Coevolution of post-merger integration and dual knowledge networks reconstruction: evidence from Chinese overseas acquisitions

Abstract

PurposePost-merger integration (PMI) is driven by coevolving processes. By integrating the literature on acquisitions with that of knowledge networks, this paper highlights different reconstruction mechanisms for dual knowledge networks during PMI – namely, internal knowledge network coupling and external knowledge network embeddedness. This paper aims to examine their coevolutionary relationships with PMI.Design/methodology/approachA coevolutionary framework is tested using a latent growth model and cross-lagged models. The analysis is based on longitudinal data collected from 116 Chinese technology-sourcing overseas merger and acquisition firms.FindingsThis paper unearths a novel idea that variations in post-merger reconstruction of dual knowledge networks can explain why some acquirers increase the degree of integration faster than the others. The results show that the internal knowledge network coupling leads to more knowledge similarity and, in turn, causes a higher degree of integration. The external knowledge network embeddedness also causes higher relative network status of the acquirer, which consequently leads to a higher degree of integration. Furthermore, results from cross-lagged models confirm that an increase in the degree of integration positively influences subsequent changes in the internal knowledge network coupling and external knowledge network embeddedness, thus forming a coevolutionary relationship over time.Originality/valueThis paper responds to recent calls for more insights into the dynamics of PMI. By highlighting different reconstruction mechanisms for internal and external knowledge networks during PMI, this paper explains why it is important to understand PMI dynamics from a dual knowledge network perspective. This paper is the first to adopt a coevolutionary perspective and provide a more comprehensive dynamic framework between PMI and reconstruction of dual knowledge networks. Besides, this paper contributes to the research on emerging market multinational corporations’ cross-border merger and acquisition integration from a dynamic perspective, revealing the time effects of traditionally favored light-touch integration.