Business models of nanotechnology companies and value creation
Bibliographic record
Abstract
The objective of the research is to identify the types of business models capable of creating value for the Canadian economy. Twenty-two founders of Canadian nanotechnology companies were interviewed. Subsequently, a statistical content analysis of the transcribed interviews was performed using Iramuteq software, followed by an interpretive analysis of the reports generated by the Iramuteq software. The results show that business models primarily based on opportunity identification do not promote value creation and capture by companies. We propose that for companies to effectively create and capture value, business models must (in addition to comprising opportunity identification activities) organize their activities in such a way that they generate virtuous circles and expansive spirals. Specifically, business models articulated in the form of an expansive spiral stimulate the economy through the multisectoral diffusion of nanotechnological products. The research results shed light on the processes and determinants of economic value creation in nanotechnology companies, enriching the model of leveraging enabling technologies proposed by Gambardella et al. (2021).
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".