Leadership style and job performance: a longitudinal approach
Bibliographic record
Abstract
Purpose This study aims to examine the relationship between leadership style and job performance by multiple mediating roles of career satisfaction and job satisfaction using the longitudinal approach for frontline employees in the Jordanian hotel sector. Design/methodology/approach This study used a survey questionnaire based on a five-year longitudinal approach. Data were collected in two-period among frontline employees in five-star hotels in Jordan. Leadership style (transformational leadership and transactional leadership) was measured in the first period, whereas job performance, career satisfaction and job satisfaction were measured in the second period. The final sample for the first and second periods comprised 314 questionnaires valid for more analysis. The statistical software of SPSS (version 25) and SmartPLS (version 3.3.5) have been used for data analysis. Findings The results demonstrated that leadership style (transformational leadership and transactional leadership) has a positive significant effect on job performance. The results demonstrated also that leadership style (transformational leadership and transactional leadership) has a positive significant effect on career satisfaction and job satisfaction. As well the results demonstrated that career satisfaction and job satisfaction have a positive significant effect on job performance. Regarding multiple mediating roles, the results demonstrated that career satisfaction and job satisfaction mediated the relationship between leadership style and job performance. Originality/value To the best of the authors’ knowledge, this is the first study of its kind to examine the relationship between leadership style and job performance by multiple mediating roles of career satisfaction and job satisfaction using the longitudinal approach among frontline employees in the hotel sector.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".