Does the consumer awareness protect the exploitation? A Quantitative study in FMCG sector
Bibliographic record
Abstract
Consumer awareness is one where the buyer could take the right decision in purchasing all types of product. Marketers in view of earning profit, neglect the interest of the consumers and this leads to exploitation of the buyers. To investigate the current scenario, this study focused on the consumer awareness in the urban and rural area towards the Fast Moving Consumer Goods (FMCG) along with the exploitation if any that existed in the market. For this purpose, 557 consumers who were using FMCG products residing in the western region of Tamilnadu were selected through cluster sampling followed by simple random sampling. To meet out the objectives, various statistical tools through SPSS 21 were applied and the result revealed that all the constructs like communication, price, labeling, promotion and unfair trade practices, if any remarkably influencing the consumer awareness. Also, labeling has a noteworthy mediating role between consumer awareness and satisfaction. But there existed a direct negative effect of consumer awareness on the satisfaction. It is suggested that marketers need to focus to fulfill all the rights of the consumers as detailed in the consumerism.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".