The Trap of Continual Ownership Change in International Equity Joint Ventures
Bibliographic record
Abstract
This article examines how multiple ownership changes unfold in international equity joint venture (IEJV) evolution and how such repeated changes impact short-term performance and long-term survival. By theorizing a new concept—the trap of continual change—in the IEJV context, we challenge the adaptive viewpoint assumed in alliance dynamics research. We propose that partners sometimes respond to an initial dissatisfaction with the venture result with a dysfunctional repetition of rearranging the ownership control structure. This continual change locks the organization into bad choices and sends it into a downward spiral. Acknowledging the mixed motive nature of inter-partner relationships, we incorporate cooperative versus competitive dynamics manifested in shared control arrangements. We propose that shared ownership control lends stability to the IEJV until the initial IEJV agreement is renegotiated; this stability is a result of the cooperative forces of mutual interdependence and mutual forbearance between the partners. However, when the power balance breaks down, the potential for inter-partner conflict increases. When the ownership control structure of the IEJV is restructured, especially multiple times, shared control arrangements become increasingly unstable as behavioral, cultural, and managerial differences are amplified.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".