Assessing Components of Judgments in an Operational Setting

The Effects of Time Pressure on Aviation Weather Forecasting
  • Cynthia M. Lusk


Aviation weather forecasting provides an excellent opportunity to study judgment and decision making under time pressure. Because the weather information supplied to air traffic controllers often determines traffic patterns, the timeliness of advisories can become critical. Significant weather activity increases demand on forecasters for rapid assimilation of information and rapid judgments. In addition, aviation forecasting represents an operational setting in which the only data available for analysis may be forecasts and outcomes. That is, in this setting, forecasters are working in “real time,” generating forecasts on the basis of dynamic information. In such a setting, it is inappropriate for researchers to intervene in order to introduce some type of experimental control. Yet it is just such situations that are the most representative and important regarding the effects of time pressure on judgment and decision making. Consequently, in such situations, statisticai decomposition of judgment and outcome data may be the best means of gaining insight into characteristics of performance affected by time pressure.


Time Pressure Discriminative Ability Task Characteristic Forecast Time High Time Pressure 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Ben Zur, M., & Breznitz, S. J. (1981). The effects of time pressure on risky choice behavior. Acta Psychoiogica, 47, 89–104.CrossRefGoogle Scholar
  2. Brehmer, B., & Joyce, C. R. B. (1988). Human judgment: The SJT view. Amsterdam: North Holl&.Google Scholar
  3. Hammond, K. R. (1988). Judgment & decision making in dynamic task. Information & Decision Technologies, 14, 3–14.Google Scholar
  4. Hammond, K. R., Hamm, R. M., Grassia, J., & Pearson, T. (1987). IEEE Transaction on systems, man, & cybernetics, SMS-17,753–770.Google Scholar
  5. Hammond, K. R., Stewart, T. R., Brehmer, B. & Steinmann, D. (1975). Social judgment theory. In M. F. Kaplan & Schwartz (Eds.), Human judgment & decision processes (pp. 271–312 ). New York: Academic Press.Google Scholar
  6. Harvey, L. O., Jr., Hammond, K. R., Lusk, C. M. & Mross, E. F. (1992). The application of signal detection theory to weather forecasting behavior. Monthly Weather Review, 120 (5), 863–883.CrossRefGoogle Scholar
  7. Mueller, C. K., Wilson, J. W., & Heckman, B. (1988). Evaluation of the TDWR aviation nowcasting experiment. In Preprints of the 3rd International Conference on the Aviation Weather System (pp. 212–216 ). Boston: American Meteorological Society.Google Scholar
  8. Payne, J. W., Bettman, J. R., & Johnson, J. J. (1988). Adaptive strategy selection in decision making. Journal of Experimental Psychology: Learning, Memory, & Cognition, 14, 534–552.Google Scholar
  9. Svenson, O., & Edl&, A. (1987). Changes of preferences under time pressure: Choices & judgments. Sc&inavian Journal of Psychology, 28, 322–330.CrossRefGoogle Scholar
  10. Yates, J. F. (1982). External correspondence: Decompositions of the mean probability score. Organizational Behavior & Human Performance, 30, 132–156.CrossRefGoogle Scholar
  11. Yates, J. F. (1990). Judgment & decision making. Englewood Cliffs, NJ: Prentice Hall.Google Scholar
  12. Yates, J. F., & Curley, S. P. (1985). Conditional distribution analyses of probabilistic forecasts. Journal of Forecasting, 4, 61–73.CrossRefGoogle Scholar
  13. Yates, J. F., McDaniel, L., & Brown, E. (1991). Probabilistic forecasts of stock prices & earnings: The hazards of nascent expertise. Organizational Behavior & Human Decision Processes, 49, 60–79.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1993

Authors and Affiliations

  • Cynthia M. Lusk
    • 1
  1. 1.Center for Research on Judgment and PolicyUniversity of ColoradoBoulderUSA

Personalised recommendations