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Record W7000480201

Examining the social responsibility image of countries: dimensions, limits and consequences

2021· dissertation· en· W7000480201 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMiddlesex University Research Repository (Middlesex University Of London) · 2021
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Identity and Reputation
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)PopulationQualitative researchFrame (networking)Identification (biology)Circumstantial evidence
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.668
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.053
GPT teacher head0.269
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it