Management accounting control systems’ impact on joint venture performance: the positive role of managers’ experience
Bibliographic record
Abstract
This study explores the impact of management planning and control systems’ use on 50/50 joint venture’s performance operating in the auto industry. It explores the effect of the use of these systems by organizations operating in turbulent environments through an analysis of the impact that managers’ experience has on the intensity and purpose of use of management planning and control systems. The study of this topic emerges as the results of previous exploratory field studies of JVs (Groot and Merchant 2000) and of JVs in the auto industry (Porporato 2013) where it is suggested that management planning and control systems’ do not have a central effect on JV performance. A survey of 35 international JVs with shared ownership (50/50) shows that organizational performance improves when the uncertainty of factors perceived as controllable by managers is reduced; a factor is perceived as controllable when the manager has a high level of past experience with it. Uncertainty as it is defined by Galbraith (1973) is reduced through an intensive use of management planning and control systems, which in turn positively affects organizational performance.
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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 | 0.001 |
| 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".