Examining the social responsibility image of countries: dimensions, limits and consequences
Notice bibliographique
Résumé
This study examines the dimensions, limits and consequences of the social responsibility image of countries (SRIC). Specifically, it develops a scale for SRIC and demonstrates how this construct impacts nation brand attractiveness towards highly skilled resources. The research is rooted in place branding, corporate social responsibility, international marketing and skilled migration studies. Although much has been written about these topics, little has been said about the possibility and benefits of applying a social responsibility framework to nation brands. A pragmatic paradigm and a mixed-method research strategy were adopted in order to explore this topic in more depth. A qualitative exploratory stage comprising four focus groups and twelve interviews were conducted with highly skilled resources working in the higher education sector of two European countries (the UK and Italy). This was followed by a quantitative confirmatory stage including a self-administered questionnaire sent via email using Qualtrics. Overall, 647 responses were collected from key informants (117 in the pilot test and 557 in the main study). Respondents were asked to express their opinion on their perception of two pre-selected nation brands, US and Canada. Qualitative data were analysed in NVivo 12 using thematic analysis. Quantitative data were analysed in IBM SPSS 26 and AMOS 26 using a two-steps CB-SEM approach. Findings confirm that SRIC is a multidimensional construct comprising three main dimensions: environmental, economic and ethical. In line with previous studies, data show that country social responsibility requires the involvement of multiple stakeholders, namely government, organisations and society. SRIC exerts a significant impact on nation brand identification (NBI) and intention to apply for a job vacancy (IAJV) but results are inconsistent regarding its relationship with corporate image. Results of the study are valid across both samples (Italian and British) meaning the model is robust and findings can be generalised. No major differences can be found between US and Canada. Concerning the limitations, SRIC suffers from two main limits, both inherited from the root construct, CSR: its contextual nature and the level of scepticism it is encountered with. The study has important theoretical, managerial and policy implications. It is one of the first research studies to apply a CSR framework to a place branding context and to propose a definition and measurement for SRIC. It is also one of the first research projects to investigate this in relation to talent attraction. Based on the study, highlighting social responsibility values and activities might prove beneficial to attract highly skilled workers. Institutions and organisations should therefore work in partnership to develop adequate programmes and a consistent narrative that might lure the best candidates. Future studies should investigate this construct in more depth. More attention should be paid to the operationalisation of the social dimension and to the link between SRIC and corporate social responsibility image (CSRI). The scale should be tested in other non-European countries and involve highly skilled resources coming from a wider range of industries.
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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 | 0,007 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,009 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,001 | 0,007 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».