Conceptualizing nation branding: the systematic literature review
Bibliographic record
Abstract
Purpose This paper aims to provide an integrated model of nation branding, propose a comprehensive definition of this concept and differentiate between nation branding and other related constructs. Design/methodology/approach To analyze nation branding academic literature, this paper used a systematic literature review approach to investigate academic studies related to nation and country branding. All relevant studies on the nation and country branding between 1996 and mid-2021 were extracted from six selected databases, including Elsevier’s Science Direct, Emerald, Sage, Wiley, Springer and Jstor, by using a Preferred Reporting Items for Systematic Reviews and Meta-Analysis process. The reviewed papers were coded and analyzed to extract themes and concepts. Findings The results of this paper show that nation branding is influenced by six main factors, namely, business and marketing, political, social and cultural, economic and labor, international and environmental factors; it comprises one key component, that is, nation branding; it results in five major consequences, including social, economic and financial, business, international and political consequences, and is moderated mainly by socio-demographic variables. Additional contributions of this paper are the proposal of a comprehensive definition of nation branding based on the extant literature and identifying nation branding differences with other constructs that sometimes have been previously used interchangeably with nation branding. This paper concludes with suggestions for future research in the field. Originality/value This paper uses the themes and concepts uncovered by the analysis to conceptualize nation branding, provides an integrated model of nation branding and distinguishes it from other related branding concepts. This paper also summarizes what nation branding is versus what it is not.
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.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".