A Dynamic Model of Individual and Collective Learning Amid Disruption

• 成果类型: Article
• 署名作者: Anderson, Edward G., Jr.; Lewis, Kyle
• 署名单位: University of Texas System; University of Texas Austin
• 刊物名称: ORGANIZATION SCIENCE
• ISSN/ISSBN: 1047-7039
• DOI: 10.1287/orsc.2013.0854
• 发表日期: 2014
• 页码: 356-376
• 关键词: organizational learning; organization change; computer simulations; Organizational behavior; system dynamics; learning curves; transactive memory systems

摘要

Using the methodology of system dynamics, we model the effects of disruptive events on learning and productivity in organizations. We leverage the learning-by-doing and transactive memory system theories to model the underpinnings of learning processes at the collective and individual levels. We simulate the impact of disruptive events on organizational productivity and performance, such as employee turnover, technological innovation, reorganization, and extreme events (such as natural disasters), which disrupt individual knowledge, collective knowledge, or both. Finally, we discuss implications of our findings for future research on organizational learning and productivity. One implication is that representing organizational learning by a single power-law learning curve or even by multiple noninteracting learning curves may be in many cases inadequate. Another is that disruptions to individual learning can be beneficial to organizations in the long run, whereas disruptions to collective learning are detrimental in the short and long run. We discuss the factors that might help organizations mitigate the negative effects of disruption so that learning can occur amid even the most disruptive events.