close
Skip to main content
Log in

Abstract

This article describes the Sugar Production Factor and its structural equivalent, the Personal Interaction task. These are two simple, individual dynamic decision-making tasks in which subjects make interdependent decisions to reach a goal, and receive feedback on the outcome of their efforts along the way. An important result from human learning experiments using these two tasks and their variants is that subjects reliably improve their ability to reach the goal over a moderate number of training trials (40–90) but do not show consistent improvement in other measures of task knowledge. These other measures focus on subjects' ability to accurately predict the task environment's response to their actions and subjects' ability to produce useful heuristics. This pattern of results runs counter to the idea that decision makers' performance in dynamic decision tasks depends critically on the predictive accuracy their internal models of the task environment. Variants of both tasks have been used to manipulate this pattern of results and explore more deeply the nature of the internal models that subjects form of the task environment. These variants are discussed in the context of other relevant findings in the dynamic decision making literature.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+
from $39.99 /Month
  • Starting from 10 chapters or articles per month
  • Access and download chapters and articles from more than 300k books and 2,500 journals
  • Cancel anytime
View plans

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • BartoA.G., BradtkeS.J., and SinghS.P. (1995), “Learning to act using real-time dynamic programming,”Artificial Intelligence, 72, pp. 81–138.

    Google Scholar 

  • BartoA.G., SuttonR.S., and C.J.C.H.Watkins (1989), “Learning and sequential decision making,” (Technical Report COINS 89–95), Amherst: University of Massachusetts.

    Google Scholar 

  • BerryD.C. (1991), “The role of action in implicit learning,”Quarterly Journal of Experimental Psychology, 43 A(4), pp. 881–906.

    Google Scholar 

  • BerryD.C., and BroadbentD.E. (1984), “On the relationship between task performance and associated verbalizable knowledge,”Quarterly Journal of Experimental Psychology, 36A, pp. 209–231.

    Google Scholar 

  • BerryD.C., and BroadbentD.E. (1987), “The combination of explicit and implicit learning processes in task control,”Psychological Research, 49, pp. 7–15.

    Google Scholar 

  • BerryD.C., and BroadbentD.E. (1988), “Interactive tasks and the implicit-explicit distinction,”British Journal of Psychology, 79, 251–272.

    Google Scholar 

  • Berry, D.C. and Dienes, Z. (1993),Implicit Learning: Theoretical and Empirical Issues. Lawrence Erlbaum Associates.

  • BrehmerB. (1990), “Strategies in real-time, dynamic decision making. In R.Hogarth (Ed.),Insights from Decision Making. Chicago: University of Chicago Press.

    Google Scholar 

  • BrehmerB. (1992), “Dynamic decision making: Human control of complex systems,”Acta Psychologica, 81, pp. 211–241.

    Google Scholar 

  • BrehmerB. (1995), “Feedback delays in complex dynamic decision tasks,” In P.Frensch, and J.Funke (Eds.),Complex Problem Solving: The European Perspective. Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • BuchnerA., FunkeJ., and BerryD.C. (1995), “Negative correlations between control performance and verbalizeable knowledge: Indicators for implicit learning in process control tasks,”Quarterly Journal of Experimental Psychology, 48 A(1), pp. 166–187.

    Google Scholar 

  • DavisF.D., and KottemanJ.E. (1995), “Determinants of decision rule use in a production planning task,”Organizational Behavior and Human Decision Processes, 64(2), pp. 145–157.

    Google Scholar 

  • DiehlE., and StermanJ.D. (1995), “Effects of feedback complexity on dynamic decision making,”Organizational Behavior and Human Decision Processes, 62(2), pp. 198–215.

    Google Scholar 

  • Dienes, Z. (1990),Implicit Concept Formation. Ph.D. thesis, University of Oxford.

  • Dienes, Z., and Fahey, R. (1994),The Role of Implicit Memory in Controlling Dynamic System. Unpublished manuscript.

  • DienesZ., and FaheyR. (1995), “Role of specific instances in controlling a dynamic system,”Journal of Experimental Psychology: Learning, Memory, and Cognition, 21 (4), pp 1–15.

    Google Scholar 

  • EdwardsW. (1962), “Dynamic decision theory and probabilistic information processing,”Human Factors, 4, pp. 59–73.

    Google Scholar 

  • FunkeJ. (1992), “Dealing with dynamic systems: Research strategy, diagnostic approach, and experimental results,”The German Journal of Psychology, 16(1), pp. 24–43.

    Google Scholar 

  • GibsonF.P., and PlautD.C. (1995), “A connectionist formulation of learning in dynamic decision-making tasks,”Proceedings of the 17th Annual Conference of the Cognitive Science Society (pp. 512–517). Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • HayesN.A., and BroadbentD.E. (1988), “Two modes of learning for interactive tasks,”Cognition, 28(28), pp. 249–276.

    Google Scholar 

  • HogarthR.M. (1981), “Beyond discrete biases: Functional and dysfunctional aspects of judgmental heuristics,”Psychological Bulletin, 90, pp. 197–217.

    Google Scholar 

  • KleinmuntzD.N. (1993), “Information processing and misperceptions of the implications of feedback in dynamic decision making,”System Dynamics Review, 9(3), pp. 223–237.

    Google Scholar 

  • KleinmuntzD.N., and ThomasJ.B. (1987), “The value of action and inference in dynamic decision making,”Organizational Behavior and Human Decision Processes, 39, pp. 341–364.

    Google Scholar 

  • LeeF.J., AndersonJ.R., and MatessaM.P. (1995), “Components of dynamic skill acquisition,”Proceedings of the 17th Annual Conference of the Cognitive Science Society, (pp. 506–511). Hillsdale, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • MarescauxP.-J., LucF., and KarnasG. (1989), “Modes d'apprentissage selective et non-selective et connaissances acquises au controle d'un processus: Évaluation d'un mod eme simulé,”Cahiers de Psychologie Cognitive Europénne, 9, pp. 239–264.

    Google Scholar 

  • McGeorgeP. and BurtonA.M. (1989), “The effect of concurrent verbalization on performance in a dynamic systems task,”British Journal of Psychology, 80, pp. 455–465.

    Google Scholar 

  • PaichM. and StermanJ.D. (1993), “Boom, bust, and failures to learn in experimental markets,”Management Science, 39(12), pp. 1439–1458.

    Google Scholar 

  • RapoportA., (1975) “Research paradigms for studying dynamic decision behavior,” In D.Wendt and C.Vlek (Eds.),Utility, Probability, and Human Decision Making. Dordrecht-Holland: D. Reidel Publishing Company.

    Google Scholar 

  • RichardsonG.P. and RohrbaughJ. (1990), “Decision making in dynamic environments: Exploring judgments in a system dynamics model-based game,” In K.Borcherding, O.I.Larichev and D.M.Messick (Eds.),Contemporary Issues in Decision Making, (pp. 463–472). North-Holland: Elsevier Science Publishers B.V.

    Google Scholar 

  • SandersonP.M. (1990),Implicit and Explicit Control of a Dynamic Task: Empirical and Conceptual Issues (Technical Report EPRL-90–02). Urbana, IL 61801: Department of Mechanical and Industrial Engineering, University of Illinois at Urbana-Champaign.

    Google Scholar 

  • SenguptaK. and Abdel-HamidT.K. (1993), “Alternative conceptions of feedback in dynamic decision environments: An experimental investigation,”Management Science, 39(4), 411–428.

    Google Scholar 

  • SquireL.R. and FrambachM. (1990), “Cognitive learning in amnesia,”Psychobiology, 18(1), 109–117.

    Google Scholar 

  • StanleyW.B., MathewsR.C., BussR.R., and Kotler-CopeS. (1989), “Insight without awareness: On the interaction of verbalization, instruction, and practice in a simulated process control task,”Quarterly Journal of Experimental Psychology, 41A(3), pp. 553–577.

    Google Scholar 

  • StermanJ.D. (1989a), “Misperceptions of feedback in dynamic decision making,”Organizational Behavior and Human Decision Processes, 43, pp. 301–335.

    Google Scholar 

  • StermanJ.D. (1989b), “Modeling managerial behavior: Misperceptions of feedback in a dynamic decision making experiment,”Management Science, 35(3), pp. 321–339.

    Google Scholar 

  • Te'eniD. (1991), “Feedback in DSS as a source of control: Experiments with the timing of feedback,”Decision Sciences, 22, pp. 644–655.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gibson, F.P. The sugar production factory—A dynamic decision task. Comput Math Organiz Theor 2, 49–60 (1996). https://doi.org/10.1007/BF00125763

Download citation

  • Issue date:

  • DOI: https://doi.org/10.1007/BF00125763

Key words