LEAN AND GLOBAL TECHNOLOGY START-UPS: LINKING THE TWO RESEARCH STREAMS
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 this paper, the authors introduce the concept of the lean global start-up (LGS) as a way of emphasising the problems for new technology start-ups when dealing separately with business development, innovation and early internationalisation. The paper has two components — an introductory conceptual part and an empirical part that should be considered as basis for the preliminary validation of the conceptual insights. The research sample includes six firms — three from Canada and three from Denmark. Two different early internationalisation paths have been identified: Lean-to-global (L2G start-ups) and lean-and-global (L&G start-ups). Both types of start-ups were found to have faced significant problems with the complexity, uncertainties and risks of being innovative on a global scale. They have however found ways of addressing these problems by a disciplined knowledge sharing and IP protection strategy and the efficient use of business and supporting and public funding mechanisms. The Danish firms have pivoted around the ways of delivering their value proposition and not around the specific value propositions themselves. The Canadian firms have actively pivoted their value proposition motivated by the degree of innovativeness of their products and the insights from business supporting organisations. The analysis of the results justifies the introduction of the LGS concept and opens the opportunity for future research focusing on the articulation of more practical LGS entrepreneurial frameworks.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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