Organizations interpret their environments by categorizing strategic issues as either opportunities or threats. They make such categorizations as inferences drawn from analogies from past experience. The accuracy of issue interpretations turns on: (1) which analogy is used, (2) what are the environment's properties, and (3) what is the timeframe? A computational model allows us to evaluate over time the accuracy of interpretations based on different forms of analogical reasoning in environments that differ in variation (unpredictability and dynamism) and complexity (dimensionality and ruggedness). This study elaborates a contingency approach to assessing analogical reasoning by organizations in which the form of analogical reasoning, environmental properties, and time all matter. Our findings indicate when particular forms of reasoning produce relatively more accurate inferences about opportunities and threats.
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