The effect of improvisation in turbulent times on IHR strategy: A case study of French MNEs in Tunisia
Bibliographic record
Abstract
This article investigates the evolution of international human resources (IHR) strategies of Western multinational enterprises (MNEs) from a strategic improvisation perspective. It analyzes the effect of the Tunisian context, after the revolution, on the strategic IHR direction of French MNEs. The study is based on qualitative research of two French MNEs in Tunisia, and the findings highlight the influence of contextual, managerial and organizational drivers on the improvisation strategy to revise the MNEs' IHR strategy. The results detail a parallel shift from an ethnocentric to a regiocentric approach, based on a minor improvisation in one case, and from an ethnocentric to a geocentric approach, following a bounded improvisation in the other. The work bears both scientific and industry value, as it defines and interrelates managerial, organizational and contextual forces, and transcribes scientific findings into practicable actions within an emerging market. The research identifies open‐mindedness, communication, local managers' skills, mutual trust and strong local networks as keys in the development of an improvisation strategy within a turbulent context.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".