Left-digit bias is a cognitive bias where individuals disproportionately focus on the leftmost digit of a number, leading to misperceptions of value or magnitude. This bias is evident in consumer behavior, where prices ending in .99 are perceived as significantly lower than those ending in .00, despite the minimal actual difference. For instance, consumers often view $4.99 as much cheaper than $5.00, which influences their purchasing decisions Sokolova, 2020. This phenomenon is not limited to low-stakes decisions; it also affects high-stakes markets such as real estate, where properties listed just below round numbers attract more competitive bidding and higher final prices Repetto, 2019.
The left-digit bias also impacts firm pricing strategies. Retailers frequently use 99-ending prices to exploit this bias, as consumers react to a 1-cent increase from a 99-ending price as if it were a much larger increase Strulov-Shlain, 2019. However, firms often underestimate the extent of this bias, leading to suboptimal pricing strategies that can result in significant profit losses. This discrepancy suggests that while firms recognize the bias, their pricing models do not fully account for its magnitude, indicating a reliance on heuristics rather than precise optimization.
Beyond consumer goods and real estate, left-digit bias influences medical decision-making and financial markets. For example, in the selection of deceased donor kidneys, organs from donors aged just above a round number (e.g., 70 years) are more likely to be discarded compared to those just below (e.g., 69 years), despite similar medical profiles Husain, 2021. Similarly, both individual and institutional investors exhibit left-digit bias in their trading behaviors, with significant buying or selling activity triggered by changes in the leftmost digit of stock prices Yu, 2023.
In summary, left-digit bias is a pervasive cognitive bias affecting various decision-making processes, from consumer purchases to high-stakes markets and medical decisions. It leads to significant misperceptions of value, influencing both individual behaviors and institutional strategies. Understanding and mitigating this bias can lead to more rational decision-making and optimized outcomes across different domains.
