The Impact of Path-Goal Leadership Styles on Work Group Effectiveness and Turnover Intention
Notice bibliographique
Résumé
Globalization and the demand for a skilled, educated, and expeditious workforce pressure organizations to leverage their diverse workforces to gain competitive advantage (Harris, 1996). Throughout the next decade, the U.S. workforce is forecasted to become even more diverse, with 75 percent of the immigrant population arriving in the United States from Asia and Latin America, with only five percent coming from Canada and Europe. Women and minorities were projected to represent 70 percent of the U.S.'s 2008 workforce (Lockwood, 2005). To maintain financial competitiveness in this diverse landscape, organizational leaders must embrace the leadership styles that are most effective in motivating the diverse groups in which many employees work. Diversity in work groups can generate significant benefits for organizations, including enhanced innovation, creativity, and productivity (Valentine, 2001). Capturing these benefits takes the right type of leadership style and skills (Jung and Sosik, 2002; Silverthorne, 2001; Waldman et al., 2001; Kim and Organ, 1986; House, 1971; Fiedler, 1967). Despite recognition that an appropriate leader can enhance a work group's performance, increase group members' job satisfaction, and reduce turnover intentions, there is scant research assessing the impact of specific leadership styles on diverse work group effectiveness and turnover intention (Duemer et al., 2004). To help fill this gap, we analyze the relationships among three Path-Goal leadership styles, diversity, work group effectiveness and work group members' turnover intention. The following section discusses the important literature about diverse work groups, work group effectiveness, turnover intention, and Path-Goal leadership styles. Then, the methods and results of our data collection and analysis are presented. Finally, the conclusions and implications of this study's findings for organizational leaders and the fields of leadership and management are explained. REVIEW OF THE LITERATURE Work Groups and Work Group Diversity Work groups are comprised of individuals who are interdependent and/ or interact with each other to complete tasks and projects that contribute to organizational productivity, innovation, and creativity. The exchange of information and know-how among work group members as they achieve common goals generates social bonds that enhance productivity and organizations' financial performance (Gil et al., 2005; Blanchard and Miller, 2001; Beck et al., 1999; Anakwe and Greenhaus, 1999; Nonaka and Takeuchi, 1995). Diverse work groups exist when members' individual attributes differ (Mannix and Neale, 2005; Hobman et al., 2004, 2003). Researchers often focus on two dimensions of group member diversity. The first is dissimilarity, which includes explicit characteristics such as age, race/ethnicity, and gender, and the second is dissimilarity, which includes relative characteristics such as functional background, educational background, and seniority (Hobman et al., 2004, 2003; Chattopadhyay, 2003; Chatman and Flynn, 2001; Williams and O'Reilly, 1998). When individuals interact with people whom they perceive as different, they tend to classify themselves and those people into social categories (Cox and Nkomo, 1990). Research has found that, early in the life of a work group, members focus on the visible aspects of diversity such as gender, race/ethnicity, and age. As group members interact, they redirect their attention to other members' non-visible features such as personality, education, expertise, values, and communication styles (Cunningham and Sagas, 2004; Hobman et al., 2004, 2003; Salomon and Schork, 2003; Richard et al., 2002; Caudron, 1994). Employees with more perceived value/informational dissimilarity with their leaders tend to be less satisfied with them and have weaker organizational attachment that those with high perceived similarity (Lankau et al. …
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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 | 0,003 | 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 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| 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
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