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While small and medium-sized enterprises (SMEs) are widely recognized as agile drivers of innovation, assessing their impact on future innovation trajectories is hampered by a critical lack of timely data, as official statistics often suffer from lags of 1–2 years. This study bridges this gap by introducing a novel framework designed to capture regional asymmetries in the SME innovation contribution to regional development using near real-time data. We propose an integrated indicator system structured around direct innovation output, indirect engagement, and institutional enablers. The implementation of our approach is based on the development of a data extraction and processing pipeline that automatically collects and systematizes monthly, regionally disaggregated data from Russia’s Unified SME Registry. This pipeline enables the continuous generation of relevant statistics on SMEs in innovation-intensive activities. Applying this framework across 85 Russian regions revealed significant asymmetries and key findings: broad regional support measures (e.g., general tax incentives) effectively increase the overall number of SMEs but weakly increase the growth of innovative SMEs specifically. The results provide a foundation for designing timely, evidence-based policy interventions to cultivate innovation-driven entrepreneurial ecosystems. This approach equips policymakers with a dynamic tool to shape future economic landscapes, enhancing regional resilience and advancing progress toward Sustainable Development Goals, particularly SDG 9 (Industry, Innovation, and Infrastructure).
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Rishko et al. (2026) studied this question.
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