| Abstrakt: |
In the complex field of evaluating leadership styles, the integration and aggregation of data has become crucial. This article delves into the use of OWA-TOPSIS, a hybrid methodology that combines the Ordered Weighted Averages (OWA) Operator and the Method for Ordering Preferences by Similarity with the Ideal Solution (TOPSIS), to achieve an accurate and holistic assessment of leadership executive. By unifying diverse data and aggregating information from multiple sources, you achieve a more complete and nuanced view of management capabilities and styles. This approach not only improves the objectivity of the analysis, but also provides a powerful tool for decision-making in complex corporate environments, where leadership skills are critical to organizational success. The OWA-TOPSIS methodology stands out for its ability to handle ambiguous and subjective information, transforming it into a quantifiable and easily interpretable result. By applying this method, you can discern more clearly which leadership styles are most effective in different contexts and specific situations. Furthermore, the flexibility of this technique allows it to be adapted to various industries and sectors, making OWA-TOPSIS a versatile solution for leadership analysis. The research detailed in this article offers an innovative and insightful perspective on how to optimize management evaluation, thereby providing essential guidance for improving organizational effectiveness through informed leadership strategically aligned with corporate objectives. [ABSTRACT FROM AUTHOR] |
