Effectiveness of Innovation Ecosystems in the Hypermodern Era: Influence on Entrepreneurial Intelligence and the Creation of Sustainable Value
Bibliographic record
Abstract
In the era of hypermodernity, innovation ecosystems have emerged as a pivotal driver of corporate competitiveness and sustainability. These ecosystems integrate diverse stakeholders—businesses, universities, public institutions, incubators, and investors—with the overarching goal of fostering collaboration, facilitating knowledge exchange, and stimulating the emergence of groundbreaking ideas. The effectiveness of such ecosystems is fundamentally influenced by entrepreneurial intelligence, defined as the capacity to identify, mobilize, and capitalize on innovative opportunities. This intelligence serves as a key determinant in the generation of sustainable value, particularly in light of contemporary social and environmental imperatives. This study investigates the measurement of innovation ecosystem effectiveness, the factors that either enhance or constrain its performance, and its influence on entrepreneurial intelligence—particularly in its capacity to generate economic, social, and environmental value. To address these research questions, a survey was conducted among 300 entrepreneurs actively engaged in various innovation ecosystems. The findings, validated through advanced statistical analyses (factor analysis, mediation analysis, and multi-group analysis), underscore the role of specific ecosystem attributes—such as actor diversity, network density, institutional support, and enabling infrastructures—as critical enablers of entrepreneurial intelligence. Moreover, the study establishes that the link between ecosystem attributes and sustainable value creation is mediated by entrepreneurial intelligence. These conclusions suggest that aligning innovation ecosystems with sustainability imperatives should be a strategic priority for entrepreneurs, policymakers, and ecosystem managers, ensuring a long-term impact and fostering resilient, innovation-driven growth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".