The effects of digital marketing implementation on online consumer in Selangor during COVID-19 pandemic
Bibliographic record
Abstract
The COVID-19 pandemic caused significant changes in many aspects especially towards small medium entrepreneurs (SMEs) as many of SMEs need to shut down their business due to movement control order (MCO) conducted by Malaysia government as SMEs cannot reach their customers. Previous studies show that having an effective digital marketing strategy in place might leave businesses vulnerable to severe setbacks towards SMEs. This research proposal aims to carry out and prove the possible potential effects and factors that influence digital marketing implementation towards online consumers in Selangor during COVID-19 pandemic. The methodology of this paper uses a descriptive qualitative approach by analyzing various previous literature on digital marketing scope of study. The sample size of the study is 235 respondents who were selected based on convenience sampling. The finding has discovered that there is a significant relationship between customer loyalty with implementation of digital marketing towards online consumers in Selangor during COVID-19 pandemic and there is a significance relationship between brand awareness and the implementation of digital marketing towards online consumer in Selangor during COVID-19 pandemic.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".