An exploratory study of Canadian international new venture firms' development in overseas markets
Bibliographic record
Abstract
Purpose In the past decade, research on rapidly internationalizing firms, commonly referred to as “international new ventures” (INVs), has mainly focused on their inception phase and relatively little is known of what becomes of these firms after this period in respect of their international marketing strategies. The purpose of this paper is therefore to gain insights into how management teams within small INVs assess international opportunities and develop appropriate international marketing strategies. Design/methodology/approach The approach employed involves interviews with key respondents in five small, independently owned firms that have a significant percentage of turnover overseas. Findings The paper identifies that specific types of knowledge are related to growth strategies as are perceptions of market potential and the management team's vision. Practical implications The results of this study provide further understanding of patterns of internationalization and more specifically that foreign market knowledge can be acquired in various ways and allows firms to become more highly committed to some remote markets much earlier than previously anticipated. This understanding could help policy‐makers to provide more targeted and relevant support to INVs. Originality/value Both planned and unplanned activities are evident in the research suggesting international marketing growth is not as strategically planned as a good deal of earlier research suggests.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".