活力
生成语法
动态能力
调解
生成模型
业务
新产品开发
控制重构
组织学习
产业组织
双灵巧性
知识管理
营销
计算机科学
社会学
人工智能
物理
量子力学
嵌入式系统
社会科学
作者
Yongjian Chen,Nicole Coviello,Chatura Ranaweera
摘要
Abstract How can firms shape their capacity to engage in major innovation when change is all around? Drawing on dynamic capability theory, we argue that a firm needs to be able to sense, seize, and transform network relationships for new product development (NPD). Referred to here as a “dynamic network capability,” this facilitates generative NPD learning, whereby the firm both (1) unlearns and (2) engages in exploratory new learning. In turn, we argue that generative NPD learning is strongly associated with a firm's capacity for major innovation. Our theorizing is supported by a study of 184 small‐ and medium‐sized, U.S. manufacturing firms. A moderated mediation analysis suggests that when external dynamism is high, generative NPD learning mediates the relationship between dynamic network capability and major innovation capacity. This indicates that the firm's ability to “relearn” is critical. This mediating effect is further strengthened when internal dynamism is also high. Our results provide empirical evidence that the higher‐order concept of a dynamic capability influences the reconfiguration of resources such as NPD knowledge. The findings also signal the combined influence of external (environmental) and internal (organizational) dynamism on this relationship.
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