The Study on Key Factors of Influencing Consumers’ Purchase of Green Buildings Application of Two-stage Fuzzy Analytic Hierarchy Process
Bibliographic record
Abstract
The rapid development of industrialization all over the world has caused the acute climatic anomaly increasingly subsequent to the 21st century. The traditional building is as the industry with energy consumption, pollution and non-environmental sense. Hence, the concept of green building has been the most effective strategy to mitigate the deterioration of the environment of urban building. The design and evaluated mechanism, the strategic boost of government and related legislation of green building were explored from the former literatures. The study of related marketing issues of green building has rarely been researched. In view of this, the study has constructed 18 crucial factors regarding the influence on consumers’ purchase on green buildings in Taiwan from the literature reviews and Delphi technique. Fuzzy Analytic Hierarchy Process (FAHP) was adopted to analyze the relative weight and the ranking of significance from individual factor. The result appeared the top 5 crucial factors that influenced consumers purchasing green buildings in Taiwan are the price of green building, the level of environmental awareness, green building material and internal structure, the level of green consumption and income in subsequence. The decision-making of the consumers would not be influenced by the green building label, the gender and the age, the environmental propaganda of government, the value of mainstream culture and economic conditions. The empirical result of study is able to be used as the reference that the government establishes the policy of green building impetus and the real estate deal plans the strategy of green building marketing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".