Article #27
1998
 
 
 
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Learning and performance in interactive dynamic decision tasks

Bud Gibson
Ann Arbor, Michigan

My research focuses on understanding factors that affect learning and performance in interactive dynamic decision tasks such as telephone based credit collections or stock trading. The work is multidisciplinary. I use computational modeling and lab experiments to build and test theories about learning. Field studies provide an opportunity to ground these two activities. This Fall I plan to begin developing experiments around a simulated credit collections task which I want to use to study the effect of fear appeals on interactive decision making.

Two recent papers provide a more in-depth review of the work, recent results, and implications for decision making which I believe may be of interest to members of the Brunswik Society. I have included the abstracts as part of this research summary. Interested parties should feel free to contact me directly (fpgibson@umich.edu) if they would like copies once the papers are ready for wider release. The first paper is:

Learning in Dynamic Tasks with Feedback Delays

Decision makers in dynamic environments (e.g., stock trading, inventory control, and firefighting) learn poorly in experiments where feedback about the outcomes of their actions is delayed. In an effort to generate ways to mitigate these effects, this paper presents two computational models of learning with feedback delays and contrasts them against human decision makers' performance. The no-memory model hypothesizes that decision makers always perceive feedback as immediate. The with-memory model hypothesizes that, over time, decision makers are able to develop internal representations of the task that help them to perform with delayed feedback. As borne out by human subjects, both models predict that a representation of past history improves learning with delay and that increasing delay increasingly degrades performance. Even though the length of training in this task exceeds that used in many laboratory-based dynamic tasks, neither the two models nor the subjects are able to effectively learn without decision aids when faced with feedback delays. When given an amount of training that may more closely approximate that provided in functioning dynamic environments such as telephone-based credit collections, the with-memory model predicts that human decision makers may learn without decision aids over the long-term when feedback delays are simple. These results raise several issues for continued theoretical investigation as well as potential suggestions for training and supporting decision makers in dynamic environments with feedback delays.

The second paper is:

Fear appeals: What happens when the credit collector calls?

When fear appeals are used to gain compliance, the target is asked to do something for which he or she has disincentive in order to avoid a worse consequence. Much emphasis has been placed on how the emotional and information content of messages concerning these consequences might be manipulated in order to raise the rate of compliance. We examined 192 contacts between credit collectors and debtors to understand the effectiveness of fear appeals in a functioning organization. Surprisingly, messages concerning the consequences of non-compliance have inconsistent or insignificant effects. Our results suggest that collectors are most effective with delinquent debtors when they focus on the specifics of what is required for compliance. This task focus during the interaction shows debtors a clear way to either minimize their negative emotion or, alternatively, to grapple with the dangers the fear appeal alerts them to. This result may have broader application in sales and other interactive boundary-spanning work roles where emotional displays have been considered important to effective performance.

Contact Bud Gibson

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