Open Innovation Performance in SMEs: Strategic Insights from Patent Analytics

Abstract

Prior research has identified a positive relationship between open innovation collaboration and innovation performance. This paper asks whether this positive relationship reported in the literature is partially driven by measurement error, e.g., misclassifications of firms’ intra-group transfers of knowledge as interactions external to the firms. Using a unique, self-compiled secondary dataset of 21,898 patent families from 44 German small- and medium-sized enterprises with 9,902 entities, we show that open innovation collaboration’s impact on innovation performance becomes insignificant when measurement distinguishes between patents from collaborations by firms within and firms beyond the same corporate trees. Boundary conditions and robustness checks yield stable results when tested against 12 patent quality-based measures of innovation performance. Our contributions motivate to revisit the assessment of open innovation performance to prevent biased results and suboptimal decision-making in implementing innovation and subsequent commercialization strategies across firms’ boundaries. We further show that complementing open innovation theory with patent quality measures enriches analytical options and allows additional insights. This adds to the broader understanding of open innovation theory, in particular open innovation outcomes.