Consumer reactions to packaging-free product dispensers: a variety of buyers' profiles to consider
Bibliographic record
Abstract
Purpose This study investigates consumer reactions to dispensers offering solid packaging-free products (e.g. pasta, lentils, cereals) integrated in a delimitated area in a grocery store. More specifically, the research examines the impacts of the overall appeal of packaging-free solid food product dispensers and their perceived ease of use on consumers' intention to use these dispensers and purchase packaging-free products. Moreover, using a set of variables, different buyer profiles are highlighted. Design/methodology/approach The field study for this research was conducted in a delimitated area (i.e. a shop within a shop) dedicated to solid packaging-free products (e.g. pasta, lentils, cereals) in a university cooperative store in the province of Quebec, Canada. A total of 456 buyers and consumers of packaging-free products from this store took part in the field study and completed our survey. Findings This study shows packaging-free dispensers' overall appeal and perceived ease of use to be determinants of consumers' intention to use these dispensers and purchase packaging-free products. The Rebus (response-based procedure for detecting unit segments) method highlights the need to consider three buyer profiles (enthusiastic, pragmatic, and sceptical) with different reactions to the specific dispensers used by retailers for packaging-free products. Originality/value This study focuses on buyers' reactions to packaging-free dispensers in stores, during the purchase process, whereas previous ones highlighted the drivers of and barriers to consumer adoption of packaging-free products (before the purchasing process starts). It also points to the need to fine-tune the segmentation of consumers of packaging-free products, which must be based not only on consumers' previous experience or familiarity with these products but also on the integration of their drivers and barriers.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".