Analogical reasoning for diagnosing strategic issues in dynamic and complex environments

• 成果类型: Article
• 署名作者: Miller, Kent D.; Lin, Shu-Jou
• 署名单位: Michigan State University; Michigan State University's Broad College of Business; National Taiwan Normal University
• 刊物名称: STRATEGIC MANAGEMENT JOURNAL
• ISSN/ISSBN: 0143-2095
• DOI: 10.1002/smj.2335
• 发表日期: 2015
• 页码: 2000-2020
• 关键词: analogy; computational model; environmental complexity; organizational decision making; strategic issue diagnosis

摘要

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. Copyright (c) 2014 John Wiley & Sons, Ltd.