Determination of the Most Charismatic Leader Using Analytic Hierarchy Process and Fuzzy TOPSIS: An Application in Turkey
Notice bibliographique
Résumé
The concepts of leaders and leadership have been dealt with by many different disciplines, such as psychology and sociology, with the fields of management and political science being foremost, and have become frequent subject matter of academic discussions and research. The first studies in this field took place at the beginning of the 20th century, with analysis of important personalities that changed the course of the history and shaped societies’ futures with their extraordinary abilities and characteristics. It was predominantly these characteristics, as well as behavioral and situational approaches, that formed the basis of these first studies. The objective of this study is to determine which of the six presidents of the Republic of Turkey, who have served or are serving as Head of State, has more of the charismatic leadership characteristics, employing an interdisciplinary methodology in which multi-criteria decision-making methods and techniques are used. Within this context, the traits that a leader and a charismatic leader should have were determined, the weights of these traits were calculated using the Analytic Hierarchy Process (AHP), the calculated weights were used in the Fuzzy TOPSIS method, and the presidents were analyzed from the perspective of charismatic leadership. The results obtained support the predictions made before the study was begun. It was determined that Turgut Ozal, who was the 8thPresident of Republic of Turkey, is the most charismatic leader among the selected presidents. The concepts of leaders and leadership have been dealt with by many different disciplines, such as psychology and sociology, with the fields of management and political science being foremost, and have become frequent subject matter of academic discussions and research. The first studies in this field took place at the beginning of the 20th century, with analysis of important personalities that changed the course of the history and shaped societies’ futures with their extraordinary abilities and characteristics. It was predominantly these characteristics, as well as behavioral and situational approaches, that formed the basis of these first studies. The objective of this study is to determine which of the six presidents of the Republic of Turkey, who have served or are serving as Head of State, has more of the charismatic leadership characteristics, employing an interdisciplinary methodology in which multi-criteria decision-making methods and techniques are used. Within this context, the traits that a leader and a charismatic leader should have were determined, the weights of these traits were calculated using the Analytic Hierarchy Process (AHP), the calculated weights were used in the Fuzzy TOPSIS method, and the presidents were analyzed from the perspective of charismatic leadership. The results obtained support the predictions made before the study was begun. It was determined that Turgut Ozal, who was the 8th President of Republic of Turkey, is the most charismatic leader among the selected presidents.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».