Impact Of Stress On Employees Job Performance A Study On Banking Sector Of Pakistan
Bibliographic record
Abstract
Bankers are under a great deal of stress and due to many antecedents of stress such as Overload, Role ambiguity, Role conflict, Responsibility for people, Participation, Lack of feedback, Keeping up with rapid technological change, Being in an innovative role, Career development, Organizational structure and climate, and Recent episodic events. One of the affected outcomes of stress is on job performance. This study examines the relationship between job stress and job performance on bank employees of banking sector in Pakistan. The study tests the purpose model in relation of job stress and its impact on job performance by using (n=144) data of graduate, senior employees including managers and customers services officers of well reputed growing bank in Pakistan. The data obtained through questioners was analyzed by statistical test correlation and regression and reliabilities were also confirmed. The results are significant with negative correlation between job stress and job performances and shows that job stress signifincently reduce the performance of an individual. The results suggest that organization should facilitate supportive culture within the working atmosphere of the organization. Keywords: Job performance, Stress, Banks
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".