Factors Influencing the Purchase Behaviour of Plant-Based Food Products in Thailand: An Extension of the Theory of Planned Behaviour
Bibliographic record
Abstract
This study aims to investigate the factors influencing the adoption intention of plant-based food products and to examine the mediating effects on the relationship between adoption intention and actual behaviour. The research is based on the Theory of Planned Behavior (TPB) as the foundational theoretical framework. Convenience sampling has been applied for data collection through an online questionnaire (G-Form), resulting in 582 usable responses. The measurement model was analyzed using Confirmatory Factor Analysis (CFA), and the structural equation model was assessed using Structural Equation Modeling (SEM). The findings indicate that factors positively influencing the adoption intention include attitudes towards plant-based food products, subjective norms, environmental concerns. Word-of-mouth communication was identified as a mediating variable in the relationship between adoption intention and actual behaviour. This research corroborates the Theory of Planned Behavior. Also, it identifies additional factors relevant to the acceptance of plant-based food products beyond the theoretical framework in Thailand. The findings provide valuable insights for business and marketing strategies about plant-based food products.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".