Brand Personality Moderating Effect on Relationship between Website Quality and Online Trust: Malaysian Online Environment Context
Bibliographic record
Abstract
The objective of this paper is to examine whether the brand personality which includes two dimensions namely, (sincerity/trustworthiness) and (youthfulness/modernity), can moderate the relationship between website quality and online trust. This study considers the impact of the quality of website on online trust and the extent it encourages purchase intentions in the Malaysian context. The data for the study were collated from responses from a sample of 229 college students in Malaysia. The survey included questions on items that measured brand personality, web site quality, online trust and purchase intentions. The data was evaluated by applying multiple regression analysis to establish the relationship among variables .The findings indicate that both dimensions of brand personality, namely (sincerity/trustworthiness) and (youthfulness/modernity) are able to moderate the relationship between web site quality and online trust. However, the results suggest that the impact of (youthfulness/ modernity) is more significant compared to (sincerity/trustworthiness).It was evident that in the Malaysian context, it was imperative for an organization to present an updated and exciting website to attract more consumers to purchase online through its website. This study enhances and augments the existing pool of knowledge on websites with special emphasis on online transactions.. This study provides a better understanding on the perception of Malaysian customers towards web-based transactions. The findings also offer valuable information to the marketing and information managers of organizations with regard to online business transactions.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".