Affective adoption of new grocery shopping modes through cultural change acceptance, consumer learning, and other means of persuasion
Bibliographic record
Abstract
Research has shown very slow consumer adoption to new grocery shopping options, particularly virtual shopping in North America. While consumers have been willing to purchase objects virtually, there is an inherent scepticism in purchasing food using these modes. Research has also shown while this may be the case in some western countries, eastern countries such as China have seen different acceptance. Urban eastern consumers have embraced virtual shopping and have already moved to hybrid shopping modes including smart grocery shopping. This paper reviews theoretical assumptions which may explain a shift in western consumer's behavioural changes and posits a hypothetical conceptual framework for future empirical investigations. The framework advances the idea that cultural change acceptance may be an antecedent to other social factors such as consumer learning, affective factors, cognitive factors, normative appeals among others, trust, perceived privacy and security, and these provide links to the adoption to these new retail modalities.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| 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".