LAUSR

Dynamic capabilities are crucial to the survival and development of enterprises in the BOP (Base/Bottom of the Pyramid, hereinafter BOP) market. The research focuses on the double-edged sword impact of relational embeddedness on dynamic capabilities via ambidextrous learning, that is moderate embeddedness facilitates dynamic capabilities while overembeddedness inhibits them. Furthermore, this study investigates whether human capital moderates the relationships between relational embeddedness and ambidextrous learning. Selecting 264 samples for empirical research, firstly, the results show that the relational embeddedness in the BOP cooperation network has an inverted U-shaped influence on ambidextrous learning and dynamic capabilities. Secondly, exploratory learning and exploitative learning play a mediating role in relational embeddedness and dynamic capabilities. Thirdly, prior experience plays a positive moderating role in relational embeddedness and exploitative learning. The conclusions facilitate understanding the antecedents of dynamic capabilities and the black box of “embeddedness paradox,” and provide empirical evidence for adjusting the human capital of enterprises, enhancing the exploratory learning capability and exploitative learning capability, and coping with the overembeddedness effects.