A B2C Business Agenda: Analyzing Customers’ Perceptions towards Bumiputera Retailers
Bibliographic record
Abstract
In business retailing, the exploration of studies on consumer demographics, behaviour, attitude and attribute are useful as a framework for profiling consumer’s ultimate choice in retail purchasing. Using data that we cross-sectionally investigated, this paper seeks to analyse customer perception towards business retailing activities of the Bumiputeras. Focusing in the state of Terengganu, 359 samples were selected among the public. Out of seven districts in the state of Terengganu, three are being chosen, representing developed, developing and less developing districts. The independent variables understudied include quality of service, attitude, interest, and risk of spending at Bumiputera retail stores. All of those are tested against customers’ perception towards Bumiputera retail store, which will serve as a dependent variable. The results demonstrate that there are significant relationship between service quality, attitude, risk and attitude towards the perception of local customers towards the perception of local customers towards business retailing of the Bumiputeras. If Bumiputeras retailers were to competitively enjoying being as the market players they should therefore acquire more initiatives and adopting strategies of continuous improvement of the above constructs for strongly positioning them in the expanding market.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".