Unraveling how knowledge-driven corporate spin-offs achieve high growth: insights from a dual-actor knowledge interconnection perspective

Purpose This study aims to explore the multiple paths through which knowledge-driven corporate spin-offs (KDCSs) achieve high growth, with a particular focus on the causal complexity underlying different condition configurations. Design/methodology/approach Based on questionnaire data collected from middle- and senior-level managers, this study uses fuzzy-set qualitative comparative analysis (fsQCA) to identify multiple effective paths toward high growth. The research integrates qualitative insights with configurational analysis to capture the complexity of KDCSs’ growth mechanisms. Findings The results reveal four typical paths to high growth for KDCSs, namely, a knowledge exploitation and relational embeddedness path, a knowledge exploration and comprehensive embeddedness path, a knowledge exploration and identity Inheritance path and a knowledge dual-balance path. These four paths demonstrate equifinality and complementarity, reflecting the diverse strategic logics of KDCSs in their growth processes. Research limitations/implications This study offers several important research implications. First, by applying fsQCA to identify multiple equifinal configurations for the high growth of KDCSs, it highlights the causal complexity and path diversity in knowledge-driven entrepreneurship, contributing to the refinement of configurational thinking in innovation and entrepreneurship research. Second, the distinction between high-growth and low-growth configurations enriches the understanding of asymmetric causal mechanisms, suggesting that the absence of certain conditions (e.g. embeddedness in the parent network) can be equally critical as their presence. Finally, the findings underscore the importance of integrating knowledge resources, entrepreneurial identity and network embeddedness into a unified analytical framework, thereby advancing theoretical conversations on the growth of corporate spin-offs. Nevertheless, some limitations remain. First, fsQCA cannot fully capture the “strong process” mechanisms underlying firm growth, which future longitudinal case studies may address. Second, the cross-sectional data collection limits the ability to capture dynamic changes in growth trajectories. Third, as this study focuses on the Chinese context, future research could extend to cross-country comparisons to test the generalizability of the findings. Practical implications First, by applying fsQCA to identify multiple equifinal configurations for the high growth of KDCSs, it highlights the causal complexity and path diversity in knowledge-driven entrepreneurship, contributing to the refinement of configurational thinking in innovation and entrepreneurship research. Second, the distinction between high-growth and low-growth configurations enriches the understanding of asymmetric causal mechanisms, suggesting that the absence of certain conditions can be equally critical as their presence. Finally, the findings underscore the importance of integrating knowledge resources, entrepreneurial identity and network embeddedness into a unified analytical framework, thereby advancing theoretical conversations on the growth of corporate spin-offs. Originality/value This study makes three theoretical contributions. First, it enriches research on entrepreneurial spin-offs by introducing a configurational perspective to explain high growth in KDCSs. Second, it deepens understanding of how knowledge sources, venture identity and network embeddedness interact to shape growth outcomes. Third, it highlights the coexistence of multiple effective paths, thereby advancing the configurational theory of entrepreneurial growth.