Researching Digital Entrepreneurship: Current Issues and Suggestions for Future Directions
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
This report documents the outcomes of a professional development workshop (PDW) held at the 40th International Conference on Information Systems in Munich, Germany. The workshop focused on identifying how information systems (IS) researchers can contribute to enriching our knowledge about digital entrepreneurship—that is, the point at which digital technologies and entrepreneurship intersect. The PDW assembled numerous IS researchers working on different aspects of digital entrepreneurship. Jointly, we delineated digital entrepreneurship from related phenomena and conceptualized the different roles that digital technologies can have in entrepreneurial endeavors. We also identified relevant strategies, opportunities, and challenges in conducting digital entrepreneurship research. This report summarizes the shared views that emerged from the interactions at the PDW and our collaborative effort to write this report. The report provides IS researchers interested in digital entrepreneurship with food for thought and a foundation for future research.
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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