The effect of process monitoring on beyond‐the‐job process improvements
Bibliographic record
Abstract
Abstract Although it has always been important for firms that employees innovate predefined processes, the working environment in which employees implement these processes has significantly changed. Currently, the working environment is often characterized by employee surveillance; that is, the way in which employees conduct a process is monitored. In the current study, we present the results of an experiment examining the effect of process monitoring on process improvements by employees. Although previous accounting literature has reported negative effects of monitoring techniques on several organizational outcomes, we show that process monitoring can have a positive effect on employees' implementation of process improvements in the absence, but not in the presence, of a firm's error avoidance policy. Without an error avoidance policy, employees are motivated to create a favorable impression in front of management by implementing process improvements. This finding has important implications for business practice. From a broader perspective, we show that the influence of action controls depends on the parameters of a cultural control.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".