When do firms learn by hiring? How complexity moderates the value of new knowledge
通过计算模型研究企业现有知识的内部和外部契合度如何影响其通过雇佣学习新知识的能力，发现内部契合度低的企业吸收新知识更快，且复杂环境下激进雇佣可能降低学习效果。
Abstract Research Summary Organizations often hire employees hoping to acquire new knowledge. While the literature has paid considerable attention to the role of the characteristics of the source of knowledge, the recipient firm, and the knowledge being transferred, it has largely overlooked those of the knowledge being replaced. Using a computational model, we examine how the pre‐existing knowledge of the hiring firm—specifically its degrees of internal and external fit—influences its ability to learn. Our findings suggest that firms with lower internal fit absorb new knowledge more quickly, even when controlling for initial external fit. We identify several mechanisms driving this dynamic, demonstrating how persistent resistance to new knowledge and sudden shifts can emerge solely through mutual learning dynamics between individuals and organizations, independent of social or cognitive constraints. Managerial Summary Companies frequently hire employees from competitors to gain new knowledge and improve performance. We show that success in learning by hiring depends not only on who firms hire but also on the characteristics of their existing knowledge. Our findings reveal two counterintuitive dynamics. First, firms whose practices exhibit a high degree of fit face greater difficulty in absorbing new knowledge. Such extant knowledge is stickier, as incumbent employees find it harder to abandon their old approaches and keep pulling the organization back to the status quo. Second, in complex environments, struggling firms that hire aggressively may learn less effectively, as multiple hires provide conflicting advice. Thus, while such firms stand to learn more from hiring, the internal dynamics of learning within the organization frustrate the firm's effort to absorb the knowledge. We subsequently present and analyze the mechanisms responsible for these outcomes.