Foreign Direct Investment and the Flying Geese Model: Japanese Electronics Firms in Asia-Pacific
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper is a critical examination of the ‘flying geese’ and ‘billiard ball’ models of foreign direct investment (FDI) and their ability to explain the spatial expansion of Japanese electronics multinationals (MNCs) in Asia-Pacific countries from 1985 to 1996. Data on Japanese FDI are analyzed in this region at the aggregate, sectoral, and firm level. The paper commences with a review of the flying geese model, especially that version which interprets Japanese FDI as a catalyst for Asian development, and the billiard ball metaphor which suggests a mechanism for host countries to ‘catch up’ with Japan. The authors then turn to an analysis of Japanese FDI in Asia-Pacific together with employment data for fourteen major firms. This allows an evaluation of the two models in terms of recent geographical patterns of investment and employment growth by electronics MNCs. A special case study of Matsushita Electric Industrial Co. Ltd (MEI) helps flesh out the evolving geography of Japanese electronics firms in Asia-Pacific. Although the results support the overall patterns suggested by the two models, the authors argue that metaphors and analogies such as flying geese and billiard balls should not be used casually and as a substitute for analysis.
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.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it