Performance management in Canadian public organizations: findings of a multi-case study
Notice bibliographique
Résumé
Purpose – Performance management (PM) is now clearly a well-established practice in public sector organizations. However, increasingly scholars have been questioning its efficacy in improving organizational performance. Research has shown that the presumed benefits remain questionable and that there are many barriers, challenges and problems in implementing PM. The purpose of this paper is to report and discuss the findings of a multi-case study that examines in more depth how five Canadian public sector organizations are implementing PM. Design/methodology/approach – A qualitative multi-case study approach was used in this study. Structured interviews were carried out in each public sector organization and the interview data were analyzed using NVivo8. Individual case profiles were also written. A cross-case analysis was carried out using data from these five cases. Findings – The cross-case analysis of the data focussed on the major themes emerging from the data with respect to challenges and barriers, success factors, context and implications for practice for PM in public sector organizations. Three contextual factors are identified and discussed in explaining some of the findings. Conclusions are drawn for making PM more effective in achieving performance improvement in public sector organizations and future directions for research. Research limitations/implications – The research findings and implications for practice are based on five Canadian public sector organizations so may limit its generalizability to public sector organizations in other countries. Practical implications – Some practical implications are discussed with respect to implementing PM more successfully in public sector organizations. This included the better integration of PM to corporate strategy, leadership in developing a positive PM culture and employee buy-in and commitment to the process. Originality/value – This qualitative multi-case study of PM in Canadian public sector organizations has not previously been done. This approach allows for a more close-up look at PM in public sector organizations especially how it is implemented and the experiences of organizational members. The paper also presents new insights on context as an important variable in explaining the findings from the cross-case analysis and points to future new directions for research and in developing a contingency theory approach to PM.
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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 | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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
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 ».