'Whew that Was Close!' How Near Miss Events Bias Subsequent Decision Making Under Risk

29 Pages Posted: 5 Jun 2005

See all articles by Catherine H. Tinsley

Catherine H. Tinsley

Georgetown University - Department of Management

Robin Dillon-Merrill

Georgetown University - Department of Decision Sciences, Information Sciences & POM

Date Written: June 1, 2005

Abstract

In two experiments, we show clear evidence of a 'near miss' bias, in that when people receive information about prior near miss events (events that could have had a positive or negative outcome, where the outcome was non-fatal) they subsequently make riskier decisions than those who receive no near miss information. We explain the near miss bias as a discounting of given probability information such that people fail to see the independence of events. In Experiment 2, we show that when probability information is made salient and the decision makers attend to this probability information as the basis for their decision, the near miss bias goes away. In Experiment 2, we also see that when people have near miss information they search significantly less for information, even when that information is costless. Results are discussed in terms of accident prevention, Bayesian updating, and the normalization of deviance.

Keywords: Near miss bias, decision making, risk

Suggested Citation

Tinsley, Catherine H. and Dillon-Merrill, Robin, 'Whew that Was Close!' How Near Miss Events Bias Subsequent Decision Making Under Risk (June 1, 2005). Available at SSRN: https://ssrn.com/abstract=736245 or http://dx.doi.org/10.2139/ssrn.736245

Catherine H. Tinsley (Contact Author)

Georgetown University - Department of Management ( email )

Rafik B Hariri Building
McDonough School of Business
Washington, DC 20057
United States
202-687-2524 (Phone)

HOME PAGE: http://explore.georgetown.edu/people/tinsleyc/

Robin Dillon-Merrill

Georgetown University - Department of Decision Sciences, Information Sciences & POM ( email )

Washington, DC 20057
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
268
Abstract Views
2,373
rank
133,889
PlumX Metrics