Bibliographic record
Abstract
This paper outlines a rational for assessing the rate of global market expansion by entrepreneurial firms. Many entrepreneurial firms are dependent for their success on global market expansion. This is especially true about firms from relatively small countries. One can conceive of two major and opposing strategies for market expansion: market diversification and market concentration. The first strategy implies a fast penetration into a large number of markets in order to achieve fast growth and a first mover advantage. The second strategy is based on concentration of resources in a few markets and gradual expansion into new territories in order to test the response before committing too much effort. The paper is updating prior work on market expansion, taking into account entrepreneurial firms in the digital age. Firms with digital products don’t have to depend on foreign distribution networks and they have new opportunities for fast entry into foreign markets. We propose a concise framework for determining the preferred rate of market expansion utilizing two key variables: the potential response function of customers and the complexity of the product. The paper include a discussion of ways to assess customers’ response to entrepreneurial innovation and additional factors that can influence the market expansion decision.
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.
How this classification was reachedexpand
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".