But they promised! How psychological contracts influence the impact of felt violations on job-related anxiety and performance
Bibliographic record
Abstract
Purpose This study unpacks the relationship between violations of organizational promises, as perceived by employees and their job performance, considering the mediating effects of job-related anxiety and moderating effects of psychological contract type. Design/methodology/approach Multi-source, multi-wave data were collected from employees and their supervisors in Pakistan. Findings Feelings of organizational betrayal may reduce job performance due to the higher anxiety that employees experience in their daily work. This mediating role of enhanced job-related anxiety in turn is stronger to the extent that employees believe that their psychological contract contains relational obligations but weaker when it contains transactional obligations. Practical implications The study gives organizational decision makers pertinent insights into how they can mitigate the risk that employees who are angry about broken organizational promises stay away from performance-enhancing work activities, namely, by managing the expectations that come along with psychological contracts. In so doing, they can avoid imposing dual harms on employees, from both a sense that they have been betrayed and the risk of lower performance ratings. Originality/value This study offers expanded insights into the process that underpins the translation of psychological contract violations into diminished job performance, by pinpointing the simultaneous roles of experienced job-related anxiety and beliefs about employer obligations.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".