The Impact of Plant Features on Consumer Preference for Outdoor Plants: The Role of Feature Type, Consumer Knowledge, and Task Involvement
Bibliographic record
Abstract
As the first trail to classify plant features into hedonic vs. utilitarian dimensions, this study investigates how consumer individual characteristics (knowledge/involvement) work jointly with plant feature types to influence preference, including three types of horticultural products: perennial (daylily), annual (geranium), and shrub (hydrangea). Discrete choice experiments and multinomial logit analysis are utilized to capture consumer preferences. The results of this study provide many insights. First, the general preference patterns for the three plants are summarized and consumer willingness-to-pay for preferred features are calculated. Second, consumer knowledge and involvement are proved to moderate consumer preference. Interestingly, consumers with a high level of knowledge and involvement prefer inferior utilitarian features more, and the hedonic value of plant products is also highlighted. Finally, the comparisons between US and Canadian consumers provide more practical implications. Based on the research findings, the theoretical and managerial contributions, limitations, and future research opportunities are discussed.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".