Configurational drivers of cross-unit R&D collaboration in large system-integrating enterprises: A qualitative comparative analysis

Effective cross-unit R&D collaboration is critical for system-level innovation in large system-integrating enterprises but remains difficult to achieve. Existing research has largely examined collaboration antecedents in isolation, offering limited insight into how collaboration emerges in complex multi-unit organizations. Drawing on the Motivation-Opportunity-Ability (MOA) framework, this study reconceptualizes cross-unit collaboration as a configurational outcome shaped by the interplay of motivational conditions (strategic cognition consensus and technical collaboration demand), opportunity conditions (institutional opportunity window and organizational slack), and ability conditions (boundary-spanning capability and digital collaboration capability). Using a mixed-method design—qualitative evidence from six enterprises followed by fsQCA of 38 organizational units (19 dyads)—we uncover four equifinal configurations associated with high collaboration performance and two associated with low performance. These findings reveal that effective collaboration arises from different alignments of motivational, opportunity-related, and ability-based conditions—strategic alignment, process-linked integration, hierarchical response, and cluster-based knowledge integration—rather than from a single set of antecedents. This study advances a configurational explanation of cross-unit R&D collaboration, extends the MOA framework to complex multi-unit settings, and offers practical insights into alternative coordination arrangements for system-level innovation.