How Could Brand Image, Ethnocentrism, and Brand Attachment Impact Consumer Behaviour in the Service Industry: A Comparative Study
Bibliographic record
Abstract
Underpinned by self-congruity theory, cognitive appraisal theory, and attachment theory, the current research develops a comprehensive theoretical framework of the key factors determining continuous purchase intention for two coffee brands by incorporating critical factors such as brand image, ethnocentrism, and brand attachment. This paper also investigates the intervening role of brand attachment in such links. The study applied a quantitative approach by gathering data through a self-administered survey from 266 consumers who purchased two coffee brands in Oman: Starbucks Coffee (as an international brand) and Fifty Five Coffee (as a local brand). Using partial least squares structural equation modeling (PLS-SEM), the empirical findings indicated that brand image significantly influenced brand attachment and continuance intention. Ethnocentrism impacted brand attachment and did not have a significant link with continuance intention for Starbucks. However, it significantly affects both brand attachment and customers’ continuance intention for Fifty Five Coffee. Brand attachment positively affects continuance intention and significantly mediates the links between brand image, ethnocentrism, and continuance intention for Starbucks and Fifty Five Coffee. The current endeavour holds a variety of theoretical and practical implications for concerned scholars and professionals respectively. The limitations and future research avenues are also outlined.
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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 | 0.002 | 0.004 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".