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
Purpose To propose a conceptual framework that facilitates the benchmarking of strategic processes necessary for entrepreneurial survival and success. Design/methodology/approach Drawing on extant literature on entrepreneurial survival, this paper considers the chaotic and emergent nature of the entrepreneurial organization and how benchmarking can contribute to a newly established firm's chances for survival and prosperity. The paper incorporates the concept of a sustainable competitive advantage in the discussion, and offers organizational culture as being the imperfectly imitable element which will contribute to the entrepreneurial firm's success. Findings Four key processes are identified that contribute to entrepreneurial viability – cooperation, sharing founder's vision, time management, and developing organizational competencies – and suggestions are offered for developing appropriate benchmarks for these processes. The paper also highlights two instruments that may be useful in this endeavor. Research limitations/implications The paper draws attention to the usefulness of benchmarking processes and not just metrics in fostering entrepreneurial survival. Key processes are identified, and suggestions are provided for researchers to begin work on developing the necessary benchmarks. Practical implications The paper not only offers a theoretical discussion of the usefulness of benchmarking processes as opposed to focusing only on outcomes, but also helps the practitioner to implement such benchmarking activities by highlighting practical instruments for this purpose. Originality/value This paper brings to bear literature from several streams of research. It takes benchmarking from its metric‐oriented focus to a more process‐focused approach, and applies it in the context of entrepreneurial survival.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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