The Relationship Between Malaysian Supermarket In-Store Shopping Experiences and Positive Word-of-Mouth
Bibliographic record
Abstract
Attitudinal loyalty such as customers’ willingness to spread positive words of mouth has received less attention compared to behavioural loyalty (e.g., reptronage intention) in retail studies, particularly in the context of supermarket. It is argued that supermarket consumers should be willingly share positive words of mouth when they are satisfied. The effect of Malaysian supermarket in-store experiences (convenience, merchandise value, internal shop environment, interaction with staff, merchandise variety, presence interaction with other customers, in-shop emotion) on customer satisfaction and mediating effect of customer satisfaction on the relationship between in-store experiences and positive WoM were examined. The results show significant relationship between customer satisfaction and willingness to spread positive WoM. Convenience and in store emotion have significant relationships with customer satisfaction, while the other in-store experiences have no significant effects on satisfaction. Customer satisfaction played mediation roles between the relationships between convenience, merchandise variety, interaction with staff and in store emotion with positive WoM. The findings provide useful insights to Malaysian supermarket retailers in understanding their target markets to encourage more positive WoM.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".