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Purpose

This study aims to examine how absorptive capacity (ACAP) dynamically interacts with network synchronization to influence capabilities formation and internationalization commitment of emerging market multinational enterprises (EMNEs) operating within global value chains (GVCs). The authors address how knowledge absorption processes evolve throughout internationalization stages and the conditions under which they may become constraining during technological transitions.

Design/methodology/approach

The authors conducted a longitudinal case study of a Brazilian auto parts manufacturer spanning four strategic periods from 1960 to 2019. Primary data were collected through semi-structured interviews with managers, customers and former partners, complemented by secondary data from internal company archives and external sources. Validity was enhanced through triangulation and a validation workshop with key informants.

Findings

The study analysis reveals that ACAP initially enables new capabilities through a virtuous cycle of learning and commitment within GVC relationships, enhancing network synchronization. However, path-dependent ACAP development eventually leads to strategic lock-in that compromises network synchronization during technological transitions. Despite maintained formal commitment levels, the firm experienced decreasing alignment with the automotive industry’s shift toward electrification, suggesting an inverted U-shaped trajectory of international commitment effectiveness.

Originality/value

This study contributes to international business theory by introducing network synchronization as a mediating construct between ACAP and international commitment. The authors identify boundary conditions for ACAP effectiveness by showing how path dependencies can create strategic lock-in that constrains EMNEs’ adaptability within GVCs, even when formal network commitments remain high. These findings extend the Uppsala internationalization model by revealing non-linear commitment trajectories shaped by network co-evolution dynamics.

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