Interactive Design of the Shopping Process Using User Experience in the Food Section of Supermarket
Bibliographic record
Abstract
The design of supermarkets in Korea is uniform, and the competition between supermarkets is mainly a price war.The purpose of this study is to combine interaction design concepts to suggest improvements to supermarkets and create a better user experience.Firstly, the theory of supermarkets, the current situation of hypermarkets, interaction design, and persona is summarized through literature research.Then an observational survey was conducted on the user characteristics and behaviors of supermarkets, etc., and a 5-point Likert scale was used to analyze the user experience satisfaction at each behavioral stage.Based on the observation results, a middle-aged female teacher was set as a persona, and the user experience analysis was conducted for each of the three cases through the six elements of interaction design to find out the inconvenience and problems of the users in the food section of the supermarket.In the conclusion section, a proposal is made based on the results of the analysis through the six elements of interaction design.In future research, the interaction design study will include the analysis of relevant aspects of the self-checkout system.We have high hopes for the application and development of interaction design in supermarkets.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".