Developing brand relationships through social media communication: a cross-cultural comparison
Bibliographic record
Abstract
Enhancing brand relationships through communication have been the focus of business strategies especially when supported by technology. The aim of this study was to examine the impact of social media (SM) communications on brand relationships and the role of SM usage in explaining brand relationship differences in different cultures. The study's theoretical framework was based on the Hofstede's cultural dimensions theory. Data were collected from SM users through online surveys in two countries: Albania and Turkey. Partial least squares structural equation modelling was used for the theoretical model. Multigroup analysis was used to compare the effects of SM communication quality between the two cultures. The overall model revealed a positive role of SM communications in strengthening consumers' relationships with brands and a moderating effect of SM usage, indicating that greater user engagement in SM leads to stronger brand relationships. The results suggest that brand relationship quality is higher in cultures with greater SM usage. Furthermore, the results showed that the direct influence of SM communication on building brand relationships is less impactful among users of a higher collectivistic culture.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".