The association between cost-standard setting and work performance: The role of information asymmetry and goal complexity
Bibliographic record
Abstract
This paper is an empirical testing of the association between Cost Standard-Setting (PSS) on Work Performance (WP), mediated With Information Asymmetry (IA), and Goal Complexity (GC). It is a rule of thumb that PSS setting can lower the level of IA and GC between the managers and the employees and leads to better WP. The present work uses a path model to measure the direct, indirect, and spurious effect between the dependent and independent variables of this study. Data were collected from ten corporate firms in Iraq via a pre-designed questionnaire survey, the questionnaire forms were distributed randomly to the firm’s top management personnel, departmental managers, engineers, accountants, and administrators who are involved in PSS. Around 350 forms were distributed for data collection, however, only 198 forms were considered for this analysis, the rest of the forms were discarded due to incompleteness or missing values. The findings of the study showed a significant direct effect of PSS on WP. Likewise, there was clear evidence of an indirect effect via the mediating variables (IA and GC). The influence of IA and GC confirms the strong association between the independent variable (PSS) on the dependent variable (WP).
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".