The influence of message frame and product type on green consumer purchase decisions : an ERPs study
Bibliographic record
Abstract
Green consumption is a crucial pathway towards achieving global sustainability goals. Product-oriented green advertisements can effectively stimulate consumers' latent needs and convert them into eventual purchasing intentions and behaviors, thereby promoting green consumption. Given that neuromarketing methods facilitate the understanding of consumers' decision-making processes, this study combines prospect theory and need fulfillment theory, employing event-related potentials (ERPs) as measures to explore changes in consumers' cognitive resources and emotional arousal levels when confronted with green products and advertising information. This enables inference regarding consumers' acceptance of purchasing and their psychological processes. Behavioral results indicated that message framing influences consumers' purchases, with consumers consuming more green in response to negatively framed advertisements. EEG results indicated that matching positive framing with utilitarian green products was effective in increasing consumers' cognitive attention in the early cognitive stage. In the late stage of cognition negative frames stimulated consumers' mood swings more, and the influence of product type depended on the role of message frames, and the consumption motivation induced by the product, whose influence was overridden by external evaluations such as message frames. These research findings provide an explanation for the impact of frame information on consumers' purchasing decisions at different stages, assisting marketers in devising diverse promotional strategies based on product characteristics to foster the development and practice of green consumption. This will further embed the concept of green consumption advocated by organizations such as the United Nations Environment Programme (UNEP), World Wildlife Fund (WWF), and Greenpeace into the public consciousness.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| 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".