The Mediating Effect of Quality and Prestige on the Relationship between Brand Globalness and Purchase Likelihood of HTC Mobile Phone
Bibliographic record
Abstract
Perceived brand quality (PBQ) and perceived brand prestige (PBP) have been considered very important mechanisms to predict the direct as well as indirect relationship between perceived brand globalness (PBG) and consumer purchase likelihood (CPL) in many studies. However, almost all studies focused on direct influence of PBQ and PBP on CPL, neglecting the mediating role of them. This study, therefore, aims at filling this research gap by investigating the mediating effects of PBQ and PBP on the relationship between the PBG and CPL in the mobile industry applied to the HTC Company. In doing so, this study used the structural equation modeling (SEM) approach to analyze a total sample of 439 college student consumers in central Taiwan. Results indicated that PBG and BPQ have positive effects on CPL while PBP did not. These findings are different from the literature that both PBQ and BBP showed significant influences on CPL. In other words, when it comes to HTC mobile phone, only PBQ could be considered as a mediating variable through which PBG indirectly affects CPL. Generally, this study opens the doors to new empirical studies in the mobile phone industry whereby readers and practitioners would understand the importance of mediator role in consumer purchase intention.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".