Corporate social responsibility and performance measurement systems in<scp>Iran</scp>: A levers of control perspective
Bibliographic record
Abstract
Abstract This study draws on Simons' levers of control model to explore how companies rely on the balanced use of diagnostic and interactive performance measurement systems (PMS) to translate corporate social responsibility (CSR) into superior performance. Data were collected based on a survey data set from 98 CFOs of public listed companies in Iran. The theoretical model was tested using partial least squares structural equation modeling (PLS‐SEM, SmartPLS 3.0), which enjoys minimum demands concerning normality assumptions and sample size. The findings show that CSR is positively associated with PMS and organizational performance. Moreover, CSR is indirectly related to organizational performance through the mediating effect of PMS. This study extends the previous literature by simultaneously incorporating resource orchestration theory in the management accounting and CSR settings. The findings provide further insights into the issue of how adopting proper management control mechanisms (e.g., balanced use of PMS) can support organizations in orchestrating the social, environmental, and economic impacts more effectively.
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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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".