The Mediating Effect of Crisis Management on Leadership Styles and Hotel Performance in Jordan
Bibliographic record
Abstract
Research scholars have argued that the emergence of the crisis in the Middle East have led to significant changes in business performance. This has been most notable in the hotels operating in the Jordanian tourist sector, thus, creating a need to investigate leadership styles, crisis management, and hotel performance in a holistic framework. However, this is quite lacking in the literature, and this needs to be addressed. Transformational leadership style and transactional leadership styles are the independent variables, crisis management is the mediating variable and hotel performance is the dependent variable. A quantitative study that used a self-administered questionnaire was carried out on 3-star to 5-star hotels operating in Jordan. The Partial Least Squares (PLS) method as part of Structural Equation Modelling (SEM) was applied to analyse the causal relationships between constructs using the software application Smart-PLS 3.0. The Partial Least Squares approach was chosen according to the research’s exploratory nature. In order to analyze data two-step approach was utilized; the first step was to test the reliability and validity of the constructs in the measurement models, the second step was to test research hypotheses in the structural models. The results show that transformational leadership has significant positive effects on hotel performance and crisis management. Transactional leadership had a significant positive effect on crisis management and crisis management had significant positive effects on hotel performance. Moreover, crisis management partially mediated the relationship between transformational leadership and hotel performance; while the relationship between transactional leadership and hotel performance was fully mediated by crisis management. These findings will help to strengthen the discussion in the extant literature.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".