Do Performance Goals and Development, Feedback and Recognition, and a Climate of Trust Improve Employee Engagement in Small Businesses in the United States?
Notice bibliographique
Résumé
Small businesses are the predominant contributors to the U.S. economy, yet they face many challenges to remain competitive and sustainable. There are several reasons a small business could fail, including a lack of human resources, limited financial resources, competition, technological advancements, disaster, and globalization. Improving employee performance by getting them engaged and productive in their work is an issue that cannot be overlooked for small businesses to function and remain competitive. There is limited empirical evidence that explains the dimensions of performance management and employee engagement in small businesses. However, how small businesses sustain their long-term performance remains uncertain. This study sought to bring together two previously distinct constructs: overall employee engagement and overall performance management, characterized by performance goals and development, a climate of trust, and feedback and recognition. The research was correlational in nature. A survey was conducted to generate and analyze data gathered from 121 employees of small businesses located in the United States. A series of Pearson correlation analyses confirmed the existence of statistically significant positive relationships between employee engagement and each variable of performance management, namely performance goals and development, feedback and recognition, and climate of trust. Notwithstanding these positive correlations, a multiple regression model with the three performance management variables as independent variables and employee engagement as the dependent variable suggested that there was a statistically significant regression model F(3, 117) = 32.34, p < .001, R2 = .453, explaining 45.3% of the variability in employee engagement. Nonetheless, this model confirmed that the variables performance goals and development and climate of trust were not statistically significant in the model (p > .05). In other words, only the feedback and recognition variable was statistically significant in the regression model, suggesting that it explained most of the variability in engagement, including that already explained by the other two variables. Overall, the outcome of this study suggests that small businesses implementing performance management processes have more engaged employees. The conclusions drawn from these findings suggest that overall performance management and overall employee engagement contribute to small business productivity and organizational success.
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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 | 0,003 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».