Does Effective Leadership Style Drive Financial Performance of Banks? Analysis in the Context of UAE Banking Sector
Bibliographic record
Abstract
The success for any organization in its competitive business arena depends upon an effective human resource system that is lien with its organizational strategy. In today’s world banks play an important role in the social economy. The banking industry falls under the service domain where efficient risk management cannot be possible without efficient and skilled manpower. The banking sector will be termed as “People Business”. The two key challenges facing banks are management of people and management of risk to determine success in the banking business. “Soft skill” is the call for today in the banking sector more than operational skills which is needed to fulfill the requirement of the customers at the counter. A combination of new technologies, diversification of products, quicker credit and risk appraisal, managing treasury and human resource at the priority would take the bank industry to the heights of international excellence. In the Gulf region, UAE is considered as a fast developing country with a strong interest for the best management practices to improve overall performance. This study targeted banks which were listed with two different markets Abu Dhabi Securities Exchange (ADX) and Dubai Financial Market (DFM). In the present study researched adopted judgment sampling approach and identified a total of 18 banks for whom selective historical financial data was available. From the results of the study it is evident that there is a direct impact of leadership style on performance of the organization. Since leadership style is one of the facets of organizational HR practices, by extension the researcher concludes that leadership style is related to the level of financial performance of an organization.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".