Marketing meets human resources : a study of employer branding practices in Canada
Notice bibliographique
Résumé
The purpose of this study was to find out the current Employer Branding Practices being used by a sample of companies in Canada. The goal was to find out how companies were creating awareness of their employer brands, how they influenced their brand consideration and feelings and judgements about that brand; and how it all came together in reflecting the overall employer branding strategy. This was achieved by interviewing the key Human Resource influencers in fifteen companies in Canada who were regarded by external awarding bodies as great employers. \nThe results of the interviews with a sample of companies in Canada revealed that the employer branding model was split into two separate parts: an internal model and an external model. Internally, the sample companies indeed had very well designed and coordinated strategies for managing and ensuring that their current employees were aware of and considered the attributes of their employer brand, had positive feelings and judgements about their employers. Overall the internal employer branding strategy although not specifically referred to by that name achieved the ultimate goal of creating brand resonance among current employees. However, noticeably absent was a coordinated effort to project that positive employer brand externally. There was very little collaboration between the Human Resources departments and the Marketing departments to create awareness and consideration of the employer brand among potential applicants. Companies instead heavily relied on their current networks, employees, clients, recruiters and the community to project and sell their employer brand externally. \nIt is therefore recommended that companies take control of managing their employer brand externally just as they do internally. A model combining the various aspects of the internal employer branding strategy that can be used to influence potential applicants’ awareness and consideration of an employer during their job search has been proposed. In order for this model to be successful, Human Resources will have to work with Marketing to devise the best way to accurately and consistently project the internal employer brand image externally using one continuous model.
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 | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,003 | 0,007 |
| Études des sciences et des technologies | 0,029 | 0,003 |
| Communication savante | 0,007 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».