Leveraging social media, big data, and smart technologies for intercultural communication and effective leadership: Empirical study at the Ministry of Digital Economy and Entrepreneurship
Notice bibliographique
Résumé
The objective of this study was to evaluate the impact of social media, big data, and smart technology on intercultural communication and effective leadership inside the Ministry of digital & entrepreneurship. The main objective was to investigate the influence of these technical elements on organizational behavior and the efficacy of leadership within the particular setting of a government ministry dedicated to digital economy and entrepreneurship. In order to accomplish this goal, a thorough empirical inquiry was done, which included gathering data from important individuals involved in the Ministry. The study intentionally selected a sample size of 379 individuals, who represented various responsibilities within the Ministry. The process of data gathering entailed the distribution of surveys and the conduction of interviews to acquire valuable insights and viewpoints from the participants. The utilization of this approach yielded a resilient dataset that is well-suited for thorough investigation. The study explored the complex connection between the use of social media platforms, the implementation of big data analytics, and the incorporation of smart technologies in influencing the dynamics of intercultural communication and leadership inside the Ministry. The results emphasized the substantial influence of social media in promoting intercultural communication and cooperation among personnel within the Ministry. Moreover, the implementation of big data analytics has become a crucial element in improving decision-making processes, impacting several facets of leadership efficacy, strategic planning, and employee involvement. Smart technologies were recognized as crucial elements in establishing efficient communication channels and facilitating effective leadership practices. The study's findings emphasized the beneficial impacts of utilizing social media, big data, and smart technology in the Ministry of digital & entrepreneurship. The research highlighted the significance of government organizations incorporating these technologies in a proactive manner to foster a work environment characterized by improved multicultural communication, well-informed decision-making and efficient leadership. This study makes a substantial contribution to the comprehension of how technological improvements might influence organizational behavior and leadership practices in a government setting. It provides essential insights for policymakers, leaders, and researchers. The findings have broader significance beyond the Ministry, serving as a basis for additional investigation into the use of technology in intercultural communication and leadership effectiveness inside government institutions.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».