Brand Experience: How Does It Affect Brand Personality and Brand Loyalty in the Egyptian Telecommunications Industry?
Bibliographic record
Abstract
Brand experience has received a lot of attention within the business industry. Customers are looking for not only valuable brand benefits but also, emotional skills as well as brand experience theory. In this regard, the Egyptian Telecommunications Industry tries, also, to provide answers on how to measure brand experience and how it affects customers’ behaviors. This research examines in the context of the Egyptian telecommunications market the relationship between Brakus et al.’s (2009) four whole experience dimensions (sensory, affective, intellectual, and behavioral), brand personality, and brand loyalty. The author produced an online questionnaire, which, based on a simple sampling method, was distributed to and collected from the Egyptian telecommunications industry (Vodafone Egypt, Orange Egypt, Etisalat Egypt, and We Egypt). Four hundred fifty questionnaires were distributed and, excluding those that were incomplete, the author obtained 392 samples. This represented an 87% response rate. The results indicate that brand experience has a positive impact on the brand’s personality. Brand experience has, also, a strong positive effect on brand loyalty and, ultimately, brand personality has a strong positive effect on brand loyalty. Besides the brand experience’s direct effect on brand loyalty, it has a significant indirect effect on brand loyalty by impacting on brand personality. Among the relationships between the variables, the relationship between brand personality and brand loyalty is the strongest. More particularly, it is noteworthy that the correlation with the findings shows that the relationship between brand experience and brand loyalty is greater than the direct relationship. Therefore, in order to strengthen customer brand loyalty, telecommunications managers should pay more attention to customer brand personality.
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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 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".