Spatial density and ambient scent: effects on consumer anxiety
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
Purpose – This replication and extension of Hirsch and Gruss examines the impact of spatial density and ambient scent on consumers' spatial perception and anxiety. The paper aims to discuss these issues. Design/methodology/approach – A 2 (spatial density: high, low)×3 (ambient scent: no scent, scent associated with spaciousness, scent associated with enclosed spaces) between-participants experimental design was implemented in a laboratory setting. A pretest determined scent selection and manipulation checks were successful. Findings – Spatial perception was influenced by spatial density, but not ambient scent. Ambient scent and spatial density interacted, such that consumers' anxiety levels significantly increased under conditions of low spatial density combined with an ambient scent associated with spaciousness, and directionally increased under conditions of high spatial density combined with ambient scent associated with enclosed space. Research limitations/implications – This research was conducted in a laboratory setting in order to increase experimental control. An exploration of the strength of the observed effects in a field (retail) setting would be insightful. Practical implications – Results of this study suggest that retailers need to consider both spatial density and choice of ambient scent carefully in order to reduce consumers' anxiety levels. Originality/value – This research is one of the few to consider the impact of spatial density and ambient scent on consumers' anxiety levels. The use of a between-participants design and the experimental manipulation of both spatial density and ambient scent results in a more rigorous test of the scent – anxiety relation observed in previous research.
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.
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 | 0.000 | 0.000 |
| 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 it