The Key Role of Consumers’ Involvement: The Case of Organic Food Consumption
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper aims to provide a better understanding of conditions that influence the gap between positive attitude and intention towards organic food products and actual behaviour regarding these products. Thus, we propose an extended version of the Theory of Planned Behaviour (TPB) to explain parts of this gap and we highlight the crucial role played by consumers’ involvement as a moderator. A structural equation modelling was performed, and the sta-tistical analysis of a sample of 1327 French consumers supports our organic food products buying behaviour model. The results showed that the difference between the means of actual behaviour was highly different between low- and high-involvement consumers. More specifically, high-involvement consumers express more positive attitudes towards buying organic food products, perceive higher subjective norms and behavioural control, they have higher behavioural intention, and buy organic food products more frequently. Additionally, the results indicated that, com-pared to low-involvement consumers, high-involvement consumers regard organic food products as more attractive, healthier, tastier, and with higher value. We proposed some marketing strategies to help managers to better promote the organic food products market and, in turn, increase their revenues. For example, marketers therefore have a vested interest in increasing consumer involvement, and, among other things, they can do so by educating them (i.e., high-lighting the benefits of consuming organic foods). Moreover, since high-involvement customers have positive atti-tude-intention and behaviour, they can be allies for marketers through their influence (social norms). Thus, we suggest the use of digital influencers to endorse organic food.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 it