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While intellectual property (IP) management is critical for innovation, specific knowledge and innovation patterns within it can obstruct commercialisation. This study explores how these patterns impede the path to market success for emerging innovations. We introduce a novel method to detect and recognise these patterns, offering insights into factors contributing to innovation system failure. Applying the Triple Helix Model, we leverage text mining, network analysis, and structural equation modelling within the Russian pharmaceutical industry. Our research reveals limitations in the triple helix model's ability to capture problematic innovation patterns. Notably, local-closed and local semi-closed innovation networks emerge as significant barriers to commercialisation, further exacerbated by foreign dominance. While strong actor synergy is crucial, it alone cannot guarantee competitive advantage. Factors like geographical distance, disciplinary silos, and limited external collaboration further hinder success. This study highlights the need for effective knowledge production and collaboration practices, alongside strong synergy, to achieve market-leading innovations. Recognising and addressing these patterns can inform policy decisions, ultimately fostering more robust innovation outcomes, advancing innovation system theory in the process.
Ibrahim Alnafrah (Fri,) studied this question.