Measuring Collaborative Synergies with Advanced Real Options: MNEs’ Sequential Acquisitions of International Ventures
Bibliographic record
Abstract
This paper aims to extend the real options theory valuing strategic collaborative synergies by advanced real options with changing volatility and contributes to the international business literature on MNEs’ sequential acquisitions of international ventures. The proposition is that collaborative synergies can be valued with advanced real options with changing volatility when an MNE is pursuing the sequential acquisition of an international venture and the MNE’s stock volatility is changing at the time of deciding on a full takeover. The paper discusses how recombining and non-recombining lattices with constant and changing volatilities can be employed to value the collaborative synergies of sequential international acquisitions. The theoretical proposition has been justified with the explanatory case study: Natura Cosméticos S.A.’s (Brazil) sequential acquisition of the Aesop brand (Australia). In conclusion, the paper discusses its findings, contributions, limitations, and future work.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".