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Abstract In this study, we conduct a panoramic analysis of two decades of open innovation (OI), leveraging topic modeling with machine learning to map out ten critical OI pathways and their associated failure mechanisms on the micro, meso, and macro levels. Open innovation has revolutionized organizational innovation, collaboration, and competition. However, it presents complexities that require a multifaceted approach to research. Our findings, informed by interpretative thematic analysis, reveal distinct scholarly debates and three primary controversies within the OI research landscape, pointing to the need for future research to integrate these diverse narratives. By providing a comprehensive synthesis of the OI field’s evolution and current state, along with an analysis of its underlying failure mechanisms, we aim to guide strategic decision-making in OI practice, and enrich the academic discourse on its operational and strategic dimensions. Finally, we highlight several potential avenues for future research that emerge from our synthesis of the literature.
Mahdad et al. (Sat,) studied this question.