Population analysis of organizational innovation and learning
本文提出从人口层面分析组织创新与学习，填补理论与实证空白，基于9年地方政府数据发现学习在人口中分布不均，出现两个子群体，且创新学习策略随时间变化。
Abstract This article argues for a population level of analysis, addressing a theoretical and empirical gap and enabling the analysis of transition, tempo, and timing at the macro level. The article examines four theories of population‐level innovation: population ecology, neo‐institutional theory, innovation diffusion, and population‐level learning theory. A population‐level empirical study of innovation and organizational learning addresses three research questions: the first and second examine patterns of innovation underpinned by learning over space and over time. The third concerns the processes and dynamics of those patterns. The data derive from the local government using mixed methods and multiple respondents over 9 years. The research shows the uneven spread of learning across the population, with the emergence of two subpopulations. Over time, innovation and learning strategies shifted. Learning in the population occurred through both direct interaction and vicarious learning from others in the population. Implications for population‐level theory, innovation, and learning are explored.