Bibliographic record
Abstract
This chapter explores Porter's idea that the most important aspect of international business strategy is four key home country location advantages, often simply referred to as ‘Porter's diamond’. Porter's idea is that, ultimately, an MNE's long-term competitiveness results from vigorous domestic pressure in its home base, forcing it to innovate and improve productivity. This idea will be examined and then criticized using the framework presented in Chapter 1. Significance In the early 1990s, Michael Porter's now-classic HBR article, ‘The competitive advantage of nations’ (and the identically named book) created substantial debate on the sources of international competitiveness. Porter argues that any company's ability to compete in the international arena is based mainly on an interrelated set of location advantages in its home country. A high level of pressure in its home base pushes the firm to innovate and to upgrade systematically, resulting in FSA creation. These FSAs are then instrumental to expansion in foreign markets. According to Porter, ‘a nation's competitiveness depends on the capacity of its industry to innovate and upgrade. Companies gain advantage against the world's best competitors because of pressure and challenge. They benefit from having strong domestic rivals, aggressive home-based suppliers, and demanding local customers.’ According to Porter, FSAs are primarily developed not because firms have a strong, internal entrepreneurial drive, or because they can easily access external resources, but because they face external pressure.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".