PurposeThe purpose of this paper is to clarify the concept of dynamic capabilities from the knowledge‐based perspective and investigate the mechanisms of dynamic capabilities on innovation performance in networked environments.Design/methodology/approachThis paper designed a seven‐point Likert questionnaire measuring the dynamic capabilities, innovation performance and network embeddedness and a sample of 218 Chinese manufacturing firms were surveyed. Structural equation modeling method was used to statistically test the theoretical hypothesis.FindingsSignificant relationships were found between dynamic capabilities and innovation performance and knowledge combination capability played a mediating role in this relationship. For the links between network embeddedness and dynamic capabilities, knowledge acquisition capability was affected mainly by relational embeddedness and the diversity of network and joint problem solving contributed much to knowledge combination capability.Research limitations/implicationsThis paper deepened the understanding on dynamic capabilities and the mechanism between network embeddedness, knowledge‐based dynamic capabilities and innovation performance. In the future, the construct of knowledge‐based dynamic capabilities calls for more examination and verification.Originality/valueDrawing on the literature of dynamic capabilities framework, knowledge‐based view and the network model, this study extends the literature of dynamic capabilities and its link with innovation performance in networked environments. Using survey data and structural equation modeling, this study offers rich evidence on the contribution of dynamic capabilities on innovation performance and the antecedents of dynamic capabilities.

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This paper investigates to what extent internal R&D efforts and different types of external knowledge sources jointly affect innovation performance of firms in emerging economies.Based on a survey about external knowledge sourcing activities of Chinese innovative firms, we categorize external knowledge sources into four groups: science-based partners; horizontal connections; value chain partners, and technology service providers. We find that both internal R&D activities and external knowledge sourcing have a positive effect on firms' innovation performance. Strong internal R&D capabilities also increase the effect of sourcing from value chain partners and horizontal connections, but we do not find support for complementarity between internal R&D and collaborations with universities and research labs. These findings jointly suggest that the mixture of different types of external knowledge partners in combination with internal R&D capabilities is crucial in understanding the role of open innovation in emerging economies.