Abstract: Modern high-tech enterprises are simultaneously embedded in various types of networks, yet there is limited research analyzing how these networks coevolve. This paper adopts a dual network embedding perspective and utilizes data from 29,145 shareholders and 35,597 directors of 338 listed public companies in the Chinese biotechnology industry from 2009 to 2021 to construct shareholder relationship networks and interlocking directorate networks. Employing social network analysis and Temporal Exponential Random Graph Model (TERGM), the paper investigates the evolutionary paths of organizational dual network embedding. The findings indicate that during the evolution of the shareholder relationship network, the internal structure becomes increasingly compact, exhibiting small-world characteristics, while the interlocking directorate network demonstrates relatively fewer internal connections, resulting in an overall sparse structure. Both networks' evolutions exhibit significant spatial homogeneity characteristics. Moreover, the establishment of relationships in the shareholder relationship network demonstrates ownership heterogeneity, indicating a higher probability of connection between state-owned and non-state-owned enterprises. The dual network embedding process demonstrates a cross-network Matthew effect, where enterprises with a greater number of connections in one network are more likely to establish new connections in the other network. By adopting a dual network embedding perspective, this study moves beyond the confines of single-network view, reflecting the practical embedding of high-tech enterprises in different networks. It examines the endogenous formation mechanisms of the shareholder relationship network and the interlocking directorate network, offering a clear depiction of the evolutionary trajectory of dual networks.