Weighting of Small Probabilities and Its Market Applications

Abstract

This paper investigates the conditions under which the phenomenon of of small is less likely to occur and their implications with regard to certain business and marketing issues. Based on recent findings in behavioral economics, the authors demonstrated that when the difference in outcome values reduces, disappears, or is no longer apparent, an alternative with a small probability is less likely to be overweighed. Further, the authors suggested a status quo effect in the weighting of a small probability with reference to people's wealth. By applying the theoretical results to a promotional context, the authors found that using a promotional incentive that offers a small chance of winning a large amount is more effective for high-priced products than for low-priced products. To test the hypotheses, three experimental studies using student subjects were performed sequentially. Each experiment had specific objectives and involved the use of a factorial design. In line with previous findings, Study 1 indicated that as the associated payoff sizes increase in choice problems, the overweighting of small probabilities tends to diminish.More importantly, when no value comparison is presented, the overweighting of small probabilities is less likely to occur. Moreover, it showed that there is a preference discrepancy between choice and matching and that the weighting of probabilities is more consistent in the matching context than in the choice context.In Study 2, the above findings were employed in issues related to lotteries and insurance pricing. The study demonstrated that consumers are more reluctant to buy a lottery or air insurance at a higher price, even if the expected payoff increases accordingly. Moreover, at the same price, the wealthier group of people is more willing to accept the lottery or insurance. Study 3 was a mixed experimental design involving eight products in four categories. In all four categories, the results showed that sweepstakes are more effective than premiumsin selling high-priced products;however, there is no significant difference between these two schemes when selling low-priced products. The findings systematically demonstrated that the of small probabilitiesis context dependent. The research provides incremental evidence for the contingent weighting model and consumer preference reversals. From the perspective of a behavioral researcher, given the different levels of outcomes, coupled with the uncertainty of how small probabilities should be interpreted, the results can be explained by differential attention and information processing. From the perspective of a decision theorist, the results reflect a strong boundary condition that contradicts the commonly held belief that probabilities and values are independent of each other. Finally, the findings have important managerial implications in successful pricing and promotional design.

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