Navigating Digital Disruption: Key Entrepreneurial Leadership Competencies for Community Enterprises – A Scoping Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the digital era, community enterprises face mounting pressure to integrate technology while maintaining their social and economic missions. Entrepreneurial leadership competencies (ELCs) are critical to navigating digital disruption and fostering sustainable development in these organizations. This study employs a scoping review methodology, guided by the PRISMA 2020 framework, to identify key ELCs required for community enterprises operating in digitally dynamic environments. A total of 16 peer-reviewed studies published between 2015 and 2025 were systematically selected from five major databases: Scopus, Web of Science, EBSCOhost, ProQuest, and Google Scholar. Five thematic clusters of ELCs emerged from the synthesis: (1) visionary and strategic orientation, (2) digital literacy and platform management, (3) innovation and adaptability, (4) risk management and cybersecurity awareness, and (5) community and stakeholder engagement. While these competencies offer a comprehensive framework for digital leadership, notable gaps remain in cybersecurity training and AI adoption. The findings inform both practice and policy by highlighting essential leadership capacities that enable community enterprises to thrive in the digital economy while remaining socially grounded. This review contributes to the literature by offering an integrated, evidence-based competency framework tailored to community enterprises in the context of digital transformation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it