Decision-Making: Inside the Mind of the Incident Commander

  • Pat TissingtonEmail author
  • Frank Watt


This chapter explores the decision-making of firefighters in greater detail. The relevance of Classical and Naturalistic Decision Theories of decision-making are critically reviewed to highlight the need for a more realistic model suitable for application in the Fire Service. Towards this goal, the current study first adopted a laddering method of knowledge elicitation to develop a set of example incidents that account for the diverse range of incidents attended. These incidents were then developed into a card-sort task to determine the relevance of time and risk (directed card-sort), and to determine other factors of relevance in decision-making (free-sort). Results suggested four dimensions of importance: crew safety, complexity of casualty rescue, time-pressure and containment. Encouraging a more explicit decision-making process, the way in which this model can act as a scaffold for learning during training activities is discussed.


  1. Adair, J. (1971). Training for decisions. Aldershot, UK: Gower.Google Scholar
  2. Adair, J. (1985). Effective decision-making. London: Pan.Google Scholar
  3. Alexander Ohlers, C. (2017). Operation inherent resolve and the Islamic state: assessing “aggressive containment”. Orbis, 61(2), 195–211.CrossRefGoogle Scholar
  4. Arbuthnot, K. (2002). Key issues in incident command. In R. Flin & K. Arbuthnot (Eds.), Incident command: Tales from the hot seat (pp. 10–31). Aldershot, UK: Ashgate.Google Scholar
  5. Barton, K. C. (2015). Elicitation techniques: Getting people to talk about ideas they don’t usually talk about. Theory & Research in Social Education, 43(2), 179–205.CrossRefGoogle Scholar
  6. Beach, L. R., & Lipshitz, R. (1993). Why classical decision theory is an inappropriate standard for evaluating and aiding most human decision making. In G. Klein, J. Orasanu, R. Calderwood, & C. Zsambok (Eds.), Decision making in action: Models and methods (pp. 21–35). Norwood, NJ: Ablex. Google Scholar
  7. Bechara, A., Damasio, H., Tranel, D., & Damasio, A. R. (2005). The Iowa gambling task and the somatic marker hypothesis: Some questions and answers. Trends in Cognitive Sciences, 9(4), 159–162.CrossRefGoogle Scholar
  8. Brunacini, A. V. (1985). Fire command. Quincy, MA: NFPA.Google Scholar
  9. Buja, A., Swayne, D. F., Littman, M. L., Dean, N., Hofmann, H., & Chen, L. (2008). Data visualization with multidimensional scaling. Journal of Computational and Graphical Statistics, 17(2), 444–472.CrossRefGoogle Scholar
  10. Cannon-Bowers, J. A., & Salas, E. (Eds.). (1998). Making decisions under stress. Washington, DC: APA.Google Scholar
  11. Canter, D., Brown, J., & Groat, L. (1985). A multiple sort procedure for studying conceptual systems. In M. Brenner, J. Brown, & D. Canter (Eds.), The research interview: Uses and approaches (pp. 79–114). London: Academic Press. Google Scholar
  12. Carroll, J. S., & Johnson, E. J. (1990). Decision research. London: Sage.Google Scholar
  13. Crichton, M. T., Flin, R., & McGeorge, P. (2005). Decision-making by on-scene incident commanders in nuclear emergencies. Cognition, Technology & Work, 7(3), 156–166.CrossRefGoogle Scholar
  14. Crichton, M. T., Flin, R., & Rattray, W. A. R. (2000). Training decision makers—Tactical decision games. Journal of Contingencies and Crisis Management, 8(4), 208–217.CrossRefGoogle Scholar
  15. Cullen, T. H. L. W. D. (1990). The public inquiry into the Piper Alpha disaster, presented to parliament by the secretary of state for energy by command of Her Majesty. London: HMSO. Google Scholar
  16. Dreyfus, H. L., Dreyfus, S. E., & Athanasiou, T. (1986). Mind over machine: The power of human intuition and expertise in the era of the computer. Oxford: Basil Blackwell.Google Scholar
  17. Drummond, I., Sheikh, G., Skinner, J., & Wood, M. (2016). Response to: Can gaming turn doctors into better tacticians? Medical Teacher, 39, 110–111. Google Scholar
  18. Endsley, M. R. (1995). Measurement of situation awareness in dynamic systems. Human Factors, 37(1), 65–84.CrossRefGoogle Scholar
  19. Fennell, D. (1988). Investigation into the King’s Cross underground fire.Google Scholar
  20. Fire and Rescue Services Act 2004. (2004).Google Scholar
  21. Fischer, U., Orasanu, J., & Wich, M. (1995, April). Expert pilots’ perception of problem situations. In Proceedings of the eighth international symposium on aviation psychology.Google Scholar
  22. Fitts, P. M. (1954). The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology, 47, 381–391.CrossRefGoogle Scholar
  23. Flin, R. H. (1997). Decision-making under stress: Emerging themes and applications. Aldershot: Ashgate.Google Scholar
  24. Flin, R., O’Connor, P., & Crichton, M. (2008). Safety at the sharp end: A guide to non-technical skills. Aldershot, UK: Ashgate Publishing.Google Scholar
  25. Grimwood, P. (1992). Fog attack: Firefighting strategy and tactics—An international view. Redhill, UK: FMJ Publications.Google Scholar
  26. Henrich, J., Heine, S. J., & Norenzayan, A. (2010). Most people are not WEIRD. Nature, 466, 29.CrossRefGoogle Scholar
  27. HM Fire Service Inspectorate. (1999). Fire service manual. Volume 2: Fire service operations. London: HMSO. Google Scholar
  28. Home Office. (1981). Manual of firemanship: Practical firemanship, Book 11. London: HMSO.Google Scholar
  29. Johnson-Laird, P. N. (1980). Mental models in cognitive science. Cognitive Science, 4(1), 71–115.CrossRefGoogle Scholar
  30. Kahneman, D. (2012). Thinking, fast and slow. London: Penguin.Google Scholar
  31. Kahneman, D., Slovic, P., & Tversky, A. (1982). Judgment under uncertainty: Heuristics and biases. Cambridge and New York: Cambridge University Press.Google Scholar
  32. Klein, G. (2000). How can we train pilots to make better decisions. In H. F. O’Neil Jr. & D. H. Andrews (Eds.), Aircrew training and assessment (pp. 165–195). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  33. Klein, G., Orasanu, J., Calderwood, R., & Zsambok, C. (1993). Decision-making in action: Models and methods. Westport, CT: Ablex Publishing.Google Scholar
  34. Kruskal, J. B., & Wish, M. (1978). Multidimensional scaling. Beverly Hills and London: Sage.Google Scholar
  35. McCann, C., & Pigeau, R. (Eds.). (2000). The human in command: Exploring the military experience. New York: Plenum.Google Scholar
  36. Moody, P. E. (1983). Decision making. New York: McGraw-Hill.Google Scholar
  37. Nisbett, R. E., & Ross, L. (1980). Human inference: Strategies and shortcomings of social judgement. Engelwood Cliffs, NJ: Prentice Hall.Google Scholar
  38. Olson, J. R., & Biolsi, K. J. (1991). Techniques for representing expert knowledge. In K. A. Ericsson & J. Smith (Eds.), Towards a general theory of expertise (pp. 240–285). Cambridge: Cambridge University Press.Google Scholar
  39. Omodei, M. M., & McLennan, J. (1994). Studying complex decision-making in natural settings: Using a head-mounted video camera to study competitive orienteering. Perceptual and Motor Skills, 79(3_Suppl.), 1411–1425.Google Scholar
  40. Orasanu, J., & Connolly, T. (1993). The reinvention of decision making. In G. Klein, J. Orasanu, R. Calderwood, & C. Zsambok (Eds.), Decision making in action: Models and methods (pp. 3–20). Norwood, NJ: Ablex.Google Scholar
  41. Orasanu, J., & Fischer, U. (1997). Finding decisions in natural environments: The view from the cockpit. In C. Zsambok & G. Klein (Eds.), Naturalistic decision making (pp. 343–357). Mahwah, NJ: Lawrence Erlbaum.Google Scholar
  42. Owen, C., Brooks, B., Curnin, S., & Bearman, C. (2018). Enhancing learning in emergency services organisational work. Australian Journal of Public Administration, 77, 715–728. Google Scholar
  43. Pearl, J. (1988). Probabilistic reasoning in intelligent systems. San Mateo, CA: Kauffman.Google Scholar
  44. Popplewell, O. (1985). Safety and control at sports grounds, interim report.Google Scholar
  45. Posadas, V. I., & Teknomo, K. (2016). Simulating police containment of a protest crowd. Simulation, 92(1), 77–89.CrossRefGoogle Scholar
  46. Rugg, G., & McGeorge, P. (1995). Laddering. Expert Systems, 12(4), 339–346.CrossRefGoogle Scholar
  47. Rugg, G., & McGeorge, P. (1997). The sorting techniques: A tutorial paper on card sorts, picture sorts and item sorts. Expert Systems, 14(2), 80–93.Google Scholar
  48. Seamster, T. L., Redding, R. E., & Kaempf, G. L. (1997). Applied cognitive task analysis in aviation. Avebury, UK: Ashgate.Google Scholar
  49. Simon, H. A. (1959). Theories of decision-making in economics and behavioral-science. American Economic Review, 49(3), 253–283.Google Scholar
  50. Skriver, J., & Flin, R. (1997). Emergency decision-making on offshore oil installations. In D. Harris (Ed.), Engineering psychology and cognitive ergonomics (Vol. 2). Aldershot, UK: Avebury.Google Scholar
  51. Smith-Jentsch, K. A., Cannon-Bowers, J. A., Tannenbaum, S. I., & Salas, E. (2008). Guided team self-correction: Impacts on team mental models, processes, and effectiveness. Small Group Research, 39(3), 303–327.CrossRefGoogle Scholar
  52. Sokol, D. K. (2013). “First do no harm” revisited. BMJ: British Medical Journal, 347, f6426. CrossRefGoogle Scholar
  53. Thunholm, P. (2005). Planning undertime-pressure: An attempt toward a prescriptive model of military tactical decision making. In H. Montgomery, R. Lipshitz, & B. Brehmer (Eds.), How experts make decisions. NJ: Lawrence Erlbaum.Google Scholar
  54. Tissington, P., & Flin, R. (2005). Assessing risk in dynamic situations: Lessons from fire service operations. Risk Management, 7(4), 43–51.Google Scholar
  55. Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty—Heuristics and biases. Science, 185(4157), 1124–1131.CrossRefGoogle Scholar
  56. Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211(4481), 453–458.CrossRefGoogle Scholar
  57. Vasilyeva, N., Gopnik, A., & Lombrozo, T. (2018). The development of structural thinking about social categories. Developmental Psychology, 54(9), 1735–1744.CrossRefGoogle Scholar
  58. Wright, G. (1984). Behavioural decision theory. Harmondsworth: Penguin.Google Scholar
  59. Yates, F. (1990). Judgement and decision making. Englewood Cliffs, NJ: Prentice Hall.Google Scholar
  60. Zsambok, C. (1997). Naturalistic decision-making: Where are we now? In C. Zsambok & G. Klein (Eds.), Naturalistic decision-making (pp. 3–16). Mahwah, NJ: LEA.Google Scholar

Copyright information

© The Author(s) 2019

Authors and Affiliations

  1. 1.University of WarwickCoventryUK
  2. 2.Birkbeck, University of LondonLondonUK

Personalised recommendations