Marketing Factors of Green Economic Effect on Consumers’ Purchase Intention for the Market of Family-sedan in Taiwan
Bibliographic record
Abstract
The problems such as the global energy demand enhancing, greenhouse effect aggravating and climate externalizing and so on have worsen increasingly subsequent to the 21st century. Enhancing consumers’ awareness of environmental protection spurred the global automobile manufacturers to produce high-tech products and services with green features on the market. The automobile distributors take the concept of green marketing as the leading appeal to attract the consumers. Fuzzy Analytic Hierarchy Process is adopted in this study to analyze the best marketing strategy carried out while the automobile distributors are selling the products with the concept of green marketing and providing the services to consumers. The results show that the top 5 key green marketing factors influence the consumers on purchasing the family-sedans are “Cost on purchase, use and maintenance”, “Ego green civil awareness of consumer”, “Certification of green mark”, “Low fuel consumption” and “Low emission”. Comparatively speaking, the key factors are unable to influence the consumers on purchasing are “The practice of principle of equitable”, “Deducting the consumption on production resources”, “Advocacy of environment protection policy”, “Recycling disposal of auto-body and components” and whether obtained “Subsidy”. One excellent product is unable to achieve the perfect sales target if without appropriate marketing strategy. With the soar of global awareness of environment protection, the corporate all over the world combines the demands of environment protection with the marketing strategy mutually. As far as the automobile distributors are concerned, the marketing strategy has been the tendency without further delay drawn up by green marketing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".