Inconsistencies in International Product Strategies and Performance of High-Tech Firms
Bibliographic record
Abstract
This article explores two unresolved issues in the international business literature. First, it is not clear why high-tech firms should standardize their product strategies across countries. Second, the rationale for high-tech firms to forge international strategic alliances (ISAs) is unknown. Drawing on organizational ecology and structural inertia theories, this study proposes that the interactions between a firm's structural inertia and environmental hostility are hazardous to firm performance and that ISAs weaken their impacts. Using data from 167 Canadian high-tech firms, this study supports that hypothesis and uncovers important implications for research and practice. Firms’ structural inertia makes inconsistency in international product strategies destructive. When structural inertia interacts with the environmental hostility associated with high-tech industries, the impacts can be stronger. High-tech firms resort to ISAs, using their partners to implement different product strategies to avoid adverse outcomes. Thus, ISAs are mechanisms that high-tech firms use to reduce the strategy inconsistencies across countries.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".