Publication | Open Access
Effects of feedback delay on learning
92
Citations
58
References
2009
Year
Educational PsychologyEducationCognitionManagementFeedback DelayAdaptive LearningDecision TheoryHuman LearningLearning ProblemHeuristics (Combinatorial Optimization)Long TermCognitive ScienceLearning SciencesLearning AnalyticsSequential Decision MakingStrategic ManagementOperations ManagementHeuristics (Behavioral Economics)Real-time Decision-makingUnderstanding Firm PerformanceLearning TheoryBusinessTime DelaysDecision Science
Barriers to organizational learning, such as time delays, are central to firm performance and affect tradeoffs between long‑term and short‑term outcomes. The study investigates how time delays between actions and outcomes impede learning and proposes heuristics applicable to various problems involving such delays. Four learning heuristics of varying complexity and rationality were built and their performance analyzed in a simple resource allocation task. All heuristics converge to the optimal solution when delays are short or correctly assessed, but learning is significantly slowed or fails when decision makers misestimate delay length, and results are robust to the organization’s rationality level. © 2009 John Wiley & Sons, Ltd.
Abstract Understanding barriers to organizational learning is central to understanding firm performance. We investigate the role of time delays between taking an action and observing the results in impeding learning. These delays, ubiquitous in real‐world settings, are relevant to tradeoffs between long term and short term. We build four learning heuristics, with different levels of complexity and rationality, and analyze their performance in a simple resource allocation task. All reliably converge to the optimal solution when there are no/short delays, and when those delays are correctly assessed. However, learning is slowed significantly when decision makers err in assessing the length of the delay. In many cases, the decision maker never finds the optimal solution, wandering in the action space or converging to a suboptimal allocation. Results are robust to the organization's level of rationality. The proposed heuristics can be applied to a range of problems for modeling learning from experience in the presence of delays. Copyright © 2009 John Wiley & Sons, Ltd.
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