Environment Systems and Decisions

, Volume 36, Issue 1, pp 34–44 | Cite as

Near-miss events, risk messages, and decision making

  • Robin L. Dillon
  • Catherine H. Tinsley


Decades of research have sought to understand how disaster preparedness decisions are made. We believe one understudied factor is the impact of near-miss events. A near-miss occurs when an event (such as a hurricane or terrorist attack) has some non-trivial probability of ending in disaster (loss of life, property damage), but the negative outcome is avoided largely by chance (e.g., at the last minute, the storm dissipates or the bomb fails to detonate). In the first of two experiments, we study reactions to a hurricane threat when participants are told about prior near-miss events. We find that people with information about a prior near-miss event that has no negative consequences are less likely to take protective measures than those with either no information or information about a prior near-miss event that has salient negative information. Similar results have been shown in prior research, but we seek to understand people’s reasoning for the different reactions. We examine the role of an individual’s risk propensity and general level of optimism as possible explanatory variables for the “near-miss” effect. We find risk propensity to be stable across conditions, whereas general optimism is influenced by the type of prior near-miss information, so that optimism mediates how near-miss information impacts protective decisions. People who experience a potentially hazardous near-miss but escape without obvious cues of damage will feel more optimistic and take less protective action. In the second study, we test messages about the hazard’s risk and examine the impact of these messages to offset the influence of near-misses. We end by discussing the implications of near-misses for risk communication.


Near-misses Risk perception Hazard warnings Natural disasters 



This research was supported by the National Science Foundation under Grant Number 1331399 and by the US Department of Homeland Security through the National Center for Risk and Economic Analysis of Terrorism Events (CREATE) under Award Number 2010-ST-061-RE0001. This research was presented at the Risk Perception and Response Conference supported by the Harvard School of Public Health. However, any opinions, findings, and conclusions or recommendations in this document are those of the authors and do not necessarily reflect views of the National Science Foundation, the US Department of Homeland Security, the University of Southern California, CREATE, Georgetown University, any component of Harvard University, or other sponsors of the Risk Perception and Response conference.


  1. Ajzen I (1991) The theory of planned behavior. Organ Behav Hum Dec 50(2):179–211CrossRefGoogle Scholar
  2. Árvai J, Rivers L (2014) Effective risk communication. Earthscan, New YorkGoogle Scholar
  3. Árvai J, Gregory R, Ohlson D, Blackwell B, Gray R (2006) Letdowns, wake-up calls, and constructed preferences: people’s response to fuel and wildfire. J Forest 104(4):173–181Google Scholar
  4. Baker EJ (1979) Predicting response to hurricane warnings: a reanalysis of data from four studies. Mass Emerg 4:9–24Google Scholar
  5. Baron RM, Kenny DA (1986) The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 51(6):1173–1182CrossRefGoogle Scholar
  6. Bier VM, Mosleh A (1991) An approach to the analysis of accident precursors. In: Garrick BJ, Gekler WC (eds) The analysis, communication, and perception of risk. Plenum Press, New York, pp 93–104CrossRefGoogle Scholar
  7. Birkland T (2006) Lessons of disaster: policy change after catastrophic events. Georgetown University Press, WashingtonGoogle Scholar
  8. Caponecchia C (2010) It won’t happen to me: an investigation of optimism bias in occupational health and safety. J Appl Soc Psychol 40(3):601–617CrossRefGoogle Scholar
  9. Devore JL (1987) Probability and statistics for engineering and the sciences, 2nd edn. Wadswach Inc, CAGoogle Scholar
  10. Dillon RL, Tinsley CH (2008) How near-misses influence decision making under risk: a missed opportunity for learning. Manage Sci 54(8):1425–1440CrossRefGoogle Scholar
  11. Dillon RL, Tinsley CH, Cronin MA (2011) Why near-miss events can decrease an individual’s protective response to hurricanes. Risk Anal 31(3):440–449CrossRefGoogle Scholar
  12. Evans J (2010) Intuition and reasoning: a dual-process perspective. Psychol Inq 21:313–326CrossRefGoogle Scholar
  13. Fischhoff B (2012) Risk analysis and human behavior. Earthscan, LondonGoogle Scholar
  14. Gilovich T, Griffin D, Kahneman D (2002) Heuristics and biases: the psychology of intuitive judgment. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  15. Job RFS, Hamer V, Walker M (1995) The effects of optimism bias and fear on protective behaviours. In: Kenny DT, Job RFS (eds) Australia’s adolescents: a health psychology perspective. University of New England Press, Armidale, pp 151–156Google Scholar
  16. Judd CM, McClelland GH (1989) Data analysis: a model comparison approach. Harcourt Brace, New YorkGoogle Scholar
  17. Kellon DS, Árvai JL (2011) Five propositions for improving decision-making about the environment in developing communities: insights from the decision sciences. J Environ Manage 92:363–371CrossRefGoogle Scholar
  18. Krizan Z, Windschitl PD (2007) The influence of outcome desirability on optimism. Psychol Bull 133:95–121CrossRefGoogle Scholar
  19. Kunreuther H, Ginsberg R, Miller L, Sagi P, Slovic P, Borkan B, Katz N (1978) Disaster insurance protection: public policy lessons. Wiley, New YorkGoogle Scholar
  20. Lant TK (1992) Aspiration level adaptation: an empirical exploration. Manag Sci 38:623–644CrossRefGoogle Scholar
  21. Lee SHV, Job RFS (1995) The effect of information on optimism bias. In: Kenny DT, Job RFS (eds) Australia’s adolescents: a health psychology perspective. University of New England Press, Armidale, pp 157–163Google Scholar
  22. Lindell MK, Perry RW (2004) Communicating environmental risk in multiethnic communities. Sage, Thousand OaksGoogle Scholar
  23. March JG, Simon H (1958) Organizations. Wiley, New YorkGoogle Scholar
  24. McGee TK, McFarlane BL, Varghese J (2009) An examination of the influence of hazard experience on wildfire risk perceptions and adoption of mitigation measures. Soc Nat Resour 22:308–323CrossRefGoogle Scholar
  25. Middleton W (1996) Give em enough rope: perception of health and safety risks in bungee jumpers. J Soc Clin Psychol 15(1):68–79CrossRefGoogle Scholar
  26. Mileti DS, O’Brien PW (1992) Warnings during disaster: normalizing communicated risk. Soc Probl 39:40–57CrossRefGoogle Scholar
  27. Radcliffe NM, Klein WMP (2002) Dispositional, unrealistic, and comparative optimism: differential relations with the knowledge and processing of risk information and beliefs about personal risk. Pers Soc Psychol Bull 28(6):836–846CrossRefGoogle Scholar
  28. Rosoff H, Cui J, John RS (2013) Heuristics and biases in cyber security dilemmas. Environment Systems & Decisions 3(4):517–529CrossRefGoogle Scholar
  29. Ross M, Sicoly F (1979) Egocentric biases in availability and attribution. J Pers Soc Psychol 37:322–336CrossRefGoogle Scholar
  30. Scheier M, Carver C, Bridges M (1994) Distinguishing optimism from neuroticism (and trait anxiety, self-mastery, and self-esteem): a reevaluation of the life orientation test. J Pers Soc Psychol 67:1063–1078CrossRefGoogle Scholar
  31. Sitkin SB, Weingart LR (1995) Determinants of risky decision-making behavior: a test of the mediating role of risk perceptions and propensity. Acad Manag J 38(6):1573–1592CrossRefGoogle Scholar
  32. Slovic P (1995) The construction of preference. Am Psychol 50:364–371CrossRefGoogle Scholar
  33. Sobel ME (1982) Asymptotic confidence intervals for indirect effects in structural equation models. Sociol Methodol 13:290–312CrossRefGoogle Scholar
  34. Suls J, Rose JP, Windschitl PD, Smith AR (2013) Optimism following a tornado disaster. Pers Soc Psychol Bull 39(5):691–702CrossRefGoogle Scholar
  35. Tierney KJ, Lindell MT, Perry RW (2001) Facing the unexpected: disaster preparedness and response in the United States. Joseph Henry Press/National Academy Press, Washington, DCGoogle Scholar
  36. Tinsley CH, Dillon RL, Cronin MA (2012) How near-miss events amplify or attenuate risky decision making. Manage Sci 58(9):1596–1613CrossRefGoogle Scholar
  37. Tversky A, Kahneman D (1974) Judgment under uncertainty: heuristics and biases. Science 185:1124–1131CrossRefGoogle Scholar
  38. Weinstein ND (1989) Effects of personal experience on self-protective behavior. Psychol Bull 105(1):31–50CrossRefGoogle Scholar
  39. Wilson RS, Árvai JL (2010) Why less is more: exploring affect-based value neglect. J Risk Res 13:399–409CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.McDonough School of BusinessGeorgetown UniversityWashingtonUSA

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