Foreign Subsidiary Exit from Africa: The Effects of Investment Purpose Diversity and Orientation
Bibliographic record
Abstract
Research Summary This study considers the exit likelihood of foreign subsidiaries operating in Africa and identifies strategic orientations that can improve their chances of survival. We find that, on average, subsidiaries entering the African market have a greater exit likelihood than those entering the OECD market. However, those subsidiaries entering the African market with diverse investment purposes or greater market‐seeking orientation are less likely to exit, as they tend to enjoy flexibility, adaptability, and learning advantages useful in mitigating economic challenges and/or tapping into strategic opportunities. Managerial summary This study examines how the decision to enter African markets relates to the exit probability of MNE subsidiaries. Using a longitudinal, paired‐sample design of Japanese foreign subsidiaries operating in Africa and OECD countries, we find that entry to Africa increases the hazard rate of subsidiaries, but that subsidiaries entering with more diverse investment purposes and greater market‐seeking orientation have a better survival likelihood. Consistent with the institutional‐based theory of corporate diversification, our findings introduce purpose diversity and market‐seeking orientation as potential mechanisms to mitigate the hazards of institutional voids/instability. Also, by looking at the phenomenon of within‐subsidiary diversity (of purposes) and its interaction with institutional conditions, we advance the notion of subsidiary scope and its implications. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".