Dmytro Halynskyi

Type of the article: Research Article

The conversion of knowledge into organizational and market performance is a central challenge for innovation-driven economies. This study examines how innovation activity and its commercialization shape the entrepreneurial performance of knowledge ecosystems, using green and digital energy start-ups as an empirical context. The aim is to investigate the non-linear relationships among knowledge creation, knowledge commercialization, and start-up development, with particular attention to whether mismatches between innovation activity and market uptake generate diminishing returns or imitation-driven entrepreneurial dynamics. The analysis is based on a balanced panel of 37 countries over the period 2018–2023, comprising 222 country-year observations. The methodology applies TWFE with DK standard errors, complemented by quadratic specifications, turning-point analysis, and lagged models. The findings reveal an inverted U-shaped relationship between innovation commercialization and start-up activity, confirmed by negative, significant squared terms for sales of new-to-market and new-to-firm innovations in green start-ups (β₂ = −0.1588) and digital start-ups (β₂ = −0.1462), with turning points at 0.1428 and 0.0021, respectively. Funding dynamics demonstrate threshold effects: product innovation has a U-shaped relationship with early-stage digital funding (β₂ = 2.0630), while process innovation strengthens later-stage funding for green (β₂ = 1.8100) and digital start-ups (β₂ = 1.8434). The knowledge commercialization gap positively affects digital start-ups (β = 0.1111), suggesting that uncommercialized knowledge may stimulate market entry. Lagged results confirm temporal effects, with past innovation commercialization reducing digital start-up activity (β = −0.2483). Knowledge creation alone does not ensure performance growth; sustainable start-up development requires effective knowledge-to-market conversion.

Type of the article: Research Article

Abstract
Innovative marketing increasingly requires reliable market intelligence signals that reduce uncertainty, support product positioning, and guide venture financing in technology-intensive green and digital markets. This study aims to assess how patent-based technological signals shape innovative market development by predicting the formation and venture financing of green and digital energy start-ups, while also examining whether entrepreneurial market entry and funding stimulate subsequent patenting activity. The empirical analysis is based on a balanced panel of 146 countries for 2000–2023, combining IEA energy start-up and funding indicators with OECD patent data. The empirical strategy follows a sequential design: descriptive statistics and log1p transformations are used to characterize the data; Dumitrescu–Hurlin panel Granger causality tests provide the main evidence on predictive causality; and PVAR, multiple-testing corrections, PPML and TWFE models are used as complementary robustness and dynamic checks. The results show highly concentrated innovative market development: average green and digital energy start-up activity is around 7 per country-year, while the median is 0 for both indicators. The Dumitrescu–Hurlin tests reveal 69 significant relationships out of 120, with stronger evidence for patents predicting start-up formation and funding than for the reverse direction. These findings remain robust after Benjamini–Hochberg correction and after excluding numerically extreme statistics. TWFE results support the positive association between climate adaptation and ICT-mitigation patents, digital energy start-up formation and early-stage digital funding, while PVAR models provide only complementary dynamic evidence and are interpreted cautiously due to stability limitations in the main GMM specification. Country fixed effects indicate that Ukraine has a more favorable estimated structural position for digital energy start-up formation than Kazakhstan and Armenia.