Implementation of Values on Family Company Succession in Bali Province, Indonesia
Bibliographic record
Abstract
The main purpose of the research is to investigate the implementation of values on family company successions in Bali. This descriptive research was conducted in family business in Bali which have done successions to, at least, their second generation. The data was analyzed qualitatively and quantitatively by using Likert scale. Meanwhile, to discover the implementation of values towards successors' performance, PLS (Partial Least Square) analysis was carried out. The research elaborates that (1) values are positive and significant effect on the characteristics of successor, (2) values did not affect the succession planning, (3) strong values which were emphasized by the owners did not affect the succession planning, (4) values did not affect the successors' performance, and (5) values which were transferred by predecessors did not have any impacts on the successors' performance. The strongest indicator of values to enhance the performance of successors was innovation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 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".