Technology oriented, service intensive, transnational entrepreneurs' international target market strategies
Bibliographic record
Abstract
This instrumental case study's objective is to understand the target market strategies of technology oriented, service intensive, transnational entrepreneurs (TEs). Existing studies featuring the merits of ‘concentration versus spreading’ target market strategies provide mixed findings, typically involving firms with product oriented as opposed to service intensive business models. Furthermore, prior research focuses on export-oriented owner-managers as opposed to TEs who have capabilities associated with being socially embedded across different countries. Interview data features the practices of 15 TEs, whose businesses involved information and knowledge-based solutions. Specifically, first generation UK-based South Asian immigrant entrepreneurs who are socially embedded in both their country of origin and country of settlement. Unique insights contribute to a microfoundational cultural perspective of business-to-business (B2B) practices, regarding a new generation of TEs, being relatively highly educated, experienced, and technologically oriented. New evidence builds on dated prior studies often featuring lower skilled and less experienced immigrant entrepreneurs in low-tech, service-oriented sectors. The choice of TEs' target market strategy is not necessarily binary in nature, whereby the importance of decision-makers possessing the ability to pivot strategies is evidenced. To varying degrees, certain TEs employ an ambidextrous approach, concentrating on key markets and entering/exiting others perceived as peripheral.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".