reviews differs such that the expected performance information is provided in terms of percentage (5%) and frequency (1 out of 20) formats, respectively. Will the perceived risk associated with purchasing the laptop differ across the two individuals? Will one of them be more likely to buy the laptop? If so, which of the two individuals, and why? What if the performance information is described positively such as functioning satisfactorily rather than negatively such as requiring repairs? Surprisingly, despite the relatively large literature examining the influence of probability format (e.g., Kirkpatrick and Epstein 1992; Slovic, Monahan and MacGregor 2000), as well as the framing of attributes and outcomes (Tversky and Kahneman 1981; Levin, Schneider and Gaeth 1998), the answers to these questions are not clear. Further, since different theoretical perspectives lead to competing predictions, the current research seeks to examine how the numeric representation of a relatively low probability in terms of a frequency versus percentage affects risk perceptions, and provide insights into the underlying reasons for the effects.