Daniel C. Feiler

Popularity, Similarity, and the Network Extraversion Bias

Using the emergent friendship network of an incoming cohort of students in an M.B.A. program, we examined the role of extraversion in shaping social networks. Extraversion has two important implications for the emergence of network ties: a popularity effect, in which extraverts accumulate more friends than introverts do, and a homophily effect, in which the more similar are two people’s levels of extraversion, the more likely they are to become friends. These effects result in a systematic network extraversion bias, in which people’s social networks will tend to be overpopulated with extraverts and underpopulated with introverts. Moreover, the most extraverted people have the greatest network extraversion bias, and the most introverted people have the least network extraversion bias. Our finding that social networks were systematically misrepresentative of the broader social environment raises questions about whether there is a societal bias toward believing other people are more extraverted than they actually are and whether introverts are better socially calibrated than extraverts.

Good Choice, Bad Judgment: How Choice Under Uncertainty Generates Overoptimism:

We examine a fundamental feature of choice under uncertainty: Overestimating an alternative makes one more likely to choose it. If people are naive to this structural feature, then they will tend to have erroneously inflated expectations for the alternatives they choose. In contrast to theories of motivated reasoning, this theory suggests that individuals will overestimate chosen alternatives even before they make their choice. In four studies, we found that students and managers exhibited behavior consistent with naïveté toward this relationship between estimation error and choice, leaving them overoptimistic about their chosen alternatives. This overoptimism from choosing positive error is exacerbated when the true values of the alternatives are close together, when there is more uncertainty about the values of alternatives, and when there are many alternatives to choose from. Our results illustrate how readily overoptimism emerges as a result of statistical naïveté, even in the absence of a desire to justify one’s decision after the choice.

A Behavioral Remedy for the Censorship Bias

Existing evidence suggests that managers exhibit a censorship bias: demand beliefs tend to be biased low when lost sales from stockouts are unobservable (censored demand) compared to when they are observable (uncensored demand). By leveraging psychological theory on wicked environments, we develop a non-constraining, easily-implementable behavioral debias technique to help mitigate this tendency in an inventory decision-making setting. The debiasing technique has individuals record estimates of demand observations (REDO): participants explicitly record a self-generated estimate of the demand realization in every period, regardless of whether or not a stockout occurs. In doing so, they construct a more representative sample of demand realizations (that differs from the sales sample). In two laboratory experiments with MBA and undergraduate students, this remedy significantly reduces downward bias in demand beliefs under censorship and leads to higher inventory order decisions.

Good Choice, Bad Judgment: How Choice Under Uncertainty Generates Overoptimism

We examine a fundamental feature of choice under uncertainty: Overestimating an alternative makes one more likely to choose it. If people are naive to this structural feature, then they will tend to have erroneously inflated expectations for the alternatives they choose. In contrast to theories of motivated reasoning, this theory suggests that individuals will overestimate chosen alternatives even before they make their choice. In four studies, we found that students and managers exhibited behavior consistent with naivety toward this relationship between estimation error and choice, leaving them overoptimistic about their chosen alternatives. This overoptimism from choosing positive error is exacerbated when the true values of the alternatives are close together, when there is more uncertainty about the values of alternatives, and when there are many alternatives to choose from. Our results illustrate how readily overoptimism emerges as a result of statistical naivety, even in the absence of a desire to justify one’s decision after the choice.

The Hot Seat: Over-Attribution to Leaders and Dismissal for Bad Luck

Are managers fired for bad luck? Although many scholars have argued that leaders receive more credit and blame for organizational performance than they deserve, there is a glaring paucity of conclu...